MR Maungwa - repository.nwu.ac.za

Effects of labour unrest on the share returns of the JSE Top 40 companies

MR Maungwa orcid.org 0000-0002-2292-4410

Dissertation accepted in fulfilment of the requirements for the degree Master of Commerce in Risk Management at the

North-West University

Supervisor: Dr SJ Ferreira-Schenk

Co-supervisor: Mr D Mokatsanyane

Graduation ceremony: June 2021

Student number: 23568763

Effect of labour strikes on the share returns of the JSE-Top 40 companies II

DECLARATION

I declare that:

“Effects of labour unrest on the share returns of the JSE Top 40 companies”

is my own work, that all the sources used or quoted have been indicated and acknowledged

by means of complete references, and that I have not previously submitted this dissertation

for a degree at any other university.

M.R. Maungwa

November 2020

Vanderbijlpark

Effect of labour strikes on the share returns of the JSE-Top 40 companies III

DECLARATION OF THE LANGUAGE EDITOR

DECLARATION OF LANGUAGE EDITING

14 November 2020

To whom it may concern

This is to confirm that I, the undersigned, have language edited the completed research of

M.R. Maungwa for the Master of Commerce in Risk Management entitled: Effects of labour

unrest on the share returns of the JSE Top 40 companies.

No changes were permanently affected and were left to the discretion of the student. The

responsibility of implementing the recommended language changes rests with the author of

the thesis.

Yours truly

Jomoné Müller

Effect of labour strikes on the share returns of the JSE-Top 40 companies IV

ACKNOWLEDGEMENT

With this submission, I would like to express my sincerest gratitude to the following persons,

for their continued support and guidance throughout this paper. In particular, I would like to

thank the following:

• God for giving me the knowledge to write this dissertation, the strength to overcome

all adversity throughout and the courage to preserve when it all seemed so bleak.

• To my supervisor Dr Suné Ferreira-Schenk, I would like to express my sincerest

gratitude for your guidance, your unweathered patience and words of

encouragement throughout this journey.

• Mr Danny Mokastanyane for your guidance, time and sacrifice, your assistance is

highly appreciated.

• To my language editor Jomone Miller for the wonderful editorial work.

• My parents Thabo Maungwa and Clara Morolong for their love and support.

• To my dear sister Reabestwe Maungwa, thank so much for your patience, love and

support. Your continued encouragement was exceptional.

• To my uncle Itumeleng Morolong for your love, endless support and motivation.

• A special thank you to my friends, family and colleagues for your support throughout

this time, your words of encouragement and understanding. Thank you.

“ Today I choose to live with gratitude for the love that fills my heart, the peace that rests

within my spirit, and the voice of hope that says all things are possible.”

– Anonymous

Effect of labour strikes on the share returns of the JSE-Top 40 companies V

ABSTRACT

Keywords: labour strikes, JSE Top 40 companies, share returns, efficient market hypothesis,

collective bargaining, event study methodology, labour strikes, global financial crises,

behavioural finance, protected and unprotected labour strikes

Labour strikes are a platform that enables workers to demonstrate their disagreement and/or

their dissatisfaction towards their employer, with respect to labour relation issues such as

remuneration, working conditions and employee benefits. Labour strikes in South Africa date

back to 1922, post the Anglo-Boer war of 1899–1902, within the mining sector and have since

become the fabric of our society in correcting historic socio-economic ails of unemployment,

minimum wages and inequality. “The right to strike” as of 1995 is recognised as a constitutional

right and fundamental tool for bargaining agents and workers. Collective bargaining is

recognised as a key determinant of an amicable labour relationship between employees and

the employers, which provide organisational rights to union representatives and facilitates

continuous centralised bargaining councils. Collective bargaining is a key means for

bargaining agents to establish fair wage and working conditions, on behalf of employees.

Labour strikes regulate and establish new terms and conditions of employment and protects

the rights of employees from arbitrary action by the employer. Collective bargaining provides

employees with a sense of respect, responsibility and dignity, it strengthens the workforce and

increases employee’s morale and productivity.

Labour strikes for businesses mean a disrupt in the day-to-day operations and in certain cases

a complete halt in production. The resolve of a labour strike results in a direct deviation in the

main purpose of a company, which is to turn a profit and maximise shareholders’ returns.

Labour strikes results in a loss in production, followed by a loss in customers as the first

consequence of a strike. The withdrawal of labour by workers results in a disturbance in the

supply chain affecting customers, companies and industries aligned with the affected

company. The occurrence of the labour strike results in losses in the value of the company

and subsequently the businesses' market share. However, the major impact endured by a

company as a result of a labour strike is the reputation of the firm. Reputational damage to a

business has a far-reaching effect on the business, affecting customers and investor

sentiment. The value of a publicly-listed company is entrenched in the share price of the

company. Investors make use of a company’s share price to gauge the market perception of

the share and determine whether a company is profitable. Investors evaluate operating

efficiency and profitability of the listed company. Labour strikes can negatively affect investor

confidence and subsequently the share returns of an affected company.

Effect of labour strikes on the share returns of the JSE-Top 40 companies VI

Labour strikes in South Africa have increased at an alarming rate following the 2008/2009

global financial crisis (GFC). The number of labour strikes following the 2008/2009 GFC more

than doubled, increasing from 51 strike incidents in 2010 to 132 in 2017. The GFC placed a

strain on global economic conditions, affecting emerging markets the most. The occurrence

of GFC exposed and deepened some of South Africa’s well-hidden vulnerabilities of poverty,

unemployment and inequality. Calls for retrenchments and accepting minimum wages have

been met with fury and frustration by workers, which has resulted in a significant rise in the

number of labour strikes. Owing to the rise in the number of labour strikes and the gap in

academic research, the study focused on examining the effects that labour strikes have on

the share returns of the JSE Top 40 companies. To achieve the primary objective the

subsequent objectives were set, establishing whether labour strikes have an effect on the

share return of the JSE Top 40 companies, identifying the effects of protected and unprotected

labour strikes, respectively, on the share returns of the JSE Top 40 companies and identify

the effects of protected and unprotected labour strikes on the share returns of the JSE Top 40

companies, respectively and collectively, before and after the day of the strike.

An event study methodology was used to examine a data sample of the JSE Top 40

companies that were affected by protected and unprotected labour strikes between 2010 and

2017, which were observed over a 61-day event window. A descriptive summary of the test

result is presented, followed by industry analysis of the affected companies, a cumulative

analysis of the effects of protected and unprotected labour strikes on the share return of the

JSE Top 40 companies are presented, together with a comparison of the effects that protected

and unprotected labour strikes had on the share returns of the JSE Top 40 companies. Along

with a comparison of the effects of protected and unprotected labour strikes on the share

return of the JSE Top 40 companies before and after the day of the strike commenced.

The study found that labour strikes have a negative effect on the share return of the JSE Top

40 companies, with a significant negative effect found in companies affected by protected

strikes. The study’s results are supported by previous researchers who found that protected

labour strikes have a greater effect on companies owning to the cost implication of a protected

labour strike. The study revealed that the majority of companies affected by labour strikes

were found within the mining sector, which was in line with the Department of Labour’s Annual

Industrial Action Report. The comparison of the effects of protected and unprotected labour

strikes on the share return of the JSE Top 40 companies support the findings of the descriptive

statistics that protected labour strikes have a greater cost implication than unprotected strikes.

This is further confirmed in examining the effects of protected and unprotected labour strikes

Effect of labour strikes on the share returns of the JSE-Top 40 companies VII

before and after the day of the strike. The results indicated that there was an immediate effect

on the share return of protected labour strikes, which rebounded after the day of the strike.

The study’s findings indicate that there is a need for cohesion during periods of wage

negotiations among bargaining agents. A conscious integrative collective bargaining approach

employed by bargaining agents will enhance cohesion and instil investor confidence in the

labour market and subsequently financial markets. A cohesive bargaining process will

eliminate losses due to disruptions in daily operations owing to labour strikes and ensure

maximum share returns to stakeholders. The study’s findings draw attention to the effect that

labour strikes have on both the employee and the employer. By avoiding the occurrence of

labour strikes the relationship between the employee and employer is maintained along with

businesses’ daily operations. This in effect will support the ailing labour market as employment

is maintained and new jobs can be made available.

Effect of labour strikes on the share returns of the JSE-Top 40 companies VIII

TABLE OF CONTENTS

DECLARATION ......................................................................................................... II

ACKNOWLEDGEMENT ........................................................................................... IV

ABSTRACT ............................................................................................................... V

TABLE OF CONTENTS .......................................................................................... VIII

LIST OF TABLES .................................................................................................. XIV

LIST OF FIGURES................................................................................................. XVI

LIST OF ABBREVIATIONS .................................................................................. XVII

CHAPTER 1: INTRODUCTION AND BACKGROUND ............................................. 1

1.1 INTRODUCTION ........................................................................................... 1

1.2 PROBLEM STATEMENT .............................................................................. 3

1.3 OBJECTIVE OF THE STUDY ....................................................................... 4

Primary objective ........................................................................................... 4

Theoretical objectives .................................................................................... 5

1.4 RESEARCH DESIGN AND METHODOLOGY .............................................. 5

1.5 RESEARCH METHODOLOGY ..................................................................... 5

Literature review ............................................................................................ 5

Empirical study .............................................................................................. 5

Sample size and sample period ..................................................................... 6

Event study methodology .............................................................................. 6

Hypothesis test statistics of abnormal returns ............................................... 8

Hypothesis test: ............................................................................................. 9

Abnormal returns ........................................................................................... 9

Z-statistic ..................................................................................................... 10

Effect of labour strikes on the share returns of the JSE-Top 40 companies IX

1.6 ETHICAL CONSIDERATIONS .................................................................... 11

1.7 CHAPTER CLASSIFICATION .................................................................... 11

CHAPTER 2: LABOUR STRIKES ........................................................................... 13

2.1 INTRODUCTION ......................................................................................... 13

2.2 DEFINING LABOUR STRIKES ................................................................... 15

Traditional strike (Primary strike) ................................................................. 15

Secondary strike (Sympathy strike) ............................................................. 16

Go-slow ....................................................................................................... 16

Work-to-rule ................................................................................................. 16

Sit-ins or work-ins ........................................................................................ 16

Lockouts ...................................................................................................... 17

2.3 A THEORETICAL FRAMEWORK FOR LABOUR STRIKES ..................... 17

The Zeuthen-Harsanyi model ...................................................................... 17

Ashenfelter-Johnson (Political model) ......................................................... 19

Hick’s bargaining theory .............................................................................. 21

2.4 COLLECTIVE BARGAINING ...................................................................... 23

2.5 PURPOSE OF COLLECTIVE BARGAINING ............................................. 23

2.6 COLLECTIVE BARGAINING AGREEMENT .............................................. 24

2.7 THE NEGOTIATING PROCESS ................................................................. 24

Preparation and discovery ........................................................................... 24

Negotiations ................................................................................................. 25

Outcome ...................................................................................................... 25

2.8 LEGAL PROCEDURE TO A LABOUR STRIKE ......................................... 27

Protected strikes and lockouts ..................................................................... 28

Illegal strikes and lockouts ........................................................................... 29

Effect of labour strikes on the share returns of the JSE-Top 40 companies X

When strike or lockout procedures do not apply .......................................... 29

2.9 REVIEW OF PREVIOUS STUDIES ............................................................ 29

2.10 GLOBAL FINACNCIAL CRISIS .................................................................. 32

The impact of the Global Financial Crisis on South Africa ........................... 35

2.11 SYNOPSIS .................................................................................................. 36

CHAPTER 3: EFFICIENT MARKET HYPOTHESIS ................................................ 37

3.1 INTRODUCTION ......................................................................................... 37

3.2 EFFICIENT CAPITAL MARKETS ............................................................... 38

3.3 ASSUMPTIONS OF AN EFFICIENT CAPITAL MARKET .......................... 38

3.4 EFFICIENT MARKET HYPOTHESIS .......................................................... 39

Weak form of efficient market hypothesis .................................................... 40

Semi-weak form of efficient market hypothesis ........................................... 40

Strong form of the efficient market hypothesis............................................. 40

3.5 THE IMPLICATION OF EFFICIENT MARKETS FOR INVESTORS ........... 41

3.6 FINANCIAL MARKET ANOMALIES .......................................................... 42

Fundamental anomalies .............................................................................. 43

3.7 BEHAVIOURAL FINANCE ......................................................................... 45

3.8 EFFICIENCY REVIEW OF THE JOHANNESBURG SECURITIES

EXCHANGE ................................................................................................ 48

3.9 SYNOPSIS .................................................................................................. 50

CHAPTER 4: RESEARCH DESIGN AND METHODOLOGY .................................. 51

4.1 INTRODUCTION ......................................................................................... 51

4.2 DATA DESCRIPTION ................................................................................. 51

Sample size and sample period ................................................................... 51

Data sample ................................................................................................ 53

4.3 EVENT STUDY METHODOLOGY .............................................................. 56

Effect of labour strikes on the share returns of the JSE-Top 40 companies XI

Event identification ...................................................................................... 57

The event periods ........................................................................................ 57

Calculation of abnormal returns ................................................................... 60

Hypothesis test statistics of abnormal returns ............................................. 62

4.4 SYNOPSIS .................................................................................................. 63

CHAPTER 5: RESULTS AND DISCUSSION .......................................................... 64

5.1 INTRODUCTION ......................................................................................... 64

5.2 DESCRIPTIVE STATISTICS ....................................................................... 65

5.3 INDUSTRY ANALYSIS OF THE JSE TOP 40 COMPANIES AFFECTED BY

LABOUR STRIKES ..................................................................................... 68

Industry distribution of the JSE Top 40 companies affected by labour strikes

……………………………………………………………………………………...69

Industry analysis of the JSE Top 40 companies affected by labour strikes . 70

5.4 CUMULATIVE ANALYSIS OF THE EFFECTS OF PROTECTED AND

UNPROTECTED LABOUR STRIKES ON THE SHARE RETURN OF JSE

TOP 40 COMPANIES.................................................................................. 96

Trend analysis of share return of companies affected by protected and

unprotected strikes, collectively ................................................................... 97

Hypothesis test of protected and unprotected strikes collectively on share

returns of affected companies ..................................................................... 98

Periodic analysis of protected and unprotected strikes collectively ........... 101

Summary hypothesis test of the JSE Top 40 companies affected by

protected and unprotected strikes, collectively .......................................... 102

5.5 COMPARISON OF SHARE RETURNS OF COMPANIES AFFECTED BY

PROTECTED AND UNPROTECTED STRIKES, RESPECTIVELY .......... 104

Trend analysis of share returns of companies affected by protected and

unprotected strikes, respectively ............................................................... 105

Effect of labour strikes on the share returns of the JSE-Top 40 companies XII

The distinction in share returns of companies affected by protected

unprotected strikes .................................................................................... 106

Periodic analysis of the JSE Top 40 companies affected by protected labour

strikes ........................................................................................................ 108

Periodic analysis of the JSE Top 40 companies affected by unprotected

strikes ........................................................................................................ 110

Summary hypothesis test of companies affected by protected and

unprotected labour strikes, respectively..................................................... 112

5.6 MOVEMENT IN SHARE RETURNS OF AFFECTED COMPANIES BEFORE

AND AFTER THE DAY OF THE STRIKE ................................................. 113

Share returns of protected strikes before and after the day of the

announcement of the strike ....................................................................... 113

Share returns of unprotected strikes before and after the day of the

announcement of the strike ....................................................................... 118

5.7 SYNOPSIS ................................................................................................ 123

CHAPTER 6: CONCLUSION AND RECOMMENDATIONS .................................. 127

6.1 INTRODUCTION ....................................................................................... 127

6.2 OVERVIEW OF THE STUDY .................................................................... 128

Theoretical objectives ................................................................................ 128

Empirical objectives ................................................................................... 128

6.3 FINDINGS OF THE STUDY ...................................................................... 130

Empirical Objective 1: Establishing whether labour strikes affect the share

returns of the JSE Top 40 companies ....................................................... 130

Empirical objective 2: Identifying the effects of protected and unprotected

labour strikes, respectively, on the share returns of the JSE Top 40

companies ................................................................................................. 131

Effect of labour strikes on the share returns of the JSE-Top 40 companies XIII

Empirical Objective 3: Identify the effects of protected and unprotected

labour strikes on the share returns of the JSE Top 40 companies,

respectively, before and after the day of the strike .................................... 131

6.4 CONTRIBUTION OF THE STUDY ............................................................ 132

6.5 CONCLUDING REMARKS AND RECOMMENDATIONS ........................ 132

6.6 LIMITATIONS AND FUTURE RESEARCH .............................................. 134

REFERENCE LIST ................................................................................................ 135

ANNEXURE 1:ETHICAL CLEARANCE ................................................................ 164

ANNEXURE 2: DECLARATION ............................................................................ 165

Effect of labour strikes on the share returns of the JSE-Top 40 companies XIV

LIST OF TABLES

Table 1.1: Sample selection criteria ........................................................................... 6

Table 3.1: Investors cognitive biases ....................................................................... 47

Table 4.1: Sample selection criteria ......................................................................... 53

Table 4.2: Protected and unprotected strikes from 2010 - 2017 ............................... 54

Table 5.1: Descriptive summary of share returns of companies affected by protected

and unprotected labour strikes ................................................................ 66

Table 5.2: Significance test: AAR mining industry .................................................... 73

Table 5.3: Significance test AAR consumer goods industry ..................................... 77

Table 5.4: Significance test of AAR of companies in the retail industry .................... 80

Table 5.5: Significance of AAR of companies in the brewery industry ..................... 84

Table 5.6: Significance test of AAR of companies in the telecommunications industry

................................................................................................................................. 87

Table 5.7: Significance test of AAR of companies in the corporate group industry .. 90

Table 5.8: Significance test of AAR of companies in the pharmaceutical industry ... 94

Table 5.9: Significance test of CAAR of the JSE Top 40 companies affected by

overall labour strikes ............................................................................... 99

Table 5.10: Interval analysis of protected and unprotected collectively .................. 101

Table 5.11: Summary significance test of share returns of companies affected by

protected and unprotected labour strikes ............................................ 103

Table 5.12: Significance test of CAAR of companies affected by protected and

unprotected strikes, respectively ......................................................... 106

Table 5.13: Interval analysis of protected labour strikes......................................... 109

Table 5.14: Interval analysis of unprotected labour strikes ..................................... 110

Table 5.15: Significances test of share return of companies affected by protected

and unprotected labour strikes, respectively ....................................... 112

Table 5.16: Share returns of companies affected by protected strikes before and

after the day of the strike ..................................................................... 115

Table 5.17: Significance test of share return of companies affected by protected

labour strikes before and after the day of the strike ............................ 118

Table 5.18: Share returns of companies affected by protected labour strikes before

and after the day of the strike .............................................................. 120

Effect of labour strikes on the share returns of the JSE-Top 40 companies XV

Table 5.19: Significance test of share return of companies affected by unprotected

labour strikes before and after the day of the strike ............................ 123

Effect of labour strikes on the share returns of the JSE-Top 40 companies XVI

LIST OF FIGURES

Figure 2.1: The Zeuthen-Harsanyi Bargaining model ............................................... 18

Figure 4.1: Performance of the JSE Top 40 index from 2010 to 2017 ..................... 52

Figure 4.2: Illustrates the event period of the study .................................................. 58

Figure 5.1: Distribution of share returns of the JSE Top 40 companies affected by

labour strikes ......................................................................................... 68

Figure 5.2: Industry distribution of the JSE Top companies affected by labour strikes

................................................................................................................................. 69

Figure 5.3: Average abnormal returns of companies in the mining industry ............. 71

Figure 5.4: Average abnormal returns of companies in the consumer goods industry

................................................................................................................................. 75

Figure 5.5: Average abnormal returns of companies in the retail industry................ 79

Figure 5.6: Average abnormal returns of the brewery industry ................................. 83

Figure 5.7: Average abnormal returns of companies in the telecommunications

industry .................................................................................................... 86

Figure 5.8: Average abnormal returns of companies in the corporate group industry

................................................................................................................................. 89

Figure 5.9: Average abnormal returns of companies in the pharmaceutical industry 93

Figure 5.10: Share return of the JSE Top 40 companies affected by protected and

unprotected labour strikes collectively ................................................... 97

Figure 5.11: Comparison of share returns of companies affected by protected and

unprotected strikes .............................................................................. 104

Figure 5.12: Difference in share returns of protected strikes before and after the day

of the announcement of the strike ....................................................... 113

Figure 5.13: Difference in share returns of companies affected by unprotected strike

before and after the day of the strike ................................................... 119

Effect of labour strikes on the share returns of the JSE-Top 40 companies XVII

LIST OF ABBREVIATIONS

AAR : Average abnormal returns

ALSA : All Share Index

CAAR : Cumulative average abnormal returns

CAR : Cumulative abnormal returns

CCMA : Commission for Conciliation, Mediation and Arbitration

CDO : Collateralised Debt Obligation

CRA : Community Reinvestment Act

ECM : Efficient capital market

EMH : Efficient market hypothesis

FSM : Financial Services Modernisation Act

GDP : Gross domestic product

GCF : Global financial crisis

JSE : Johannesburg Securities Exchange

Effect of labour strikes on the share returns of the JSE-Top 40 companies 1

CHAPTER 1: INTRODUCTION AND BACKGROUND

The most difficult thing is the decision to act, the rest is merely tenacity. –Amelia Earhart

1.1 INTRODUCTION

The advent of the 2008/2009 global financial crisis (GFC) placed a strain on global economic

conditions, affecting emerging markets the most as they still find it difficult to recover from to

date (Industrial action report, 2015). The recession resulted in high price levels, growth in

unemployment and slow economic growth. Men and women across the world are subjected

to accepting minimum wages as a result of sluggish global economic conditions (International

Labour Organization, 2016). The Industrial Action Report (2017), indicates that labour strikes

following the 2008/2009 GFC more than doubled, increasing from 51 strike incidents in 2010

to 132 in 2017. The rise in the number of labour strikes remains as a result of wage

discrimination, inequality and socio-economic conditions (Jorge & Adams, 2018). In 2010 a

historical number of 20 674 737 working days1were lost in production (Industrial Action Report,

2017). The number of days lost in production was primarily a result of prolonged public servant

strikes where workers demanded an increase in wages, bonus and better working conditions

(Industrial Action Report, 2010).

The notion of subscribing to minimum wages has been met with fury and frustration in South

Africa’s labour market. South Africa’s labour market has long been characterised by historical

socio-economic disparities of high levels of unemployment, minimum wages and high levels

of inequality (World Bank, 2018). Theses socio-economic disparities have been strained by

economic conditions, which have decreased consumer’s purchasing power and resulting in

higher wage demands and subsequent labour strikes (Department of Labour, 2016).

South Africa’s labour market has as a result of sluggish economic conditions been affected by

the significant rise in the number of labour strikes in the last decade. In 2010, the South African

army was deployed to hospitals across the country during a public servant strike involving 12

labour unions and more than 1.3 million workers ranging from teachers, police, nurses and

custom officials in a 20-day long strike (Smith, 2010). During this period, hospital entrances

were blocked, colleagues assaulted, surgeries and schools disrupted, and this was despite

court interdicts preventing workers from striking (Ceruti, 2010).

1 The number of working days lost due to labour strikes, is a measure of the total number of workers

involved directly in the strike or lockouts multiplied by the length of the work stoppage (Industrial Action Report, 2016)


On the 10th of August 2012, 3000 mine workers walked off the job and embarked on what

management regarded as an illegal wildcat strike (South African History Online(SAHO), 2012).

The incident is perceived as the most devastating strike incident since the history of

democracy. The strike resulted in the death of 34 miners, 78 wounded and 200 arrested after

police opened fire on workers (De Waal, 2012). The strike was characterised with acts of

intimidation from members of the South African Police Service, security guards and labour

union members (Bruce, 2015).

The Rustenburg platinum belt, infamous for the Marikina massacre, experienced one of

]history’s most abnormal labour strike on the 23rd of January 2014 (England, 2014). According

to Molatlhwa (2017), 700 000 mineworkers downed tools and embarked on a five-month long

strike ending on 23rd June 2014. The 2014 platinum belt strike is regarded as the longest strike

to take place in South African history (Stroddard, 2014). The strike was prolonged because of

workers’ additional demands, which employers regarded as impractical (SAHO, 2014). In

addition to their salary increase of R5000, workers demanded back pay for the duration of the

strike, living allowance and further requested affected mining houses not to take criminal

action against workers suspected of violence during the strike (Burkhardts, 2014).

The reoccurring nature of labour strikes demonstrates a general depiction of South Africa’s

labour market, which according to Urbach (2010), is as certain as death and taxes. According

to Ackerman (2016), labour strikes are among many other reasons, investors have lost

confidence in the South African economy. Ndenze (2014) found that labour strikes such as

the 2014 platinum belt strike had damaged South Africa’s wider investor sentiment and had

brought the country’s economy to the brink of recession. The resolve of labour strikes results

in losses to both firms and workers, firms lose out in profitability due to days lost in production,

whereas workers lose out in wages as a result of the no work, no pay agreement between

employer and employee (Amegee, 2010). An extreme example of this is found in the 2014

platinum miners’ strike affecting three mine houses: Impala Platinum, Amplats, and Lonmin.

The six-month long strike resulted in the three mining houses losing out on 40 per cent of

production, which amounted to R24.1 billion in revenue (Fin24, 2014). Workers lost out on

R10.6 billion in wages (Simelane et al., 2014).

Labour strikes disrupt the main purposes of a company. The resolve of a labour strike causes

interruptions in a company’s’ production line and subsequently affects a company’s profit

margin (De wet, 2012). The main purpose of a company is profit maximisation for its

shareholders (Mankiw, 2013). Profit maximisation is regarded as businesses attempt to deliver

maximum value from operational inputs, through increasing operating efficiency and

increasing economies of scale and reducing redundant functions (Varian, 2010). Halts in


production are disruptions to daily operations of the company, which interferes with the

company’s efforts to derive maximum value from its daily operations (Mas, 2008).

The value of a publicly listed company is entrenched in a company’s share price. Investors

make use of a company’s share price to gauge the market perception of the security and

determine whether a company is profitable (Bernstein & Damodaran, 1998). Investors

evaluate operating efficiency and profitability of the listed company (Chandra, 2012). Labour

strikes affect investor confidence, and subsequently the share returns of an affected company.

Investors and labour departments have been able to quantify losses resulting from labour

strikes in the form of salaries and wages and revenue, however, a gap remains in quantifying

the impact that labour strikes have on the share returns of a company (Seedat, 2013).

1.2 PROBLEM STATEMENT

According to Condon (2018), “the right to strike is made up of a delicate balance between the

power of a firm and the rights of employees and is considered as a sign of a healthy

democracy”. The South African constitution, as of 1996, recognises the right to strike as an

important bargaining tool for labour unions (Labour Relations Act, 11 of 2002). Labour strikes

are regarded as a movement aimed at improving working conditions, which unions together

with their members accomplish through placing pressure on their employers (McGregor,

2018). According to Taylor (2004), labour strikes improve work morale, lowers absenteeism

and increases productivity. Du Toit (2000) affirms that “good labour relations attempt to

advance collective bargaining as a means of securing labour peace, social justice, economic

development, and employee equality”.

The South African economy has, however, been long burdened by the significant rise in labour

strikes following the GFC. The GFC revealed some of South Africa’s well-hidden

vulnerabilities, namely unemployment, inequality and poverty (Zini, 2008). Much of these

vulnerabilities have been the cause of increased labour strikes, owing to worker’s demands

for better working conditions, higher wages and equal pay (Chabalala, 2014). Ngidi (2011)

stresses that the government’s and trade union’s efforts to improve employees’ standard of

living and address wage discrimination have failed and have resulted in an increase in the

number of private companies and services delivery strikes. Labour strikes have had an

adverse effect on business affecting production, profitability, consumer and investor

confidence (Ganda & Ngwakwe, 2015).

Businesses in their various forms endure a direct and indirect cost implication as a result of

labour strikes. According to Israelstam (2017), the loss of production and customers is usually

the first consequence of a strike. Workers' withdrawal of labour results in a disturbance in the

https://www.goodreads.com/author/show/3166620.Prasanna_Chandra


supply chain affecting customers, companies, and industries aligned with the affected

company (Sapa, 2013). The impact of the labour strike results in losses in the value of the

company and subsequently the businesses' market share. However, the major impact

endured by a company as a result of a labour strike is the reputation of the firm (Ngidi, 2011).

Reputational damage to a business has a far-reaching effect on the business, affecting

customers and investor sentiment.

The desire for higher wages and equality in the workplace, in relation to the desire for

maximum share returns to shareholders presents a delicate balance in South Africa operating

environment (Botha, 2014). The conflicting interests of workers and shareholders are

exacerbated by the historical structural imbalance of South Africa’s labour market and the

effects of the GFC, that has resulted in an increase in labour strikes (Ganda & Ngwakwe,

2015). Workers have been demanding higher wages due to the loss in purchasing power,

while firms are focused on attaining the primary objective of obtaining maximum share returns.

The competing desires of workers and shareholders, that has resulted in a rise in labour strikes

has necessitated the need to evaluate the effects of labour strikes on the share returns of

companies listed on the Johannesburg security exchange (JSE) Top 40 index. The outcome

of the study will provide an understanding of the effects of labour strikes on invest confidence.

The purpose of the study is to examine the effect that labour strikes have on firms, more

specifically, how they affect the share return of companies listed on the JSE Top 40 index.

Limit research has been done on evaluating the effects of labour strikes on the share return

of companies listed on the JSE Top 40 index. Previous studies by Neumann (1980), Bhana

(1997), DiNardo and Hallock (2000) and Seedat (2013) focused on the effects of labour strikes

on specific industries, the predictability of labour strike and the effects of labour strikes on

publicly listed companies. This leaving a gap for research specifically aimed at understanding

the effects of labour strikes on the share return of companies listed on the JSE Top 40 index.

The makes use of an event study methodology to evaluate the share returns of affected

companies before the announcement of a strike, during and after the strike. The study begins

by providing a literature review of labour strikes, financial markets, followed by a layout of the

event study methodology. An empirical study is conducted followed by results discussion,

recommendations, and conclusion.

1.3 OBJECTIVE OF THE STUDY

Primary objective

The primary objective of the study is to evaluate the effects that labour strikes have on the

share returns of the JSE Top 40 companies.


Theoretical objectives

In order to achieve the primary objective, the following theoretical objectives were formulated

to contextualise the study:

• Provide a theoretical overview of labour strikes to establish a general understanding of the

dynamics of labour strikes and how the resolve of a strike is established with respect to

protected and unprotected strikes; and

• Provide an overview of the efficient market hypothesis (EMH) as a basis of proving whether

the event of labour strikes does affect the share price of publicly listed companies.

1.4 RESEARCH DESIGN AND METHODOLOGY

In order to achieve the primary objective of the study an empirical study was conducted, and

the objectives were as follows:

• Establishing whether labour strikes affect the share returns of the JSE Top 40

companies;

• Identifying the effects of protected and unprotected labour strikes, respectively, on the

share returns of the JSE Top 40 companies; and

• Identify the effects of protected and unprotected labour strikes on the share returns of

the JSE Top 40 companies, respectively and collectively, before and after the day of the

strike.

1.5 RESEARCH METHODOLOGY

The study comprises a literature review and an empirical study. Quantitative research, using

secondary data, are used for the empirical portion of the study.

Literature review

The study makes use of secondary data obtained from multiple sources from previous studies,

journal articles, newspaper articles, textbooks, and websites.

Empirical study

The empirical study makes use of an event study methodology. The study assesses share

returns of affected companies, against potential returns companies would have obtained in

the absence of the strike. The period in which the strike occurred must be identified, along

with the precise date of the announcement of the strike together with the date of completion.

The historical price movement of the affected companies was collected and a series of

statistical tests (described in the following section) were conducted, to identify abnormalities

in price movements.


Sample size and sample period

A sample of the JSE Top 40 companies was taken from the JSE all share market. The sample

frame consisted of companies ranging from all economic sectors, for example,

telecommunications, consumer goods, and manufacturing. An all economic sector sample

was used in the study due to the focus of the study being on the event of labour strike affecting

the JSE Top 40 companies, which cuts across all economic sectors. Historical share price

movement recorded daily was used to analyse the significant effect that labour strike has on

affected companies. Daily historical price movements from 2010 to 2017 were considered to

conduct the study. The study focuses on the period post the 2008/2009 financial crisis and as

a result, the sample period is from 2010 to 2017. The data set was collected from IRESS, a

leading provider of financial data feeds and analytical tools, the annual industrial action report

and secondary data from newspaper articles such as News24, Money Web, Business Day

live, etc.

The study identified 41 companies from a pool of 256 companies which were affected by

labour strikes and were listed on the JSE All Share Index. The study identified that of the 256

companies affected by labour strikes 41 companies that were listed on the JSE Top 40 index

at some point in time between 2010 and 2017. Of the 41 companies identified, 32 companies

were affected by protected labour strikes and 9 were affected by unprotected labour strikes.

Table 1.1 presents the study’s data sample selection criteria.

Table 1.1: Sample selection criteria

SAMPLE SELECTION CRITERIA Number of companies

1. Companies affected by labour strikes between 2010 and 2017

259

2. Companies listed on the JSE Top 40 index affected by labour strikes

41

3. Companies listed on the JSE Top 40 index affected by protected strikes

32

4. Companies listed on the JSE Top 40 index affected by unprotected strikes

9

Event study methodology

The study made use of an event study to assess the share returns of the JSE Top 40

companies that have been affected by labour strikes. An event study is a statistical method

commonly used in financial research to measure the effect of identifiable events on financial

variables (Brooks, 2014). Announcement of acquisitions, mergers, firm’s dividends pay-outs


and entry into or deletions of a stock from an index and labour strikes take the form of

identifiable events.

The first paper on event studies was] written in the 1930s, however, modern-day event studies

pay attribute to Ball and Brown (1968) and Fama et al. (1969), for the groundwork of their

studies (Mackinlay, 1997). Ball and Brown’s work was primarily aimed at testing the ECM and

whether the arrival of new information to the market will result in an immediate reaction in the

share price movement. According to Neuhierl et al. (2008), identification of such a reaction is

obtained through assessing the expected returns a firm would have attained had the event not

occurred against the abnormal returns obtained as a result of the event.

The model identifies three periods of an event, namely, the estimation window, the event

window, and the post-event window. Normal returns of affected firms are calculated in the

estimation window, whereas abnormal normal returns are estimated within the event window.

Abnormal returns provide insight into whether the event had an effect on the firm, whether

information pertaining to the event was leaked, or whether the market needs additional time

to process the information. The post-event window estimation provides an assessment of the

performance of the share price after the event has occurred (Benninga, 2008)

Event windows over which observations are made require specification in terms of the length

of the event window. The length of the event window is determined by the purpose of the

study, whether the researcher seeks to observe the long-term effect of the event or the short-

term effect (Brooks, 2014). Studies that consider months and several years assess long event

windows. Studies that consider 5, 10, 20- or 30-day periods assess a short event window. For

this study, a 30-day period prior to and post the event were considered. The event window is

represented by “zero”, the period prior the event is represented by a negative count to -30, a

positive count to 30 for the post-event.

Event studies can be conducted by making use of the market model, the constant expected

returns model, and a capital pricing model. According to Brooks (2014), the market model is

the most commonly used. The market model makes its deductions through correlating

abnormal return of the firm against a reference market (Kothari et al., 2004).

In order to obtain abnormal returns, of the difference between actual return and expected

return was estimated during the event period (Brown & Warner, 1958):

𝐴𝑅𝑖𝑡 = 𝑅𝑖𝑡 − 𝐸(𝑅𝑖𝑡) (1.1)

Where:


𝐴𝑅𝑖𝑡 are abnormal returns of the affected company 𝑖 on period 𝑡;

𝑅𝑖𝑡 are normal returns of the company 𝑖 in period 𝑡; and

𝐸(𝑅𝑖𝑡) are the returns of the company 𝑖 on period 𝑡.

Calculation of normal returns will then be estimated. Actual share returns of change in share

price:

𝑅𝑖𝑡 = 𝐼𝑛(𝑃𝑖𝑡

𝑃𝑖𝑡−1) (1.2)

Where:

𝑅𝑖𝑡 is the share price of company 𝑖 on period 𝑡 ; and

𝑃𝑖𝑡 is the share price on period’s 𝑡 -1.

Expected returns using the market model will be estimated to establish whether abnormal

returns differ from normal return. Estimated as follows:

𝐸(𝑅𝑖𝑡) = 𝛼𝑖 + 𝛽𝑖𝑅𝑚𝑡 + 𝑒𝑡 (1.3)

Where:

𝐸(𝑅𝑖𝑡) is the expected return on the company 𝑖 during the period 𝑡;

𝛼𝑖 is the intercept of the regression;

𝛽𝑖 is the slope of the regression;

𝑅𝑚𝑡 is the return on the market during period 𝑡; and

𝑒𝑡 The error terms.

The abnormal return in equation one is subsequently:

𝐴𝑅𝑖𝑡 = 𝑅𝑖𝑡 − 𝐸(𝑅𝑖𝑡) = 𝑅𝑖𝑡 − 𝛼𝑖 − 𝛽𝑖𝑅𝑚𝑡 (1.4)

The outcome of Equation 1.4, therefore, provides an indication as to whether labour strikes

do affect the share returns of the JSE Top 40 companies, with regard to protected strikes and

unprotected strikes.

Hypothesis test statistics of abnormal returns

The outcome of abnormal returns provides an indication as to whether labour strikes do affect

the returns of an affected company. An outcome of greater than zero in the event window,

allows the researcher to conclude that the identified event does result in movements in the


share price of the identified firm (Mackinlay, 1997). The study in this regard considered the

hypothesis test that is described in the section to follow.

Hypothesis test:

- Null hypothesis (𝑯𝟎𝟏): The resolve of labour strikes does not affect the share returns of

the JSE Top 40 companies.

- Alternative hypothesis(𝑯𝑨𝟏): The resolve of labour strikes affects the share returns of


- Null hypothesis (𝑯𝟎𝟐): Protected labour strikes do not have a greater negative impact on

share returns of the JSE Top 40 companies, in relation to unprotected labour strikes.

- Alternative hypothesis (𝑯𝑨𝟐): Protected labour strikes have a greater negative impact

on the share returns of the JSE Top 40 companies, in relation to unprotected labour strikes.

- Null hypothesis (𝑯𝟎𝟑): The resolve of protected labour strikes does not result in a change

in the share returns of the JSE Top 40 companies after the day of the strike.

- Alternative hypothesis (𝑯𝑨𝟑): The resolve of protected labour strikes results in a change


- Null hypothesis (𝑯𝟎𝟒): The resolve of unprotected labour strikes does not result in a

change in the share returns of the JSE Top 40 companies after the day of the strike.

- Alternative hypothesis (𝑯𝑨𝟒): The resolve of unprotected labour strikes result in a


Abnormal returns

Estimations of aggregate abnormal returns are required to conclude the researcher’s findings

concerning sample events. Average abnormal returns (AAR) and cumulative abnormal returns

(CAR) are to be estimated in this regard. The estimation of AAR tests the significant effect of

the event on individual share prices over the event window (Woon, 2004). The outcome of the

estimation provides a generalised outcome of the study. AAR for all companies in the sample

for day 𝑡 was estimated as follows:

𝐴𝐴𝑅𝑡 =1

𝑁∑ 𝐴𝑅𝑖𝑡

𝑁𝑖=1 (1.5)

𝑁 indicates the number of companies in the sample.

CAR estimation will be as follows:

𝐶𝐴𝑅𝑖 = ∑ 𝐴𝑅𝑖𝑡𝐾𝑖=1 (1.6)


CAR estimates the sum of abnormal returns of company 𝑖 during the event window.

𝐾 indicates the number of days in the event window.

AAR estimations are followed by cumulative average abnormal returns (CAAR). According to

Eventstudytools (2003), CAAR is an additional estimation that provides an overall indication

of the impact caused by the event, more especially in cases where the event is not exclusive

to the event window. CAAR is represented by the following equation:

𝐶𝐴𝐴𝑅𝑇 = ∑ 𝐴𝐴𝑅𝑡𝑇𝑡=1 (1.7)

Z-statistic

In order to conclude the above-mentioned calculations, a z-statistic must be estimated to test

the set hypothesis. Estimations of the z-statistic indicated as to whether abnormal returns

deviate from zero (Massey & Miller, 2006). The outcome of the estimate in terms of its size

and direction of the z-statistic indicated the significance of the test statistics. Calculation of the

z-statistic is as follows:

𝑍𝐴𝑅 =𝐴𝑅𝑖𝑡

𝑆𝐷(𝐴𝑅𝑖𝑡) (1.8)

Where:

𝑍𝐴𝑅 is the z-statistic of abnormal returns

𝑆𝐷(𝐴𝑅𝑖𝑡) is the sample standard deviation of abnormal return.

𝑆𝐷(𝐴𝑅𝑖𝑡) = √1

𝑇0−1∑ (𝐴𝑅𝑖𝑡 − 𝐸(𝐴𝑅𝑡))2𝑇0

𝑡−1 (1.9)

Where:

𝑇0 is the period of the event (estimation window)

At a significant level of 5 per cent, the z-statistic was compared with z-critical value.

If the z-statistic > z-critical value then the null hypothesis will be rejected, thus indicating that

abnormal returns deviated significantly from zero.

If the z-statistic < z-critical value then the null hypothesis will not be rejected, thus indicating

that abnormal returns did not deviate significantly from zero.


1.6 ETHICAL CONSIDERATIONS

The study was conducted according to the ethical guidelines and principles as prescribed by

the North-West University (NWU, 2016). The study is considered to be of low ethical risk owing

to its use of secondary share price and labour strikes data. The share price data were obtained

from INET BFA IRESS, for which the university has a license for. The share price and labour

strike data were public information and were freely available. The study obtained ethical

clearance from the Research Committee of the Faculty of Economic Sciences and

Management Sciences with the ethics clearance number NWU-00584-20-A4.

1.7 CHAPTER CLASSIFICATION

The study comprised of the following chapters:

Chapter 1: Introduction and problem statement

Chapter 1 presents an introduction to the study, which contextualise the overall objectives of

the study, the theoretical and empirical objective of the study as well as the methodology which

is followed to attain the research objectives.

Chapter 2: Labour strikes

Theoretical background to the labour strikes is provided to establish a general understanding

of the dynamics of labour strikes, and how the resolve of a strike is established. The theoretical

background of labour strikes is supported by the background of GFC and how it may have

affected South Africa’s labour market.

Chapter 3: Efficient Market Hypothesis

Theoretical background to efficient markets is provided as a basis and enables the researcher

to establish whether the JSE is an efficient market and most importantly whether labour strikes

affect the share price movement of publicly listed companies.

Chapter 4: Research design and methodology

Chapter 4 presents a discussion on event methodology followed by the study. The discussion

encompasses the steps taken during data collection, as well as the model used to reach the

empirical objectives of the study.

Chapter 5: Results and discussion

The results obtained from the model estimation along with their interpretation are presented

in Chapter 5.


Chapter 6: Conclusion

Chapter 6 concludes the study by providing a summary, concluding the results and providing

possible recommendations for further research.


CHAPTER 2: LABOUR STRIKES

To fulfil the promise of economic opportunity, we must remain true to the principle that

collective bargaining is a cornerstone of a free society and indispensable to a strong middle

class.-Tom Perez

2.1 INTRODUCTION

The South African constitution as of 1995 recognised the right to strike as an important

bargaining tool for labour unions (Labour Relations Act, 11 of 2002). Labour unions in the

representation of their members have increasingly exercised their right to strike over the past

few years. Workers together with their unions have made use of “labour strikes” as a tool to

demonstrate their disagreements and/or dissatisfaction regarding labour relation issues such

as remuneration, working conditions and employee benefits towards their employer (Lester,

2014). Section 213 of the Labour Relations Act of 1995 defines labour strike as “the partial or

complete concerted refusal to work, or the retardation or obstruction of work, by persons who

are or have been employed by the same employer or by different employers, to remedy a

grievance or resolve a dispute in respect of any matter of mutual interest between employer

and employee, and every reference to work’ in this definition includes overtime work, whether

it is voluntary or compulsory”.

Labour strikes in South Africa date back to 1922, post the Anglo-Boer war of 1899–1902,

within the mining sector (Norman, 1922). The end of the war saw an influx of unskilled white

unemployed labours entering the urban areas in search of employment (Sahistory, 2012). The

mining industry, throughout the period, had developed a racial hierarchical division of labour

whereby supervisory and skilled jobs were performed by white labourers and unskilled work

and low paying labour was reserved for black and coloured labourers (Dickens, 2015). Mine-

owners according to Egan (2006), had developed a division of labour policy to maintain a

balance that protected their interests without disturbing the racial social order within the

industry.

Prompted by the rising in cost of operations and the drop in the price of gold during the

economic depression, which followed World War l, the division of labour policy resulted in an

overarching conflict of interest and political disenchantment in the workforce (Hirson, 1993).

Mine executives and The Chamber of Mines planned to reduce the colour bar and increase

the ratio of black to white workers (Visser, 2003). The Chamber of Mines gave notice that it

would be abandoning the division of labour policy and would replace 2000 semi-skilled white

men with cheaper black labour, this gave rise to the labour revolt (Davenport, 2013). White


labours used the uprising as an attempt to place pressure on mining companies and the state

to back down on the policy to save on labour costs by employing black labourers in positions

that should have been reserved for them (Warwick, 2012). As a result, labour strikes erupted

in early 1921 and intensified as the year progressed (Krikler, 2006).

South Africa during this period became more industrialised, which placed pressure on the

government to protect skilled white workers in the mining and manufacturing industry, and as

a result enacted the Industrial Conciliation Act of 1924, the Wage Act of 1925 and the Mines

and Works Amendment Act of 1926 (Williams, 1923). The Industrial Conciliation Act of 1924

set up a mechanism for consultation between employer’s organisations and trade unions

(Davis, 1989). The Wage Act set up a board to recommend minimum wages and conditions

of employment (Lucas, 1933). The Mines and Works Amendment Act of 1926 firmly

established the principle of the colour bar in certain mining jobs (Conradie, 2016).

The enactment of the Industrial Conciliation Act, the Wage Act and Mines and Works

Amendment Act of 1926 was met with resistance in the 1946 “African Mineworkers Strike”

(Webb, 2012). On 12 August 1946, African mine workers of the Witwatersrand went on strike

demanding more equitable wages (SAhistory, 2012). The strike was motivated by the

imbalance caused by the apartheid-era legislation, which presented favourable employment

opportunities and higher wages for white labourers (O’Mera, 1975). The strike played a

significant role in the recourse towards the apartheid era which altered political thinking in the

liberation movement (Venter, 2003). It served as a revelation in South Africa’s labour industry,

which has come to witness an increase in labour unions, the number of labour strikes and the

number of days lost in production and the sophistication within the labour market (Condon,

2018). This has today earned South Africa the status of strike capital of the world (Urbach,

2010).

The chapter aims to achieve the study’s first theoretical objective of establishing a general

understanding of the dynamics of labour strikes and how the resolve of a strike is established

with respect to protected and unprotected strikes.The chapter presents definitions and

concepts related to labour strikes, which included collective bargaining, collective bargaining

agreements, labour strike, protected and unprotected strikes. The chapter explains the

theories of collective bargaining and outlines the theoretical framework of labour strikes. The

chapter further presents a review of the results of past empirical studies relating to labour

strikes and their effects on financial markets. This followed by an overview of the GFC and the

effects it has on South Africa’s economy. A synopsis of the chapter is provided to summaries

the chapter.


2.2 DEFINING LABOUR STRIKES

Labour strike is a term used by employers and within the business community to describe the

organising of employees through labour unions (Ally, 2015). Labour strikes are regarded as

the ultimate sanction enforced by labour unions demonstrating member’s dissatisfaction

towards their employer regarding unfair labour practices such as wages and working

conditions (Barker, 2015). Labour strikes are characterised by the partial or complete

withdrawal of labour services by union members (Kerruish, 2017). McConnell et al. (2009)

indicate that labour strike often entails the violent disruptions by disgruntled workers

obstructing the day-to-day operations of a firm, subsequently resulting in a halt in production.

According to Hyman (1984), labour strike can be defined as “the refusal to work and/or the

retardation of work, which is instituted to remedy a grievance or resolve a dispute on any

matter of mutual interest”. Bendix (1996) describes labour strikes as “a short-term, collective

deferral of work, with the aim to put production on hold and to force the employer to take the

demands of the workers seriously”. Labour strikes are regarded “as an integral part of

collective bargaining, which regulates the power relationship between the employer and the

employee” (Mamoria et al., 2008). Johnson (2014) states that “labour strikes are a sign of a

healthy economy, which eradicates management’s unilateral decision-making regarding

employee working conditions”.

Labour strikes occur as a result of varying reasons that range from; health hazards in the

workplace, working hours, wages, demand for leave with pay, discrimination, inadequate

working tools, training and development and aggressive behaviour by management (Raje,

2019). Disgruntled employees faced with dissatisfactory working conditions, such as low

minimum wages are willing and more inclined to embark on a strike as they have very little to

lose and are willing to take the risk to improve working conditions and increased compensation

(Power, 2013). According to Bendix (1996) workers demonstrate their dissatisfaction by

means of a traditional strike (primary strike), secondary strikes (sympathy strike), go-slow,

work-to-rule, sit-ins or lock-ins and lockouts. The various forms of labour strike are outlined

below as follows:

Traditional strike (Primary strike)

Primary strikes are a conventional form of industrial action that is directly aimed at the

employer or group of employers with whom the grievance is lodged against (Finnemore,

1996). Garber and Potgieter (2007) defined a traditional strike as “an intensive and a brief


suspension of workers’ services from the firm to remove concerns in the employment

relationship that the employer is willing to offer when negotiations take place”.

Secondary strike (Sympathy strike)

Secondary strikes are regarded as a sympathetic form of industrial action that occurs as a

result of a primary strike (Chand, 2016). The Labour Relations Act of 1995 defines a secondary

strike as, “a strike or conduct in contemplation or furtherance of a strike that is in support of a

strike by other employees against their employer but does not include a strike in pursuit of a

demand referred to a council if the striking employees employed within the registered scope

of that council have a material interest in that demand”.

Go-slow

Go-slows are a form of labour strikes that is characterised by a slowdown in a firm's normal

level of production, as a result of workers taking more time than usual to complete their work

(Dundon, 2011). Go-slows creates difficulties on the part of the employer to justify wage cuts

and/or implement disciplinary action due to workers' attendance at their workstations (Zondo,

2009). According to Hammett et al. (1957), go-slows are pressure tactics that are less risky

than a full-on strike. Adavbiele (2015) indicates that for a go-slow to fall within the definition of

strike action and be offered protection, it must be concerted, retard the progress of work and

be accomplished by industrial demand.

Work-to-rule

Employees in a work-to-rule form of labour strike slowdown work by insisting on strict

interpretations of duties stipulated in their employment contract or recognition agreement

(Grogan, 2014). According to Swepston (2013), by employees requesting detailed instructions

on how to complete tasks, production is negatively impacted. A firm often devises newer and

quicker methods of production, which do not amount to a strict amendment of workers

contract, as result workers can refuse to adopt new methods of work and retarded work

processes (Mbona, 2014). Consequently, the enforcement of disciplinary action and refusal of

remuneration becomes difficult to employ.

Sit-ins or work-ins

Sit-ins or work-ins are labour strikes in which workers disrupt operations by occupying their

workplace, obstructing the employer’s control over work processes (Valticos, 2013). This

action constitutes a protected strike as it results in the retardation of the work process (Rycroft

& Jordaan, 1991).


Lockouts

According to Kujinga and Van Eck (2018), lockouts are a deprivation of work premises on the

part of the employer to force workers to accept their demands. Lockouts are employer’s

recourse to labour strikes and are a means of last resort to compel workers to submit to their

demands (Venter & Levy, 2014). Lockouts can either be offensive or defensive. During

offensive lockouts, employers seek to impose a request by preventing employees from

entering their place of employment (Maddux, 1967). Defensive lockouts occur in response to

a strike and usually occur when the employer wants to enforce the seriousness of their final

offer or remove striking workers from their premises (Leroy, 1996). Defensive locks can be

implemented to legitimise non-payment of wages to striking workers (Botha & Lephoto, 2017).

2.3 A THEORETICAL FRAMEWORK FOR LABOUR STRIKES

Economists have long been interested in modelling collective bargaining (Filer et al., 1996).

Their interest in labour strikes has resulted in several competing explanations for the existence

of labour strikes in the face of the Hicks paradox (Hirsch & Addison, 1986). According to

Ehrenberg and Smith (2000), Sir John Hick’s model of strikes in the bargaining process is the

first, simplest and well-known model explaining the existence of strikes. Sloane et al. (2013)

suggested that in the face of Hick’s paradox two of the best-known models to explain collective

bargaining were proposed by Zeuthen-Harsanyi (1956) and Ashenfelter-Johnson (1969). The

competing models are outlined below to provide context to how labour strike ensues,

beginning with Zeuthen-Harsanyi (1956), followed by the Ashenfelter-Johnson “political

model” and ending with Hicks paradox.

The Zeuthen-Harsanyi model

One of the best-known models of collective bargaining proposed is that of Zeuthen (1930),

whose model is sequential and focuses on the willingness of bargaining agents to risk the

possibility of a labour strike by rejecting the initial offer made by opposing bargaining agents

(Saraydar, 1965). Zeuthen’s model was reformulated by Harsanyi (1956) and was

subsequently renamed as the “Zeuthen-Harsanyi model” (Crawford, 1980). Harsanyi

demonstrated Zeuthen’s model by making use of an axiomatic approach, which specified a

set of criteria’s that a solution should satisfy (Bishop, 1964). Harsanyi set up a Pareto optimal

criterion, which was similar to that of Nash’s (1950) and was described as more rigorous in

nature (Farber, 1986). The three criteria are set by Harsanyi through Nash (1950) namely

Pareto optimal, Pareto improvement and Pareto sub. Figure 2.1 below demonstrates

Harsanyi’s reformulation of Zeuthen’s model:


Figure 2.1: The Zeuthen-Harsanyi Bargaining model

Source: Sloane et al. (2013)

Figure 2.1 illustrates the bargaining proceedings afforded by Zeuthen-Harsanyi’s model, which

illustrates the three Pareto optimal criteria. Bishop (1964) demonstrates Zeuthen’s theory by

making use of a static utility frontier curve, which represents gains from bargaining agents

derived from settlements. According to Hamermesh (1973), bargaining agents are likely to

assume extreme positions, denoted by A and B, this is due to the likelihood of the negotiations

process encompassing an element of bluffing. Zeuthen-Harsanyi’s negotiations proceed with

the assumption that bargaining agents have compared the utility derived from accepting a

certain offer made by the opposing party and the expected utility of turning down an offer and

risking labour strike in anticipation of a more favourable offer (Damme, 1986).

In Figure 2.1 unions are denoted as E, while the employers are denoted as F. Unions in the

bargaining process are said to gain utility from an offer by the employer 𝑢𝐸𝐹, whereas the utility

from its own offer is set at 𝑢𝐸𝐸 if its offer is accepted by the employer and 0 if it is rejected

(Harsanyi, 1956). Unions will hold out on its own offer: 𝑢𝐸𝐹 ≤ (1 − 𝑐𝐸)𝑢𝐸𝐸, whereas 𝐶𝐸 is the

probability the union attaches to the probability of disagreement (Nash, 1953). Nash (1953)

further states that equally, the employer will hold out for its own offer if: 𝑢𝐹𝐸 ≤ (1 − 𝑐𝐹)𝑢𝐹𝐹,

whereas 𝑢𝐹𝐸 denotes the employer’s utility from an offer made by the union, 𝑢𝐹𝐹 the utility

from its own offer if accepted by the union, and 𝐶𝐹 is the perception of the probability of

disagreement. According to Harsanyi (1977), the rearrangement of each inequality thus gives

the maximum probability that each side will risk in holding out for their own preferred outcome

as 𝑐𝐸 ≤𝑢𝐸𝐸 −𝑢𝐸𝐹

𝑢𝐸𝐸 and𝑐𝐹 ≤

𝑢𝐹𝐹−𝑢𝐸𝐹

𝑢𝐹𝐹 .


Zeuthen assumes the party with the lower value of c, the bargaining agent’s willingness to risk

labour strike, is likely to make some form of concession (Svejnar, 1980). Union are likely to do

so if 𝐶𝐸 ≤ 𝐶𝐹, which will be the case if, on substitution and rearrangement of, 𝑢𝐸𝐸𝑢𝐹𝐸 ≤

𝑢𝐸𝐹𝑢𝐹𝐹 (Coddington, 2003). The inequality equation represents the utility outcome of the

negotiation, with the left side representing the hatched area and the right-hand side

representing the dotted area in Figure 2.1. The outcome of Figure 2.1 thus satisfies the Pareto

optimal criterion for the union to concede. The effect of this concession will be to raise the

utility product 𝑢𝐸𝐸𝑢𝐹𝐸 until it is large enough to reverse the inequality and elicit a corresponding

concession by the employer will in a similar way, increase the utility product 𝑢𝐸𝐹𝑢𝐹𝐹 that it

proposes (Vestchera, 2018). Successive concessions thus raise the overall size of the utility

gains (the bargaining process is a positive-sum game), with the outcome being where this

product is maximised – point C in Figure 2.1 – which coincides with equal sharing of the utility

gains (i.e.𝑢𝐹∗ = 𝑢𝐸

∗ ).

Ashenfelter-Johnson (Political model)

Ashenfelter-Johnson's model also referred to as the “political model” is regarded as the most

influential theoretical model of labour strikes (Lewin et al., 1992). The Ashenfelter-Johnson

model is referred to as the “political model” due to its nature of involving three parties in the

negotiations process of collective bargaining (Dickerson, 1992). The negotiations process in

Ashenfelter-Johnson’s “political model”, include management, union leaders and the rank and

file union representatives also referred to as a principal-agent relationship (Gart, 1966).

Ashenfelter-Johnson’s model argues that principal-agents enter negotiations with competing

agendas and varying information regarding involved parties' concession schedule (Nayar,

1996). According to Siebert et al. (1985), a union leader’s objectives include the union’s

survival and growth as well as their own political survival, which at times does not coincide

with the interest of its members. Firms enter negotiations with the intent to retain the present

value of their current and future profits, whereas union file members intend to optimise future

employee benefits (Rosa, 2013).

Rank and file members are known to be more extreme in their wage demands than their

leaders, which is as a result of their lack of knowledge of their employee’s concession

schedule (Ross, 1948). Union leaders may realise within negotiations that their members’

demands are unattainable, and should they not be able to persuade their members to concede

and accept a lower increase, unions may have to incur a strike (Cramton & Tracy, 2002).

Union leaders, as a result, are forced to strike rather than risk being seen to be colluding with

management, even though this may not be in the interest of its members (McConnell, 1989).


Due to the costs associated with strikes, union member’s aspirations gradually moderate over

time low enough for union leaders to settle without appearing to have colluded with

management, due to the cost of strike action (Booth, 1995).

As a result, Ashenfelter and Johnson (1969) concluded that labour strikes are the equilibrating

mechanism that squares up union membership’s wage expectations with what the firm may

be prepared to pay. Subsequently, Ashenfelter and Johnson (1969) define unions concession

schedule as 𝑦𝐴 =∆𝑊

�̅� proportional wage increases acceptable to rank and file members, where

∆𝑊 are the absolute wage increase and �̅� the existing wage. They assumed that the union’s

concession depends on the length of the strike and as a result formulated according to:

𝑦𝐴 = 𝑦∗ + (𝑦0 − 𝑦∗)𝑒−𝑡𝑠

𝑦∗ = 𝑙𝑜𝑤𝑒𝑠𝑡 𝑎𝑐𝑐𝑒𝑝𝑡𝑎𝑏𝑙𝑒 𝑤𝑎𝑔𝑒𝑠

𝑆 = 𝑆𝑡𝑟𝑖𝑘𝑒 𝑙𝑒𝑛𝑔𝑡ℎ

𝑦0 = 𝑊𝑎𝑔𝑒𝑠 𝑎𝑐𝑐𝑒𝑝𝑡𝑎𝑏𝑙𝑒 𝑎𝑡 𝑡ℎ𝑒 𝑠𝑡𝑎𝑟𝑡 𝑜𝑓 𝑛𝑒𝑔𝑜𝑡𝑖𝑎𝑡𝑖𝑜𝑛𝑠

𝜏 = 𝑡ℎ𝑒 𝑟𝑎𝑡𝑒 𝑜𝑓 𝑑𝑒𝑐𝑎𝑦 𝑜𝑓 𝑎𝑐𝑐𝑒𝑝𝑡𝑎𝑏𝑙𝑒 𝑤𝑎𝑔𝑒 𝑖𝑛𝑐𝑟𝑒𝑎𝑠𝑒𝑠 𝑑𝑢𝑟𝑖𝑛𝑔 𝑡ℎ𝑒 𝑠𝑡𝑟𝑖𝑘𝑒

Figure 2.2: Ashenfelter and Johnson's model ─ The union concession curve

Source: Ashenfelter and Johnson (1969)

Figure 2.2 illustrates union leaders’ pursuit of their own objectives in meeting the level of

benefits acceptable to their members, along with firms assumed knowledge of union’s

concession schedule parameters and attempt to maximise the present value of its current and

future profits, choosing to pay higher wages by agreeing to the union’s last demands, or

refusing their demands and accepting a strike to secure a lower settlement. The outcome of


Ashenfelter-Johnson Political model was illustrated by Farber (1978) and was depicted as

follows:

Figure 2.3: Ashenfelter and Johnson's model-concession outcome

Source: Boeri and Van Ours (2013)

Farber (1978) merges the firm’s iso-profit contours with the union’s concession schedule

curve. In Figure 2.3 the firm’s iso-profit contours are represented by . The contour curves

closer to the origin, which represents higher profits for the firm. The firm in this regard

maximises profits subject to the union’s concession schedule. Figure 2.3 presents two

scenarios with the firm accepting a strike on the left resulting in a concession at tangency A

and the firm avoiding a strike and accepting union’s demands on the right at tangency B.

According to Sapsford and Tzannatos (1993), despite being regarded at the most influential

and intuitive model, Ashenfelter and Johnson’s “political model” was criticised for assuming:

• Strikes are seen to be caused by unions alone;

• Union leadership is essentially passive and allow their members to go on strike; and

• Asymmetry of treatment between a maximising employer with perfect knowledge and a

non-maximising union with ignorant members.

Hick’s bargaining theory

Sir John Hick’s model of labour strikes is one of the earliest and most widely employed models

of labour strikes (Elliot, 1990). Hick’s paradox models the bargaining process by which

bargaining agents form concessions to reach a bargaining agreement (Kennan, 1986). Hick’s

model incorporates a union resistance curve and employer concession curve (Saraydar,

1971). The union resistance curve illustrates the length of time that workers would be prepared


to strike rather than allow their wages to fall below the corresponding wage level, whereas the

employer’s concession curve illustrates the wage rise the employer will be willing to concede

to rather than experience the cost associated with the concession just balance (Hicks, 1932).

Figure 2.4: Hick's Bargaining Model

Source: Sapsford (1980)

Figure 2.4 illustrates the Hick’s bargaining theory, which describes the process of concessions

that will be made by bargaining agents as they move towards an agreement. The employer

concession curve in Figure 2.4 is drawn upward sloping illustrating the expected duration of a

strike and the increased cost of a strike, it demonstrates the employer’s willingness to concede

to higher wages to avoid the high costs that come with strikes (Pantsios & Polachek, 2017).

However, the employer concession curve becomes progressively shallower, reflecting the

existence of an upper bound limit on acceptable wages the employer will agree to regardless

of the duration of the strike, indicating when it will prefer to shut down rather than coinciding

to union demands (Flatua, 2001).

The union resistance curve is assumed to be negatively sloping considering workers' ability to

contemplate longer work stoppages with their associated loss in earnings (Riddel, 1980). The

union resistance curve and employer concession curve intersect as the length of the strike

increases, representing the maximum expected strike length (Shove, 1989). According to

Laing (2011), should the strike last longer than the maximum expected strike length the losses

associated with the strike will be so great that workers will instead prefer to simply accept the

competitive wages.


Hick’s theory argues that if bargaining agents were equally informed about the concession

and resistance curves, and were able to identify an equilibrium point, bargaining agents would

have agreed at wage 𝑊∗ and would have avoided the costs that would otherwise be suffered

by both parties (Rice, 1977). Therefore, Hick’s states that rational fully informed bargaining

agents would never engage in labour strike considering it is always better to negotiate.

2.4 COLLECTIVE BARGAINING

Le Grange (1996) defines collective bargaining as “a process of decision making between

employers and trade unions, to arrive at an agreed set of rules that govern the substantive

and procedural terms of the relationship between the employer and trade unions, and aspects

of and issues arising out of the employment situation”. Somer (1980) defines collective

bargaining as “the continuous relationship between an employer and a designated labour

organisation representing a specific unit of employees to negotiate written terms of

employment”. Collective bargaining is entered into with the intent of reaching cordial

agreements, through negotiating in good faith (Ndumo, 2005). Seedat (2003) describes

collective bargaining as the key determinant of an amicable labour relationship between

employer and employee, which provides organisational rights to union representatives and

facilitates continuous centralised bargaining councils. The International Labour Organisation

(1998) describes collective bargaining as “the fundamental right and the key means by which

employers and their organisation and trade unions establish fair wage and working conditions,

on behalf of their employees”.

2.5 PURPOSE OF COLLECTIVE BARGAINING

The purpose of collective bargaining is to reach an agreement through compromise and/or

concessions (Bendix, 2000). The process of collective bargaining is initiated with the intent of

regulating and establishing new terms and conditions of employment (Davidov, 2004).

Collective bargaining carries out an economic function that establishes fair wages and working

conditions, a social function that acts as a judicial system that protects the rights of employees

from arbitrary action by management as well as a political function that brings democracy to

the workplace (Rycroft & Jordaan, 1992).

The collective bargaining process is essential as it provides employees with a sense of

respect, responsibility and dignity (Gernigo et al., 2000). Collective bargaining strengthens the

workforce and increases employee morale and productivity. According to Smriti (2004),

collective bargaining further protects and discourages employers from making unilateral

decisions regarding employee working conditions. Collective bargaining creates a mechanism


of effectiveness and efficiency (Anon, 2006). The collective bargaining process creates ease

in the agreement review, conflict resolution, and communication.

More importantly, collective bargaining reduces the cost of high labour turnover, creates

stability and ensures continued productivity within the firm (Montoya, 2015). In addition to

employee and employer benefits at a social level collective bargaining creates peace within

the labour market, it creates a harmonious labour environment, which translates into social

and economic development as the discrimination and exploitation of workers are continuously

regulated (Harrison, 2004).

2.6 COLLECTIVE BARGAINING AGREEMENT

The collective bargaining process is concluded with the formation of a collective bargaining

agreement. A collective bargaining agreement is a written agreement between the employer

and employees’ trade union, which stipulates the terms and conditions of employment

concerning the employee following the negotiation processes (Gorman, 1976). The bargaining

agreement outlines working conditions, working hours, remuneration, bonuses and work

benefits (Davey, 1987). The Labour Relations Act of 1995, defines a collective bargaining

agreement “as a written agreement concerning the terms and conditions of employment or

any other matter of mutual interest concluded by one or more employees, one or more

registered employers’ organisations, or one or more registered employers and or

organisations”. A collective bargaining agreement functions as a labour contract between a

labour union and the employer (Schnabel et al., 2005). The collective bargaining process is

initiated in instances where an existing agreement is terminated and requires a review when

a conflict of interest arises, and existing agreements are rejected, or when disputes or

grievances arise, and a renewed agreement is required (Nel, 2002).

2.7 THE NEGOTIATING PROCESS

The negotiation process of collective bargaining comprises three stages, namely: preparation

and discovery stage, bargaining stage and resolution stage (Anthopoulos &

Xristiananopoulou, 2012).

Preparation and discovery

During the preparation and discovery stage leading up to negotiations, bargaining agents are

required to gather all relevant data and information, set out bargaining objectives and establish

the tone of the proceedings (Craver, 2007). The preparation stage of the negotiations is an

important stage of the process that involves unions engaging in consultative sessions with


union members regarding the status of their current wages, working conditions and grievances

(Katz et al., 2015). Correspondently, employer representatives assemble intimate knowledge

of the organisation, its structure, its current and projected financial position, total wage bill and

other labour costs as well as productivity levels (Fells, 2000). Together with the knowledge of

the union, its membership numbers, their likely aims, objectives and approach to negotiations

based on the previous agreements should be explored.

The outcome of the engagement forms the basis for the bargaining agent’s demands, which

sets the tone for negotiations (Stein, 1989). During the preparation stage, details of the

engagement are outlining, which entail where negotiations are to take place, the rules of

engagement, publicity releases, the payment system of union representatives and allied

issues (Wakelin, 2012). Preparation for negotiations enables bargaining agents to move from

conflicting perceptions and behaviours to co-operative perceptions and behaviours (Zartman,

1989).

Negotiations

The opening stage of negotiations is an extremely important occasion; wherein the tone of the

negotiations is set, and demands are clearly and unambiguously outlined, thus expediting the

proceedings (Finnemore & Van der Merwe, 1994). Opening statements within negotiations

include statements of intent in which parties outline what they would like to achieve (Suffield

et al., 2019). The opening statement in the negotiations is often characterised by extremely

high proposals and counteroffers by bargaining agents, which may lead to labour strikes if

extremely unreasonable (Venter & Levy, 2014). As a result, the bargaining process may be

longer due to varying counteroffers, complexities of the bargaining agent’s demand and the

number of bargaining proposals.

Outcome

Bargaining agents may employ either a distributive or integrative approach when negotiating

(Walton & McKersie, 1965). Walton (1965) describes the distributive approach as a

competitive approach by agents bargaining over the larger claim of resources. The distributive

approach is often referred to as the win-lose approach (Slabbert & Swanepoel, 1998).

Negotiators who make use of the distributive approach are not bothered by the response of

the opposing bargaining agents involved (Han et al., 2012). The distributive approach is

characterised by bargaining agents contend or concede to the final offer in the negotiations

process (Thompson et al., 1996).


Distributive approach

The distributive approach to collective bargaining is a competitive bargaining strategy in which

one party gains only if the party loses. Section 2.7.3.1. presents the various forms of

distributive approach namely contending, conceding and Integrative approach.

Contending

According to Han et al. (2012), bargaining agents believe that they can force the other party

to concede to their demands, thus rejecting opposing agent’s final offer, resulting in a strike or

lockout on the part of respective bargaining agents. Fells (2009) states that there are several

factors that impact the contention of bargaining agents’ final offer, which include: agents

placing a higher value on a claim that is supported by a likely outcome, expecting the other

party to concede, having no time constraints, having little concern for future interactions with

the other party, and having little concern for the other party’s outcome.

Conceding

By conceding a negotiator gives into the opposing parties' demands. Carnevale and Pruitt

(1992) believe the reasons bargaining agents conceded may be as a result of a poorly

conceived case or realised value in the continuous relationship with the opposing agent.

Venturini (1981) outlines that conceding to opposing agents' demands has the following

implications; the negotiator must account for his or her constituency, where a concession is

often rarely the mandate or desired outcome because of the cost that is invariably incurred.

By conceding on one issue, a negotiator may be perceived as weak and thus be targeted in

other negotiations. However, Carnevale and Pruitt (1992) held that conceding to opposing

agents' demands may have strategic value. By making minor concessions a negotiator

increases their leverage on more pertinent issues (Hilty & Carnevale, 1993).

Integrative approach

An integrative approach is employed when bargaining agents co-operate in their negotiation

process and focus solely on creating value for both parties (Katz & Kochan, 2000). The

integrative approach is also known as the win-win approach (Fisher & Ury, 1983). According

to Thompson (1991), by adopting an integrative approach, bargaining agents embark on a

culture of relationship-building and information sharing. However, Hawes and Fleming (2014),

state that the integrative approach entails collaboration among bargaining agents involved.

The integrative approach is characterised by a compromise and willingness of bargaining

agents to make concessions to achieve a mutually acceptable outcome (Lewicki et al., 2006).


Compromising

According to Blake and Mouton (1979), concessions are central to seeking a compromise.

However, bargaining agents should seek a compromise with their underlying mandate and

issues in mind. Effective collective bargaining negotiations are a fundamental part of sound

labour relations (De Dreu et al., 1946). By addressing issues in an open forum and actively

seeking solutions, parties are better positioned to build an employment relationship based on

trust and understanding (Michael & Micheal, 2012). Effective collective bargaining is important

in light of achieving social, political and economic transformation through increased

productivity, job security, motivation and involvement in union activities (Olotuah & Olotuah,

2016)

2.8 LEGAL PROCEDURE TO A LABOUR STRIKE

The Labour Relations Act of 1995 stipulates that “workers have the right to strike and

employers have the right to a lockout, where a resolution cannot be obtained in a labour

matter”. Furthermore, the Labour Relations Act of 1995 outlines procedures, criteria and

limitations that apply to warrant a protected strike. Figure 2.5 illustrates the legal procedure

together with set criteria for a strike to be regarded as protected. Cliffe Dekker Hofmeyr (2019)

describes a protected strike as a strike that complies with the set criteria in the Labour

Relations Act of 1995, where the subject matter of the strike is legitimate and procedural

requirements are complied with before the strike commences.


Figure 2.5: Legal procedure towards protected strikes and lockouts

Source: Bendix (2001)

Protected strikes and lockouts

Section 64 of the Labour Relations Act, 66 of 1995 warrants the following conditions to be

adhered to for a strike or a lockout to be regarded as legal:

• The dispute must have been referred to a Bargaining Council or the Commission for

Conciliation, Mediation and Arbitration (CCMA);

• Opposing bargaining agents on the part of the employer or the part of the employee must

have been issued with a certificate stating that the dispute has not been resolved;

• A 30-day period must have elapsed since referral, or an agreed-upon extension period

has elapsed since the referral was received by the council or the commission; and

• In the event of a proposed industrial action on the part of the employee, 48 hours written

notice of a strike is issued to:

a. The employer; or

b. A council (if the dispute relates to a collective agreement to be concluded in a

council); or

c. To an employers’ organisation (if the employer).


• In the event of a proposed lockout by the employer, 48 hours written notice of a lockout is

given to:

a. The trade union.

b. To the workers (should workers have no trade union representatives).

c. A council (if the dispute relates to a collective agreement to be concluded in a

council).

• In the event of a proposed strike or lockout where the state is the employer, a seven-day

notice of the commencement of a strike or lockout must be issued to representatives of

the opposing bargaining agent.

Illegal strikes and lockouts

Section 64 of the Labour Relations Act, 66 of 1995 regard strikes and lockouts to be illegal

and unprotected if:

• A collective bargaining agreement or arbitration award binds the parties;

• An agreement is referred for arbitration or to the labour court;

• A wage determination binds the parties and it is less than 1 year old; and

• The parties are providing an essential or maintenance service.

When strike or lockout procedures do not apply

• The Labour Relations Act of 1995 outlines that strike, and lockout procedures do not

apply when:

- Bargaining agents follow set procedures in a council’s constitution, (The strike or

lockout follows a predetermined collective agreement procedure);

- Workers strike in response to an illegal lockout, (employers lock workers out in

response to an illegal strike); and

- The employers unilaterally change workers’ working conditions and refuse to

restore them.

2.9 REVIEW OF PREVIOUS STUDIES

The effects of labour strikes on financial markets have been researched at length in the past

decade. Researchers have analysed the effects that labour strikes have had on shareholder

value, equity returns, economic performance, and investor confidence. These studies made

use of regression analysis, event study methodology and accounting-based ratio analysis.

Studies by Neumann (1980), Bhana (1997), DiNardo and Hallock (2000) and Seedat (2013)


are presented below to present related findings of the effect of labour strikes on the share

return of publicly listed companies.

The earliest paper on labour strikes and financial markets was by Neumann (1980), who

observed the predictability of labour strikes and the effect they have on the share return of

publicly listed companies. Neumann (1980) opposed the narrative that strikes are random and

unpredictable and that they are as a result of an error in the bargaining process, as well as

barging agents’ anticipation of opposing agents' demands. Neumann (1980) challenges Hick’s

(1966) theoretical rationale of faulty negotiations. Neumann (1980) indicates that the reason

labour strikes are predictable is due to political or organisational lines, which outlines the need

for labour strikes, as they facilitate unions’ relevance. He argues that faulty negotiations are

contradictory to the concept of mature collective bargaining, a term used to refer to long-term

labour market equilibrium.

Neumann’s rationale of labour strikes being predictable hinges on protocols outlined during

the negotiations process. He defines a protocol as “a set of rules whose value depends on the

cost of bargaining agents allowing a dispute to go unresolved and for alternative methods of

resolving labour disputes to take course”. Neumann (1980) elaborates that “a protocol is best

thought of as a complex mixture of contractual statements and determined rules for a set

procedure at a specific event a ‘dictionary’ that translates the actions and statements of the

parties into a common language”. According to Neumann (1980), the foundation around the

concept of a set protocol is embedded in contractual relationships. Neumann (1980) indicates

that the idea of bargaining relationships as protocols, with behaviour signalling by both parties,

explains a certain type of predictability in strikes and has implications for the statistical study

of several aspects of strike activity, which included the duration of a strike and predictability of

the strike.

Neumann (1980) indicates that if strikes were unpredictable losses from the strike activity

should be concentrated on the day of the strike, and if they were completely predictable the

market would not factor in the possibility of a strike before the day of announcement or

commencement of the strike. Making use of the capital asset pricing model and the EMH

Neumann (1980) proved that strikes are predictable. Evidence from his study indicates that

several trading days before the commencement of the strike and the impending conclusion of

the strike resulted in declines in the market value of the affected firms. According to Neumann

(1980), there is not a full adjustment in the share value of affected firms, however, there is a

significant negative excess return on the date of conclusion of the strike. Neumann (1980)

further found that the share price of the security does not recover from the effects of the strike

and that the longer the strike the greater the cost implication to the firm.


Another study was conducted by Bhana (1997), whose objective was to determine the effects

of industrial strikes on the value of shares listed on the JSE from 1983 to 1993. His study

observed the short-term effect of labour strike on companies listed on the JSE, which

comprised a random sample of 50 companies that were involved in labour strikes during the

10-year period. The observed sample was restricted to companies whose shares were

continuously listed on the JSE during the event period.

Bhana (1997) established that strikes have a negative effect on the value of a firm’s share

price and that losses are not temporary, meaning that losses to firms are sustained and firms

do not recover from incurred losses. A window period of 30 days before the announcement of

a strike and 30 days after the strike commenced were observed. In the event window, Bhana

(1997) found that there were significant movements in the price of a firm’s shares 5–10 days

before the announcement of the strike, the day before the announcement, on the day of the

strike and 10 days after the strike. Bhana (1997) findings were indicative of the notion that

capital markets are usually able to anticipate whether a looming contract deadline will result

in a strike or settlement.

Bhana (1997) states that sophisticated investors who had access to news wire stories would

have had access to information the day before the announcement of the strike, thus it is not

unexpected that significant changes were found before the announcement. The study

concluded that labour strikes have a negative effect on abnormal returns and that financial

markets react spontaneously to the receipt of public information prior and post the

announcement of the strike. As a result of the predictability of the strike, Bhana (1997)

concluded that there were inefficiencies in the JSE. Bhana (1997) also concluded that the

longer the duration of the strike the greater the cost implication. A study conducted by DiNardo

and Hallock (2000) focuses on the effects of labour strikes on financial markets in the early

1920s and late 1930s. The study makes use of a combination of labour and market data, to

assess the market’s interpretation of labour conflict and the effect of major strikes between

world wars on detailed industry stock prices.

The study analysed a sample of 36 strikes. Due to limitations of market data captured during

the study period, the first strike started in January 1925 and the last strike ended May 1937.

The study observed strikes occurring in 17 different industries, having an average strike

duration of 5.5 months. DiNardo and Hallock (2000) observed labour strike per industry and

on a monthly base, making the event month 0. The study observed the strike in terms of month

0 to month +1, -1 to month +1, -2 to month +2 and -3 to month +3. However, DiNardo and

Hallock (2000) made an analysis of -1 to 1 month due to its outcome and relevance.


DiNardo and Hallock (2000) found that labour strikes have a negative effect on the industry

stock value of a firm. DiNardo and Hallock (2000) further revealed that prolonged strikes,

violent strikes, strikes where unions “win”, industry-wide strikes that lead to union recognition,

and strikes that lead to large wage increases lead to larger negative share returns than the

actual strike itself. The study further establishes that market prices adjust to the arrival of

“news” of a strike long before its announcement. DiNardo and Hallock’s (2000) study strongly

suggests that although the financial markets generally expected unions to “lose”, they viewed

union victories as quite important determinants of the share of firm profits going to

stockholders.

A similar study was conducted by Seedat (2013) whose study was aimed at analysing the

effects of the labour strike on the share value of the South African gold industry, from January

2007 to December 2012. The study observed the impact of unprotected strikes and protected

strikes and their impact on the day of the announcement and their effect as a result of the

duration of the strike. Seedat (2013) selected 30 companies that were affected by labour strike

and observed 70 days prior and 30 days following the day of the announcement were

observed.

Seedat (2013) established that labour strikes do not have a negative effect on shareholder

value of securities, with less significance found in unprotected strikes. Due to the nature of the

strike, firms were not financially obligated to meet worker’s demands, thus no financial

implications were perceived (Seedat, 2013). The opposite was found in protected strikes,

where greater significance was found in share price due to perceived financial implications of

the strike by investors. Seedat (2013) also revealed that strikes that lasted for a shorter period

have greater significance than prolonged strikes, proving that strikes that have a shorter

duration have greater financial implications. This is due to firms giving into labour unions’ high

initial demand in the negotiations process after the firm realises its financial capacity to meet

their demands and cannot afford a halt in production.

2.10 GLOBAL FINACNCIAL CRISIS

Many economists consider the 2007–2008 GFC to have been the most severe economic crisis

since the Great Depression of the 1930s (Eigner & Umlauft, 2015). The GFC was a worldwide

economic event that began in 2007 with the collapse of the US housing market, which

developed into an international banking crisis (Duignan, 2019). The gradual increase in the

default rate in the US house market developed into what is now known as the US subprime

mortgage crisis (Kojucharov et al., 2008). Owing to deregulation, low interest rates,

securitisation, the Community Reinvestment Act of 1977 (CRA), reckless lending and


mortgage guarantees the US subprime housing market led to the financial crisis and

consequently a global recession (Jurek & Marszaùek, 2014).

According to Tobak (2010), the intentions of the CRA were misused and misguided by a long

string of politically motivated amendments to the act. Tobak (2010) highlights that the checks

and balances that were put in place to ensure that lenders do not write bad loans were

gradually removed. The CRA was enacted to create access to home loans for low-income

households (Quercia & Janneke, 2009). Referred to as subprime lending. In 1997 the US

administration placed pressure on public sector mortgage lending institutions Fannie Mae and

Freddie Mac to start lending to low- and moderate-income households (Taylor, 2008). This led

to ease in credit conditions, weak and fraudulent underwriting practices and predatory lending

(Fligstein & Roehrkasse, 2015).

The changes in the credit market led to a high mortgage approval rate, which resulted in an

appreciation in the US housing market and subsequently the “subprime mortgage bubble”

(Mckibbin & Stocekel, 2009). Homeowners, according to Justiniano et al. (2015) took interest

in the low interest rates and growing value in the US housing market and extended a line of

credit against their homes. Homeowners did this to buy up more houses and resell against

their growth in value (Franzese, 2013). Interest rates in the US rose from 1 per cent to 5.35

per cent between 2004 and 2006. The rapid rise in interest rates placed a strain on

households, resulting in high default rates as homeowners could no longer keep up with

regular payments. This led to high delinquency rates and subsequent foreclosures.

The US banking sector took a strain due to a high delinquency rate, which developed from a

rapid devaluation in financial instruments (Farhi & Cintra, 2009). In 1999, US banks lobbied

congress to enact the Financial Services Modernisation Act (FSM), which allowed banks to

use depositor’s money to invest in derivative instruments (Amadeo, 2019). Amadeo (2019),

further indicates that banks argued that the enactment of the FSM Act would enable them to

compete with foreign firms. The Commodity Futures Modernisation Act, in the year to follow,

exempted credit default swaps and other derivatives from regulations (Lipton, 2018). The US

banking sector took advantage of the deregulation of bank laws and embarked on a journey

of securitisation. With deregulation in place, conducive economic conditions and heightened

endorsement of CRA, banks created interest-only loans that were affordable to subprime

borrowers (Chwieroth, 2011). According to Prithard (2019), interest-only loans are loans that

temporarily allows borrowers to pay only the interest costs, without requiring them to pay down

the loan balance.


Banks later securitised subprime loans and package them as Collateralised Debt Obligations

(CDOs), also known as mortgage-backed securities, and sold them to investment firms (Baily

et al., 2008). According to Buffet (2016), banks were able to pass CDOs as low-risk securities

to investors as they were often backed by credit default swaps. CDOs were a means for banks

to remove risks on their balance sheets and maintain prudential banking requirements. Banks

demanded that more mortgages be sold to support the profitable sale of derivative instruments

(Amadeo, 2019). The demand for increased sales of mortgages led to fraudulent underwriting

practices and predatory lending (Patterson & Koller, 2011). As a result, the percentage sale

in subprime mortgages doubled, from 9 per cent to 20 per cent, between 2000 and 2006

(Ariccia et al., 2008). By 2007 the US housing market had grown into a $1.3 trillion-dollar

industry, ending the 2001 recession.

According to Fiorillo (2018), in 2004 when the US Federal Reserve began to increase interest

rates, homeowners could no longer afford payments on their loans and as a result, investors

suffered immense losses. Fiorillo (2018) further elaborates the Federal Reserve’s interest rate

hikes placed pressure on the housing market, causing the US subprime housing bubble to

burst. Investors became conscious of CDOs and were reluctant to participate in the credit

market (Reiff, 2013). The scepticism in the CDO market created a credit freeze in the banking

sector as banks become warry of interbank lending, owing to scepticism over the extent of

bad loans on their rival’s books (Afonso et al., 2010). This created a solvency and liquidity

crisis, which led to a loss in confidence in the banking sector and the credit market

(Chiaramonte, 2018). Investors and depositors panicked and began to withdraw their equity

and cash deposits from banks (Morgenson, 2011).

The impact of the subprime mortgage crisis in the US was quickly felt across the world,

affecting global financial systems (Baxter, 2013). As liquidity challenges became more serve

investors around the world began to withdraw funds from emerging markets and placing them

in safe-haven investments to avoid further risks (Kynge, 2015). Stock markets around the

world declined. International banks began tightening operations and cancel billions in bond

sales owing to market conditions (Berrospide, 2012). Consumers around the world were soon

hard hit by an increase in the cost of living, which caused a general slowdown in global

economic activity and a rise in prolonged unemployment (Allen & Gale, 2007). According to

Nanto (2009), the sudden slowdown in large, industrialised economies resulted in a call for

stimulus packages by the US government to restore confidence in the financial system and

restore solvency and liquidity.


The impact of the Global Financial Crisis on South Africa

The South African economy was severely affected by the GFC. Unlike most developing

countries, emerging markets and many other industrialised countries (Rena, 2017). South

Africa has historically been a significant player in international markets (Padayachee, 2010).

Owing to its open market and trade linkages to the global arena. The South African economy

experienced a deterioration in foreign direct investments, remittances and a large decline in

commodity prices (Zini, 2008). Rena and Msoni (2014) indicate that the GFC sent the country’s

economy into a recession in 2008/09 for the first time in 19 years. Exposing some of the

country’s vulnerabilities. Steyler and Powell (2010) explain that the GFC and the recession

that followed exacerbated long-standing structural problems of poverty, unemployment and

inequality in the economy. Haroon (2010) further explains that the GFC has deepened an

already existing national crisis in a country where 40 per cent of the population is unemployed

and income inequality is among the highest in the world.

The GFC took a while to develop and started showing its effects in the middle of 2007 into

2008 (Gupta, 2012). Economic activity in South Africa started declining for the first time in the

last quarter of 2008 by 1.8 per cent, which was followed by a drastic decline of 6.4 per cent in

the first quarter of 2009, and thereafter 3 per cent in the second quarter of 2009 (Steyler &

Powell, 2010). This placed South Africa in a technical recession as the overall gross domestic

product (GDP) contracted by 1.8 per cent at the end of 2009 (Verick, 2010). According to

Marumoage (2014), contractions in the country’s economy resulted in large job losses as

companies retrenched and felt that they could no longer sustain operations that were no longer

financially feasible. The wide retrenchment of employees led to a significant increase in the

number of unannounced strikes, which further impacted economic output (Forstater, 2013).

As a result of economic conditions, almost a million employees lost their jobs and

unemployment grew from 21.9 per cent early to 25 per cent in 2008 (Kantor, 2018). The South

African economy was losing 198 000 jobs year-on-year in the second quarter of 2009, which

signified a bleeding labour market (Marumoage, 2014). According to Statistics South Africa

(2014), job losses were more pronounced in the more labour intense sectors of the economy,

which included the mining, manufacturing, construction and trade sector. Consequently,

according to Hofmeyr (2012), semi-skilled, unskilled workers, including the youth bore the

brunt of the recession. According to the National Treasury (2010), of the million employees

that lost their jobs, 527 000 were semi-skilled and 219 000 were unemployed youth.


2.11 SYNOPSIS

This chapter was set out to achieve the study’s first theoretical objective of contextualising

labour strikes through formulating an understanding of labour strikes, their dynamics and how

the resolve of labour strikes are established with respect to protected and unprotected labour

strikes. The chapter further presents a background of the GFC and how it affected South

Africa’s labour market, with respect to protected and unprotected labour strikes. The chapter

identifies the right to labour strikes as an importance bargaining platform for labour unions,

who have increasingly exercised their right to strike in recent years to address employee’s

disagreements and/or dissatisfaction regarding labour relation issues. The chapter presents a

brief history of labour strikes in South Africa, followed by a theoretical background to labour

strikes.

The theoretical background defines labour strikes in their various forms and provides

competing theoretical frameworks of Zeuthen-Harsanyi (1956), Ashenfelter-Johnson (1969)

and Hick’s (1932) bargaining theory. The theoretical background further presents definitions

of the collective bargaining and outlines the purpose of collective bargaining, along with the

collective bargaining agreement. A detailed process of the negotiations process to collective

bargaining is presented, together with the legal procedure to protected labour strikes. To

support the study’s findings, a review of previous papers by Neumann (1980), Bhana (1997),

DiNardo and Hallock (2000) and Seedat (2013) are presented.

Chapter 3 presents a literature review of the EHM, which aims to present the theoretical

background to efficient markets and provide a basis that will enable the researcher to establish

whether the JSE is an efficient market and whether labour strikes affect the share price

movement of publicly listed companies.


CHAPTER 3: EFFICIENT MARKET HYPOTHESIS

Believe you can and you’re halfway there. –Theodore Roosevelt

3.1 INTRODUCTION

The theory of an efficient market is one of the most debated and controversial subjects within

finance, contesting whether the arrival of information in a random and unpredictable manner

results in unbiased movement in the share price of a security (Van Wyk et al., 2012). The

subject of efficient markets is regarded as one of the most fundamental and exciting areas in

financial debates, which questions price changes in security markets and how these changes

occur (Russel & Torbey, 2002.). The excitement and controversy surrounding the subject of

efficient capital markets (ECM) attract a large number of market participants in their various

forms. Academicians, investors and portfolio managers who participate in financial markets

for their respective motives, which in end filter into establishing areas of arbitration in price

movements of securities.

The ECM has been researched extensively, following Eugene Fama’s fair game theory

(Towers, 2002). Research relating to the EMH has refined the realism of the marketplace to

include costly information, transactional costs, financing cost, agency costs and real-world

frictions (Ang at el., 2011). The fair game model is the first theory to have contextualised the

EMH (Fama, 1970). Research prior to the fair game model was extensive though it was

baseless as it lacked theoretical backing. The fair game model contended that “investors can

be confident that the current price of a security fully reflects all available information about

security, therefore the expected return of the security is consistent with its risk” (Fama, 1970).

As a result of the extensive research relating to the EMH, alternative theories and dimensions

surrounding the theory, have added to the controversy that is the EMH. Latif et al. (2011)

categorise alternative theories into fundamental, technical, market anomalies and behavioural

finance. Behavioural finance has strongly contested the concept of ECM, which brings

intriguing insights on reasons for many of the identified anomalies in financial markets (Lo,

2005). However, according to Degutis and Novickyte (2014), “the efficient market theory

remains an important part of modern finance as its empirical evidence is ambiguous, but the

concept itself is sound”.

The chapter aims to achieve the study’s second theoretical objective of providing an overview

of the efficient market, which is used as a basis of proving whether a labour strike does affect

the share price of a publicly listed company. The chapter is subdivided into seven sections

that define an efficient market, the assumptions of an efficient market, implications of EMH,


financial market anomalies, behavioural finance and efficiency review of the JSE. Finally, a

synopsis of the chapter.

3.2 EFFICIENT CAPITAL MARKETS

The theory of efficient markets was formalised by Fama (1970) who stated that “in an efficient

market, on average, the competition will cause the full effects of new information on the

intrinsic value of securities reflecting instantaneously in its actual price”. Researchers over the

past decades have redefined efficient markets, which has given rise to several versions of the

definition.

Jensen (1978) defined an efficient market as “a market that takes into consideration all

available information about a security, given the available information set, making it impossible

for traders to make an economic profit”. Ang et al. (2011) defined an efficient market as “a

market in which the price of a security reacts instantaneously without any form of bias to the

arrival of new information to the market”. Malkiel (1992) regard an efficient market as a “market

that fully and accurately reflects all relevant information relating to a security in determining

the securities price”. A simpler version of this definition was provided by Maxym (2000) who

defined “an ECM as a market in which the prices of a security adjust rapidly to the arrival of

new information”.

The idea behind an ECM is that there is very little room for arbitration in financial markets,

where investors can generate abnormal amounts of profit from movements in share prices of

a security (Delcey, 2018). The share price of a security in ECM fully reflects investor

expectations that are shaped by the available information set (Erdugan, 2012). Therefore, the

efficient market produces prices that are accurate in terms of current knowledge regarding a

security, allowing investors to make informed decisions when participating in inefficient

markets (Lorie et al., 1985).

Efficient markets are such that securities with high-expected returns have correspondingly

high levels of risk, meaning market participants within an information efficient market are

exposed to the perceived risk of a security, which is consistent with the rate of return of the

security (Reilly & Brown, 2015). Investors entering the market inherit the same amount of risk

as expected returns (Andersen & Nielsen, 2011).

3.3 ASSUMPTIONS OF AN EFFICIENT CAPITAL MARKET

The following assumptions must be met for a market to be regarded as efficient:


• A market requires a large number of independent, competing, profit-maximising

participants who analyse and value securities;

• New information arriving at the marketplace regarding securities must come in a

random fashion; the timing of individual announcements is required to be independent

of each other; and

• Competing investors attempt to adjust security prices rapidly to reflect the effect of the

new information, price adjustments by individual investors are assumed to be

independent and non-bias.

The EMH theory suggests that “the asset prices are determined by demand and supply in

competitive markets with rational investors” (Belke & Polleit, 2009). Rational investors gather

information very rapidly and immediately incorporate this information into share prices. Price

adjustments realised from ECM may be imperfect, though they present a true reflection of

investor’s perception of the security (Kehinde, 2012). This implies that price adjustments

regarding securities may under or over adjust, though the adjustments in either direction

presented by the arrival of new information to the marketplace constitute an ECM (Roschkow,

2013). Price adjustments in the market are made evident by the presence of a large number

of competing for profit-maximising investors looking to take advantage of the arrival of new

information and create abnormal profits (Titan, 2015).

The combination of the manner in which information arrives at an ECM together with a large

number of competing profit-maximising participants gives precedence to the reality that price

adjustments of securities are random and independent (Guduza & Phiri, 2017). Thus, the

assumption of an information efficient market implies that markets require a minimum amount

of trading that affect price adjustments of securities, as a result of a large number of competing

investors, rendering the market efficient.

3.4 EFFICIENT MARKET HYPOTHESIS

The EMH is divided into three forms of hypotheses namely weak, semi-weak and strong, which

are categorised concerning the type of information set involved. Fama (1970) divided the

overall EMH into sub-hypothesis in an attempt to formalise the growing empirical evidence

relating to efficient markets. EMH was conceptualised from the random walk theory, which

describes the random departure from a security’s previous price due to the arrival of

unhindered information to the marketplace. The categories of EMH are presented below:


Weak form of efficient market hypothesis

The weak form of EMH informs market participants that the current price of security fully

reflects all available information regarding a security (Karz, 2012). The weak form of EMH

suggests that no further value can be derived from analysing historical market information,

implying that market participants should not be able to consistently outperform the markets

and generate abnormal profits by making use of publicly available information (Gimba, 2010).

Historical market data in the form of price movements, trading volumes and rates of return are

easily assessable and are thus already incorporated into the share price of securities.

Technical analysis guidelines in this regard cannot be used to generate consistent profit,

implying that information is already incorporated in the market price and cannot, therefore,

affect future price movements of a security (Moberek & Keasey, 2000).

Semi-weak form of efficient market hypothesis

The semi-strong form of EMH suggests that all publicly available information concerning a

security is already incorporated into the market price of the security (Derdas, 2009). Semi-

strong EMH considers public information not limited to historical market information,

companies’ annual reports, company announcements, macroeconomic factors, political news

and all forms of information sets that are not necessarily financial in nature (Sandhar et al,

2009). As a result, the semi-strong form of EMH embraces the weak form of EMH (Khan &

Ikram, 2010). The semi-strong EMH asserts that market participants are unable to consistently

generate abnormal profits with information that is widely known, as market prices adjust rapidly

to the arrival of new information (Haugen, 2001). Therefore, discrediting fundamental analysis

when determining whether the value of a security is undervalued or overvalued.

Strong form of the efficient market hypothesis

The strong form EMH asserts that the current market price of a security fully reflects all public

and private information pertaining to the security (Lindner et al., 2010). The strong form of

EMH extends the assumption of a perfect market, wherein the prices of securities are shaped

by public and private sources of information (Malinowski, 2013). This form of EMH suggests

that company management cannot generate abnormal profits from trading on insider

information i.e. important announcements, strategies and company decisions (Clarke et al.,

2001). Chau and Dimitri (2008) assert that private information is already accounted into

securities’ market prices, the rationale behind the notion is that unbiased markets anticipate

private information before the decision is made or rather announced. Therefore, no group of

market participants has monopolistic access to information that generates superior rates of

returns (Brigham & Houston, 2007).


3.5 THE IMPLICATION OF EFFICIENT MARKETS FOR INVESTORS

The EMH has an important implication on investment analysts as well as portfolio managers.

The question of securities’ price movement regarding why they move and the changes that

take place is of importance (Dobbins & Witt, 1979). Investors participate in the securities

market to identify securities that are undervalued and can provide them with abnormal returns

on investment in the future. Several market participants believe that they can select securities

that will outperform the market and use a variety of forecast and valuation techniques, such

as fundamental and technical analysis to make investment decisions (Timmermann &

Granger, 2004). Fundamental and technical analysis respectively enables analysts to identify

undervalued securities and determine the correct timing of entering an investment

(Petrusheva & Jordanoski, 2016).

Fundamental analysis is regarded as a process of analysing macroeconomic, industry and

company-specific conditions that influence the risk-return on an investment (Abarbanell &

Bushee, 1998). Analysts that make use of this form of evaluation believe that the value of a

security is dependent on underlying economic factors (Brigham & Houston, 2007). Meaning

that if economic conditions were to change within the operating environment of a security, the

value of the security is likely to be affected. The implication of EMH on fundamental analysis

is that above-average returns can only be attained if market participants have access to

reports of superior analysis and can invest in the findings before a large number of profit-

maximising competitors establishes that there is a discrepancy in the intrinsic value of the

security (Suresh, 2013).

Technical analysis is an attempt by technical analysts, or technicians, to evaluate historical

price movements of security to generate abnormal trading profits from reoccurring patterns in

securities’ price movements (Achelis, 2000). Technicians make use of a wide range of graphs

and charts to identify buying and selling signals in historical price movements (Wilder, 1978).

Technical analysts believe that individual investors do not analyse information, nor do they act

upon it immediately when analysed (Pring, 2002). According to Bodie et al. (2014), the

implication of EMH for technical analysis is that the use of historical trading information only

should not enable the investor to generate abnormal returns, particularly if risk and transaction

costs are taken into consideration.

Portfolio management is “the art and science of making decisions regarding investment mix

and policy, matching investment objectives, asset allocation for individuals and institutions and

balancing risk against performance” (Chandra, 2012). Portfolio management decision making

entails determining strengths, weaknesses, opportunities, and threats in the choice of debt vs.


equity, domestic vs. international, growth vs. safety, and many other trade-offs encountered

in the attempt to maximise returns a]t a given appetite for risk. Portfolio management follows

either a passive or active investment strategy.

Passive investment management is the most common form of investment management

strategy, which incorporates either a buy-and-hold or indexing approach. According to Malkiel

(2003), indexing is a passive management strategy that attempts to construct a portfolio that

tracks the performance of an index. The purpose of indexing is to provide investors with

returns that match that of the identified index. Passive portfolio management minimises trading

and investing fees and avoids having to correctly anticipate the future (Walden, 2015).

Active management is a portfolio management strategy that involves major adjustments to the

portfolio. Active management relies on portfolio managers to continuously identify

undervalued securities to exploit any form of discrepancy in the intrinsic value of the security

and identify the correct timing of entering the market (Stotz, 2005). Unlike the passive

management strategy, active portfolio management requires managers to forecast securities

performance, time the market and select securities that provide abnormal returns (Block &

Hirt, 2012). An active portfolio management strategy is geared towards outperforming a

particular index (Grinold & Kahn, 1996).

The EMH emphasises that the intrinsic value of a security is accurate at all times and attempts

by investors to obtain abnormal returns for security price movement is a time-consuming

exercise, which awards inconsistent returns and is to be eroded by management costs,

taxation, transaction (Degutis & Novickyte, 2014). Thus, implications for portfolio managers

without access to information of superior analysis is to follow a passive investment

management strategy that aims to track a market rather than to outperform the market

(Jegadeesh & Titman, 1993). Portfolio returns are optimised through diversification and asset

allocation; thus, portfolio managers must construct a portfolio that is geared towards the

investor’s appropriate phase and risk profile within the investor life cycle.

3.6 FINANCIAL MARKET ANOMALIES

The EMH has been challenged extensively over the years, which has given rise to several

alternative theories that contest its premise. According to Kartasova (2014), market

participants argue inconsistencies in the EMH as a result of observed deviations from its

assumptions. Financial market anomalies are empirically observed patterns in the share price-

return of a security, which are inconsistent with EMH (Dalika & Seetharam, 2015). EMH theory

argues that market participants cannot gain abnormal returns or consistently outperform the


market. However, financial market anomalies present opportunities wherein investors are

capable of taking advantage of abnormal behaviour in the securities price movement and gain

abnormal returns (Muhammad & Rahman, 2010). Bowman and Buchanan (1995) believe that

financial market anomalies are as a result of shortfalls in models applied in testing EMH, as

opposed to inefficiencies in the market. Financial market anomalies often seem to disappear,

reverse or soothe after they have been documented and analysed, raising questions as to

whether profit-making opportunities exist in the past and have since been arbitraged or they

are simply statistical peculiarity that engrossed the attention of market participants (Schwert,

2003). There are a vast number of documented financial market anomalies, which can be

categories as fundamental, technical and calendar anomalies (Latif et al., 2011).

Fundamental anomalies

Fundamental anomalies are financial market anomalies, which are observed in the evaluation

of companies (Dana & Cristina, 2013). Financial market anomalies are found in company-

specific characteristics, selection of equity evaluation strategies and the recognition of the

company and the abnormal returns that they present. The more recognised fundamental

anomalies are the size effect, closed-ended mutual funds, neglect and Institutional holdings.

The size effects

The size effect is a financial market anomaly that observes the size of a firm in relation to its

share return. Banz (1981) discovered that the profitability achieved by small, capitalised firms

are on average greater than that of large capitalised firms. Banz (1981) affirmed that the size

of a firm serves as a proxy for risk. He found that smaller firms carry greater risk than larger

firms and as a result market forces place downward pressure on the share price of smaller

capitalised firms providing investors with higher returns (Friend & Larry, 1988). Owing to the

risk factor that small, capitalised firms carry, the investors expect equal returns for their

accepted level of risk. According to Crain (2011), researchers deem smaller firms to be riskier

than larger firms and constantly try to identify their underlying sources of risk.

The value effects

The “value effect” also known as the “book-to-market” effect, explains a market tendency for

the value of a security to outperform its benchmark security in the long run (Banko et al., 2006).

Value securities are defined as securities that trade at a lower price relative to their book value

(Fama & French, 1992). Value securities offer investors a high dividend yield and low price-

to-earnings ratio. The value effect is given rise by an overreaction to the growth aspect of the

undervalued security (Basu, 1977).


Neglected firm effect

The “neglected firm effect” explains the market phenomenon that firms that are evaluated by

lessor analysts present greater abnormal returns (Sharma, 2015). Kenton (2018) attributes

the abnormal returns of neglected securities to lower levels of liquidity and limited information

regarding the security.

Institutional holding

Institutional holding refers to the ownership of securities by investors. Market anomalies have

indicated that there is a strong correlation between high returns and securities that are held

by a few institutions (Arbel & Strebel, 1983)

Technical anomalies

Technical anomalies are financial market anomalies, which are related to technical analysis

techniques. Researchers have tested technical trading systems established that securities’

prices adjust rapidly to the arrival of information and that technical analysis techniques are not

likely to provide an advantage to investors who use them (Ahmad & Ali, 2008). However,

investors have argued that there is validity to some technical strategies.

Calendar anomalies

Calendar anomalies are seasonal anomalies that present familiar patterns in the price

movements of a security over a period of the year (Karz, 2010). Calendar anomalies present

opportunities, which allow investors to take advantage of abnormal price movements in

securities and gain abnormal returns (Boudreaux, 1995). Due to the relation of the anomaly

with specified periods over the calendar year, the anomaly is regarded as calendar anomalies

and as a result of the annual occurrence, they are also referred to as seasonal or seasonality

anomalies (Darrat et al., 2013). Calendar anomalies can occur either at a specific time of the

day, a specified day of the week, a specific week in the month or in a specific week in the year.

Four of the most arguable calendar anomalies are namely day-of-the-week effect, turn-of-the-

month effect, month-of-the-year effect and holiday (Hansen & Lunde, 2003).

Day-of-the week effect

Day-of-the week effect is a calendar anomaly, which illustrates that expected returns from

security price movements are not the same throughout weekdays. Day-of-the-week effect

states that expected returns from security price movements are significantly low on a Monday


and are abnormally high on a Friday (Cross, 1973). As a result of the negative downside on a

Monday, the anomaly is referred to as the weekend effect (French, 1980).

Turn-of-the-month

Turn-of-the-month is a calendar anomaly, which has found a correlation between the first half

of the month beginning from the last few days of the previous month and abnormal expected

abnormal returns from price movements in securities (Nikkinen et al., 2007). This implies that

the average daily returns of stocks on the turn-of-the-month are different (Liu, 2013).

The month-of-the-year effect

The “month-of-the-year effect” is a calendar anomaly that refers to months within a year that

exhibits abnormal returns. Correlation between abnormal returns and the month varies

between different countries (Gultekin & Gultekin, 1983). In the United States of America,

abnormal returns are obtained in December, whereas in India they are obtained in March

(Thushara & Perera, 2013). Though, the effect is often referred to as the January effect as

most countries such as United Kingdom and Tokyo’s’ abnormal returns are obtained in

January.

Holiday effect

The holiday effect is a seasonal anomaly that illustrates the behaviour of security price

movements around public holidays. Abnormal returns are obtained before holidays as

opposed to normal trading days and post-holidays (Lakonishok & Smidt, 1988).

3.7 BEHAVIOURAL FINANCE

Behavioural finance is the study of psychological factors, which influence the behaviour of

investors in financial markets (Birau, 2012). The study demonstrates behavioural cognitive

psychology of human decision making in financial economics (Gupta et al., 2014). It focuses

on how investors interpret information and the decisions that they take following their

interpretation (Shefrin, 2000). Early studies on behaviour finance are found in the 1800s and

pay homage to Mackay (1841), Lebon (1982) and Seldon (1912). Their studies build the

foundation of behavioural finance, presenting various observations on group behaviour in

financial markets, popular mind effects in groups and the emotional and psychological forces

at work on investors and traders in financial markets (Ricciardi & Simon, 2000). The study by

Mackay (1841), Lebon (1982) and Seldon (1912) originated the theory of behavioural finance

by integrating interdisciplinary concepts of psychology, sociology and finance.


Behavioural finance assumes that the information structure and characteristics of market

participants play a significant role on individual’s investment decisions as well as market

outcomes (Birau, 2011). Behavioural finance believes that market participants process

information using emotional filters, which influence their decision making (Thaler, 1990).

Emotional filters or rather psychological complexities are primary feelings of fear, panic

anxiety, envy, euphoria, greed, satisfaction, ambition or vanity (Cisler et al., 2010). Market

participants are likely to act complacent in their decisions and make a suboptimal decision that

violates traditional finance claims of rationality as a result of emotional filters (Goetzmann &

Peles, 1993). Decisions made by market participants in this regard, distort market efficiency,

share returns and portfolio performance (Barber & Odean, 1999). Market participants

experience various emotions and make decisions owing to their emotional filters referred to

as decision-making biases.

Decision-making behaviours are classified as biases and affect individual’s decision making,

particularly in finance and investment (Balaji, 2013). Decision-making biases sit deep within

our psyche and assist us in information processing and decision making (Hirschey et al.,

2008). Decision-making biases are circumstantial and arise in various situations and at times

contradict one another, recorded decision biases are presented below:


Table 3.1: Investors cognitive biases

Bias Description

Anchoring

The tendency to be over-influenced by the earliest information presented to us when making decisions, thus allowing oneself to be driven to a decision or conclusion that is biased towards the initial piece of information (the “anchor”).

Loss aversion The tendency to strongly prefer decisions that allow us to avoid losses over those that allow us to acquire gains shows that the human perception of a loss is as much twice as powerful as that of an equal gain.

Endowment effect

The tendency to place greater value on a good that we own than that which we place on an identical good that we do not own.

Framing effect The tendency to react to, judge, or interpret the exact same information in distinctly different ways depending on how it is presented to us, or framed.

Confirmation bias The tendency to overweight, seek out, or more readily recall information in a way that confirms our preconceived belief, while simultaneously undervaluing or ignoring information that disproves our preconceived beliefs.

Hindsight bias The inclination, after an event has occurred, to see the event as having been predictable, even if there had been little to no objective basis for predicting it.

Availability heuristic

A common mental shortcut that causes individuals to rely on immediate information or examples that come to mind first when evaluating a specific topic concept, method or decision.

Sunk cost fallacy The tendency to irrationally include sunk costs (costs that have already been incurred and ate irrecoverable) as a factor in our forward decision making.

Gambler’s fallacy The tendency to believe that, if something happens more frequently than “normal” during a period of time, it must happen less frequently in the future, or vice versa.

Hot-hand fallacy

The mistaken belief that an individual who has experienced success with a random event has a greater chance of continuing that success in subsequent attempts.

Money illusion The tendency to think of currency in nominal terms rather than in real terms (i.e. consider only nominal value instead of real purchasing power).

Source: Roze (2017)

Behavioural finance has grown rapidly over the past twenty years and as a result of observed

deviations in investor’s behaviour, challenges the assumptions of traditional financial and

economic theory (Byrne & Utkus, 2013). Traditional finance and economic theory pronounce

that capital markets are efficient, and it is not possible to outperform the market over the long

term (Fama, 1998). The theory further emphasises that investors are rational, and their

emotions are not swayed by the arrival of new information to the marketplace (Timmermann,

2004). Behavioural finance questions the assumptions of ECMs, investor’s certainty regarding

future market activity and EMH’s presumption of investor’s behaviour (Sharma, 2016).

Researchers believe that behavioural finance explains market anomalies and that financial

theory should take account of observed human behaviour. Therefore, it was worthy to mention

behavioural finance biases as it can contribute to the behaviour of stock markets and the price

of a security during a labour strike.


3.8 EFFICIENCY REVIEW OF THE JOHANNESBURG SECURITIES

EXCHANGE

The theory of the EMH has been researched at length and alongside it the efficiency of various

capital markets. Researchers have argued that for capital markets to perform its role, the

market must be efficient (Phiri, 2015). Market regulators are constantly imposing new rules

and regulations to ensure that capital markets are competent (Angel, 2014). An information

efficient market implies that capital and risks are appropriately priced without any distortions

(Stout, 1988). Researchers have published numerous papers concerning the “weak form of

EMH” as a means of validating or dismissing the validity of an efficient market (Urquhart,

2013). The weak form of EMH informs market participants that the current price of a security

fully reflects all public information regarding the security (Nasser, 2015). This section thus

presents a qualitative review of studies on the JSE to ensure that indeed the JSE is an ECM.

The outcome of the review informs the researcher that market data from the JSE is valid and

that the JSE can be used as a proxy to prove the effects of labour on listed companies.

A more recent study on the efficiency of the JSE was conducted by Guduza and Phiri (2017).

Guduza and Phiri (2017) who studied individual and panel unit root tests on 4 equity and 7

bond markets on the JSE, making use of monthly data from 2002 to 2016. Guduza and Phiri

(2017) found evidence supporting that the JSE equity and bond market follow a weak form of

market efficiency. Guduza and Phiri (2017) determined that the observed data failed to

produce evidence of unit root behaviour and concluded that the JSE is an ECM. This was in

no way a surprise to Guduza and Phiri (2017) as the JSE was recognised by the World

Economic Forum in 2014 as the most efficiently regulated exchange worldwide.

Chitenderu et al. (2014) tested the existence of the random walk hypothesis on the JSE All

Share Index (ALSI) between 2000 and 2011. Unit root and autocorrelation tests were

conducted and revealed that the JSE ALSI between 2000 and 2011 followed a random walk

process. Chitenderu et al. (2014) concluded that the JSE ALSI conforms to a weak form of

market efficiency and as a result, the opportunity to create abnormal returns can be ruled out.

Heymans and Santana (2018) conducted an in-depth study on the efficiency of sub-indices

on the JSE. Heymans and Santana (2018) confirmed that the JSE is an informationally

efficient market, however, believed the sub-indices of the JSE experiences periods of

efficiency and inefficiency. Heymans and Santana (2018) found that the more newly

formulated indices on the JSE presented periods of inefficiency, thus present opportunity for

active portfolio managers to create or obtain excessive returns. Heymans and Santana (2018)

highlighted that the Top 40 index ranked as a highly efficient index, with small-cap index

ranking as a less efficient index. Phiri (2015) conducted a similar study to Heymans and


Santana (2018) and investigated the efficiency of five general sub-indices of the JSE,

concerning the weak form of EMH. Phiri (2015) conducted several unit roots tests, namely

Dickey-Fuller test, Threshold autoregressive unit root test, and a three-regime unit root test,

observing weekly data from 2000 to 2014. Phiri (2015) concluded that under a linear

framework the JSE stock indices were stationary and supported the weak form of market

efficiency, whereas under nonlinearity majority of market data received violate the

assumptions of a weak form of EMH.

Bonga-Bonga (2012) in his study of “The Evolving Efficiency of the South African Stock

Exchange” examined market data from the JSE, concerning the weak form of market

efficiency. Bonga-Bonga (2012) tested the efficiency of the JSE under the hypothesis that

emerging markets’ efficiency are constantly evolving as their regulatory environment

enhances through time. Bonga-Bonga (2012) tested market data from 1995 to 2007 and made

use of time-varying and fixed parameter GARCH model in a testing set hypothesis. The study

revealed that the JSE over the testing period proved to be an efficient market and followed

assumptions of the weak form of a market hypothesis.

Gräter and Struweg (2015) conducted similar research as Bonga-Bonga (2012) and tested

the efficiency of developing markets with a focus on the JSE. Gräter and Struweg (2015)

revealed evidence both in favour and against the JSE following a weak form of market

efficiency. An augmented Dickey-Fuller and Phillips-Perron tests were conducted on data from

1999 to 2014. A null hypothesis test relating to whether logarithmic returns had a unit root and

are, therefore, a weak form efficient was tested, concerning both unit root tests. In both cases

Gräter and Struweg (2015) rejected the null hypothesis, proving that for the observed period

the JSE was not efficient. Simons (2006) tested the efficiency of African Stock Markets,

namely, Ghana, Mauritius, Egypt and South Africa. The test results revealed that the South

African securities exchange follows a weak form of market efficiency and thus returns on the

South African securities market are independent and follow a random walk.

The review of past research on market efficiency of the JSE reveals that the JSE is an efficient

market. Researchers have found evidence that in most cases that observed data drawn from

the JSE possessed unit root and thus follows a stationary process. The outcome of the unit

root tests informed researchers that the price movement of securities on the JSE followed a

random walk. Researchers in this respect were able to conclude that the JSE conforms to a

weak form of market efficiency. This informs market participants that price movements on the

JSE are random and unbiased and as such abnormal returns cannot be gained from the JSE.

The outcome of the review informs the researcher that the JSE is an information efficient

market and is a credible proxy to test the effects of labour strikes on JSE Top 40 companies.


3.9 SYNOPSIS

Chapter 3 was set out to achieve the study’s second theoretical objective of providing a

background to the EMH and assisting the researcher to establish whether the JSE is an

efficient market. The chapter begins with a background to the theory of efficient market

hypothesis, detailing its origin and how it was contextualised by Eugene Fama. This is followed

by definitions of efficient capital markets, assumptions of what makes an efficient capital

market and the three forms of efficient market hypothesis. The implications of an efficient

capital market are presented, together with financial market anomalies. Financial market

anomalies present irregulates that challenge the premise of the efficient market hypothesis.

The various forms of financial market anomalies are presented, with details of Behavioural

finance being presented as the leading financial market anomaly to challenge the efficient

market hypothesis. Lastly, the chapter conducted a qualitative analysis of the JSE to establish

whether it is an efficient market. This was in line with ensuring that the study's test results are

accurate and a reliable conclusion of the effects that labour strikes have on the share return

of JSE Top 40 companies. Studies by Guduza and Phiri (2017), Chitenderu et al. (2014),

Heymans and Santana (2018), Bonga-Bonga (2012) and Gräter and Struweg (2015) were

reviewed.

Chapter 4, which follows, presents the study’s research design, research approach, sampling

procedure and data collection method employed to achieve the study’s empirical objective.


CHAPTER 4: RESEARCH DESIGN AND METHODOLOGY

“We will either find a way or make one.”

Hannibal (247-182 BC)

4.1 INTRODUCTION

This chapter discusses the research approach, methodology and data employed to achieve

the research objectives and answers the questions posed by the study. Section 4.2 presents

a layout of the data description, which includes a description of the data sample, the sample

size and sample period observed during the study. Section 4.2.2 presents the data sample

employed by the study. Whereas Section 4.3 discusses the event study methodology used to

assess the impact of labour strikes on the share return of the JSE Top 40 companies. A

summary of the chapter is presented in the synopsis in Section 4.4.

4.2 DATA DESCRIPTION

Sample size and sample period

The data sample used in the study is extracted from the JSE. The JSE ALSI is South Africa’s

primary market in multi-asset class securities exchange. The JSE ALSI is designed to illustrate

the performance of South African companies and provide market participants with a

comprehensive set of complementary indexes that measure the performance of major capital

and industry segments (FTSE Russell fact sheet, 2019). The headline indices are the JSE

ALSI, the JSE Top 40 index, mid-cap index, small-cap index and Fledging Index

(Johannesburg Security Exchange, 2019).

The JSE Top 40 index represents 40 of the biggest companies trading on JSE ALSI. As of 31

December 2017, the JSE Top 40 index comprised 40 out of 352 companies on the JSE ALSI

and represented over 80 per cent of the total market capitalisation of the enlisted companies.

The JSE Top 40 index is a fair reflection of market activity and serves as a proxy for the overall

South African Market (Kotze, 2017). Consequently, the study makes use of the daily historical

price movement of the JSE Top 40 companies when assessing the effects of labour strikes

on affected companies.

The JSE Top 40 index following the 2008/2009 financial crisis has traded significantly well

amidst the global and domestic political instability between 2010 and 2017. The index endured

a steady growth of 104 per cent from 23066.67 points between 2010 and 2014, resulting in a

significant increase in market capitalisation. Growth in the index steadied between 2014 and


2016 with markets trading between 41543.66 and 49081.01 points. The decline in market

growth was due to increased tension in global and domestic instability. Towards the end of

the 2016 financial year, the JSE Top 40 index rebounded and began to trend again, growing

by 28,8 per cent between 2016 and 2017. The overall performance of the JSE Top 40 index

between 2010 and 2017 was 138 per cent.

Figure 4.1: Performance of the JSE Top 40 index from 2010 to 2017

Source: JSE (2017)

The study observed 41 companies which were listed on the JSE Top 40 index between 2010

and 2017 and were affected by labour strikes. Of the 41 companies that were affected by

labour strikes, 32 were affected by protected strikes and 9 were affected by unprotected

strikes. The study focused on the period post the 2008/2009 financial crisis and as a result,

the sample period observed was between 2010 and 2017.

The daily historical price movements of affected companies were extracted from IRESS, a

leading provider of financial data feeds and analytical tools. The list of companies listed on the

JSE Top 40 index between 2010 and 2017 was obtained from the JSE. The identified labour

strikes were obtained from the annual industrial action report and from secondary data sources

such as newspaper articles from News24, MoneyWeb, Business Day live, etc.

20000

30000

40000

50000

60000

IND

EX P

OIN

TS

DATE

FTSE/JSE Top 40 Index

Top 40 Companies Linear (Top 40 Companies)


Data sample

The data sample used in the study was selected by making use of the set of selection criteria

listed in Table 4.1. Companies that had been affected by labour strikes between 2010 and

2017 were identified. The list of identified companies was narrowed down to companies that

were enlisted on the JSE Top 40 index, in their respective years between 2010 and 2017. The

study identified 41 companies that were affected by labour strikes during this period. The 41

companies were categorised in accordance with the nature of the strike, which affected the

identified company. The data sample comprised 32 companies that were affected by protected

labour strikes and 9 companies that were affected unprotected labour strikes.

Table 4.1: Sample selection criteria

SAMPLE SELECTION CRITERIA Number of companies

1. Companies affected by labour strikes between 2010 and 2017

259

2. Companies listed on the JSE Top 40 index affected by labour strikes

41

3. Companies listed on the JSE Top 40 index affected by protected strikes

32

4. Companies listed on the JSE Top 40 index affected by unprotected strikes

9

The data sample comprises the events listed in Table 4.2. The identified companies in Table

4.2 were selected from a pool of companies that were enlisted on the JSE Top 40 index

between 2010 and 2017 and had been affected by a labour strike either in the form of a

protected strike or unprotected strike.


Table 4.2: Protected and unprotected strikes from 2010 - 2017

Company Sector Protected/Unprotected Date

Start Date 2017

1. Shoprite Retail Protected 22-Dec-17

2. Tiger Brands Consumer Goods Protected 08-Aug-17

2016

3. Shoprite Retailer Protected 04-Apr-16

4. Glencore Mining Protected 05-Apr-16

5. Sibanye Gold Mining Protected 06-Apr-16

6. Bidvest Group Corporate group Protected 11-May-16

7. Aspen Pharmacare Holdings Pharmaceutical Protected 29-Jul-16

8. Anglo America Mining Protected 27-Oct-16

9. Impala Platinum Holdings Mining Protected 27-Sep-16

10. Tiger Brands Consumer Goods Protected 13-Oct-16

2015

11. MTN Telecommunications Unprotected 20-May-15

12. Glencore Mining Protected 04-Oct-15

13. Anglo America Mining Protected 04-Oct-15

2014

14. Impala Mining Protected 23-Jan-14

15. Anglo America Mining Protected 23-Jan-14

2013

16. AngloGold Ashanti Mining Protected 03-Sep-13

17. Anglo America Mining Unprotected 14-May-13

18. BHP Billiton Mining Protected 18-Nov-13

19. Exxaro Resources Ltd Mining Unprotected 05-Mar-13

20. SABMiller Brewery Protected 30-Sep-13

21. Tiger Brands Consumer Goods Protected 15-Nov-13


2012

22. AngloGold Ashanti Mining Unprotected 20-Sep-12

23. Mining Protected 28-Jul-12

24. Impala Platinum Mining Unprotected 20-Jan-12

25. Kumba Iron Ore Ltd Mining Unprotected 03-Oct-12

2011

26. African Rainbow Min Ltd Mining Protected 29-Aug-11

27. Anglo American Plc Mining Protected 24-Jul-11

28. AngloGold Ashanti Ltd Mining Protected 28-Jul-11

29. Exxaro Resources Ltd Mining Protected 24-Jul-11

30. Gold Fields Ltd Mining Protected 28-Jul-11

31. Harmony Gm Co Ltd Mining Protected 28-Jul-11

32. MTN Group Ltd Telecommunications Unprotected 14-Mar-11

2010

33. Anglo American Plat Ltd Mining Unprotected 13-Sep-10

34. Bhp Billiton Plc Mining Protected 27-Aug-10

35. Exxaro Resources Ltd Mining Protected 23-Aug-10

36. Harmony Gm Co Ltd Mining Protected 13-Jan-10

37. Impala Platinum Hlgs Ltd Mining Protected 21-May-10

38. Kumba Iron Ore Ltd Mining Protected 04-Oct

39. SABMiller Plc Brewery Protected 27-Jan-10

40. Anglo American Plc Ltd Mining Unprotected 27-Sep-10

41. Bhp Billiton Plc Mining Protected 08-Dec-10

Effect of labour strikes on the share returns of the JSE Top 40 Companies 56

4.3 EVENT STUDY METHODOLOGY

The study made use of an event study statistical model to assess the share price movement

of the JSE Top 40 companies, which have been affected by labour strikes. An event study is

a statistical study that attempts to examine the behaviour of a firms’ stock price movement

around corporate events (Kothari & Warner, 2006). According to Bowman (1983) event study

is also known as residual analysis and abnormal performance index test. Bowman (1983)

regard event studies as “an analysis of security price behaviour around the time of an

information announcement or event”. An event study is an important methodological approach

to market-based empirical research in finance and accounting used to examine a variety of

events such as the announcements of annual accounting earnings, accounting principle

changes, large block trades and corporate mergers (Mackinlay, 1997).

Event studies play a significant role in enabling stakeholder understanding of the degree of

abnormal performance in the share price movement of a security at the time of information

announcement or an event (Woon, 2004). The study provides a measure of impact analysis

of an announcement or event concerning the share return of a security (Corrado, 2011). The

primary objective of an event study is to determine whether there is an abnormal price

movement in the share price of a security, which is due to an associated event (Gilson & Black,

2003). Market efficiency is a key assumption of event studies (McWilliams & Siegal, 1997).

Market efficiencies identify the economic effects of an event (Tabak, 2010). According to

Jonsson and Radeschnig (2014), the effects of an event should immediately reflect in the

stock price of an affected company.

The first published work on event studies was conducted in the 1930s by Dolley (1933), who

examined the price effects of stock splits (Mackinlay, 1997). However, modern-day event

studies attribute the main groundwork of the study to Ball and Brown (1968) and Fama et al.

(1969) on their respective studies on “Information Content of Earnings” and “The Effects of

Stock Splits after removing the effects of simultaneous dividend increases”. Ball and Brown

(1968) conducted a rigorous investigation of the information contained in the annual earnings

announcement and their results served to clarify the understating of accounting information.

Fama et al. (1969) investigated the behaviour of stock prices during the 60 months

surrounding the months of stock splits, their findings found that security prices adjust rapidly

to the information implicit in a stock split.


Event identification

In this study, labour strikes have been identified as the event of interest and has been defined

as, “The partial or complete concerted refusal to work, or the retardation or obstruction of work,

by persons who are or have been employed by the same employer or by different employers,

for the purpose of remedying a grievance or resolve a dispute in respect of any matter of

mutual interest between employer and employee, and every reference to ‘work’ in this

definition includes overtime work, whether it is voluntary or compulsory” (Labour Relation Act,

1995). As per the prerequisite of protected labour strikes following Section 64 of Labour

Relations Act, 66 of 1995 employees or employers who propose to embark on a labour strike

must issue his or her employers or employees with a 48-hour notice of intent. As a result,

movement in the share price of the security is expected on the day of the announcement of

the strike, being two days prior to the actual event.

The event periods

Event studies break down an event into three categories, which is regarded as the estimation

window, the event window and the post-event window (Benningia, 2008). The combined

windows are known as the event period. Researchers conducting an event study either

observe the long-term effects or the short-term effects of an event (Ryngaert & Netter, 1990).

Studies observing the long-term effects of an event consider monthly, yearly or several year

intervals, whereas studies that consider the short-term effects of an event observe the event

over a 5, 10 or 20-day interval (Thompson, 1993). Due to the duration of a bargaining process,

the study observed the short-term event window.

Estimation window

The estimation window is the period prior to the event window. The historical data regressed

in the estimation window is utilised to estimate the normal return of the affected security would

have obtained in absence of the identified event. The normal returns estimated in the event

window are regarded as the expected return of the security. The estimation window must be

long enough to get an accurate and reliable regression between the affected security and the

market portfolio (Gao et al., 2014). Armitage (1995) recommends an estimation period of

anything from 100 to 300 days for daily observations and 24 to 60 months when analysing

monthly historical data. An estimation window of 300 days prior to the event window was

observed to estimate expected returns. According to Krivin et al. (2003), it is important to


ensure that the estimation window and event window do not overlap, preventing any

contamination of the expected return estimate.

Event window

The abnormal returns are observed within the event window and are regarded as the returns

gained due to the identified event. The abnormal returns are estimated by deducting expected

returns from actual returns (Temming, 2014). The outcome of the abnormal returns provides

insight regarding the effects of the identified event on the return of the affected security

(Solibakke, 2002). The length of the event window is determined by the purpose of the study

(Woolridge, 2013). The study observed a window period of 61 days. A 30-day period prior and

post the day of the event was observed. The day of the event was observed as “zero”. A 30-

day period prior to the day of the event was observed owing to the legal requirement of a

labour dispute being referred to a bargaining council or the CCMA. According to Section 64 of

Labour Relations Act, 66 of 1995 a 30-day period must have elapsed since a referral, or an

agreed-upon extension period has elapsed since the referral was received by the council of

the commission. A 30-day period post the strike was observed to examine the continued effect

of the strike on the company share price.

The post-event window

The post-event window provides an assessment of the performance of the share price after

the event has occurred (Kliger & Gurevich, 2014). The outcome of the post-event window

provides insight as to whether the firms share price returns to equilibrium (Shaheen, 2006).

Figure 4.2: Illustrates the event period of the study

-300 -30 0 30

𝑇0 𝑇1 𝑇2

Time

(days)

Estimation Window Event Window

Labour Strike


Normal returns estimation models

Normal returns are the returns that would have realised in the absence of an identified event

(Brown & Warner, 1968). Normal returns are estimated by means of modelling expected

returns. According to Mackinlay (1997), expected returns models take the form of statistical

models, which make use of statistical assumptions to generate a sample of data and economic

models, which make use of investor behavioural impact. Statistical models and economic

models in each respect take the form of the constant mean return model, the market model

and the capital asset pricing model and arbitrage pricing theory (Cox, 2006). The most

commonly used models when estimating expected returns are the constant expected return

model and the market model (Pettengill & Clark, 2001). The constant mean return model

assumes that the mean return of a given security is constant throughout time, whereas the

market model assumes a stable linear relation between the market return and the security

return (Cable & Holland, 1999).

The constant mean return model is the simplest model when estimating expected returns,

researchers find that by making use of historical return averages outperforms the more

complicated approaches because of the models' estimation error term (Brooks, 2014).

However, according to Campbell et al. (1997), the market model provides an improvement in

relation to the constant mean return model, by removing the portion of the return that is related

to variation in the market’s returns, the variance of the abnormal return is reduced. Campbell

et al. (1997) further explain that by removing the variation in returns the market model

increases researchers’ ability to detect event effects. Due to its ability to detect the effects of

an event, the study made use of the market model to estimate the expected return.

Expected returns were estimated using the market model and were estimated as follows:

𝐸(𝑅𝑖𝑡) = 𝛼𝑖 + 𝛽𝑖𝑅𝑚𝑡 + 𝑒𝑡 (4.1)

Where:

𝐸(𝑅𝑖𝑡) is the expected return on the company 𝑖 during the period 𝑡;

𝛼𝑖 is the intercept of the regression;

𝛽𝑖 is the slope of the regression;

𝑅𝑚𝑡 is the return on the market during period 𝑡; and

𝑒𝑡 is the error term.


Calculation of normal returns is then estimated. Actual share returns of change in share price:

𝑅𝑖𝑡 = 𝐼𝑛(𝑃𝑖𝑡

𝑃𝑖𝑡−1) (4.2)

Where:

𝑅𝑖𝑡 is the share price of company 𝑖 on period 𝑡; and

𝑃𝑖𝑡 is the share price on period’s 𝑡-1.

Calculation of abnormal returns

Abnormal returns

Abnormal returns are the residual outcome of expected returns and actual returns (Silzle &

Ung, 2016). Abnormal returns (AR) are estimated by subtracting expected returns and actual

returns of affected security in the event window (Brown & Warner, 1968). The captured AR

allow researchers to examine the individual impact of an event on the affected security. The

AR of each firm 𝑖 on day 𝑡 are based on the market model and are defined as follows:

𝐴𝑅𝑖𝑡 = 𝑅𝑖𝑡 − 𝐸(𝑅𝑖𝑡) (4.3)

Where:

𝐴𝑅𝑖𝑡 are abnormal returns of the affected company 𝑖 on period 𝑡;

𝑅𝑖𝑡 are normal returns of the company 𝑖 in period 𝑡; and

𝐸(𝑅𝑖𝑡) are the expected returns of the company 𝑖 on period 𝑡.

The abnormal return in equation one is subsequently:

𝐴𝑅𝑖𝑡 = 𝑅𝑖𝑡 − 𝐸(𝑅𝑖𝑡) = 𝑅𝑖𝑡 − 𝛼𝑖 − 𝛽𝑖𝑅𝑚𝑡 (4.4)

The outcome of Equation 4 provides the researcher with an indication of the magnitude and

direction of impact of a strike, the share returns of an affected JSE Top 40 company, in relation

to protected and unprotected strikes.

Average abnormal returns

In order to examine the outcome of the overall sample event returns and draw a conclusion of

the results of individual companies’ AR, the abnormal returns of affected companies must be


aggregated over time and for all securities. The individual daily AR are aggregated for each

day to obtain the AAR. The estimation of AAR tests the significant effect of the event on

individual share prices over the event window (Woon, 2004). The outcome of the estimation

provides a generalised outcome of the study. AAR for all companies in the sample for day 𝑡

were estimated as follows:

𝐴𝐴𝑅𝑡 =1

𝑁∑ 𝐴𝑅𝑖𝑡

𝑁𝑖=1 (4.5)

𝑁 indicates the number of companies in the sample.

Cumulative abnormal returns

According to Erlien (2011), observations of individual AR of firms do not provide a holistic

representation of the event of interest. As a result, AR must be aggregated to provide a holistic

view of the event of interest. CAR is aggregated across time for company 𝑖 in observation of

the overall impact of the event. The CAR is estimated by summing up the AR of the days in

the event window 𝑘 and is estimated as follows:

𝐶𝐴𝑅𝑖 = ∑ 𝐴𝑅𝑖𝑡𝐾𝑖=1 (4.6)

Cumulative average abnormal returns

The final calculation of AR prior to significance testing is that of CAAR. CAAR aggregate the

AR across both time and the firm’s yields and provides an overall indication of the impact of

the event of interest (Boehmer et al., 1991). The CAAR can be calculated by aggregating the

AARs for the respective period or by aggregating the average of the CARs given the specified

window period.

CAAR is represented by the following equation:

𝐶𝐴𝐴𝑅𝑇 = ∑ 𝐴𝐴𝑅𝑡𝑇𝑡=1 (4.7)

And

𝐶𝐴𝐴𝑅𝑡 =1

𝑁∑ 𝐶𝐴𝑅𝑡

𝑁𝑖=1 Or 𝐶𝐴𝐴𝑅𝑡 = ∑ 𝑤𝑖

𝑁𝑖=1 ∗ 𝐶𝐴𝑅𝑡 (4.8)

Z-statistic

In order to conclude the above-mentioned calculations, a z-statistic must be estimated to test

the set hypothesis. Estimations of the z-statistic will provide an indication as to whether AR


deviate from zero (Massey & Miller, 2006). The outcome of the estimate in terms of its size

and direction of the z-statistic indicates the significance of the test statistics. Calculation of the

z-statistic is as follows:

𝑍𝐴𝑅 =𝐴𝑅𝑖𝑡

𝑆𝐷(𝐴𝑅𝑖𝑡) (4.9)

Where:

𝑍𝐴𝑅 is the z-statistic of abnormal returns; and

𝑆𝐷(𝐴𝑅𝑖𝑡) is the sample standard deviation of abnormal return.

𝑆𝐷(𝐴𝑅𝑖𝑡) = √1

𝑇0−1∑ (𝐴𝑅𝑖𝑡 − 𝐸(𝐴𝑅𝑡))2𝑇0

𝑡−1 (4.10)

Where:

𝑇0 is the period of the event (estimation window)

At a significant level of 5 per cent, the z-statistic will be compared with z-critical value.

If the z-statistic > z-critical value then the null hypothesis will be rejected, thus indicating that

abnormal returns deviated significantly from zero.

If the z-statistic < z-critical value then the null hypothesis will not be rejected, thus indicating

that abnormal returns did not deviate significantly from zero.

Hypothesis test statistics of abnormal returns

The outcome of AR provides an indication as to whether labour strikes does affect the returns

of an affected firm. An outcome of greater than zero in the estimation, allows the researcher

to conclude that the identified event does result in movements in the share price of the

identified firm (Mackinlay, 1997). The study considered in this regard the hypothesis test that

is described in the section to follow.

Hypothesis test:

The following hypothesises were tested to achieve the study’s empirical research objectives:


















4.4 SYNOPSIS

Chapter 4 presents the research design and methodology applied to achieve the study’s

empirical objectives set out in Chapter 1. The chapter specifies the research design, research

approach, sampling procedure and data collection method employed to assess the effect of

labour strikes on the share return of JSE Top 40 companies. To achieve the study’s objective

the study identified 41 companies which were affected by protected and unprotected labour

strikes between 2010 and 2017 and were listed on JSE Top 40 index at the time of the labour

strike. Of the 41 companies identified, 32 companies were affected by protected labour strikes

and nine were affected by unprotected labour strikes. The study employed an event study

methodology to assess the effects of labour strikes on the share return of JSE Top 40

companies. The model observed a window period of 61 days, 30 days before and after the

day of the strike and zero as the day of the strike. A z-statistic is incorporated to evaluate

whether the AR obtain are significant enough to reject the study’s null hypotheses, making the

statements true for the alternative hypotheses at the specified confidence level.

The research approach employed in this chapter contributes to the analysis and interpretation

of the study’s empirical findings presented in Chapter 5. Chapter 5 presents, analysis and

interprets the study's findings, leading to the conclusion and recommendation presented in

Chapter 6.


CHAPTER 5: RESULTS AND DISCUSSION

An investment in knowledge pays the best interest.” Benjamin Franklin

5.1 INTRODUCTION

The purpose of this chapter is to present the empirical findings of the study. The primary

objective of the study was to establish whether the resolution of labour strikes affects the share

return of the JSE Top 40 companies. The results of the empirical objectives detailed in Chapter

1 and their related hypotheses are re-stated to test the study’s objective. The empirical

objectives detailed in Chapter 1 entailed:


companies;


share returns of the JSE Top 40 companies; and


the JSE Top 40 companies, respectively and collectively, before and after the day of the

strike.

The following hypothesises are detailed to test the above empirical research objectives:


















In order to achieve the study’s objectives, the aforementioned hypotheses were tested

employing an event study methodology. The results of the applied methodology are presented,

analysed and interpreted. This chapter is presented as follows:

● Section 5.2 presents a descriptive summary of the CAAR of the JSE Top 40 companies

affected by protected and unprotected strikes, collectively and respectively;

● Section 5.3 presents an industry-specific analysis of companies affected by labour

strikes;

● Section 5.4 presents an overall analysis of the effects that protected and unprotected

labour strikes had on the JSE Top 40 companies between 2010 and 2017, collectively;

● Section 5.5 presents a comparison of the share returns of the JSE Top 40 companies

affected by protected and unprotected strikes; and

● Section 5.6 presents an analysis of share returns of companies affected by protected

and unprotected strikes before and after the day of the event.

5.2 DESCRIPTIVE STATISTICS

Section 5.2 presents and interprets the descriptive statistics of CAAR of the JSE Top 40

companies affected by protected and unprotected strikes, collectively and respectively. A data

sample of the JSE Top 40 companies, which were affected by protected and unprotected

labour strikes between 2010 and 2017, was observed over a 61-day event window. The data

sample comprised of 32 companies which were affected by protected labour strikes and 9

companies that were affected by unprotected labour strikes. The study observed an event

window of 61 days, 30 days before and after the day of the strike, including Day 0 as the day

of the strike. The descriptive summary of share returns of companies affected by protected

and unprotected strikes are presented in Table 5.1.


Table 5.1: Descriptive summary of share returns of companies affected by protected and unprotected labour strikes

Descriptive statistics

Overall strikes Protected Unprotected

Event day 0 0 0

Sample size 41 32 9

Sample mean -0.44% -1.52% 3.35%

Median -0.48% -1.49% 3.48%

Standard deviation 0.0056 0.0087 0.0133

Sample variance 0.003% 0.008% 0.017%

Kurtosis 2.91 2.19 3.69

Skewness -0.297 0.04 -0.89

Jarque-Bera 0.87 1.70 8.82

Probability 0.646% 0.428% 0.012%

Minimum -2.03% -3.53% -0.13%

Maximum 0.58% 0.46% 5.75%

The data sample revealed that labour strikes have a negative effect on the share returns of

the JSE Top 40 companies. The collective CAAR of protected and unprotected strikes over

the 61-day event window indicates that companies affected by labour strikes experienced

average losses of 0.44 per cent in share returns. Protected strikes presented greater losses

of the 2 types of strikes, with an average negative return of 1.52 per cent and maximum losses

of 3.53 per cent. The share returns of companies affected by unprotected strikes maintained

a positive share return of 3.48 per cent and experienced a maximum loss of 0.13 per cent.

The movement in share returns of companies affected by unprotected strikes indicates that

unprotected labour strikes do not affect the share returns of the JSE Top 40 companies.

The observed losses in the share returns of affected companies are consistent with the

findings of Bhana (1997) and Seedat (2013), who found that protected labour strikes have a

greater cost implication to the employer as opposed to unprotected labour strikes. Bhana

(1997) and Seedat (2013) believe that due to the nature of unprotected strikes, employers are

not obligated to the demands made by workers and as a result of no cost implication related

to unprotected strikes. Seedat (2013) found that with protected strikes markets perceive that

there will be an increase in employees’ wages during times of wage negotiations, which

subsequently results in increased costs to the investor. Norton Rose Global (2009) reasons

that the share value of companies affected by unprotected strikes is retained as the employer


is not obligated to increase the wages of their workers or even retain workers who have been

engaging in unprotected strikes.

The CAARs of companies affected by protected and unprotected strikes collectively varied

with an average of 0.56 per cent. A greater variance of 1.7 per cent was found in CAAR of

unprotected strikes, which coincided with a standard deviation of 1.33 per cent. The variation

in the standard deviation of companies affected by unprotected labour strikes was 0.46 per

cent greater than that of protected strikes. Variance and standard deviation in the share return

of securities are viewed as signs of volatility in the share price of securities (Williams, 2016).

The study’s findings of volatility in the share returns of companies affected by protected and

unprotected strikes, respectively, align with findings of Chabalala (2014) who found that

periods of labour strikes presented a high degree of share price volatility and decline in profits

for companies. Chabalala (2014) found that volatility in the movement share price of

companies affected by labour strikes increased throughout the strike, owing to a loss in

production, resources and investor confidence.

The distribution of CAAR of protected and unprotected strikes collectively indicate that periods

of labour strikes present a slight decline in share returns of affected companies. However,

share returns of affected companies do not deviate significantly from their mean average

returns. This is evident in the 0.3 skewness and 2.91 kurtosis coefficient, which present a

normal distribution in the share return of the affected companies. The significant contribution

in the skewness of labour strikes collectively (protected and unprotected strikes) was due to

the distribution of CAAR of unprotected strikes, which were moderately skewed with a negative

coefficient of 0.89. Protected strikes presented a more symmetrical sample distribution, with

a coefficient of 0.04. The distribution in share returns of companies affected by protected

strikes indicated that there was no significant movement in the share return of companies

affected by protected strikes and confirms that markets anticipate wage negotiations and price

it in share price movement of affected companies.


Figure 5.1: Distribution of share returns of the JSE Top 40 companies affected by labour strikes

The Jarque-Bera p-values of overall strikes (protected and unprotected strikes collected) and

protected strike of 0.646 per cent and 0.428 per cent, respectively, failed to reject the null

hypothesis of normality. The outcome of the Jarque-Bera p-values confirms normal distribution

of overall strike action and protected strikes. The Jarque-Bera statistic confirms the skewness

of the unprotected strikes. Unprotected strikes presented a p-value of 0.012 per cent,

subsequently rejecting the null hypothesis of normality making the statement true for the

alternative hypothesis. This subsequently confirms that there is drastic movement in the share

price movement of securities during periods of wage negotiations.

5.3 INDUSTRY ANALYSIS OF THE JSE TOP 40 COMPANIES AFFECTED

BY LABOUR STRIKES

This section aims to present an industry analysis of the JSE Top 40 companies that were

affected by labour strikes between 2010 and 2017. Its purpose is to identify which industries

were affected by a large number of labour strikes and to observe the movement in share

returns of affected companies with respect to the announcement of labour strikes.


Industry distribution of the JSE Top 40 companies affected by labour

strikes

Figure 5.2 presents an illustration of the JSE Top 40 companies which were affected by labour

strikes per industry. Figure 5.2 aims to illustrate the number of companies per industry affected

by labour strikes and which industry was most affected by labour strikes.

Figure 5.2: Industry distribution of the JSE Top companies affected by labour strikes

The study found that majority of the labour strikes found in the sample were experienced within

the mining and consumer goods industry. Thirty of the 41 companies listed on the JSE Top

40 index were companies in the mining industry, while 3 were found within the consumer

goods industry. The least amount of labour strikes was found within the pharmaceutical and

corporate group industry with each industry experiencing 1 strike. Companies within the

telecommunications, brewery and retail industry each experienced 2 strikes during the

observed period.

The study’s findings of South Africa’s mining industry, as 1 of the major industries affected by

labour strikes, is in line with the Department of Labour’s Annual Industrial Action Report

(2016), which highlights that South Africa’s labour market is dominated by strikes within the


public sector, manufacturing, transport, construction and mining industry. According to IAR

(2017), the increase in the number of labour strikes within these industries was due to growth

in unionisation and labour intensity of the industries. Phoshoko (2018) writes that growth in

the number of labour strikes in the mining industry is due to historical discrimination and

exploitation of mining employees. The number of workdays2 lost in South Africa’s mining

industry grew by 822 465 from 361 113 in 2010 to 1 183 581 2017 (IAR, 2017). According to

Bhorat, Naidoo and Yu (2014), the increasing number of strike incidents in the mining industry

during August 2012 had the potential to increase public strikes in the economy.

Industry analysis of the JSE Top 40 companies affected by labour

strikes

This section presents the industry-specific analysis of the AAR of companies that were

affected by labour strikes. It aims to identify AR of affected companies per industry and identify

a trend in AR over the 61-day event window. The analysis begins with the mining industry,

followed by consumer goods, retailers, brewery, telecommunications, corporate groups and

pharmaceuticals. The AAR of the affected JSE Top 40 companies were observed to assess

the effect that labour strikes had on affected companies.

The AAR represents the AR of multiple events of the same type and aims to establish a market

response pattern of the observed event (Neuhierl et al., 2011). According to Ting (2017), AR

is the difference between actual and expected asset price obtained as a result of a specific

event. AR concludes the price impact of specified events through statistical testing (Granhol

& Gustafsson, 2017). The AARs of affected companies are modelled over the 61-day event

window on the vertical and horizontal axis respectively. The day of the strike is illustrated with

a solid line at “zero”.

Industry analysis of companies in the mining industry affected by

labour strikes

Figure 5.3 presents the movement in AAR of the JSE Top 40 companies within the mining

industry that were affected by labour strikes between 2010 and 2017. The graph illustrates

financial markets' response to the arrival of news of labour strikes during periods of wage

negotiations within the mining industry.




Figure 5.3: Average abnormal returns of companies in the mining industry

The share returns of companies within the mining industry experienced a significant amount

of volatility throughout the event window. A large amount of volatility in share returns of the

affected mining companies was observed in the 30 days before the day of the strike. Closer

to the day of the strike from Day 10, volatility in the share return of the affected mining

companies increased as the shares of affected companies traded at a new low between 0.65

per cent and negative 0.69 per cent. At Day -2, on the day of the announcement of the strike,

the share returns of the affected companies dropped significantly and rebounded on Day -1

right past the day of the strike. Drastic movement is observed in the share returns of affected

mining companies between day “zero”, when the strike commenced, and Day 14. Between

Day 0 and 14, the share returns of affected companies fluctuated between 1.46 per cent and

-0.99 per cent, with sharp movements observed between Day 4 and 14. Towards the end of

the event window from Day 14 to 30, volatility in the share returns of affected mining

companies subsided and began to trade upwards.

The significant amount of volatility in the share returns of affected mining companies is

attributed to workers will to risk a labour strike to obtain the most favourable outcome during

wage negotiations, along with the arrival of news of a looming strike to financial markets

(Saraydar, 1965). According to Zeuthen (1930), Hicks (1932) and Ashenfelter and Johnson

(1969), workers enter labour negotiations based on a suitable concession of an expected

value of holding out for the most desired outcome during wage negotiations. Zeuthen-Harsanyi

-1,5%

-1,0%

-0,5%

0,0%

0,5%

1,0%

1,5%

2,0%

-30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30

Av

era

ge A

bn

orm

al

Retu

rns %

Event Window

AAR: Mining Industry


(1956) models the bargaining proceedings during wage negotiations by making use of a static

utility frontier curve that represents gains bargaining agents derived from settlements at

various points on the utility frontier curve. Hick (1932) presents the duration of an expected

labour strike in relation to a favourable settlement of a strike and is centred around the cost

implications of an elongated strike. Ashenfelter and Johnson (1969) similarly model the

duration of a labour strike in relation to a favourable wage settlement, however, focus their

argument around competing agendas and varying information regarding involved party’s

concession schedule.

Breakdowns in wage negotiations are described by Neumann (1980) as procedures

respective bargaining agents follow at a specific event, a “dictionary” which translates the

actions and statements of the parties into a common language. Neumann's (1980)

assumptions of “set protocols” align with Zeuthen-Harsanyi (1956) assumption that bargaining

agents have compared the utility derived from accepting a certain offer made by the opposing

party and the expected utility of turning down an offer and risking labour strike in anticipation

of a more favourable offer (Damme, 1986). The observed volatility in the share returns of

affected mining companies is indicative of breakdowns in wage negotiations along with

bargaining agents concession curves. Breakdowns in wage negotiations are evident in 30

days before the day of the strike with share returns of affected mining companies becoming

increasingly volatile 10 days before the day of the strike and 14 days after the strike

commenced. Signs of a compromise in the settlement are observed after day 14, with the

share returns of affected mining companies trade upwards.

These findings correlate with that of Hick (1932) that labours strikes are less likely to proceed

for a sustained period owing to a cost implication of a labour strike. Nigidi (2011) found that

the share returns of companies in the mining industry experienced a decline before the day of

the strike, with volatility observed 4 days before the day of the strike, thereafter, declining past

the day of the strike and not returning to equilibrium. The study’s findings differed from that of

Nigidi (2011), the study found significant volatility throughout the event window whereas

moderate volatility is observed in Nigidi’s (2011) findings.

Significance test of AAR of companies in the mining industry

Table 5.2 presents the significance test of the AAR of mining companies affected by labour

strikes over the observed 61-day event window. The significance tests aimed to identify on

which days over the event window were the AR of affected companies are significant. The AR

of the affected mining companies were tested at a 95, 90 and 80 per cent confidence interval.


Table 5.2: Significance test: AAR mining industry

Significance test: AAR mining industry

Event window Average abnormal return z-statistic

-30 0.85% 1.63*

-29 -0.51% -1.02

-28 0.52% 0.97

-27 0.18% 0.31

-26 0.19% 0.34

-25 -0.68% -1.35*

-24 -0.31% -0.63

-23 -0.55% -1.10

-22 -0.49% -0.99

-21 0.93% 1.78**

-20 -0.36% -0.73

-19 -0.35% -0.71

-18 0.50% 0.95

-17 0.32% 0.59

-16 1.06% 2.03***

-15 0.00% -0.02

-14 -0.45% -0.91

-13 0.52% 0.98

-12 0.49% 0.92

-11 0.65% 1.24

-10 -0.38% -0.77

-9 0.06% 0.09

-8 -0.67% -1.34*

-7 0.08% 0.13

-6 0.08% 0.13

-5 -0.85% -1.69**

-4 0.29% 0.54

-3 0.14% 0.25

-2 -0.69% -1.38*

-1 0.24% 0.44

0 0.13% 0.22


1 0.19% 0.35

2 0.34% 0.62

3 0.32% 0.59

4 1.45% 2.80***

5 -0.50% -1.0 1

6 -0.99% -1.96***

7 -0.16% -0.35

8 0.26% 0.48

9 -0.12% -0.26

10 -0.47% -0.95

11 0.15% 0.26

12 1.11% 2.13***

13 -0.78% -1.54*

14 -0.17% -0.36

15 -0.47% -0.96

16 0.19% 0.33

17 -0.04% -0.11

18 -0.59% -1.17

19 -0.03% -0.09

20 0.59% 1.11

21 -0.27% -0.56

22 0.15% 0.27

23 -0.20% -0.42

24 -0.02% -0.0 8

25 0.72% 1.37*

26 -0.21% -0.44

27 -0.12% -0.27

28 -0.44% -0.88

29 0.04% 0.04

30 0.10% 0.17

Significant at 95 per cent confidence interval *** Significant at 90 per cent confidence interval ** Significant at 80 per cent

confidence interval *

Throughout the event window, significant AR were found at various confidence intervals.

During the 30 days of wage negotiations before the day of the strike, significance was found

on Day -30, -25, -21, -16, -8, -5, and on the day of the announcement of the strike at Day 2.


On the day of the strike on Day 0, there were no significant AR. Over the 30-day wage

settlement period, significant AR were found on Day 4, 6, 12, 13, and 25. The significant AR

found at the confidence intervals of 95, 90, and 80 per cent allow the researcher to conclude

that periods of wage negotiations in the mining industry results in abnormal share returns of

affected mining companies.

Industry analysis of companies in the consumer goods industry

Figure 5.4 presents the movement in AAR of the JSE Top 40 companies within the consumer

goods industry that were affected by labour strikes between 2010 and 2017. The graph

illustrates financial markets' response to the arrival of news of labour strikes during periods of

wage negotiations within the consumer goods industry.

Figure 5.4: Average abnormal returns of companies in the consumer goods industry

The movement in the share return of companies within the consumer goods industry is

synonymous with the Ashenfelter-Johnson (1956) “Political Model” theory. The share returns

of companies in the consumer goods industry presented volatility throughout the event

window. The share returns of affected companies fluctuated between 1.28 per cent and

negative 1.89 per cent. The volatility in the share returns of affected consumer goods

companies signals conflicting interest in barging agents' demands. Neumann's (1980) theory

of “set protocol” is exhibited profoundly in the drastic movement of affected consumer goods

companies. Breakdowns in wage negotiation as a result of “set protocols”, signal a looming

-2,50%

-2,00%

-1,50%

-1,00%

-0,50%

0,00%

0,50%

1,00%

1,50%

-30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30

Av

era

ge A

bn

orm

al

Retu

rns %

Event Window

AAR: Consumer Goods Industry


strike to financial markets and arrive as bad news translating into volatility in the share return

of affected companies. The drastic movement in the share return of affected companies in the

consumer industry is observed 22 days before the day of the strike and 26 days after the

commencement of the strike. Signs of a recovery in the share returns of affected consumer

goods companies are observed 20 after the strike commenced. Findings of recovery in the

share returns of affected consumer goods companies 20 days after the commencement of the

strike further support Ashenfelter and Johnson's (1956) theory of conflicting interests and

increased cost of an elongated strike.

Significance test of AAR of companies in the consumer goods

industry

Table 5.3 presents the significance test of AAR of companies within the consumer goods

industry which were affected by labour strikes over the observed 61-day event window. The

significance tests aim to identify on which days over the event window were the AR of affected

companies significant. The AR of the affected companies were tested at a 95, 90 and 80 per

cent confidence interval.


Table 5.3: Significance test AAR consumer goods industry

Significance test: AAR consumer goods industry

Event window Average abnormal returns Z-statistic

-30 0.02% 0.20

-29 -0.37% -0.34

-28 -0.60% -0.66

-27 0.75% 1.23

-26 0.15% 0.39

-25 0.32% 0.62

-24 -0.33% -0.29

-23 0.70% 1.15

-22 -0.93% -1.12

-21 -1.23% -1.54*

-20 -0.07% 0.08

-19 -0.67% -0.75

-18 0.18% 0.43

-17 0.87% 1.39*

-16 0.05% 0.25

-15 -0.23% -0.15

-14 -0.03% 0.13

-13 0.26% 0.54

-12 -0.43% -0.43

-11 -0.54% -0.57

-10 0.19% 0.44

-9 -0.22% -0.13

-8 1.28% 1.95**

-7 0.79% 1.28

-6 -0.03% 0.14

-5 -1.20% -1.49*

-4 0.68% 1.13

-3 -0.15% -0.02

-2 -0.64% -0.71

-1 0.08% 0.29

0 0.95% 1.49*

1 -0.23% -0.15


2 0.33% 0.64

3 -1.49% -1.90**

4 0.02% 0.20

5 -0.91% -1.08

6 -0.67% -0.75

7 -0.95% -1.14

8 -0.91% -1.09

9 0.54% 0.93

10 0.60% 1.01

11 1.02% 1.59*

12 -0.35% -0.32

13 -0.97% -1.17

14 -0.73% -0.84

15 -0.33% -0.28

16 0.07% 0.27

17 -0.68% -0.77

18 -0.50% -0.52

19 -1.89% -2.45***

20 -0.92% -1.10

21 0.44% 0.79

22 -1.52% -1.93**

23 1.22% 1.88**

24 0.80% 1.29*

25 -0.46% -0.46

26 -0.43% -0.43

27 -0.35% -0.31

28 0.52% 0.91

29 0.94% 1.48*

30 0.44% 0.79



The share returns of companies within the consumer goods industry presented significant AR

throughout the event window. Significant AR of companies within the consumer goods industry

were mostly found at a confidence interval of 90 per cent. Before the day of the strike,

significance was found at Day 21, -17, -8 and -5. On the day of the strike at a confidence


interval of 90 per cent, significant AR of 1.49 were found. Days after the commencement of

the strike significant AR were found on Day 3, 11, 19, 22, 23, 24 and 29. Significance in the

share returns of affected companies throughout the event window informs the researcher that

periods of wage negotiations within the consumer goods industry result in significant AR.

Industry analysis of companies in the retail industry

Figure 5.5 presents the movement in AAR of the JSE Top 40 companies within the retail



negotiations within the retail industry.

Figure 5.5: Average abnormal returns of companies in the retail industry

The movement in share returns of companies within the retail industry presented similar

movement as the movement in share returns of companies within the consumer goods

industry that were affected by labour strikes. Volatility in the share returns of affected retail

companies is observed throughout the event window between Day 24, before the day of the

strike, and Day 24 after the strike had commenced. The share of affected retail companies

fluctuated between 1.28 per cent and negative 1.89 per cent. Zeuthen (1930) and Ashenfelter

and Johnson's (1956) theory is observed in the movement of share returns of companies in

the retail industry. Zeuthen (1930) argues that workers are willing to risk a labour strike to

obtain the most favourable outcome and is demonstrated in the several break downs of the

-2,0%

-1,5%

-1,0%

-0,5%

0,0%

0,5%

1,0%

1,5%

-30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30

Av

era

ge A

bn

orm

al

Retu

rns

%

Event Window

AAR: Retail Industry


negotiation process, which has translated to the volatility of share return. The volatility of share

returns of companies in the retail industry increased drastically 8 days before the day of the

strike, showing no sign of a resolution closer to the day of the strike with share returns dropping

on the day of the announcement of the strike. Volatility in the share return continued for an

extended period, showing signs of a wage settlement at Day 20 with the share return of

companies in the retail industry trading up.

Significance test of the AAR of companies in the retail industry

Table 5.4 presents the significance test of AAR of companies within the retail industry that

were affected by labour strikes over the observed 61-day event window. The significance tests

aim to identify on which days over the event window were the AR of affected companies

significant. The AR of the affected companies were tested at a 95, 90, and 80 per cent

confidence interval.

Table 5.4: Significance test of AAR of companies in the retail industry

Significance test: AAR retail industry

Event window Average abnormal returns z-statistic

-30 0.62% 0.30

-29 0.00% -0.15

-28 -0.59% -0.58

-27 -0.32% -0.38

-26 3.89% 2.66***

-25 -0.10% -0.23

-24 2.46% 1.63*

-23 -1.70% -1.38*

-22 0.30% 0.06

-21 1.46% 0.90

-20 0.38% 0.12

-19 1.90% 1.22

-18 -1.31% -1.10

-17 0.65% 0.32

-16 0.80% 0.43

-15 3.10% 2.09***

-14 -0.43% -046

-13 0.79% 0.42


-12 -3.32% -2.55***

-11 -1.77% -1.43*

-10 0.11% -0.07

-9 0.27% 0.04

-8 1.75% 1.11

-7 0.88% 0.49

-6 1.82% 1.16

-5 -2.24% -1.77**

-4 2.30% 1.51*

-3 -0.08% -0.21

-2 -2.19% -1.74**

-1 -2.42% -1.90**

0 0.11% -0.07

1 2.00% 1.30*

2 -1.35% -1.13

3 0.61% 0.29

4 -1.31% -1.10

5 -0.06% -0.19

6 -0.18% -0.28

7 -0.10% -0.22

8 0.32% 0.08

9 -1.47% -1.21

10 -0.08% -0.21

11 -0.83% -0.76

12 -0.23% -0.32

13 0.41% 0.15

14 1.13% 0.66

15 2.06% 1.34*

16 1.84% 1.18

17 0.35% 0.10

18 0.11% -0.07

19 1.06% 0.62

20 0.64% 0.31

21 -0.22% -0.31

22 -0.72% -0.67

23 0.04% -0.12


24 0.35% 0.10

25 2.13% 1.39*

26 0.96% 0.54

27 -1.70% -1.38*

28 -0.04% -0.18

29 -0.30% -0.37

30 0.29% 0.06

Significant at 95 per cent confidence interval *** Significant at 90 per cent confidence interval **Significant at 80 per cent


The share returns of companies in the retail industry presented significant AR at various

confidence intervals throughout the event window. In the 30 days of wage negotiations,

significant AR at a confidence interval of 95 per cent were found on Day 26, -15, and -12.

Closer to the day of the strike between Day 5 and -1, significant AR were found at a confidence

interval of 90 per cent. Significant AR were found on Day 2 on the day the strike was

announced. No significant AR were found on the day of the strike at Day 0. In the 30 days

after the strike had commenced, fewer days with significant AR were found. Significant AR

after the strike had commenced were found on Day 1, 15, 25, and 27. The significant AR found

throughout the event window, inform the researcher that periods of wage negotiations in the

retail industry resulting in significant AR.

Industry analysis of companies in the brewery industry

Figure 5.6 presents the movement in AAR of the JSE Top 40 companies within the brewery



negotiations within the brewery industry.


Figure 5.6: Average abnormal returns of the brewery industry

The share return of companies in the brewery industry presented less instability in comparison

to companies in the mining, consumer good and retail industry. The affected companies share

return fluctuated between 1.80 per cent and negative -2.53 per cent. Significant movement in

share return is observed between Day 16 and -14, -12 and -10 and Day 4 and -2. The drastic

movement in share returns of companies in the brewery industry before the day of the strike

is symbolic of the bargaining agent’s rejections of wage offers and counteroffers along

respective bargain agents concession curve. A similar drastic movement in share returns of

affected brewery companies is observed throughout the 30 days settlement window. Instability

in the share return of the affected brewery companies subsided later in the event window on

Day 28, illustrating signs of an elongated labour strike.

Significance test of AAR of companies in the brewery industry

Table 5.5 presents the significance test of AAR of companies within the brewery industry that

were affected by labour strikes over the observed 61-day event window. The significance tests

aim to identify on which days over the event window were the AR of affected companies

significant. The AR of the affected companies were tested at a 95, 90 and 80 per cent

confidence interval.

-3,0%

-2,5%

-2,0%

-1,5%

-1,0%

-0,5%

0,0%

0,5%

1,0%

1,5%

2,0%

-30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30

Ave

rag

e A

bn

orm

al R

etu

rns

%

Event Window

AAR: Brewery Industry


Table 5.5: Significance of AAR of companies in the brewery industry

Significance Test: AAR brewery industry

Event window Average abnormal return z-statistic

-30 0.40% 0.60

-29 0.01% 0.13

-28 -0.15% -0.07

-27 -0.02% 0.09

-26 -0.64% -0.66

-25 1.36% 1.76**

-24 -0.19% -0.11

-23 -0.01% 0.11

-22 -0.54% -0.53

-21 0.27% 0.45

-20 -0.90% -0.97

-19 0.30% 0.48

-18 -0.94% -1.02

-17 -0.07% 0.03

-16 -2.17% -2.49***

-15 0.13% 0.27

-14 -0.01% 0.11

-13 0.82% 1.11

-12 -1.98% -2.27***

-11 0.13% 0.27

-10 0.93% 1.24

-9 0.55% 0.78

-8 -0.27% -0.21

-7 0.47% 0.69

-6 -0.28% -0.22

-5 0.53% 0.76

-4 -0.12% -0.0 2

-3 -0.76% -0.80

-2 -0.44% -0.41

-1 -0.76% -0.79

0 1.44% 1.85**


1 -0.80% -0.85

2 -0.68% -0.70

3 -0.82% -0.87

4 -1.33% -1.49*

5 0.52% 0.75

6 -0.04% 0.07

7 -1.08% -1.18

8 0.27% 0.44

9 -1.57% -1.77

10 -0.34% -0.29

11 -0.09% 0.01

12 0.19% 0.35

13 1.80% 2.29***

14 -0.49% -0.47

15 -0.39% -0.35

16 0.83% 1.11

17 0.36% 0.56

18 0.60% 0.84

19 0.10% 0.24

20 0.37% 0.56

21 -0.19% -0.11

22 -2.53% -2.93***

23 1.56% 2.00***

24 0.03% 0.16

25 0.57% 0.81

26 -0.78% -0.83

27 0.14% 0.29

28 0.01% 0.13

29 0.38% 0.57

30 0.29% 0.47

Significant at 95 per cent confidence interval ***Significant at 90 per cent confidence interval **Significant at 80 per cent


The share returns of affected brewery companies present significant AR throughout the event

window. Major significant AR were found at a 95 per cent confidence interval on Day 16 and

-12 before the day of the strike. After the strike had commenced, significant AR at a 95 per


cent confidence interval where found on Day 13, 22 and 23. The share returns of affected

brewery companies presented significant abnormal return on the day of the strike at a 90 per

cent confidence interval. The findings of significant AR throughout the event window enable

the researcher to conclude that periods of wage negotiations and strikes result in significant

AR for companies in the brewery industry.

Industry analysis of companies in the telecommunications industry

Figure 5.7 presents the movement in AAR of the JSE Top 40 companies within the

telecommunications industry that were affected by labour strikes between 2010 and 2017.

Figure 5.7 illustrates financial markets' response to the arrival of news of labour strikes during

periods of wage negotiations within the telecommunication industry.

Figure 5.7: Average abnormal returns of companies in the telecommunications industry

The share returns of companies in the telecommunication industry presented similar

movements as companies in the consumer goods and retail industry. Drastic movement in the

share returns of the affected brewery companies is observed in the 30 days before the day of

the strike. With share returns of affected telecommunications companies fluctuating between

3.40 per cent and negative 1.92 per cent. Instability in the 30 days before the day of the strike

illustrates intense labour negotiation with signs of rejected wage offers translated to financial

markets. This is observed in the drastic decline in share return on Day 2, on the day of

announcement of the strike. In the settlement window, instability in the share return of the

-3%

-2%

-1%

0%

1%

2%

3%

4%

-30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30

Avera

ge A

bnorm

al R

etu

rns %

Event Window

AAR: Telecommunications Industry


affected telecommunication companies subsided showing signs of an early settlement, with

share returns of affected companies rebounding at Day 14.

Significance test of AAR of companies in the telecommunications

industry

Table 5.6 presents the significance test of AAR of companies within the telecommunication

industry that were affected by labour strikes over the observed 61-day event window. The


companies significant. The AR of the affected companies were tested at a 95, 90, and 80 per


Table 5.6: Significance test of AAR of companies in the telecommunications industry

Significance test: AAR telecommunications industry


-30 -1.85% -2.01***

-29 0.20% 0.01

-28 0.26% 0.07

-27 0.27% 0.09

-26 -0.26% -0.44

-25 -1.24% -1.40*

-24 3.40% 3.17***

-23 -0.22% -0.40

-22 -0.42% -0.60

-21 0.20% 0.01

-20 0.17% -0.02

-19 -1.70% -1.86**

-18 0.65% 0.46

-17 -0.11% -0.29

-16 0.48% 0.29

-15 1.33% 1.13

-14 -0.36% -0.53

-13 -1.46% -1.62*

-12 -0.01% -0.19

-11 -0.04% -0.22

-10 1.13% 0.92

-9 1.73% 1.52*


-8 1.98% 1.77**

-7 -0.36% -0.54

-6 -0.88% -1.0 5

-5 1.53% 1.32

-4 0.01% -0.18

-3 2.64% 2.42***

-2 -0.83% -1.00

-1 0.36% 0.17

0 0.23% 0.05

1 -1.36% -1.53*

2 0.47% 0.28

3 1.34% 1.14

4 -0.25% -0.43

5 -0.18% -0.37

6 0.53% 0.34

7 -0.50% -0.68

8 0.36% 0.17

9 -1.21% -1.38

10 0.28% 0.09

11 1.09% 0.89

12 -1.92% -2.07***

13 0.36% 0.17

14 0.55% 0.36

15 -0.06% -0.24

16 0.55% 0.35

17 -0.62% -0.80

18 -1.12% -1.29*

19 0.81% 0.61

20 -0.10% -0.28

21 -0.0 1% -0.19

22 0.28% 0.09

23 -0.23% -0.41

24 0.77% 0.57

25 0.57% 0.38

26 1.82% 1.61*

27 0.54% 0.34


28 0.86% 0.66

29 0.23% 0.04

30 0.69% 0.49



The share returns of affected telecommunications companies presented significant AR

throughout the event window at various confidence intervals. Significance in AR during 30-

day wage negotiations were found on Day -25, -24, -19, -13, -9, -8 and -3. In the 30 days after

the strike had commenced significant AR were found on Day 1, 12, 18 and 26. The

observations indicate that there was a great amount of significant AR during 30 days before

the strike. The findings of significant AR indicate that in periods of wage negotiations in the

telecommunications industry result in AR.

Industry analysis of companies in the corporate group industry

Figure 5.8 presents the movement in AAR of the JSE Top 40 companies within the corporate

group industry that were affected by labour strikes between 2010 and 2017. The graph

illustrates financial markets' response to the arrival of news of labour strikes during periods of

wage negotiations within the corporate group industry.

Figure 5.8: Average abnormal returns of companies in the corporate group industry

-5%

-4%

-3%

-2%

-1%

0%

1%

-30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30

Av

era

ge A

bn

orm

al

Retu

rns %

Event Window

AAR: Corporate Group


The share returns of companies in the corporate group industry presented stable yet AR in

the 30 days before the day of the strike. Instability in the share return of the corporate group

is observed in the settlement window between Day 14 and 30. However, according to

Sharenet (2016) observed volatility in the share return of the affected company is a result of

the corporate announcement in the share returns of Bidvest. The movement in share returns

of companies in the corporate group industry informs the researcher that labour strikes did not

affect the share return of the affected company.

Significance test of AAR of companies in the corporate group

industry

Table 5.7 presents the significance test of AAR of companies within the corporate group





Table 5.7: Significance test of AAR of companies in the corporate group industry

Significance test: AAR corporate group industry


-30 -0.26% 0.22

-29 0.11% -0.13

-28 0.10% 0.36

-27 0.58% 0.09

-26 0.63% 0.07

-25 0.59% -0.03

-24 0.27% 0.01

-23 0.18% -0.12

-22 0.06% 0.25

-21 0.15% 0.19

-20 0.36% -0.10

-19 0.08% 0.21

-18 0.10% -0.26

-17 -0.23% 0.36

-16 -0.11% -0.05

-15 -0.24% 0.31


-14 -0.18% 0.13

-13 -0.03% 0.01

-12 -0.24% -0.04

-11 -0.32% 0.00

-10 -0.36% 0.13

-9 -0.26% 0.00

-8 -0.27% 0.02

-7 -0.18% 0.26

-6 -0.18% 0.06

-5 -0.25% 0.38

-4 0.04% 0.13

-3 -0.01% 0.10

-2 0.20% -0.06

-1 -0.05% 0.03

0 -0.01% 0.09

1 -0.14% 0.11

2 -0.16% -0.07

3 -0.20% -0.06

4 -0.22% -0.20

5 -0.34% 0.32

6 -0.23% 0.17

7 -0.13% -0.14

8 -0.22% 0.11

9 -0.31% -0.18

10 -0.45% 0.19

11 -0.57% 0.34

12 -0.43% 0.50

13 -0.1 9% -7.52***

14 -4.67% 0.83

15 -4.19% 0.50

16 -3.94% 0.21

17 -3.88% 0.29

18 -3.67% -0.02

19 -3.64% 0.23

20 -3.38% 0.06

21 -3.53% 0.22


22 -3.51% 0.14

23 -3.34% 0.16

24 -3.31% -0.28

25 -3.37% 0.45

26 -3.22% 0.15

27 -3.33% 0.06

28 -3.60% 0.09

29 0.97% 0.34

30 0.68% 0.39



The share returns of companies within the corporate group industry presented significance on

Day 13 after the strike had commenced. Significance was found at a confidence interval of 95

per cent. Significance in the corporate group industry was found only on Day 13, which is not

enough to conclude that periods of wage negotiations in the corporate group industry result in

significant AR.

Industry analysis of companies in the pharmaceutical industry

Figure 5.9 presents the movement in AAR of the JSE Top 40 companies within the

pharmaceutical industry which were affected by labour strikes between 2010 and 2017. The

graph illustrates financial markets response to the arrival of news of labour strikes during

periods of wage negotiations within the pharmaceutical industry.


Figure 5.9: Average abnormal returns of companies in the pharmaceutical industry

The share returns of companies in the pharmaceutical industry presented significant volatility

through the event window. The share return of affected companies fluctuated between 3.40

per cent and negative 1.92 per cent. with great volatility observed in the 30 days before the

day of the strike. In the 30 days before the strike commenced, drastic movement in the share

returns of affected companies was observed on Day 23, -19, -14, -12, -6, and on the day of

the announcement of the strike at Day 2. The observed volatility in the share returns of the

affected pharmaceutical subsided in the 30-day settlement window after the strike

commenced. The movement in the share returns of the affected pharmaceutical companies is

synonymous with Hick’s (1932) theory. The 30-day negotiations window illustrates rejections

in bargain agents’ concessions curve that continues shortly after the strike commences. On

Day 14, signs of wage agreement are observed with the share return of the affected

pharmaceutical company rebounding and entering a growth trajectory.

Significance test of AAR of companies in the pharmaceutical industry

Table 5.8 presents the significance test of AAR of companies within the pharmaceutical



-3%

-2%

-1%

0%

1%

2%

3%

4%

-30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30

Av

era

ge A

bn

orm

al

Retu

rns %

Event Window

AAR: Pharmaceutical Industry




Table 5.8: Significance test of AAR of companies in the pharmaceutical industry

Significance test: AAR pharmaceutical industry

Event window Average abnormal return z-statics

-30 -0.23% -0.43

-29 -0.09% -0.38

-28 -0.14% -1.03

-27 -0.34% 1.07

-26 -0.25% 0.11

-25 -0.34% -0.60

-24 -0.17% -0.37

-23 -0.34% 0.18

-22 -0.32% 0.72

-21 -0.24% -1.27

-20 -0.17% 0.58

-19 -0.10% -0.90

-18 -0.13% -1.12

-17 -0.35% 0.76

-16 -0.11% 0.22

-15 0.13% -0.13

-14 0.17% -0.8

-13 0.19% 5.63***

-12 0.98% 0.33

-11 0.89% 1.57*

-10 1.07% -0.11

-9 1.12% 0.04

-8 1.17% -0.08

-7 1.14% -0.94

-6 0.94% 0.44

-5 1.14% -1.27

-4 0.92% -0.39

-3 0.99% 1.23

-2 1.26% -0.13

-1 1.16% -0.11


0 1.12% 0.07

1 1.14% -0.20

2 1.14% 1.36 *

3 0.63% 0.42

4 0.64% -0.16

5 0.44% 0.20

6 0.47% 1.33*

7 0.63% -0.93

8 0.53% 0.00

9 0.64% -0.61

10 0.51% -1.14

11 0.53% -1.03

12 0.45% 0.06

13 0.31% -0.68

14 0.25% -0.0 9

15 0.25% 0.79

16 0.34% -0.93

17 0.25% -0.15

18 0.07% 0.31

19 0.06% -0.24

20 0.05% -0.52

21 -0.04% 0.18

22 -0.17% -0.75

23 -0.15% -0.18

24 -0.17% -0.71

25 -0.18% 1.01

26 0.07% -0.09

27 0.18% -0.12

28 0.16% 0.47

29 0.30% -0.41

30 0.26% -0.73



The share returns of companies in the pharmaceutical industry present significant AR

throughout the event windows at various confidence intervals. Significance in AR was found


on Day 13, -11, 2, 6. The significant AR of affected pharmaceutical companies were not

enough to conclude that periods of wage negotiations in the pharmaceutical industry result in

significant AR.

5.4 CUMULATIVE ANALYSIS OF THE EFFECTS OF PROTECTED AND

UNPROTECTED LABOUR STRIKES ON THE SHARE RETURN OF

JSE TOP 40 COMPANIES

This section presents the result of the primary objective. The primary objective is to test

whether the announcement of labour strikes affects the share return of the JSE Top 40

companies. A trend analysis of the CAAR of the companies affected by protected and

unprotected strikes collectively are presented. Followed by the outcomes of the primary

hypothesis. Figure 5.10 presents a graphical representation of the effect that labour strikes

had on the share returns of the JSE Top 40 companies. The modelled data sets are inclusive

of both protected and unprotected strikes and represent the share returns of companies

affected by labour strikes over the event window. The average CAAR of both protected and

unprotected strikes is modelled at -0.44 per cent, which illustrates the average returns

investors were likely to obtain within the event window. The event's confidence interval is

presented at 0.0 per cent and -0.9 per cent. The confidence interval informs the researcher of

the sample parameter in which the share returns of the affected company is likely to fluctuate

within (Kenton, 2020).


Figure 5.10: Share return of the JSE Top 40 companies affected by protected and

unprotected labour strikes collectively

Trend analysis of share return of companies affected by protected and

unprotected strikes, collectively

The movement in CAAR of companies affected by protected and unprotected strikes

collectively revealed that affected companies experience significant instability throughout

periods of wage negotiations. The share returns of affected companies varied from 0.6 per

cent at Day 21 to -2.0 per cent at Day 5. Adverse movement in the share returns of the affected

companies was found within the early stages of the negotiations process, 6 days before the

day of the strike and continued to 12 days after the day of the strike. Miller and Modigliani

(1961) attributed volatility in share returns of companies engaging in wage negotiations to the

arrival of news of a looming strike to financial markets. Miller and Modigliani's (1961) findings

are supported by Bhana (1997), who attributed movement in share returns of companies

engaging in wage negotiations to leakages of insider information relating to potential strikes.

-2,1%

-1,8%

-1,5%

-1,2%

-0,9%

-0,6%

-0,3%

0,0%

0,3%

0,6%

-30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30

CA

AR

%

Event window

Share Return of the JSE Top 40 Companies affected by Protected and Unprotected strikes collectively

Cumlative AverageAbnormal Returns

95 %above

95 %below

Average


During the first 15 days of wage negotiations, the share returns of affected companies varied

between 0.58 per cent and -0.7 per cent. Similar volatility is observed 5 days before the day

of the strike and 12 days after the day of the strike and varied between -1.8 per cent and -2

per cent. Observed volatility in the share returns of the affected companies is attributed to a

breakdown in set protocol during wage negotiations, which subsequently translated into “bad

news” in the market. Neumann's (1980) study believed that strikes are predictable as a result

of “set protocols” determined by bargaining agents within the preparation and discovery stage

of wage negotiations. Neumann (1980) described “set protocols” as procedures respective

bargaining agents follow at a specific event, a “dictionary” that translates the actions and

statements of the parties into a common language.

Five days after the strike, the share returns of companies affected by protected and

unprotected strikes collectively rebounded and began to recover entering a growth trajectory

that continued until Day 23. Growth in the share returns of the affected companies showed

signs of a settlement that was perceived as a positive sign by the market. The observed

findings of the recovery in share returns of companies affected by protected and unprotected

strikes collectively are consistent with those of Nigidi (2011). According to Nigidi (2011) labour

strikes in South Africa is generally short and lasts between 1 and 5 days, he further adds that

the decline in share returns prior and post the day of the strike are short-lived and quickly

recover. The findings by Nigidi (2011) are affirmed by Nelson, Amoaka-Adu, and Smith (1994)

that strikes lasting only a few days generally reduce the share returns of affected companies

owing to the costs and benefits of strikes.

Hypothesis test of protected and unprotected strikes collectively on

share returns of affected companies

This section presents the results of the primary hypothesis test of whether the resolution of

labour strikes results in abnormal share returns of affected companies. A "z-test" at a

confidence interval of 95 per cent and a "critical value of 1.96" was considered in the study as

a measure of significance. The outcome of the z-statistic greater than the z-critical value of

1.96 allows the researcher to reject the null hypothesis thus making the statement true for the

alternative hypothesis. The study’s alternative hypothesis informs the researcher that the

resolve of protected and unprotected strikes (collectively), affect the share return of the JSE

Top 40 companies, negatively. Table 5.9 presents the z-test on CAAR of protected and

unprotected strikes collectively over the 61-day event window.


Table 5.9: Significance test of CAAR of the JSE Top 40 companies affected by overall labour strikes

Share return of the JSE Top 40 companies affected by overall labour strikes

Day Cumulative average

abnormal returns z-statistic

-30 0.33% 1.04

-29 0.05% 0.18

-28 -0.25% -0.73

-27 -0.38% -1.19

-26 -0.64% -1.59*

-25 -0.25% -0.85

-24 -0.39% -1.19

-23 0.13% 0.43

-22 0.58% 1.60*

-21 -0.02% -0.08

-20 0.28% 0.95

-19 0.52% 1.48*

-18 0.16% 0.41

-17 -0.11% -0.24

-16 -0.56% -1.51*

-15 -0.70% -2.82***

-14 -0.32% -1.43*

-13 -0.71% -2.26***

-12 -0.52% -1.64*

-11 -1.06% -2.77***

-10 -0.82% -2.62***

-9 -0.94% -3.46***

-8 -0.77% -1.99***

-7 -0.92% -4.12***

-6 -0.96% -2.75***

-5 -0.18% -0.26

-4 -0.80% -2.55***

-3 -1.25% -2.62***

-2 -0.39% -1.37*

-1 -0.59% -2.12***

0 -0.80% -1.87**


1 -0.99% -3.82***

2 -1.07% -2.59***

3 -1.18% -3.47***

4 -2.03% -5.33***

5 -1.76% -5.38***

6 -1.03% -4.19***

7 -0.77% -2.93***

8 -0.95% -2.62***

9 -0.73% -3.10***

10 -0.48% -1.33*

11 -0.74% -2.80***

12 -1.28% -3.67***

13 -0.80% -0.33

14 -0.68% -2.18***

15 -0.40% -1.21

16 -0.60% -1.95**

17 -0.51% -1.66**

18 0.07% 0.26

19 0.26% 0.84

20 0.08% 0.30

21 0.23% 0.88

22 0.36% 0.96

23 0.44% 1.41**

24 0.32% 1.12

25 -0.30% -0.86

26 -0.18% -0.54

27 -0.07% -0.30

28 0.12% 0.40

29 -0.05% -0.15

30 -0.16% -0.59



At a confidence interval of 95 per cent and z-critical value of 1.96, significant z-statistics were

found on Day -15, -13, -11 to -6, -4, -3 and -1 on days before the day of the strike. After the

day of the strike, significant z-statistics were found on Day 1 till today 9 thereafter on Days 11,


12 and 13. On the day of the announcement of the strike (“Day 2”) and the day of the strike

(“Day 0”), there was no significance, meaning that "no abnormal returns" were obtained on

the day of the announcement and the day of the strike.

Periodic analysis of protected and unprotected strikes collectively

Table 5.10 presents an interval analysis of share returns of companies affected by protected

and unprotected strikes collectively. The table presents the average CAAR standard deviation

and z-statistic at a 5, 10 and 20- and 30-day interval before the day of the strike, after the day

of the strike and the overall event. The interval analysis aims to provide periodic analysis of

the event window.

Table 5.10: Interval analysis of protected and unprotected collectively

Interval analysis

Periods Variables 5-day 10-day 20-day 30-day

Before the event CAAR -0.641% -0.762% -0.531% -0.382% STDEV 0.026 0.006 0.022 0.022 z-test -1.784 -2.384 -1.683 -1.201

After the event CAAR -2.026% -2.026% -0.779% -0.496% STDEV 0.022 0.020 0.027 0.024 z-test -4.120 -3.477 -2.359 -1.495

Overall event CAAR -1.003% 0.277% -0.659% -0.445% STDEV 0.024 0.022 0.024 0.023 z-test -2.853 -2.880 -2.017 -1.357

Before the day of the strike

The interval analysis before the day of the strike indicates that average share returns of

companies affected by protected and unprotected strikes collectively gradually declined over

the 30, 20- and 10-day interval, with average share returns of negative 0.382 per cent, 0.531

per cent and 0.762 per cent, respectively. Within 5 days before the day of the strike, the

average share returns of affected companies began to gradually increase to negative 0.641

per cent. Over the 30, 20, and 5-day intervals, the share returns of affected companies showed

relatively increased volatility of 0.022 at a 20- and 30-day interval and 0.026 within 5 days

before the day of the strike. At the 10-day interval before the day of the strike volatility was

relatively low at 0.006. Abnormal share returns of the affected companies were significant

within 10 days before the day of the strike and less significant in the 5-, 20- and 30- days

interval before the day of the strike. At a 95 per cent confidence interval and z-critical value of


1.96, 10 days before the day of the strike the study rejects the null hypothesis, making the

statement true for the alternative hypothesis that AR are observed 10 days before the day of

the strike.

After the day of the strike

After the day of the announcement of the strike, the share returns of the affected companies

increased significantly over the first 10 days of the strike with an average CAAR of -2.026 per

cent. The share returns of the affected companies began to decline after the 10-day interval,

between the 20- and 30-day intervals to -0.779 per cent and -0.496 per cent, respectively.

Abnormal share returns were found within the 5, 10 and 20-day intervals. Volatility in the share

return of the affected companies fluctuated between 0.020 and 0.027.

Overall event

Observation of share returns over the 5 days before and after the day of the strike, together

with 10 and 20 days before and after the day of the strike indicate that over a 20-day event

window, labour strikes resulted in significant AR of -2.853, -2.880 and -2.017, respectively.

Volatility in the share returns of the after companies fluctuated between 0.022 and 0.023 over

the 5,-10,-20, and 30-day event window for before and after the day of the strike.

Summary hypothesis test of the JSE Top 40 companies affected by

protected and unprotected strikes, collectively

In order to conclude the hypothesis test on whether the resolution of labour strikes affects the

share returns of the JSE Top 40 companies, a significance test considering each day of the

61-day event window was conducted. Table 5.11 presents the cumulative outcome of the

significance test of protected and unprotected strikes collectively over the 61-day event

window. The hypothesis test is performed at a confidence interval of 95 per cent and a z-

critical level of 1.96.


Table 5.11: Summary significance test of share returns of companies affected by protected and unprotected labour strikes

Event outcome: Effects of protected and unprotected strikes collectively

CAAR

AR

-0.445%

n1

61

0.005557118

H0 AR=0

H1 AR0

Test statistic -2.46

Probability that H0 is true 0.02

Significance level a 5%

Confidence level 95%

Critical value 1.96

DF 59

Std error 0.20%

95% CI -0.04%

-0.85%

Test Reject H0

At a 95 per cent confidence interval and z-critical value of 1.96, the research rejects the null

hypothesis with a z-statistic of -2.46. This makes the statement true for the alternative

hypothesis that the resolve of labour strikes affects the share returns of the JSE Top 40

companies.


5.5 COMPARISON OF SHARE RETURNS OF COMPANIES AFFECTED

BY PROTECTED AND UNPROTECTED STRIKES, RESPECTIVELY

This section aims to satisfy the objective of identifying whether there is a distinguishable

difference in the share return of companies affected by protected and unprotected strikes,

respectively. The test performed in this section aims to examine the study’s second

hypothesis. Figure 5.11 presents a graphical representation of the share returns of the JSE

Top 40 companies that were affected by protected and unprotected strikes, respectively. The

below graph illustrates the movement in share returns of companies affected by labour strikes,

the average share returns and the confidence intervals of both protected (P) and unprotected

(UP) strikes over the 61-day window period.

Figure 5.11: Comparison of share returns of companies affected by protected and

unprotected strikes


Trend analysis of share returns of companies affected by protected and

unprotected strikes, respectively

The share returns of companies affected by protected and unprotected strikes illustrate

varying trajectories in their movement in share returns of affected companies. Companies

affected by protected strikes experienced a decline in share returns at the start of the

negotiations period, which continued to decline past the day of the strike. The returns of

companies affected by protected strikes rebounded and began to grow 5 days after the day of

the strike. In contrast, the share returns of companies affected by unprotected strikes

maintained a growth trajectory well into the period of wage negotiations. Fifteen days closer

to the day of the strike, the share returns of companies affected by unprotected strikes began

to deteriorate, reaching a low 2 days before the day of the strike. Following the day of the

announcement of the strike, the share returns of the affected companies rebounded and

continued to trade right after the day of the strike.

The trend in share returns of companies affected by protected and unprotected strikes depicts

the findings of Seedat (2013), Bhana (1997), and Norton Rose Global (2009). Illustrating the

belief that companies affected by unprotected strikes have no cost implication on the share

returns of affected companies as a result of affected companies not bearing any obligation to

protesters' demands due to the nature of the strike. This is illustrated in the maintained growth

in share returns during the negotiations period, which experienced a slight decline 15 days

closer to the day of the strike, thereafter, continuing to trend between a confidence interval of

2 per cent and 4.66 per cent after the day of the strike. Confidence intervals are statistical

measures of a probability that a population parameter will fall between 2 set values for a certain

proportion of times (Kenton, 2020). The trend in share returns of companies affected by

unprotected strikes remained within the estimated confidence interval, further illustrating no

cost implication as movements in share returns were certain.

In contrast, the share returns of companies affected by protected strikes began to deteriorate

at the start of the wage negotiation and continued through till the day of the strike. The decline

in the share returns illustrated the market's expectation of a potential increase in operational

costs at the start of wage negotiations. This is further observed in the drastic decline in share

return on Day 1, following the announcement of the strike continuing to 5 days after the strike.

On Day 5, the share return of the affected companies rebounded and began to grow indicating

a positive perception in wage settlements. The trend in share return traded outside of the


sample’s confidence interval illustrating uncertainty in the share returns of companies

engaging in protected wage negotiations.

The distinction in share returns of companies affected by protected and

unprotected strikes

Table 5.12 presents the comparison of the effects that an unprotected strike has on the share

return of the JSE Top 40 companies in relation to the share return of protected strikes. This

section aims to test our second hypothesis that aims to establish whether there is a distinction

between the share returns of companies affected by unprotected strikes, in relation to

companies affected by protected strikes. Similarly, a z-statistic at a confidence interval of 95

per cent and a z-critical value of 1.96 was considered in the study as the measure of

significance.

Table 5.12: Significance test of CAAR of companies affected by protected and unprotected strikes, respectively

Share returns of the JSE Top 40 companies affected by protected (P) and unprotected (UP) strikes

Day Cumulative average abnormal returns (P)

z-statistic Cumulative average

abnormal returns (UP) z-statistic

-30 0.46% 1.21 -0.13% -0.26

-29 0.06% 0.17 0.02% 0.04

-28 -0.32% -0.75 0.02% 0.07

-27 -0.55% -1.38** 0.22% 0.63

-26 -1.02% -2.09*** 0.71% 1.27

-25 -0.87% -2.51*** 1.93% 4.33***

-24 -0.97% -2.88*** 1.65% 1.76**

-23 -0.69% -1.96*** 2.99% 6.34***

-22 -0.28% -0.63 3.59% 6.17***

-21 -1.24% -3.93*** 4.22% 8.94***

-20 -0.88% -2.37*** 4.34% 11.99***

-19 -0.82% -1.92*** 5.17% 10.15***

-18 -1.46% -3.08*** 5.75% 13.22***

-17 -1.50% -2.92*** 4.73% 5.65***

-16 -2.01% -4.30*** 4.47% 12.96***


-15 -2.03% -7.08*** 3.94% 8.11***

-14 -1.75% -6.68*** 4.62% 10.28***

-13 -2.53% -7.54*** 5.53% 8.33***

-12 -2.15% -5.55*** 5.12% 12.73***

-11 -2.84% -5.94*** 5.11% 15.44***

-10 -2.42% -6.45*** 4.74% 9.77***

-9 -2.60% -8.22*** 4.83% 9.08***

-8 -2.24% -4.90*** 4.34% 6.13***

-7 -2.38% -9.21*** 4.15% 8.77***

-6 -2.41% -5.45*** 4.08% 13.50***

-5 -1.27% -1.50* 3.68% 6.24***

-4 -2.05% -5.35*** 3.58% 8.01***

-3 -2.16% -3.75*** 2.02% 3.32***

-2 -1.40% -4.12*** 3.20% 6.56***

-1 -1.64% -5.16*** 3.12% 5.12***

0 -1.97% -3.85*** 3.31% 4.44***

1 -2.48% -8.42*** 4.22% 11.76***

2 -2.59% -4.91*** 4.21% 13.22***

3 -2.54% -6.06*** 3.59% 8.71***

4 -3.53% -7.78*** 3.24% 5.00***

5 -3.12% -7.86*** 3.03% 6.37***

6 -2.20% -7.58*** 3.11% 7.76***

7 -2.12% -7.16*** 3.99% 7.26***

8 -2.36% -5.22*** 4.01% 9.51***

9 -2.21% -8.08*** 4.46% 9.45***

10 -1.95% -4.42*** 4.66% 8.17***

11 -2.06% -6.45*** 3.92% 10.03***

12 -2.63% -6.28*** 3.48% 5.91***

13 -2.00% -0.65 3.45% 14.05***

14 -1.88% -4.89*** 3.60% 9.63***

15 -1.47% -3.82*** 3.43% 5.57***

16 -1.48% -4.12*** 2.60% 5.05***

17 -1.49% -3.95*** 3.03% 8.11***

18 -0.75% -2.56*** 3.04% 6.40***

19 -0.46% -1.25 2.93% 4.92***

20 -0.91% -3.17*** 3.67% 5.13***


21 -0.53% -1.80** 3.01% 6.45***

22 -0.46% -1.01 3.34% 7.96***

23 -0.42% -1.10 3.54% 9.01***

24 -0.39% -1.17 2.93% 5.18***

25 -1.33% -3.16*** 3.40% 9.20***

26 -1.01% -2.57*** 2.84% 4.84***

27 -0.64% -2.65*** 2.08% 5.90***

28 -0.36% -0.99 1.95% 4.06***

29 -0.60% -1.49 2.02% 4.16***

30 -0.80% -2.61*** 2.21% 3.32***



At a confidence interval of 95 per cent and a z-critical value of 1.96, there is a clear indication

that labour strikes affect the share return of the JSE Top 40 companies. Greater significance

is found in the share returns of unprotected strikes that continued to trade as normal and only

began to experience losses in share returns 18 days before the day of the strike and right

through the event day. AR were equally found in the share returns of protected strikes. The

share returns of affected companies experienced significant losses from the beginning of the

negotiations period right through the announcement of the strike and the day of the strike. The

share returns of companies affected by protected companies rebounded after the day of the

strike.

Periodic analysis of the JSE Top 40 companies affected by protected

labour strikes

Table 5.13 presents an interval analysis of share returns of companies affected by protected

strikes. Table 5.13 presents the average CAAR, standard deviation and z-statistic of protected

labour strikes at a 5, 10 and 20- and 30-day interval, before the day of the strike, after the day

of the strike and the overall event. The interval analysis aims to provide periodic analysis of

the event window.


Table 5.13: Interval analysis of protected labour strikes

Interval analysis protected strikes


Before the event CAAR -1.703% -2.057% -1.927% -1.465% STDEV 0.028 0.007 0.024 0.023 Z-Test 1.081 -5.412 -5.075 -3.875

After the event CAAR -3.529% -3.529% -2.012% -1.559% STDEV 0.024 0.022 0.029 0.026 Z-Test -7.005 -6.749 -5.231 -4.105

Overall event CAAR -2.248% 0356% -1.969% -1.519% STDEV 0.026 0.023 0.026 0.024 Z-Test -5.341 -5.974 -5.121 -3.988


The average share returns of protected labour strikes gradually declined over the 10-, 20-,

and 30-day intervals before the day of the strike from -1.465 per cent to -2.057 per cent. In

the 5 days interval before the day of the strike, the average share returns of the affected

company rebounded to -1.703 per cent. The average share returns of protected labour strikes

presented similar results as protected and unprotected strikes, collectively, with volatility

fluctuating between 0.028 and 0.023 within the 5, 20-, and 30-day interval. At the 10-day

interval before the day of the strike, volatility was relatively low with 0.007. The average share

returns of the affected companies at 10-, 20- and the 30-day interval before the day of the

strike presented abnormal share returns with z-statistics greater than 1.96 critical value at a

confidence interval of 95 per cent. The 5-day confidence interval before the day of the strike

presented a z-statistic smaller than the z-critical value, indicated this within 5 before the day

of the strike share returns, affected companies did not present significant AR.


After the day of the strike, the average share returns of affected companies gradually declined

with each interval from – 3.529 to -1.559 per cent in the 5-day interval to the 30-day interval.

The 5-, 10-, 20- and 30-day interval after the day of the strike for protected labour strikes

presented z-values greater than the z-critical value of 1.96 at a 95 per cent confidence interval.

This was indicated after the day of the strike; share returns of affected companies present AR.

Volatility in the average share returns of affected companies fluctuated between 0.022 and

0.029.


Overall event

The average share returns of protected labour strikes varied over the 5-, 10-, 20- and the 30-

day interval before and after the day of the strike, between -1.465 and -2.057 per cent. At the

5-day interval before and after the day of the strike, the average share returns of the affected

companies were significantly higher than the share returns of affected companies at intervals

10, 20, and 30 before and after the day of the strike, with share returns of -2.248 per cent. At

the 10-day interval before and after the day of the strike the average share returns of affected

companies declined to 0.356 per cent. The average share returns of companies affected by

protected labour strikes over the periodic interval of 5, 10, 20 and 30 days before and after the

day of the strike, indicates that protected labour strikes result in significant AR. The z-statistic

of the protected strikes 5, 10, 20 and 30 days after the day of the strike was greater than the

z-critical value of 1.96 at a 95 per cent confidence interval.

Periodic analysis of the JSE Top 40 companies affected by unprotected

strikes

Table 5.14 presents an interval analysis of share returns of companies affected by unprotected

strikes. Table 5.13 presents the average CAAR, standard deviation and z-statistic at a 5-, 10-

and 20- and 30-day interval, before the day of the strike, after the day of the strike and the

overall event. The interval analysis aims to provide periodic analysis of the event window.

Table 5.14: Interval analysis of unprotected labour strikes

Interval analysis unprotected strikes


Before the event CAAR 3.120% 3.774% 4.326% 3.392%

STDEV 0.016 0.003 0.015 0.015 z-test 1.305 7.650 9.268 7.156

After the event CAAR 3.657% 3.852% 3.583% 3.299% STDEV 0.013 0.014 0.014 0.014 z-test 9.014 8.722 8.101 7.404

Overall event CAAR 3.382% 0.572% 3.939% 3.345% STDEV 0.016 0.015 0.015 0.015 z-test 7.160 8.008 8.581 7.233



The share returns of companies affected by unprotected labour strikes maintained a relatively

high AAR over the 5, 10, 20, 30-day interval, before the day of the strike. In the 5-day interval

before the day of the strike, AAR of affected companies declined relative to the 10-, 20- and

30-day intervals. The standard deviation of 0.016 indicated that there was an increase in

volatility in the 5-day interval after the decline in volatility in the 10-day interval. The increase

in volatility is attributed to markets’ anticipation of a looming strike as a result of increased

movement in the share return of the affected companies. Significant AR were found in the 10-

, 20-, and 30-day intervals. In the 5-day interval, the share returns of affected companies did

not present significant AR. This indicating the market's anticipation of a looming strike was

indefinite.


The share return of affected companies was relatively higher in the respective intervals after

the strike commenced, in relation to the intervals in the 30 days before the day of the strike.

The share returns of affected companies fluctuated between 3.299 per cent and 3.657 per

cent, within the respective intervals. Movement in the share returns of affected companies

after the strike commenced was relatively stable, volatility across respective intervals

fluctuated between 0.013 and 0.014. Significant AR were found across the respective intervals

in the 30 days after the strike commenced. This informed the researcher that the markets did

not anticipate the advent of an unprotected strike.

Overall strikes

The share returns of affected companies presented similar returns over the 5, 20, 30-day

interval, except for the 10-day interval. The decline in share return in the 10-day interval over

the 61-day event window indicates that there is less of an opportunity for profit-taking in the

10-day interval. Volatility in the share return of the affected companies remained relatively

stable across, respective intervals, fluctuating between 0.015 and 0.016. Significant AR were

found across respective intervals indicating that periods of labour strikes result in significant

AR.


Summary hypothesis test of companies affected by protected and

unprotected labour strikes, respectively

This section aims to assess the distinction in share returns of companies affected by protected

and unprotected strikes, respectively. Table 5.15 presents a summary overview comparing

the effects of protected and unprotected labour strikes on the share returns of the JSE Top 40

companies. The z-test is conducted at a confidence interval of 95 per cent and a critical level

of 1.96.

Table 5.15: Significances test of share return of companies affected by protected and unprotected labour strikes, respectively

Event outcome: Comparison between protected and unprotected strikes

Protected Unprotected

-1.52% 3.35%

n1 n2

61 61

0.87% 1.33%

H0 =

H1 ≠

Test statistic 3.78

Probability that H1 is true 0.025%



Critical value 1.96

DF 120

Std error 0.05%

95% CI -0.65%

-2.39%

Test Reject H0

95% CI 4.66%

2.03%

In order to summarise the hypothesis test comparing the share returns of the JSE Top 40

companies affected by protected and unprotected strikes. The outcome of the z-test in Table

5.15 presented a z-statistic of 3.78, which was greater than the z-critical value of 1.96 at a 95

per cent confidence interval. This allowed the researcher to reject the null hypothesis, making


the statement true for the alternative. Thus, the researcher can conclude that there is a

distinction in the share returns of companies affected by protected and unprotected strikes.

5.6 MOVEMENT IN SHARE RETURNS OF AFFECTED COMPANIES

BEFORE AND AFTER THE DAY OF THE STRIKE

This section of the chapter establishes whether there is a difference in the movement in share

returns of companies affected by protected and unprotected strikes, respectively, before and

after the day of the strike.

Share returns of protected strikes before and after the day of the

announcement of the strike

Figure 5.12 presents the difference in share returns of protected strikes before and after the

day of the strike. Modelled on Figure 5.12 are the CAAR of protected, their average CAARs

and their respective confidence intervals.

Figure 5.12: Difference in share returns of protected strikes before and after the day of the announcement of the strike


Trend analysis of the movement in share return of companies affected

by protected strike before and after the day of the strike

Figure 5.12 illustrates that there is a clear difference in the movement in share returns of

companies affected by protected strikes before and after the day of the strike (Day 0). Before

the day of the strike, the share returns of affected companies started to decline at the

beginning of the negotiations process at Day 30. Figure 5.12 illustrates the decline in share

return of affected companies continued from Day 30 until Day - 5. Five days before the day of

the strike the share returns of affected companies started showing signs of recovery and

began to rebound. Volatility in share return is observed between Day 5 and Day 1, with share

returns dropping on the day of the strike. It is observed in Figure 5.12 that the share returns

of the affected companies continue to show signs of recovery right through to Day 25 where

it starts to reach equilibrium.

The deterioration in share returns of companies affected by protected strikes is attributed to

leakage of private information and implicit cost of a protected strike Seedat (2013), Bhana

(1997). Imberman (1979) in support of Norton Rose Global (2009) adds that the decline in

share return of companies affected by protected strikes before the day of the strike is due to

publicised disagreements during wage negotiations, companies desire to stockpile produce

and standard cost of operations. Imberman (1979) highlights that publicised disagreements

during wage negotiations often result in hostility affecting future productivity and workers'

concerns of finished products.

According to Imberman (1979), when interruptions in supply occur during labour strikes;

employers resort to stockpiling which results in incurred costs by the employer engrossing the

share returns of investors. The costs associated with stockpiling entail: overtime for workers,

transportation cost of warehouses, and additional warehouse space. Additional costs

absorbing investor share returns are the standard operating costs of the company, which entail

the loss of trained employees, which left the company during the strike, cost of idle machinery

during the strike and overtime to replenish depleted inventory.

Recovery in the share returns of companies affected by protected strikes is observed 2 days

after the day of the strike. The findings align with Nigidi (2011), who indicated that labour

strikes in South Africa generally last 1–5 days. Nigidi (2011) added that owing to the general

duration of the strikes in South Africa, costs associated with labour strikes are not inflated as

strikes do not commence for an extended period. The negative reaction in share return can

be attributed to investor sentiments and the factors of the uncertainty of the wage settlement,


which subsequently rebound on Day 5. The rebound in share returns on Day 5 are sentiments

of a positive wage settlement received by the market.

Hypothesis test of the share returns of companies affected by

protected strikes before and after the day of the strike

Table 5.16 presents the results of the z-test on the movement in share returns of companies

affected by protected labour strikes before and after the day of the strike. The CAAR of

companies affected by protected strikes and their respective z-statistic are presented in Table

5.16. The study conducts its z-statistic at a confidence interval of 95 per cent with a z-critical

value of 1.96.

Table 5.16: Share returns of companies affected by protected strikes before and after the day of the strike

Share returns of companies affected by protected labour strikes before and after the day of the strike

Day Cumulative average

abnormal return (P) z-statistic

-30 0.460% 1.21

-29 0.061% 0.17

-28 -0.321% -0.75

-27 -0.551% -1.38*

-26 -1.020% -2.09***

-25 -0.865% -2.51***

-24 -0.966% -2.88***

-23 -0.688% -1.96***

-22 -0.277% -0.63

-21 -1.242% -3.93***

-20 -0.880% -2.37***

-19 -0.819% -1.92**

-18 -1.461% -3.08***

-17 -1.501% -2.92***

-16 -2.006% -4.30***

-15 -2.031% -7.08***

-14 -1.747% -6.68***

-13 -2.529% -7.54***


-12 -2.147% -5.55***

-11 -2.843% -5.94***

-10 -2.423% -6.45***

-9 -2.602% -8.22***

-8 -2.244% -4.90***

-7 -2.380% -9.21***

-6 -2.406% -5.45***

-5 -1.270% -1.50**

-4 -2.051% -5.35***

-3 -2.158% -3.75***

-2 -1.398% -4.12***

-1 -1.636% -5.16***

0

1 0.503% 1.71**

2 -0.608% -1.16

3 -0.560% -1.34**

4 -1.533% -3.38***

5 -1.132% -2.85***

6 -0.231% -0.79

7 -0.151% -0.51

8 -0.385% -0.85

9 -0.243% -0.89

10 0.015% 0.04

11 -0.097% -0.30

12 -0.648% -1.55*

13 -0.034% -0.01

14 0.084% 0.22

15 0.484% 1.26

16 0.476% 1.32*

17 0.464% 1.23

18 1.190% 4.04***

19 1.472% 3.98***

20 1.031% 3.57***

21 1.406% 4.75***

22 1.472% 3.19***

23 1.515% 3.96***


24 1.547% 4.64***

25 0.625% 1.49*

26 0.939% 2.39***

27 1.304% 5.43***

28 1.576% 4.35***

29 1.338% 3.32***

30 1.143% 3.73***



Table 5.16 illustrates that the z-statistic of companies affected by protected strikes gradually

deteriorated throughout the 30-day negotiations periods. Following the day of the strike, the

z-statistics of the affected companies along with their share returns rebound and continued to

grow throughout the event window. The z-test, in Table 5.16, informs the researcher that

before the day of the strike there are significant losses in share returns of affected companies.

Table 5.16 illustrates that after the day of the strike share returns of the affected companies

experience significant growth as it rebounds.

Summary hypothesis test of companies affected by protected labour

strikes before and after the day of the strike

Table 5.17 presents the distinction in share returns of companies affected by protected strikes

before and after the day of the strike. Table 5.17 summarises the hypothesis test by comparing

share returns of the JSE Top 40 companies affected by protected strikes before and after the

day of the strike. The z-test is conducted at a confidence interval of 95 per cent and a critical

level of 1.96.


Table 5.17: Significance test of share return of companies affected by protected labour strikes before and after the day of the strike

Event outcome: Variance in share return before and after the day of the strike

Cumulative before Cumulative after

μ1 μ2

-1.46% 0.43%

n1 n2

30 30

σ1 σ2

0.0086 0.0088

H0 μ1 = μ2

H1 μ1 ≠ μ2

Test statistic 8.45

Prob that H0 is true 0%

Significance level α 5%


Critical value 2.00

DF 58

Std error 0.22%

95% CI -1.24%

-1.96%

Test Reject H0

Table 5.17 indicates that a z-statistic of 8.45 was obtained to establish the distinction in share

returns of companies affected by protected strikes before and after the day of the strike. The

obtained z-statistic in Table 5.17 is significantly greater than the z-critical value of 1.96. This

allowed the researcher to reject the null hypothesis. Therefore, making the statement true that

there is a clear distinction in the share return of companies affected by protected strikes before

and after the day of the strike.

Share returns of unprotected strikes before and after the day of the

announcement of the strike

Figure 5.13 presents the difference in share returns of unprotected strikes before and after the

day of the strike. Modelled on Figure 5.13 are the CAAR of protected, their average CAARs

and their respective confidence intervals.


Figure 5.13: Difference in share returns of companies affected by unprotected strike before and after the day of the strike

Figure 5.13 illustrates that there is a clear distinction in the share return of companies affected

by unprotected strikes before and after the day of the strike. In contrast with the movement in

share returns of companies affected by protected strikes, the share returns of companies

affected by unprotected strikes maintain a growth trajectory well into the negotiations process

and started to decline -17 days before the day of the strike. Figure 5.13 indicates that at Day

17 the share returns of the affected companies begin to enter a downward trajectory, which

continued right through the day of the announcement of the strike (Day 2) and the day of the

strikes (Day 0). Following the day of the strike, the share returns of the affected company

begin to trade at a significantly new low and showed signs of recovery at the end of the event

window.

Maintained growth in the share returns of companies affected by unprotected strikes at the

start of the wage negotiations are attributed to unprotected strikes going undetected before

the day of the strike and there not being cost implications to demands made by workers

engaging in unprotected strikes (Norton Rose Global, 2009). The gradual decline in share

return closer to the day of the strike at Day 17, is attributed to market speculation of a looming

unprotected strike and leaked information regarding internal grievances between workers and


the affected firms along with their unions. Increased tension between the affected firm and

their workers can be observed at Day 2 and the day of the strike with the share returns

dropping significantly on the day of the strike and continuing to Day 2. From Day 2 of the strike,

the share return of affected companies normalises and can trade at a new low and without

recovering. According to Seedat (2013) much as there are no cost implications to unprotected

strikes, signs of a decline in the share returns of the affected company are evident.

Hypothesis test of the share returns of companies affected by

unprotected labour strikes before and after the day of the strike

Table 5.18 presents the difference in share returns of companies affected by unprotected

strikes before and after the day of the strike. The CAAR of companies affected by unprotected

strikes and their respective z-statistic are presented in Table 5.18. The study conducted the

z-test at a confidence interval of 95 per cent with a z-critical value of 1.96.

Table 5.18: Share returns of companies affected by protected labour strikes before and after the day of the strike

Share returns of affected companies before and after the day of the strike

Day Cumulative average abnormal return (UP) z-statistic

-30 -0.131% -0.26

-29 0.025% 0.04

-28 0.022% 0.07

-27 0.222% 0.63

-26 0.712% 1.27

-25 1.926% 4.33***

-24 1.651% 1.76**

-23 2.995% 6.34***

-22 3.592% 6.17***

-21 4.221% 8.94***

-20 4.341% 11.99***

-19 5.174% 10.15***

-18 5.750% 13.22***

-17 4.734% 5.65***

-16 4.468% 12.96***

-15 3.942% 8.11***

-14 4.621% 10.28***


-13 5.532% 8.33***

-12 5.117% 12.73***

-11 5.108% 15.44***

-10 4.737% 9.77***

-9 4.829% 9.08***

-8 4.343% 6.13***

-7 4.151% 8.77***

-6 4.080% 13.50***

-5 3.677% 6.24***

-4 3.580% 8.01***

-3 2.018% 3.32***

-2 3.200% 6.56***

-1 3.123% 5.12***

0

1 -0.9397% -2.62***

2 0.9253% 2.91***

3 0.2869% 0.70

4 -0.0824% -0.13

5 -0.2982% -0.63

6 -0.2085% -0.52

7 0.6933% 1.26

8 0.7146% 1.70**

9 1.1858% 2.51***

10 1.3934% 2.44***

11 0.6280% 1.61*

12 0.1757% 0.30

13 0.1365% 0.56

14 0.2918% 0.78

15 0.1219% 0.20

16 -0.7423% -1.44*

17 -0.2985% -0.80

18 -0.2870% -0.61

19 -0.4015% -0.67

20 0.3717% 0.52

21 -0.3177% -0.68

22 0.0289% 0.07


23 0.2338% 0.60

24 -0.3949% -0.70

25 0.0846% 0.23

26 -0.4905% -0.84

27 -1.2795% -3.63***

28 -1.4128% -2.94***

29 -1.3348% -2.74***

30 -1.1465% -1.73**



The outcome of the z-statistics of companies affected by unprotected strikes before and after

the day of the strike are inverse in relation to the z-statistics of companies affected by protected

strikes. The z-statistic of companies affected by unprotected strikes in Table 5.18, presented

significantly high-test values at the beginning of the negotiations period, between Day 23 and

-1. Following the day of the strike, the z-statistic of the affected companies deteriorated

significantly as the share returns of the affected companies began to decline. The outcome of

the z-statistics informs us that share returns of affected companies maintain a positive

trajectory 30 days before the strike and deteriorate after the day of the strike.

Summary hypothesis test of companies affected by unprotected labour

strikes before and after the day of the strike

Table 5.19 provides a summary outcome of the distinction in share returns of companies

affected by unprotected strikes before and after the day of the strike. Table 5.19 presents the

summary overview of share returns of the JSE Top 40 companies affected by unprotected

strikes before and after the day of the strike. A z-test is conducted at a confidence interval of

95% and a critical level of 1.96.


Table 5.19: Significance test of share return of companies affected by unprotected labour strikes before and after the day of the strike

In order to summarise the hypothesis test with respect to the difference in share returns of

companies affected by unprotected strikes before and after the day of the strike over the 61-

day window period at a confidence interval of 95 per cent and a critical value of 1.96. Table

5.19 indicates that a z-test statistic of -9.93 which is significantly greater than the z-critical

value of 1.96. This allows the researcher to reject the null hypothesis. Therefore, making it

true that there is a clear distinction in the share return of companies affected by unprotected

strikes before and after the day of the strike.

5.7 SYNOPSIS

The objective of this chapter was to present the empirical findings of the study’s objectives.

The chapter presented an analysis and interpretation of the study’s findings and detailed how

the study’s objectives and hypothesis were tested and achieved. An event study methodology

was applied in an attempt to identify abnormal share returns investors are likely to obtain as a

result of labour strikes. The AAR and CAAR of the JSE Top 40 companies affected by

Event outcome: Average differences before and after

Cumulative before Cumulative after

μ1 μ2 3.39% -0.08%

n1 n2 30 30

σ1 σ2 0.0177 0.0072

H0 μ1 = μ2 H1 μ1 ≠ μ2

Test statistic -9.93

Probability that H1 is true 0.0%



Critical value 1.96

DF 58

Std error 0.69%

95% CI 4.77%

1.96%

Test Reject H0


protected and unprotected labour strikes between 2010 and 2017 were estimated, analysed

and interpreted. In order to examine the results, the following analysis was conducted:

• A descriptive summary of the CAAR of protected and unprotected labour strikes, as a

collective and in their respective form.

• An industry-specific analysis of respective companies.

• A cumulative analysis of the effects of protected and unprotected labour strikes on the

share return of the JSE Top 40 companies.

• A comparison of the effects that protected and unprotected labour strikes had on the


• A comparison of the effects of protected and unprotected labour strikes on the share

return of the JSE Top 40 companies before and after the day of the strike was

conducted.

The descriptive summary revealed that labour strikes have a negative effect on the share

return of the JSE Top 40 companies. The study found that protected labour strikes had a

greater effect on the share returns of affected companies as a result of the cost implication of

protected labour strikes. The study findings were supported by results from previous studies

that attributed to the negative effects of protected labour strikes to the market’s perception of

increased cost to the company as a result of employees demands and employer’s subsequent

obligation to employee demands. Unprotected labour strikes in relation to protected strikes,

experienced a significant amount of volatility due to a loss in daily production, resources and

investor confidence.

The study’s industry analysis revealed that the mining industry experienced a large number of

labour strikes in relation to all other industries. These findings were in line with the Department

of Labour’s Annual Industrial Action Report, which found that South Africa’s labour market was

dominated by strikes within the public sector, manufacturing, transport, construction and

mining industry and attributed their reoccurrence to growth in unions and the historical

discrimination and exploitation of employees, specifically within the mining industry. The

study’s industrial analysis further revealed that the share returns of affected companies

experienced a significant amount of volatility throughout the 61-day event window across all

industries. The volatility in share returns of affected companies per industry was attributed to

workers' willingness to ensure a labour strike to obtain the most favourable outcome during

wage negotiations, along with the arrival of news of a looming strike to financial markets.


These findings were based on Zeuthen (1930), Hicks (1932) and Ashenfelter and Johnson

(1969), who found that workers enter labour negotiations based on a suitable concession of

an expected value of holding out for the most desired outcome during wage negotiations.

The cumulative analysis of the effects of protected and unprotected labour strikes on the share

return of the JSE Top 40 companies affirmed that labour strikes affect the share return of

affected companies. The trend analysis of the movement in share returns of protected and

unprotected labour strikes, collectively, presented a decline in the share return of affected

companies 21 days before the day of the strike, which continued passed the day of the strike

and rebounded 5 days after the day of the strike. The movement in share returns of affected

companies prior to the day of the strike was attributed to the arrival of news of a looming strike

to financial markets. Significant AR at a confidence interval of 95 per cent were found between

15 days before the day of the strike and 9 days after the strike commenced. A summary

analysis of the cumulative effects of protected and unprotected labour strikes on the share

return of the JSE Top 40 companies concluded that labour strikes affect the share return of

affected companies.

A comparison of the effects of protected and unprotected labour strikes on the share return of

the JSE Top 40 companies was conducted to identify a distinction in share return of affected

companies. The study found that in contrast to the share return of companies affected by

unprotected strikes the share returns of companies affected by protected labour strikes

declined at the beginning of the wage negotiation and continued past the day of the strike and

rebounded after the day of the strike. The share returns of companies affected by unprotected

strikes maintained a growth trajectory and only experienced a decline in share return 15 days

closers to the day of the strike. However, 5 days before the day of the strike the share return

of companies affected by unprotected strikes rebounded and began to trade past the day of

the strike. The movement in share returns of companies affected by protected and unprotected

strikes affirmed the market perception of there not being a cost implication to companies

affected by unprotected labour strikes. Significant AR were found in the share returns of both

protected and unprotected strikes. The summary significance test revealed that there is a

distinction in the movement in share returns of companies affected by protected and

unprotected labour strikes.

A final evaluation of the movement in share return of companies affected by protected and

unprotected labour strikes before and after the day of the strike was conducted. The findings

of the evaluation correlated with the findings in Section 5.4, which found a significant decline

in the share return of companies affected by protected labour strikes before the day of the


strike, which later rebound after the day of the strike. Correspondingly, the share return of

unprotected strikes maintained a growth trajectory prior to the day of the strike and continued

to trade after the day of the strike.


CHAPTER 6: CONCLUSION AND RECOMMENDATIONS

“You will never plough a field if you only turn it over in your mind.” Irish Proverb

6.1 INTRODUCTION

South African companies experienced a large increase in the number of labour strikes

following the 2008/2009 GFC. The GFC placed a strain on global economic conditions,

resulting in high price levels, growth in unemployment, and slow economic growth. The

occurrence of the GFC exposed a large number of South Africa’s socio-economic ails of

minimum wages, high levels of unemployment and inequality, which resulted in increased

demands from workers to employers. Men and women around the world were subjected to

accepting minimum wages as a result of sluggish global economic conditions. The notion of

accepting minimum wages was with fury and frustration in South Africa’s labour market,

resulting in a large increase in the number of labour strikes.

Labour strikes in South Africa more than doubled following the GFC, increasing from 51 in

2010 to 132 in 2017. In 2010 a historical number of 20 674 737 working days3 were lost in

production, as a result of prolonged public servant strikes. The rise in the number of labour

strikes was as a result of wage discrimination, inequality, and socio-economic conditions. The

reoccurrence of labour strikes in South Africa between 2010 and 2017 was likened to the

certainty of death and taxes. The increase in labour strikes during 2014 dampened investor

confidence and brought the country’s economy to the brink of recession.

The effect of labour strikes resulted in losses to both workers and employers. In periods of

labour strikes workers lost out in salaries and wages owing to the no work no pay agreement

between workers and the employer. In contrast, firms lost out on days in production and

subsequently lost in profits. Firms are established with the main purpose of creating profits

and providing maximum share returns for shareholders, through the reduction of redundant

functions and optimum usage of production inputs. The share value of publicly listed

companies is embedded in the share price of the firm. Investors make use of a company’s

share price to evaluate the market’s perception of a security. Disruptions in daily operations

of a firm in the form of labour strike are a halt in production, which affects investor confidence

and subsequently investor share returns.




The study observed the resolve of labour strikes and how it affected share returns of the JSE

Top 40 companies, through an event study methodology. The study examined 41 companies

listed on the JSE Top 40 index which were affected by labour strikes between 2010 to 2017.

The data sample comprised companies from the mining, consumer goods, retail, brewery,

telecommunications, corporate and pharmaceutical industry. The purpose of this chapter is to

present a summary of the achieved theoretical and empirical objectives. The main findings of

the empirical objectives are discussed to highlight the contribution of the study.

Recommendations of the study are drawn from the literature review and the research findings.

The concluding remarks and recommendations of the study are present in the last section of

the chapter, followed by limitations of the study and future research opportunities of the study.

6.2 OVERVIEW OF THE STUDY

The study’s recommendations are articulated in this chapter based on the insights gained from

the previous five chapters, which have contributed to the research findings. This section of the

chapter provides a synopsis of the chapters encountered in the study. In Chapter 1, an

introduction and background to the study are provided, along with the problem statement,

which gave rise to the need to conduct the study. Chapter 1 outlined the primary objective,

theoretical objectives, and empirical objectives and the set-out hypotheses to be

accomplished in accordance with the problem statement. The primary objective of the study

is to evaluate the effects that labour strikes have on the share returns of JSE Top 40

companies.

Theoretical objectives

In order to achieve the primary objective, the following theoretical objectives were formulated

to contextualise the study:

• Provide a theoretical overview of labour strikes to establish a general understanding of the

dynamics of labour strikes and how the resolve of a strike is established with regard to

protected and unprotected strikes.

• Provide an overview of the EMH as a basis of proving whether the event of labour strikes

does affect the share price of publicly listed companies.

Empirical objectives

In order to achieve the primary objective of the study an empirical study was conducted, and

the objectives were as follows:



companies.




the JSE Top 40 companies, respectively, and collectively, before and after the day of

the strike.

Chapter 2 aimed to achieve the theoretical objective I set out in Chapter 1. The chapter

commenced by contextualising labour strikes in the South African context, by providing a

historical background of labour strikes, defining labour strikes in their different forms and

providing a theoretical framework to labour strikes. The nature and purpose of collective

bargaining as a critical function of wage negotiations are defined in Chapter 2, detailing the

process of collective bargaining, the various approaches to collective bargaining, and legal

procedure to labour strikes. A review of previous studies evaluating the effect that labour

strikes had on the share return of affected companies is provided to further contextualise the

study and provide supporting evidence as a base to the study. The chapter further provides

background to the GFC, which gave rise to the financial crises and how it affected the South

African economy.

Correspondingly, Chapter 3 was aimed to achieve theoretical objective II laid out in Chapter

1. The chapter began with providing historical background and insight into the EMH. The

introduction to Chapter 3 was followed by definitions of an ECM and the assumptions of what

makes an ECM. The three forms of EMH are later detailed, along with the implications that

investors face when participating in ECM. Developments around the EMH in the form of

“financial market anomalies” are presented. A large focus is given to “behavioural finance” as

the most recent and influential financial market anomaly to contend the EMH. Chapter 3 further

presented a review of other previous studies with respect to the JSE being an ECM to provide

supporting evidence of the JSE being an efficient market.

Chapter 4 detailed and described the research design and methodology followed to gather

and analyse the data to achieve the study’s empirical objectives. Chapter 4 provided

supporting arguments for using the research approach, the sample design process, the

sample size as well as the research instrument used in the collection and analyses of the data

sample. The study made use of a quantitative research approach to evaluate the data sample.

A sample pool of 259 companies listed on the JSE ALSI were identified have been affected


by labour strikes between 2010 and 2017. Of the 259 companies, 41 companies were listed

on JSE Top 40 index. The study evaluated 32 JSE Top 40 companies that were affected by

unprotected strikes and 9 JSE Top 40 companies that were affected by unprotected labour

strikes.

Chapter 5 presents a detailed analysis and interpretation of the quantitative analysis

performed to achieve the study's empirical objectives. The chapter began by detailing the

empirical objectives and restating the set hypotheses to achieve the study's research

objective. A descriptive analysis of the results was presented, followed by an industrial

analysis of the various JSE Top 40 companies affected by labour strikes. This was followed

by an analysis of how protected and unprotected labour strikes, collectively, affected the share

return of affected companies. Further analysis of the effects of protected and unprotected

labour strikes, respectively, on the share returns of JSE Top 40 companies were presented.

This is followed by an analysis of the effects of protected and unprotected labour strikes before

and after the day of the strike, respectively.

6.3 FINDINGS OF THE STUDY

The primary objective of the study was to evaluate the effect that labour strikes have on the

share return of the JSE Top 40 companies. In order to achieve the primary research

objectives, the following empirical objectives were formulated and achieved.

Empirical Objective 1: Establishing whether labour strikes affect the

share returns of the JSE Top 40 companies

Empirical objective 1 was established to evaluate the effect that labour strikes have on the

share return of the JSE Top 40 companies. This objective was achieved in Section 5.4 by

evaluating CAAR of the JSE Top 40 companies affected by protected and unprotected strikes,

collectively. A trend analysis of the movement in share return of affected companies was

conducted, followed by a z-statistical significance test, a periodic analysis of CAAR and a

summary significance test. The study found that periods of wage negotiations resulted in a

significant amount of volatility in the share returns of affected companies, throughout the event

window. A significant amount of AR was found 16 days before the day of the strike, on the day

of the strike, and continued to 17 days after the labour strike commenced. Greater movement

in CAAR of affected the JSE Top 40 companies was found between the 5- and the 10-day

interval before and after the day of the strike. The summary significance test concluded that


indeed the resolve of protected and unprotected labour strikes affects the share return of JSE

Top 40 companies.

Empirical objective 2: Identifying the effects of protected and

unprotected labour strikes, respectively, on the share returns of the JSE

Top 40 companies

Empirical objective 2 was established to identify a distinction in how protected and unprotected

labour strikes affect the share return of the JSE Top 40 companies. The objective was

achieved in Section 5.5, through the evaluation of the CAAR of JSE Top 40 companies

affected by protected and unprotected labour strikes, respectively. A clear distinction in the

movement in share return of companies affected by protected and unprotected labour strikes

was found. The share return of companies affected by protected labour strikes deteriorated

from the beginning of the wage negotiations and recovered after the day of the strike. While

the share return of companies affected by unprotected labour strikes maintained a growth

trajectory from the beginning of the wage negotiations and began to decline 15 days before

the day of the strike, re-bounding 5 days before the day of the strike and continuing to trade

throughout the event window. The z-test found significant AR throughout the event window for

both protected and unprotected strikes. The summary significance test concluded that the

resolve of protected and unprotected labour strikes, respectively, affect the share return of

JSE Top 40 companies.

Empirical Objective 3: Identify the effects of protected and unprotected

labour strikes on the share returns of the JSE Top 40 companies,

respectively, before and after the day of the strike

Empirical objective 3 was formulated to present the effects of protected and unprotected

labour strikes, respectively, on the share returns of the JSE Top 40 companies before and

after the day of the strike. This objective was achieved in Section 5.6. The CAAR of companies

affected by protected and unprotected labours strikes were examined. The study found that

there is a notable difference in the movement in the share return of the affected companies

before and after the day of the strike. Similarly, to the outcome of empirical objective 2, the

share returns of companies affected protected labour strikes deteriorated in the 30 days before

the day of the strike and rebounded in the 30 days after the strike has commenced. The

opposite was found for the share returns of companies affected by unprotected strikes. The

share returns of companies affected by unprotected labour strikes maintained a positive

growth trajectory before the day of the strike and later deteriorated significantly after the day

of the strike.


6.4 CONTRIBUTION OF THE STUDY

Labour strikes are increasingly becoming a custom in South Africa’s economy. The growth in

incidents and days lost in production threaten investor confidence. Previous studies have

examined the effect that labour strikes have in the form of losses in salaries and wages and

revenue, which ultimately affect household income and the financial position of a firm. A gap

remained in accessing the effect that labour strikes have on the share return of publicly listed

companies. The study aimed to bridge the research gap on the impact that labour strikes have

on the share returns of publicly listed companies.

This was established through the achievement of empirical objective one. The findings of

empirical objective one bridged the gap in financial markets' understanding of the impact that

labour strikes have on the share returns of publicly listed companies. The study’s findings will

assist investors and portfolio managers to optimise their share returns during periods of labour

strikes. It will further induce consciousness of the impact of wage negotiations on companies

and implore bargaining agents to employ an integrative approach when engaging in wage

negotiations.

6.5 CONCLUDING REMARKS AND RECOMMENDATIONS

The outcome of studies primary objective indicated that labour strikes (protected and

unprotected) affect the share return of affected companies. Protected strikes were

found to have a greater effect on the share return of affected companies as a result of

the cost implication of a protected strike. The share returns of companies affected by

protected strikes begin to deteriorate at the start of the wage negotiation and continued

past the date of the strike. The share return of the affected company’s began to recover

at 5 days after the day of the strike. The immediate response to the arrival of news of

a looming strike to financial market at the start of the wage negotiation and throughout

the negotiation period to day 5 after the day of the strike reflects the efficiency of the

JSE. The decline in share return of affected companies at the start of wage negotiation

is an indication of a loss in investor confidence to the news a looming labour strike

arriving at the market.

The outcome of the study’s findings is indicative of the need for a conscious integrative

approach to wage negotiations. This is supported by the observed recovery in the


share return of affected companies 5 days after a settlement is reached. The early

recovery in share return is supported by Hick’s (1932) theory, that argues that if

bargaining agents were equally informed about the concession and resistance curves,

and were able to identify an equilibrium point, bargaining agents would have agreed

on a wage agreement and would avoid the costs suffered by both parties as a result

of the strike. A conscious integrative approach to wage negotiations will enhance

cohesion among bargaining agents and instil investor confidence in the labour market

and subsequently financial markets. In closing, a cohesive collective bargaining

process will eliminate losses due to disruptions in daily operations owing and ensuring

maximum share returns to stakeholders.


6.6 LIMITATIONS AND FUTURE RESEARCH

The study was limited by a lack of data, which indicated dates in which respective labour

strikes were concluded. The lack of data quality restricted the study from accessing the effects

of short- and long-term labour strikes on the share returns of the JSE Top 40 companies. This

further prevents the study to accurately access the time it takes for the share price of

companies affected by labour strikes to return to equilibrium. The limitations of the study

created opportunities for further research in areas where the study fell short and areas of

interest. The following areas are identified as areas of future research:

• Assessing the effect of short-term labour strikes on the share return of the JSE Top 40

companies, in relations to the effects of long-term strikes.

• Examining the duration, it takes for the share return of affected companies to return to

equilibrium.

• Exploring the impact of media coverage on the share return of JSE Top 40 companies.

• Accessing the impact of prolonged labour strikes on household income earning, with

respect to earnings forgone in pursuit of a more worthwhile wage agreement.


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ANNEXURE 1:ETHICAL CLEARANCE


ANNEXURE 2: DECLARATION

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