National and provincial labour market trends...

Statistical release P0211.4

National and provincial labour market trends

2003-2013

05 November 2013

Enquiries: Forthcoming issue: Expected release date

User Information Services Quarter 4, 2013 February 2014 Tel: (012) 310 8600/4892/8390

Statistics South Africa P0211.4

National and provincial labour market trends, 2003-2013


National and provincial labour market trends over the last decade, 2003- 2013

National and provincial labour market trends over the last decade

The national labour market results mask variations at provincial level which can often be quite large. The nine provinces differ in population size; land mass; demographic profile and economic structure. This report is the first in a quarterly series which will be released when the QLFS results are reported. The aim is to provide users with an analysis of various aspects of the South African labour market at provincial level based on current labour market information. Each report will focus on a different theme and the time frame of analysis will vary. Given that the QLFS series began in 2008, prior to which its predecessor the Labour Force Survey (LFS) was only conducted in March and September each year, analysis based on the 10-year period will not be undertaken in every report. The structure of these thematic reports will be in the first instance to report at national level and then across the nine provinces. The intention is that users are able to see how the provinces perform relative to each other and how they contribute to the national labour market picture. The results for each province will then be analysed as separate reports to provide an indepth understanding of the impact that a particular aspect of the labour market has on provincial labour market outcomes. Against this background, this – the first report - aims to bridge the gap in our understanding of the interrelationship between the national labour market results and those of the provinces over the last decade with special emphasis on employment outcomes by industry. Data sources used in this report are as follows:

2003 to 2007 - September LFS each year 2008 to 2013 – Q3: QLFS each year

The analysis suggests that provincial differences in the key labour market indicators are linked to various factors such as the labour intensity of the industrial base in each province and the education and skills level of the workforce.

_____________________________

PJ Lehohla Statistician-General: Statistics South Africa


National and provincial labour market trends, 2003-2013

Contents

1. South Africa labour market trends, 2003-2013

2. Western Cape labour market trends, 2003-2013

3. Eastern Cape labour market trends, 2003-2013

4. Northern Cape labour market trends, 2003-2013

5. Free State labour market trends, 2003-2013

6. KwaZulu-Natal labour market trends, 2003-2013

7. North West labour market trends, 2003-2013

8. Gauteng labour market trends, 2003-2013

9. Mpumalanga labour market trends, 2003-2013

10. Limpopo labour market trends, 2003-2013

11. Appendix

National and provincial labour market trends over the last decade

2003 – 2013

Statistics South Africa South Africa-1 P0211.4

South Africa labour market trends, 2003-2013

1. Introduction The national results often mask large provincial variations. As a result, this report focuses on provincial labour market trends and patterns over the period 2003 to 2013 with special emphasis on the industrial profile over the period. However, it should be noted that mining is a very clustered industry, hence the industry might not have been adequately captured by the QLFS sample. For more robust mining estimates, please use the Quarterly Employment Statistics (QES). Data sources are based on the Labour Force Survey (LFS) conducted in September over the period 2003 to 2007 and the Quarterly Labour Force Survey (QLFS) conducted in the third quarter of subsequent years. Figure 1: Real GDP at constant 2005 market prices* and employment

Note: * Refers to seasonally adjusted annual figures. Both GDP and employment are for the third quarter each year.

Over the ten year period under review, two distinct patterns are evident (Figure 1). There was steady growth in both output and jobs in the first five years followed by a downturn in 2009 as the global economic recession took hold. Both output and jobs have been on an upward trend in recent years but only in Q3: 2013 has the level of employment surpassed the 2008 peak. While 2,1 million jobs were gained over the 10 year period, the working age population also increased - by 4,9 million persons. This resulted in a decline in the percentage of South Africans aged 15-64 years with jobs (the absorption rate1) from 44,5% in Q3: 2008 to 41,9% in Q3: 2013 It is widely recognised that the pace of economic growth plays a crucial role in providing job opportunities in the labour market. In South Africa, estimates vary regarding the growth rates that need to be achieved and sustained to reduce unemployment to acceptable levels. “Those specified have ranged from 4.5% (MTSF 2004-2007) to ‘at least 6%’ (ASGISA for 2010–14), between 4% and 7% (New Growth Path), 7% (the Minister of Finance and National Treasury), and most recently, with much precision: 5.4% (the National Development Plan)2”.

2. The provincial picture

Reflecting the national picture, Table 1 shows that following a five-year period of relatively strong economic growth, in each province the value of goods and services produced also declined in 2009. The largest contractions in economic activity occurred in Northern Cape, North West and Free State where real GDPR fell by over 2,0% in 2009. 1 Also called the employment-to-population ratio, measures the percentage of the working age population aged 15-64 years who are employed.

2 http://www.econ3x3.org/article/reducing-unemployment-waiting-high-growth-waiting-godot#sthash.5rsJiF2l.dpuf

10 500

11 500

12 500

13 500

14 500

15 500

16 500

17 500

18 500

19 500

0

500 000

1 000 000

1 500 000

2 000 000

2 500 000

2003 04 05 06 07 08 09 10 11 12 2013

Thousand (Broken scale)

Rands Million GDP (LHS) Employment (RHS)



Table 1: GDPR* at Constant 2005 prices - percentage changes

2004 2005 2006 2007 2008 2009 2010 2011

Average annual 2003-2011

Per cent

Western Cape 5,7 5,9 5,9 6,2 4,3 -1,3 2,7 3,6 4,1 Eastern Cape 3,6 4,9 5,4 5,4 3,7 -1,1 2,4 3,4 3,4 Northern Cape 2,5 3,6 4,1 3,9 1,7 -3,2 2,4 2,2 2,1 Free State 4,0 4,2 4,5 4,5 3,1 -2,1 2,3 2,5 2,8 KwaZulu-Natal 4,5 5,8 5,5 5,9 4,0 -1,5 3,5 3,6 3,9 North West 3,5 5,1 4,5 4,2 2,2 -2,6 2,9 2,7 2,8 Gauteng 5,2 5,5 6,4 6,0 4,0 -1,3 3,5 4,0 4,1 Mpumalanga 4,1 4,6 4,6 4,7 2,3 -1,7 2,7 2,5 2,9 Limpopo 3,1 4,3 4,8 4,5 2,6 -1,7 2,6 2,2 2,8

GDPR at market prices 4,6 5,3 5,6 5,5 3,6 -1,5 3,1 3,5 3,7

Note: GDPR refers to gross domestic product regional

Across the provinces, the post-recession period has been characterised by generally lower growth rates than occurred before the recession. Figure 2 shows that over the 8 year period (2003 to 2011) the average annual growth in output was 3,7% for the country as a whole and somewhat higher in Western Cape (4,1%), Gauteng (4,1%) and KwaZulu-Natal (3,9%). Figure 2: Average annual rate of growth of real GDPR , 2003 to 2011

Figure 3: Contribution to GDPR at current market prices, 2011

Note: GDPR refers to gross domestic product regional

The contribution that each province makes to national output varies from as little as 2,2% in Northern Cape to as much as 34,5% in Gauteng (Figure 3). Provincial differences in employment reflect the employment intensity of various industries and differences in the economic structure of the provinces. The industrial base varies hugely across the nine provinces. In 2011, value added by the Agriculture industry accounted for 6,0% of the goods and services produced in Northern Cape, but less than 1% in Gauteng. And whereas the Mining industry accounted for 25% of the value of goods and services produced in Northern Cape, North West, Mpumalanga and Limpopo, in other provinces such as Western Cape and Eastern Cape there was little such industrial activity. Manufacturing accounted for 10–20% of output in Eastern Cape, Western Cape, KwaZulu-Natal, Gauteng and Mpumalanga, but less than 5% in provinces such as North West, Limpopo and Northern Cape. And the Finance industry featured prominently in the goods and services produced in Western Cape (27%) and Gauteng (23%) but accounted for 11–12% in provinces such as Mpumalanga, North West and Northern Cape. General government services also played an important role in the economic fortunes of the provinces, contributing 22,0% to output in Eastern Cape and 10–17% in the other provinces.

2,1

2,8

2,8

2,8

2,9

3,4

3,9

4,1

4,1

3,7

0,0 1,0 2,0 3,0 4,0 5,0

Northern Cape

Limpopo

North West

Free State

Mpumalanga

Eastern Cape

KwaZulu-Natal

Western Cape

Gauteng

GDPR at market prices

%

Western Cape, 14,2

Eastern Cape, 7,5

Northern Cape, 2,2

Free State, 5,3

KwaZulu-Natal, 15,7

North West, 6,5

Gauteng, 34,5

Mpumalanga, 7,0

Limpopo, 7,1

Rands 2 917 538m



Table 2: Employment shares by industry, 2011

Agri culture Mining

Manufact uring Utilities

Const-ruction Trade Transport Finance Services Phholds Total

Western Cape 5,9 0,2 16,1 0,5 7,1 22,1 5,8 15,1 20,9 6,3 100,0 Eastern Cape 4,9 0,1 13,5 0,4 8,9 22,6 5,4 10,4 25,3 8,6 100,0 Northern Cape 18,5 4,1 4,7 0,8 6,1 14,3 4,1 8,1 29,7 9,7 100,0 Free State 8,5 2,7 8,1 0,4 8,5 22,2 4,3 9,3 25,1 10,9 100,0 KwaZulu-Natal 4,0 0,5 16,1 0,5 9,3 23,1 6,8 11,0 20,2 8,3 100,0 North West 4,7 16,6 9,1 0,4 6,5 20,0 3,3 8,4 22,2 8,9 100,0 Gauteng 1,1 0,7 15,3 0,6 6,9 22,6 6,8 18,0 19,7 8,2 100,0 Mpumalanga 8,3 6,8 8,5 2,2 8,1 24,4 4,3 9,1 18,4 9,8 100,0 Limpopo 7,8 6,0 6,7 0,7 9,7 24,7 3,6 6,8 25,1 8,9 100,0

South Africa 4,6 2,3 13,3 0,6 7,9 22,6 5,7 12,9 21,5 8,4 100,0

Table 2 shows that in 2011, in terms of employment, Mining accounted for a relatively small share of all jobs in provinces such as Mpumalanga (6,8%) and Limpopo (6,0%) yet as discussed earlier in these provinces Mining contributed over 25% to output. Figure 4: Education level of the labour force by province, 2003

Figure 5: Education level of the labour force by province, 2013

Education plays an important role in ensuring that individuals are able to take advantage of employment opportunities that arise. The ILO notes that “An increasingly important aspect of labour market performance and national competitiveness is the skill level of the workforce. The level of educational attainment is one indicator of labour force skill levels. These are important determinants of an economy‟s capacity to compete successfully in world markets and to make efficient use of rapid technological advances; they are also among the factors determining the employability of workers”. Figure 4 and Figure 5 show that over the 10

year period 2003–2013, the education profile of the labour force improved in every province such that for

the country as a whole, the percentage of the labour force with “Matric and higher” education levels increased from 40,6% in 2003 to 48,9% in 2013. A similar trend is evident in every province. Despite this improvement, more than half of the labour force currently has education levels below the matric level. In provinces such as Eastern Cape and Limpopo three out of every five individuals in the labour force fall into this education category. To the extent that labour demand favours skilled and semi-skilled labour then the unemployment situation will continue to be cause for grave concern.

49,5

58,0

58,9

64,6

63,6

64,0

69,0

70,0

65,2

58,9

49,6

41,4

40,8

35,2

35,2

35,8

30,4

29,8

34,2

40,6

0% 20% 40% 60% 80% 100%

Gauteng

Western Cape

KwaZulu-Natal

Mpumalanga

North West

Free State

Northern Cape

Eastern Cape

Limpopo

RSA

Less than matric Matric plus Other

40,4

49,5

50,6

55,8

56,5

56,9

58,0

59,0

62,1

50,4

58,5

49,7

49,0

42,7

43,2

42,9

41,7

40,7

37,0

48,9

0% 20% 40% 60% 80% 100%

Gauteng

Western Cape

KwaZulu-Natal

Mpumalanga

North West

Free State

Northern Cape

Eastern Cape

Limpopo

RSA

Less than matric Matric plus Other



3. National labour market developments 2003 to 2013 Figure 6: Trends in key labour market indicators in South Africa, 2003-2013

Note: RHS refers to right hand scale

The steady rise in employment over the period 2003 to 2008 was generally accompanied by a reduction in unemployment. As a result, the labour absorption rate also rose from 41,8% in 2003 to 44,7% in 2007 and the unemployment rate declined from 24,8% to 21,0% over the same period. In the post-recession period since 2010, the slowdown in employment growth and rising unemployment has generally resulted in higher unemployment rates each year and labour absorption rates hovering around 41% mark. Relatively high labour force participation rates in the early period were driven by employment expansion while in the latter period, the growth in unemployment was the underlying factor in maintaining labour force participation rates at levels similar to the earlier period. Figure 7: Labour market indicators (official) Figure 8: Labour market rates

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Employed 11 959 12 265 13 034 13 601 13 609 13 810 13 133 12 972 13 318 13 646 14 029

Unemployed_Official 3 947 3 659 4 001 3 859 3 623 4 154 4 241 4 397 4 443 4 667 4 609

Absorption rate (RHS) 41,8 42,2 44,1 45,3 44,7 44,5 41,6 40,4 40,9 41,3 41,9

U.Rate_Official (RHS) 24,8 23,0 23,5 22,1 21,0 23,1 24,4 25,3 25,0 25,5 24,7

LFPR_Official (RHS) 55,6 54,8 57,6 58,2 56,7 57,9 55,0 54,2 54,6 55,5 55,7

5,0

15,0

25,0

35,0

45,0

55,0

65,0

0

2 000

4 000

6 000

8 000

10 000

12 000

14 000

16 000 % (Broken scale)

Thousand

14 029

4 609

14 826

18 638

33 464

11 959

3 947

12 679

15 906

28 585

2 070

663

2 146

2 732

4 878

1,6

1,6

1,6

1,6

1,6

0 10 000 20 000 30 000 40 000

Employed

Unemployed

Not economically active

Labour force

Working age

Thousand

2003 2013 %Annual Change 2003-2013

65,1

55,7

41,9

35,6

24,7

68,7

55,6

41,8

39,1

24,8

0,0 20,0 40,0 60,0 80,0

Labour force participation rate _Expanded

Labour force participation rate _Official

Absorption rate

Unemployment rate_Expanded

Unemployment rate_Official

%

2003 2013



The working age population increased by 4,9 million over the period 2003–2013 - at an annual rate of 1,6%. Over the same period, the annual rate of growth in employment, unemployment and the labour force also increased by 1,6% resulting in the unemployment rate (official) remaining virtually unchanged at 24,7% in 2013. Although 2,1 million jobs were gained over the ten year period, this was not enough to offset the increase in the working age population and like the unemployment rate there was little change in the absorption rate. Based on the expanded definition, the unemployment rate declined from 39,1% in 2003 to 35,6% in 2013. Figure 9: Unemployment rates (Official) for key groups

Note: The change is measured in percentage points.

Unemployment falls disproportionately on the black African population, the youth and women. Figure 9 shows that over the 10 year period 2003 to 2013:

The unemployment rate among women is substantially higher than among men. The rate among women declined by 1,7 percentage points but increased among men from 21,7% in 2003 to 23,1% in 2013.

Youth unemployment rates are more than double that of adults.

The black African group has the highest unemployment rate in the country and there was a modest decline in the rate from 29,2% to 28,1% over the 10 year period.

The largest decline occurred among the Indian/Asian group (by 5,0 percentage points) but the rate increased for the coloured (0,6 of a percentage point) and white (1,7 percentage points) population groups.

23,1

26,7

14,9

34,8

28,1

24,2

10,8

6,6

21,7

28,4

12,6

35,9

29,2

23,6

15,8

4,8

1,3

-1,7

2,3

-1,0

-1,1

0,6

-5,0

1,7

0,0 10,0 20,0 30,0 40,0

Men

Women

Adults

Youth

Black African

Coloured

Indian/Asian

White

%

2003 2013 Change



4. Provincial changes in key labour market indicators Figure 10: Change in employment, 2003–2013

Figure 11: Change in unemployment, 2003–2013

Note: Based on LFS Sep: 2003 and QLFS Q3: 2013

Figure 12: Change in the not economically active, 2003–2013

Figure 13: Change in the labour force, 2003–2013

Note: Based on LFS Sep: 2003 and QLFS Q3: 2013

Figure 10 shows that between 2003 and 2013, the average annual growth in employment and unemployment (Figure 11) differed markedly across the provinces. This in turn had implications for the size of the labour force and key labour market indicators such as the unemployment rate, the labour force participation rate and the absorption rate. In North West, Free State and Northern Cape the annual average growth in employment over the ten year period was the lowest in the country. This was accompanied by relatively rapid annual growth in unemployment at 7,4% in Mpumalanga, 4,0% in Free State and 3,8% in Northern Cape – the highest rates in the country. The net result was labour force growth at an average annual rate of 3,3% in Mpumalanga and less than one percent in Northern Cape and Free State (Figure 13). Over the same period there was very little growth in the not economically active population in these provinces (Figure 12).

-98

1

18

141

196

255

345

429

783

2 070

-1,2

0,0

0,2

0,8

2,1

2,1

3,7

1,8

2,1

1,6

-500 0 500 1 000 1 500 2 000 2 500

Free State

Northern Cape

North West

Western Cape

Mpumalanga

Eastern Cape

Limpopo

KwaZulu-Natal

Gauteng

RSA

Thousand

Employed %Annual

-73

-61

18

37

91

124

124

191

211

663

-2,6

-2,0

0,3

3,8

1,8

4,0

2,4

7,4

1,7

1,6

-500 0 500 1 000 1 500 2 000 2 500

Limpopo

North West

KwaZulu-Natal

Northern Cape

Western Cape

Free State

Eastern Cape

Mpumalanga

Gauteng

RSA

Thousand

Unemployed %Annual

11

26

71

96

168

170

435

455

714

2 146

0,1

0,9

0,7

1,3

1,6

0,8

2,3

2,1

2,2

1,6

-500 0 500 1 000 1 500 2 000 2 500

Mpumalanga

Northern Cape

North West

Free State

Western Cape

Eastern Cape

Limpopo

Gauteng

KwaZulu-Natal

RSA

Thousand

Not economically active %Annual

-43

26

38

232

272

379

387

447

994

2 732

-0,4

0,2

0,9

1,0

2,2

2,2

3,3

1,4

2,0

1,6

-500 0 500 1 000 1 500 2 000 2 500

North West

Free State

Northern Cape

Western Cape

Limpopo

Eastern Cape

Mpumalanga

KwaZulu-Natal

Gauteng

RSA

Thousand

Labour force %Annual



Figure 14: Unemployment rate by province (official)

Figure 15: Absorption rate by province


Figure 14 shows that in 2013, Free State and Eastern Cape had the highest unemployment rates in the country. The rate was lowest in Limpopo and KwaZulu-Natal. Over the period 2003–2013 the largest decline occurred in Limpopo (down by 11,1 percentage points) from 28,8% to 17,8% followed by North West (down by 4,6 percentage points). The major contributing factor to the decline in the unemployment rate in Limpopo is the rapid growth in employment (averaging 3,7% annually over the period 2003–2013). This resulted in an increase in the absorption rate from 27,9% to 32,2% - the largest increase in the country. In five of the other provinces the unemployment rate increased over the past ten years – by as much as 10,5 percentage points in Free State and 8,7 percentage points in Mpumalanga. Figure 16: Labour force participation rate by province (official)


Over the period 2003 and 2013 the stability in the labour force participation rate masks large provincial variations (Figure 16). Driven by increases in both employment and unemployment, the rate in Mpumalanga was 7,7 percentage points higher in 2013 compared with ten years earlier. The second largest increase occurred in Eastern Cape where the rate rose by 3,5 percentage points over the period. In six of the nine provinces the rate declined.

17,8

20,9

23,4

24,3

26,6

26,6

28,0

30,8

34,0

24,7

28,8

23,5

21,7

25,0

17,9

31,3

21,2

30,4

23,5

24,8

-11,1

-2,6

1,7

-0,7

8,7

-4,6

6,8

0,5

10,5

-0,1

0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0

Limpopo

KwaZulu-Natal

Western Cape

Gauteng

Mpumalanga

North West

Northern Cape

Eastern Cape

Free State

RSA

%

2003 2013 Change

31,3

32,2

35,7

38,2

38,9

41,4

42,7

52,1

52,7

41,9

29,0

27,9

35,3

38,5

47,1

45,3

41,5

54,2

52,4

41,8

2,2

4,2

0,4

-0,3

-8,2

-3,8

1,3

-2,1

0,3

0,1

0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0

Eastern Cape

Limpopo

North West

KwaZulu-Natal

Free State

Northern Cape

Mpumalanga

Western Cape

Gauteng

RSA

%

2003 2013 Change

39,1

45,2

48,3

48,6

57,5

58,2

59,0

68,0

69,6

55,7

39,3

41,7

50,3

51,4

57,4

50,5

61,6

69,3

69,8

55,6

-0,2

3,5

-2,0

-2,7

0,1

7,7

-2,6

-1,3

-0,2

0,1

0,0 20,0 40,0 60,0 80,0

Limpopo

Eastern Cape

KwaZulu-Natal

North West

Northern Cape

Mpumalanga

Free State

Western Cape

Gauteng

RSA

%

2003 2013 Change



Figure 17: Unemployment rate by sex, 2003 Figure 18: Unemployment rate by sex, 2013

In 2003, female unemployment rates were higher than male rates in every province – by as much as 11,0 percentage points in Free State (Figure 17). Ten years later, in every province except Mpumalanga the gap between male and female rates improved. In 2013, in Eastern Cape the female unemployment rate was actually lower than the male rate (by 1,7 percentage points). Figure 19: Unemployment rate among youth and adults, 2003

Figure 20: Unemployment rate among youth and adults, 2013

In both 2003 and 2013, in every province, the youth unemployment rate was more than two times that of adults (Figures 19 and 20). In 2003 youth rates were the highest in North West (47,2%) where it was three times that of adults. In 2013, Free State (46,7%) had the highest rate (2,2 times that of adults). Limpopo had the third highest youth unemployment in 2003 but by 2013 the youth rate was the lowest in the country.

15,2

20,1

20,4

16,9

18,6

21,3

26,5

28,4

27,9

21,7

20,9

23,7

26,8

26,8

29,6

29,7

30,8

32,3

36,0

28,4

17,9

21,7

23,5

21,2

23,5

25,0

28,8

30,4

31,3

24,8

5,7

3,6

6,4

9,9

11,0

8,4

4,2

3,9

8,1

6,7

0,0 10,0 20,0 30,0 40,0

Mpumalanga

Western Cape

KwaZulu-Natal

Northern Cape

Free State

Gauteng

Limpopo

Eastern Cape

North West

RSA

%

Female Male Difference Both sexes

17,9

20,5

22,2

21,5

25,5

31,6

25,1

21,2

31,7

23,1

17,6

21,4

24,9

27,6

28,3

29,9

31,6

33,4

36,6

26,7

17,8

20,9

23,4

24,3

26,6

30,8

28,0

26,6

34,0

24,7

-0,2

1,0

2,7

6,1

2,7

-1,7

6,5

12,2

4,9

3,6

0,0 10,0 20,0 30,0 40,0

Limpopo

KwaZulu-Natal

Western Cape

Gauteng

North West

Eastern Cape

Northern Cape

Mpumalanga

Free State

RSA

%

Female Male Difference Both sexes

27,2

30,4

30,7

34,1

35,0

36,6

42,6

44,8

47,2

35,9

8,4

10,8

10,5

10,5

13,9

10,1

15,7

15,7

15,8

12,6

3,3

2,8

2,9

3,2

2,5

3,6

2,7

2,9

3,0

2,8

0,0 10,0 20,0 30,0 40,0 50,0

Mpumalanga

Western Cape

Northern Cape

KwaZulu-Natal

Gauteng

Free State

Limpopo

Eastern Cape

North West

RSA

%

Adults Youth Youth:Adult ratio

26,7

29,8

32,3

35,0

36,9

37,1

39,1

41,5

46,7

34,8

9,2

11,0

14,5

15,9

14,7

16,7

15,6

19,1

21,0

14,9

2,9

2,7

2,2

2,2

2,5

2,2

2,5

2,2

2,2

2,3

0,0 10,0 20,0 30,0 40,0 50,0

Limpopo

KwaZulu-Natal

Western Cape

Gauteng

Mpumalanga

North West

Northern Cape

Eastern Cape

Free State

RSA

%

Adults Youth Youth:Adult ratio



5. Employment by industry

Figure 21: Trends in employment by industry, 2003 to 2013

Note: Based on Sept results of the LFS 2003-2007 and third quarter results of the QLFS thereafter.

Employment trends based solely on the third quarter of each year show that employment peaked at 13,8 million in 2008 – the highest level in five years. The 1,9 million jobs gained over the period 2003–2008 was due to expanding employment opportunities in every industry other than Mining and Agriculture. The economic recession which began in 2009, resulted in widespread contractions in employment across all industries except Community and social services. In 2009 and 2010 as many as 836 000 jobs were lost. In the past three years the trend in employment in most industries has been upwards, signalling that a broad-based recovery may be underway. Of the 2,1 million jobs that were created over the 10-year period, the Community and social Services industry accounted for the largest number (814 000) followed by Finance

(727 000) and Construction (389 000). Over the same period, the biggest job losses occurred in Agriculture

(down 188 thousand) and Private households (down 114 000).

Figure 22: Employment by industry Figure 23: Share of employment by industry

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Agriculture 894 773 702 833 770 776 660 640 624 661 706

Mining 396 295 311 316 323 315 304 303 324 349 389

Manufacturing 1 713 1 842 1 833 1 864 1 941 1 955 1 771 1 713 1 737 1 727 1 667

Utilities 83 84 87 102 84 100 86 99 73 105 129

Construction 692 882 999 1 103 1 093 1 123 1 097 1 076 1 086 1 046 1 081

Trade 2 794 2 874 3 424 3 523 3 410 3 205 2 903 2 947 3 012 2 962 3 007

Transport 628 671 715 697 734 787 760 773 756 834 861

Finance 1 183 1 271 1 387 1 395 1 447 1 669 1 735 1 625 1 768 1 811 1 910

Services 2 331 2 285 2 299 2 434 2 540 2 623 2 658 2 678 2 836 3 025 3 145

Private hholds 1 246 1 288 1 277 1 334 1 266 1 255 1 154 1 119 1 098 1 124 1 132

500

1 000

1 500

2 000

2 500

3 000

3 500

4 000

Thousand

129

389

706

861

1 081

1 132

1 667

1 910

3 007

3 145

83

396

894

628

692

1 246

1 713

1 183

2 794

2 331

4,5

-0,2

-2,3

3,2

4,6

-1,0

-0,3

4,9

0,7

3,0

1,6

46

-7

-188

233

389

-114

-46

727

213

814

2 070

0 1 000 2 000 3 000 4 000

Utilities

Mining

Agriculture

Transport

Construction

Phholds

Manufacturing

Finance

Trade

Services

Total

Thousand

2003 2013 Change %Annual 2003-2013

0,9

2,8

5,0

6,1

7,7

8,1

11,9

13,6

21,4

22,4

0,7

3,3

7,5

5,2

5,8

10,4

14,3

9,9

23,4

19,5

0,0 5,0 10,0 15,0 20,0 25,0

Utilities

Mining

Agriculture

Transport

Construction

Phholds

Manufacturing

Finance

Trade

Services

%

2003 2013



The steady increase in jobs in the Community and social services and Finance industries over the past 10 years resulted in the largest increases in the shares of these industries in total employment over the period. By 2013, Trade had been replaced by Community and social services as the biggest provider of jobs in the economy. Job losses in Agriculture and Private households over the same period are reflected in declining shares of these industries in total employment. Table 3: Change in employment by province and industry, 2003 - 2013

Agriculture Mining Manufacturing Utilities Construction Trade Transport Finance Services Phholds Total

Thousand

Western Cape -49 1 -43 6 0 20 18 123 92 -27 141 Eastern Cape -31 -2 41 10 45 55 14 60 101 -38 255 Northern Cape -22 -7 -5 0 13 -12 2 14 34 -16 1 Free State -40 -59 -23 0 16 -26 5 23 32 -26 -98 KwaZulu-Natal -56 22 -20 -4 98 90 71 98 176 -48 428 North West -22 30 -4 1 17 -24 -1 30 43 -51 18 Gauteng 13 -70 4 7 104 79 96 283 198 67 782 Mpumalanga -4 22 -20 13 37 -1 10 59 67 12 196 Limpopo 23 55 25 13 57 32 18 38 71 13 345

South Africa -188 -7 -46 46 389 213 233 727 814 -114 2 070

Over the last ten years, job losses in the Agriculture industry were widespread across the provinces. Only in Gauteng (up 13 000) and Limpopo (up 23 000) did jobs in the industry increase. The decline in Mining employment in Free State (down 59 000) and Gauteng (down 70 000) over the same period was largely on account of job losses in the gold industry. In every province except Eastern Cape, Limpopo and to a lesser extent Gauteng - employment in the Manufacturing industry also declined. Over the ten year period, the Construction, Finance and Services industries in every province gained jobs. Although in most provinces jobs in the Trade industry increased, in Northern Cape, Free State and North West there was a decline.

Figure 24: Employment by industry and occupation

Figure 25: Employment by industry and level of education

In 2013 as many as 25,6% of employed persons held skilled positions as against 22,9% ten years ago in 2003. While semi-skilled positions remained virtually unchanged at around 46% of total employment over the same period, unskilled positions declined from 30,9% in 2003 to 28,3% in 2013. Reflecting the national trend, in each of the industry groupings there was an increase in skilled jobs over the ten year period – particularly in the secondary industries (Figure 24). Figure 25 suggests that irrespective of industry group, the education profile of employed persons was better in 2013 than 10 years ago in 2003. And notably, the skills level required in the primary industries is reflected in the educational profile of people employed in that industry – which has the highest percentage of persons with education levels below matric.

22,9

25,6

27,5

29,2

16,0

20,0

6,8

7,1

46,2

46,1

40,0

43,3

67,9

59,0

44,4

38,1

30,9

28,3

32,6

27,5

16,1

21,0

48,8

54,8

0% 20% 40% 60% 80% 100%

2003

2013

All industries

2003

2013

Tetiary industries

2003

2013

Secondary industries

2003

2013

Primary industries

Skilled Semi-skilled Unskilled

56,4

47,3

50,6

42,8

61,8

53,2

83,2

73,0

27,7

31,0

30,2

32,4

27,8

30,8

11,6

18,5

15,2

20,9

18,6

24,0

9,8

14,9

4,5

7,7

0% 20% 40% 60% 80% 100%

2003

2013

All industries

2003

2013

Tertiary industries

2003

2013


2003

2013

Primary industries

Below matric Matric only Tertiary education Other



Figure 26: Share of skilled occupations by province Table 4: Change in employment by

occupation, 2003 - 2013

Gauteng and Western Cape had the highest percentages of employed individuals in skilled occupations in both 2003 and 2013. North West and Limpopo had the lowest percentages in that occupation category in 2013. And over the ten year period those were the only two provinces where there was a decline in the share of skilled occupations among employed individuals – by 1,2 percentage points in North West and by 0,9 of a percentage point in Limpopo. The outcome in Limpopo was the result of the large increase in employment relative to the increase in skilled employment of 54 000 jobs. Figure 27: Share of employment by sector Table 5: Change in employment by sector,

2003 - 2013

In 2013, formal sector employment accounted for a higher share of total employment (71,3%) compared with ten years earlier (65,3%). And while over the period 2003 to 2013, there was little difference in the percentage of persons employed in the informal sector, as discussed earlier, there was a decline in the share of persons employed in agriculture and private households. Provincial changes in sectoral employment over the 10 year period show that formal sector jobs increased in every province except Free State (down by 27 000). Relatively few jobs were created in the informal sector over the period (168 000 compared with 2,2 million in the formal sector). But the sector continues to provide a livelihood for many vulnerable groups with as many as 2,2 million of the 14,0 million employed persons in 2013 having informal sector jobs.

16,8

17,8

18,0

20,2

20,8

22,0

23,5

29,0

33,3

25,6

18,0

18,8

17,8

20,1

17,4

20,0

22,1

23,0

28,5

22,9

-1,2

-0,9

0,2

0,1

3,4

2,0

1,4

6,0

4,8

2,7

0,0 10,0 20,0 30,0

North West

Limpopo

Mpumalanga

Free State

Northern Cape

Eastern Cape

KwaZulu-Natal

Western Cape

Gauteng

RSA

%

2003 2013 Change

65,371,3

16,815,6

7,55,0

10,4 8,1

0%

20%

40%

60%

80%

100%

2003 2013

Private households

Agriculture

Informal sector

Formal sector

Skilled

Semi-skilled Unskilled Total

Thousand

Western Cape 143 63 -65 141 Eastern Cape 77 117 61 255 Northern Cape 10 11 -20 1 Free State -19 -53 -26 -98 KwaZulu-Natal 133 210 86 429 North West -6 20 4 18 Gauteng 427 273 82 784 Mpumalanga 37 106 53 196 Limpopo 54 189 101 344

RSA 857 936 274 2 070

Formal sector

Informal sector

Agri culture

Private hholds Total

Thousand

Western Cape 182 35 -49 -27 141 Eastern Cape 310 14 -31 -38 255 Northern Cape 28 11 -22 -16 1 Free State -27 -5 -40 -26 -98 KwaZulu-Natal 490 42 -56 -48 429 North West 104 -12 -22 -51 18 Gauteng 716 -11 13 67 783 Mpumalanga 182 6 -4 12 196 Limpopo 220 89 23 13 345

RSA 2 204 168 -188 -114 2 070



Figure 28: Share of formal sector by province Figure 29: Share of informal sector by

province

The formal sector accounts for the largest share of total employment in Gauteng and Western Cape and the smallest share in Limpopo. Over the period 2003 to 2013 the formal sector share in total employment increased in every province – the largest increase occurred in Eastern Cape (by 13,3 percentage points) and North West (by 12,5 percentage points). The informal sector share in total employment was highest in Limpopo. Over the period 2003 to 2013 the share declined in every province except Free State, Western Cape and Northern Cape. Figure 30: Trade union membership by industry Figure 31: Trade union membership by province

Figure 30 shows that there was a decline in trade union membership by employees over the past 10 years – from 34,5% in 2003 to 27,8% in 2013 (by 6,6 percentage points). Employees in the Mining and Utilities industries were the most unionised and in those industries membership increased over the period. In all other industries, trade union membership declined over the 10-year period. In this regard, the Transport and Community services industries were the hardest hit. Unionisation was highest in North West and Free State in 2013. Only in North West and Northern Cape did union membership increase over the past 10 years – by 2,0 and 1,2 percentage points respectively (Figure 31).

53,3

61,6

65,2

65,6

65,7

70,8

74,6

76,8

79,2

71,3

48,6

54,3

51,9

61,2

56,8

62,5

62,1

72,5

76,4

65,3

4,7

7,3

13,3

4,4

8,9

8,3

12,5

4,3

2,8

6,1

0,0 20,0 40,0 60,0 80,0

Limpopo

Mpumalanga

Eastern Cape

Free State

Northern Cape

KwaZulu-Natal

North West

Western Cape

Gauteng

RSA

%

2003 2013 Difference

9,6

10,3

11,7

13,0

14,2

16,8

20,6

21,3

28,7

15,6

6,1

9,1

14,7

15,0

13,2

18,1

24,2

25,6

29,9

16,8

3,6

1,2

-3,0

-2,0

1,0

-1,3

-3,5

-4,3

-1,3

-1,3

0,0 20,0 40,0 60,0 80,0

Northern Cape

Western Cape

Gauteng

North West

Free State

KwaZulu-Natal

Eastern Cape

Mpumalanga

Limpopo

RSA

%

2003 2013 Difference

0,7

5,0

9,2

16,2

19,0

27,9

32,5

52,1

61,1

78,6

27,8

4,3

8,1

13,2

19,1

22,0

33,3

37,1

57,0

47,1

76,6

34,5

-3,6

-3,1

-4,0

-2,9

-3,0

-5,4

-4,6

-4,9

14,0

2,0

-6,6

0,0 20,0 40,0 60,0 80,0

Private hholds

Agriculture

Construction

Trade

Finance

Transport

Manufacturing

Community

Utilities

Mining

Total

%

2003 2013 Change

24,2

26,2

26,5

28,1

28,3

31,5

31,8

34,5

42,3

27,8

30,9

32,8

31,6

40,2

37,9

30,4

40,9

43,5

40,3

34,5

-6,7

-6,6

-5,1

-12,0

-9,6

1,2

-9,2

-9,0

2,0

-6,6

0,0 20,0 40,0 60,0 80,0

Gauteng

KwaZulu Natal

Western Cape

Limpopo

Eastern Cape

Northern Cape

Mpumalanga

Free State

North West

RSA

%

2003 2013 Change



6. Hard facts Provincial differences in the key labour market indicators are linked to various factors such as the labour intensity of the industrial base in each province and the education and skills level of the workforce. Over the 10-year period 2003 to 2013 the following is noteworthy:

More than 2 million jobs were created. Over 300 000 occurred each year since 2011, with the largest job gains of 383 000 in Q3: 2013.

Although employment levels in Q3: 2013 are now higher than the peak reached in 2008 before the recession, the absorption rate at 41,9% in Q3: 2013 remained below the levels achieved in Q3: 2008 (44,5%). In effect, the percentage of South Africans aged 15-64 years who have jobs has fallen in the post-recession period.

Employment increased in all provinces except Free State over the period – the largest increases were in Gauteng (up 783 000), KwaZulu-Natal (up 428 000) and Limpopo (up 345 000). Very few employment gains occurred in Northern Cape (1 000) and North West (18 000).

Agriculture and Private households lost jobs over the 10-year period (down by 188 000 and 114 000 respectively). Employment levels rose in most of the other industries with the biggest job gains over the period in Services (up 814 000) and Finance (up 727 000).

Reflecting the national outcome, except for Limpopo and Gauteng, the Agriculture industry contracted in every province. And in six of the nine provinces employment in Private households also declined over the period.

Over the period, the increase in employment was offset by rising unemployment (up 663 000) and the unemployment and absorption rate remained virtually unchanged.

The unemployment rate was highest in Free State in 2013 and it also increased by the largest amount in that province over the 10-year period (by 10,5 percentage points). This was accompanied by a decline in both the absorption rate and the labour force participation rate. In five of the other provinces the unemployment rate also increased over the past ten years.

Absorption rates were highest in Gauteng and Western Cape in both 2003 and 2013. Over the same period the rate was lowest in Eastern Cape and Limpopo. The largest decline in the rate occurred in Free State (by 8,2 percentage points) and Northern Cape (by 3,8 percentage points).

In 2003 the gap between male and female unemployment rates was largest in Free State (11,0 percentage points). By 2013 it had narrowed to 4,9 percentage points – but both male and female rates were the highest in the country. In Eastern Cape and Limpopo the female unemployment rate in 2013 was lower than the male rate (by 1,7 and 0,2 percentage points respectively).

In every province the youth unemployment rate was more than double that of adults. However, over the 10-year period the rate among youth declined from 35,9% in 2003 to 34,8% in 2013.

The largest job losses in Manufacturing occurred in Western Cape, Free State and Mpumalanga. Job gains in the Finance industry (727 000) were largely on account of Gauteng, Western Cape and KwaZulu-Natal.

The Community and social services industry gained the most jobs over the ten year period driven by increases in every province. Gauteng, KwaZulu-Natal and Eastern Cape made the largest contributions to the job gains in the industry.

Of the 2,1 million jobs gained over the 10-year period 936 000 were semi-skilled and 858 000 were skilled.



The formal sector accounted for the largest share of total employment in Gauteng and Western Cape. The informal sector was largest in Limpopo and Mpumalanga. Over the period 2003 to 2013 the largest employment gains were in the formal sector.

The Mining and Utilities industries are the most unionised. They are also the only two industries in which the share of employees who belong to a trade union went up over the 10-year period. Union membership was highest in North West and Free State.

Western Cape labour market trends over the last decade

2003–2013

Statistics South Africa Western Cape-1 P0211.4

Western Cape labour market trends, 2003-2013

Western Cape The Western Cape province is in south-western South Africa. With a population of 5,8 million according to Census 2011, it is the fourth most populous province in South Africa and, with an area of 129 462 square kilometres, it is also the fourth most extensive. Approximately two-thirds of the province's population live in metropolitan areas. Finance, real estate, information communication and technology (ICT), retail and tourism are the main contributors to the provincial economy. After Gauteng and KwaZulu-Natal, the Western Cape's Manufacturing industry is the third-largest contributor to national employment levels in the industry. The Western Cape's total GDP for 2011 was R413 235 million, accounting for 14,2% of the national total – making the province the third largest contributor to national output. Figure 1: Trends in key labour market indicators in Western Cape, 2003–2013

RHS refers to read values on the right-hand side. The results for 2003-2007 are based on the September LFS while those the subsequent years are based on the Q3:QLFS.

Figure 1 shows that the number of employed persons in the Western Cape has increased from 1,7million in 2003 to a high of 1,9million in 2006, after which employment decreased to 1,8million in 2013. The number of unemployed persons increased by 91 000, from 475 000 in 2003 to 566 000 in 2013. The official unemployment rate declined from 21,7% in 2003 to a low of 17,6% in 2006. Since then, the unemployment rate increased by 5,8 percentage points to reach 23,4% in 2013. Both the labour force participation rate (LFPR) and absorption rate have decreased over the ten-year period; the absorption rate declined from 54,2% in 2003 to 52,1% in 2013 while the LFPR declined from 69,3% in 2003 to 68,0% in 2013.

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Employed 1 708 1 716 1 803 1 915 1 881 1 775 1 790 1 754 1 806 1 806 1 849

Unemployed 475 455 478 408 453 435 512 527 550 615 566

Unemployment rate (RHS) 21,7 21,0 21,0 17,6 19,4 19,7 22,2 23,1 23,3 25,4 23,4


Labour force participation rate (RHS) 69,3 67,3 69,2 69,0 68,3 67,4 69,0 67,3 68,4 69,2 68,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

0

500

1 000

1 500

2 000

Broken scale

%

Thousand



Figure 2: Labour market rates Figure 3: Labour market indicators (official)

Figure 2 shows that the official unemployment rate increased from 21,7% in 2003 to 23,4% in 2013 (an increase of 1,7 percentage points), which is lower than the national average rate of 24,7% in 2013.The expanded unemployment rate decreased by 1,6 of a percentage point to reach 25,7%.The absorption rate decreased by 2,1 percentage points between 2003 and 2013.The official LFPR decreased by 1,3 percentage points over the ten-year period, while expanded LFPR decreased by 4,4 percentage points. Figure 3 shows that all labour market indicators in the Western Cape have increased between 2003 and 2013. The working age population increased by 400 000 persons while the labour force increased by 232 000, from 2,2 million in 2003 to 2,4 million in 2013. The number of employed and unemployed persons increased over the period; employment increased from 1,7 million in 2003 to 1,8million in 2013 while unemployment also increased from 475 000 in 2003 to 566 000 in 2013. Figure 4: Unemployment rates (official) for key groups

Among both men and women, the unemployment rate increased over the ten-year period. The unemployment rate increased by 1,2 percentage points for women and 2,1 percentage points for men. The unemployment rate for youth increased by 1,9 percentage points while that of adults increased by 3,7 percentage points. An unemployed young person was three times more likely to be unemployed compared to an unemployed adult in 2003; by 2013 this gap had declined to twice as likely. Within the population

70,1

68,0

52,1

25,7

23,4

74,5

69,3

54,2

27,3

21,7

0,0 20,0 40,0 60,0 80,0

Labour force participation rate_Expanded

Labour force participation rate_Off icial

Absorption rate


Unemployment rate_Off icial

%

2003 2013

1 849

566

1 137

2 415

3 552

1 708

475

969

2 183

3 152

141

91

168

232

400

0 1 000 2 000 3 000 4 000

Employed

Unemployed


Labour force

Working age

Thousand

2003 2013 Change 2003-2013

33,2

23,5

7,6

4,5

32,3

14,5

22,2

24,9

34,6

21,3

6,6

6,5

30,4

10,8

20,1

23,7

0,0 10,0 20,0 30,0 40,0

Black African

Coloured

Indian/Asian

White

Youth

Adults

Men

Women

%

2003 2013



groups, an increase in the unemployment rate was observed for coloured people and Indians/Asians while there was a decrease in the unemployment rate for other population groups over the period (Figure 4). Figure 5: Trends in employment by industry, 2003-2013

Due to small sample size, Mining and Utilities industries have been removed; the sample is too small for reliable estimates

Figure 5 shows that over the period under review, the Trade industry had consistently employed the higher number of persons (404 000 in 2013) while Mining and Utilities accounted for the least number of jobs. The second largest industry employer, Community and social services, has seen employment increase from 296 000 to 388 000 in 2013. Apart from Trade and Community and social services, Manufacturing and Finance and other business services also account for a high number of employed persons in the province. Figure 6: Share of employment by industry Figure 7: Employment by industry

Due to small sample size,Mining and Utilities industries have been removed; the sample is too small for reliable estimates.

Trade was the industry with the largest share in employment in the province, with the contribution declining marginally by 0,7of a percentage point to 21,8% in 2013. This is despite an increase in employment of 141 000 over the period in the province (Figure 6). Figure 6 also indicates that in terms of the employment share, Finance and other business services increased by 5,8 percentage points and Community and social

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Agriculture 187 116 108 133 143 115 123 136 113 123 139

Manufacturing 289 311 293 316 290 314 282 261 276 287 246

Construction 134 147 165 149 181 176 159 141 129 135 134

Trade 384 367 470 494 448 407 396 369 397 383 404

Transport 100 83 91 85 86 88 88 107 105 92 118

Finance 182 232 218 247 251 244 259 252 288 273 305

Services 296 307 304 315 309 309 349 364 364 377 388

Private hh 127 143 144 165 154 109 128 110 119 119 99

50

150

250

350

450

550Thousand

(Broken scale)

5,4

6,4

7,3

7,5

13,3

16,5

21,0

21,8

7,4

5,8

7,9

11,0

16,9

10,7

17,3

22,5

0,0 5,0 10,0 15,0 20,0 25,0

Private households

Transport

Construction

Agriculture

Manufacturing

Finance

Services

Trade

%

2003 2013

99

118

134

139

246

305

388

404

127

100

134

187

289

182

296

384

-27

18

0

-49

-43

123

92

20

141

-2,4

1,7

0,0

-3,0

-1,6

5,3

2,7

0,5

0,8

0 100 200 300 400 500

Private households

Transport

Construction

Agriculture

Manufacturing

Finance

Services

Trade

Total

Thousand

2003 2013 Average annual rate of change Change in employment



services increased by 3,7 percentage points between 2003 and 2013. Manufacturing employment declined by 3,6 percentage points. Figure 7 shows that only three industries shed jobs between 2003 and 2013 while the other seven industries gained jobs. The biggest increase in employment was observed in the Finance and other business services in Western Cape. Although the province gained 141 000 jobs, the average annual rate of change was low at 0,8%; the average annual rate of change was 5,3 % in the Finance and other business services industry and it gained 123 000 jobs.



In Western Cape, Figure 8 shows that primary industries are dominated by low-skilled workers, a finding in contrast with the national picture. In secondary industries, the semi-skilled comprise more than half of those employed and high-skilled workers accounted for one in five employed in 2013. For tertiary industries, one in three was high-skilled while one in five was low-skilled. Figure 9 shows that for all industries, the share of employed persons with less than matric declined between 2003 and 2013, while the share of those with matric increased from 29,2% to 33,8% over the period. Figure 8 indicates that employed persons in the primary industries were low-skilled and Figure 9 confirms this; more than 80% have less than matric as their highest level of education. Of those in tertiary industries, more than 35% have matric as their highest level of education in both 2003 and 2013, confirming the findings on higher skills levels in these industries.

Figure 10: Share of employment by sector

29,0

23,0

33,6

28,5

21,6

16,3

6,7

7,0

45,8

45,9

45,3

45,0

58,4

62,5

16,2

13,5

25,2

31,1

21,1

26,5

20,1

21,3

77,0

79,5

0,0 20,0 40,0 60,0 80,0 100,0

2013

2003

All industries

2013

2003

Tertiary industries

2013

2003


2013

2003

Primary industries

%

High skilled Semi skilled Low skilled

44,8

54,0

38,5

44,2

51,7

65,4

85,1

84,6

33,8

29,2

36,6

35,1

33,1

23,4

9,4

8,0

20,7

16,1

24,6

20,1

13,4

10,4

4,6

6,1

0,0 20,0 40,0 60,0 80,0 100,0

2013

2003

All industries

2013

2003

Tertiary industries

2013

2003


2013

2003

Primary industries

%

Below matric Matric only Tertiary

72,5 76,8

9,110,3

11,07,5

7,4 5,4

0,0

20,0

40,0

60,0

80,0

100,0

2003 2013

%

Private households

Agriculture

Informal sector

Formal sector



Employment by sector in Figure 10 highlights that more than 76% of people in Western Cape were employed in the formal sector in 2013, up from 72,5% in 2003. Formal sector employment increased by 4,3 percentage points between 2003 and 2013 while it decreased by 3,5 percentage points in Agriculture. Private households share in employment declined by 2,0 percentage points in favour of job gains in the informal sector, which increased by 1,2 percentage points between 2003 and 2013. Figure 11: Trade union membership by industry

Due to small sample size, Mining and Utilities industries have been removed; the sample is too small for reliable estimates.

Overall, affiliation with trade unions has decreased between 2003 and 2013 in Western Cape. The biggest decline was observed in the Transport industry (16,5 percentage points) followed by the Manufacturing and Construction (at 9,4 and 9,3 percentage points respectively) and Agriculture (8,9 percentage points) industries. Union membership for those working in the private households is the lowest among all industries at 1,2% in 2013 (Figure11). Hard facts

The province created 141 000 jobs over the last ten years, however, current employment levels are still 66 000 below the peak of 1,9 million employed in 2006.

The unemployment rate for youth increased by 1,9 percentage points while that of adults increased by 3,7 percentage points between 2003 and 2013.

Employed persons in the primary industries were low-skilled and more than 80% had less than matric as their highest level of education. The share of low-skilled employed persons in the primary industries decreased form 79,5% in 2003 to 77,0% in 2013.

The Trade industry contributed the largest share in employment (22,5% in 2003 and 21,8% in 2013) in the province with the formal sector creating more than 78% over the 10 year period in this industry.

More than 70% of those employed between 2003 and 2013 in the Western Cape were employed in the formal sector, with an increase of 4,3 percentage points formal employment reached 76,8% in 2013.

1,2

3,6

9,3

19,7

22,0

25,1

36,2

49,0

26,5

0,0

12,5

18,6

19,9

15,6

41,6

45,6

53,9

31,6

0,0 10,0 20,0 30,0 40,0 50,0 60,0

Private households

Agriculture

Construction

Trade

Finance

Transport

Manufacturing

Services

Total

%

2003 2013

Eastern Cape labour market trends over the last decade

2003-2013

Statistics South Africa Eastern Cape-1 P0211.4

Eastern Cape labour market trends, 2003-2013

Eastern Cape

The Eastern Cape is the second largest province in South Africa after the Northern Cape in terms of land area(168 966 square kilometres), and it has a population of about 6,5 million people according to Census 2011. The capital of the province is Bhisho, but its two largest cities are Port Elizabeth and East London. The province consists of six district councils and two metropolitan municipalities and is predominantly rural. While the province is often regarded as one of the poorest in the country, its contribution to the national GDP of 7,5% is the fourth highest among the provinces. The top three industries in terms of employment are Community and social services, Trade, and Manufacturing.

Figure 1: Trends in key labour market indicators in Eastern Cape, 2003–2013

RHS refers to read values on the right-hand side. The results for 2003-2007 are based on the September LFS while those the subsequent years are based on the Q3:QLFS.

Figure 1 shows that in Eastern Cape, between 2003 and 2013, employment reached a peak of 1 335 000in 2006, declining to 1 278 000 in 2009; since then, 55 000 jobs have been created. Over the last ten years employment grew by 255 000 jobs, while the absorption and labour force participation rate also increased. The absorption rate increased by 2,3 percentage points to 31,3% while the labour force participation rate increased by 3,5 percentage points to 45,2%. Both these rates are somewhat lower than the national average and are the second lowest among all nine provinces. The official unemployment rate was the lowest in 2007 (24,6%), and increased by less than one percentage point over the ten-year period. The current rate of 30,8% is the highest since 2003.


2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Employed 1 078 1 178 1 272 1 335 1 329 1 329 1 278 1 306 1 298 1 330 1 333

Unemployed_Official 470 462 510 553 435 505 471 487 483 539 594



LFPR_Off (RHS) 41,7 43,6 46,7 48,9 45,1 45,8 43,0 43,4 42,6 44,2 45,2

5,0

10,0

15,0

20,0

25,0

30,0

35,0

40,0

45,0

50,0

55,0

0

200

400

600

800

1 000

1 200

1 400


Thousand

56,1

45,2

31,3

44,3

30,8

58,0

41,7

29,0

49,9

30,4

0,0 20,0 40,0 60,0 80,0

Labour Force participation rate_Expanded

Labour Force participation rate_official

Absoprtion rate

Unemployment rate_expanded

Unemployment rate_official

%

2003 2013

1333

594

2334

1926

4260

1 078

470

2 164

1 547

3 712

255

124

170

379

549

0 1000 2000 3000 4000 5000

Employed

Unemployed


Labour force

Working age

Thousand

2003 2013 Change 2003-2013



Figures 2 and 3 indicate the labour market rates and measures in Eastern Cape between 2003 and 2013. The official unemployment rate increased by 0,4 of a percentage point as the number of the unemployed persons increased by 124 000 over the period. This increase of 124 000 amounts to 18,7% of the net increase in national unemployment over the ten-year period. Based on the expanded definition, the unemployment rate declined by 5,6 percentage points (Figure 2) Over the 10 year period, Figure 3 shows that the working age population increased from 3,7 million in 2003 to 4,3 million in 2013 an increase of 549 000 over the period. Over the same period, the labour force also increased (by 379 000) as a result of the increase in both unemployed (up 124 000) and employed (up 255 000) persons.

Figure 4: Unemployment rates (official) for key groups

Figure 4 shows that the unemployment rate among men increased from 28,4% in 2003 to 31,6% in 2013 while, among women, the rate declined by 2,4 percentage points. In 2013, the unemployment rate among men was higher than the rate for women by 1,7 percentage points; this gender gap decreased from 3,9 percentage points in 2003.

The unemployment rate among black Africans increased by 1,4 percentage points while, among other population groups, the rate declined by 2,0 percentage points over the ten-year period.

The youth unemployment rate was higher as compared to the rate for adults. In both years, the unemployment rates for youth were above 40%. The province had the second highest youth unemployment rate at 41,5% in 2013.In addition, this rate was above the national average of 34,8%. A young person in the Eastern Cape is 2,2 times more likely to be unemployed relative to an adult.

34,3

19,2

41,5

19,1

31,6

29,9

32,9

21,2

44,8

15,7

28,4

32,3

1,4

-2,0

-3,4

3,4

3,2

-2,4

0,0 10,0 20,0 30,0 40,0 50,0

Black African

Other population groups

Youth

Adults

Men

Women

%

2003 2013 Change



Figure 5: Trends in employment by industry, 2003-2013


Figure 5 shows an upward trend in employment in the Community and social services industry since 2003, with the exception of 2006 when employment declined by 2 000 jobs; and in 2013 where it declined by 18 000 jobs. The largest gain in employment was observed in the Agriculture industry, which grew by 13 000 jobs followed by Construction with an increase of 10 000 jobs between 2012 and 2013. The largest decline in employment was observed in the Trade industry which lost 21 000 jobs in 2013 compared to 2012. The smallest contributors to employment in the province were Transport and Agriculture. Figure 6: Share of employment by industry Figure 7: Employment by industry


Figure 6 shows that in Eastern Cape, the share of the Trade industry in employment remained stable over the period. The Community and social services (24,7%) and Trade (21,9%) industries contributed the

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Agriculture 103 102 88 147 90 75 74 76 67 60 73

Manufacturing 125 169 159 166 167 195 163 159 171 163 167

Construction 108 111 99 152 155 100 107 120 107 143 153

Trade 236 266 354 323 339 314 290 328 296 313 291

Transport 52 55 65 58 68 75 76 67 75 69 66

Finance 66 72 83 90 108 106 131 102 138 120 125

Services 229 265 270 268 284 321 321 330 330 348 330

Private hh 154 134 146 121 112 138 109 118 106 109 116

50

100

150

200

250

300

350

400

Thousand

4,9

5,5

9,4

8,7

11,5

12,5

21,9

24,7

4,8

9,6

6,1

14,3

10,0

11,6

21,9

21,3

0,0 5,0 10,0 15,0 20,0 25,0 30,0

Transport

Agriculture

Finance

Private household

Construction

Manufacturing

Trade

Services

%

2003 2013

66

73

116

125

153

167

291

330

52

103

154

66

108

125

236

229

14

-31

-38

60

45

41

55

101

2,4

-3,5

-2,8

6,7

3,6

2,9

2,1

3,7

0 100 200 300 400

Transport

Agriculture

Private household

Finance

Construction

Manufacturing

Trade

Services

Thousand

2003 2013 % Annual 2003-2013 Change



largest share to employment, while Transport (4,9%) and Agriculture (5,5%) contributed the smallest share. The largest decline in the industry contribution to total employment was observed in Private households, which declined by 5,6 percentage points between 2003 and 2013.The largest increase occurred in the Community and social services industry (3,4 percentage points). Over the ten-year period, the largest gain was observed in the Community and social services industry (101 000) followed by Finance and other business services; and Trade with increases of 60 000 and 55 000 jobs respectively (Figure 7).The largest decline in employment was observed in Private households (38 000) and Agriculture (31 000). Finance and other business services grew by 60 000 jobs with the highest annual rate of change (6,7%). Figure 8: Employment by industry and occupation


Over the ten-year period there was a modest improvement in the skills profile of the province. The share of persons in higher skilled occupations increased from 20,0% to 22,0%. But this masks the deterioration in the share of low-skilled occupations in the primary industries, although the industries in this group; Agriculture and Mining account for small shares of total employment in the province. More than 55,0% of all employed persons had less than a matric level of education in both 2003 and 2013. In all the industry groupings the share of those who are better educated increased over the period. The share of those with a tertiary qualification in secondary industries increased from 5,6% to 10,4%

22,0

20,0

25,6

25,0

15,8

10,2

3,7

6,6

42,3

41,4

42,0

34,9

47,5

67,4

21,6

29,1

35,7

38,6

32,3

40,0

36,7

22,4

74,7

64,3

0,0 20,0 40,0 60,0 80,0 100,0

2013

2003

All industries

2013

2003

Tertiary industries

2013

2003


2013

2003

Primary industries

%

High skilled Semi skilled Low skilled

55,9

67,0

51,5

61,1

60,8

74,5

90,2

91,8

28,4

20,3

30,1

22,6

28,5

19,6

6,6

5,3

15,3

12,4

18,0

15,9

10,4

5,6

2,2

2,8

0,0 20,0 40,0 60,0 80,0 100,0

2013

2003

All industries

2013

2003

Tertiary industries

2013

2003


2013

2003

Primary industries

%

Less than matric Secondary Comple Tertiary



Figure 10: Share of employment by sector Figure11: Trade union membership by industry

Due to small sample size,Mining, Private household and Utilities industries have been removed; the sample is too small for reliable estimates

Figure 10 shows the share of employment by sector, while figure 11 shows the trade union membership of employees by industry. The trade union membership in all industries except Agriculture declined over the ten-year period (2003 to 2013). The largest decline in trade union membership was observed in Manufacturing (11,6 percentage points), followed by Finance and other business services (7,3 percentage points), and Trade (5,8 percentage points). In terms of employment by type of sector, the results show that employment declined in all sectors except in the formal sector. This indicates that over the ten-year period other sectors lost jobs in 2013 in favour of the formal sector. The share of employment in the formal sector increased from 51,9% in 2003 to 65,2% in 2013. On the other hand, employment in Private households declined by 5,6 percentage points while Agriculture and the informal sector declined by 4,1 and 3,6 percentage points respectively.

Hard facts

Employment expanded by 255 000 jobs in the Eastern Cape over the last ten years.

The official unemployment rate (30,8%) in 2013 for the Eastern Cape is above the national average (24,7%).

In 2013, the unemployment rate amongst women (29,9%) was below both the provincial average (30,8%) and the rate for men (31,6%).

The unemployment rate amongst women declined over the ten-year period while the rate for men increased.

The Community and social services industry contributed the largest share (24,7%) of employment in the province, creating 101 000 jobs over the last tenyears.

Almost three quarters of persons in primary industries were low-skilled and the share increased by 10,4 percentage points between 2003 and 2013.

Employment among semi-skilled occupations in secondary industries saw the largest decline of 19,9 percentage points over the period.

The labour force increased by 379 000 over the ten-year period.

51,9

65,2

24,2

20,69,6

5,514,3

8,7

0,0

20,0

40,0

60,0

80,0

100,0

2003 2013%

Private hholds

Agriculture

Informal sector

Formal sector

7,5

9,2

14,3

17,7

31,7

36,6

59,1

28,3

10,1

7,1

20,1

25,0

31,9

48,2

63,5

37,9

-2,6

2,0

-5,8

-7,3

-0,2

-11,6

-4,4

-9,6

0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0

Construction

Agriculture

Trade

Finance

Transport

Manufacturing

Community

Total

%

2003 2013 Change

Northern Cape labour market trends over the last decade

2003 - 2013

Statistics South Africa Northern Cape-1 P0211.4

Northern Cape labour market trends, 2003-2013

Northern Cape

The Northern Cape covers 30% (362 599 km2) of the country’s land area, while it is home to 2,2% (1,1 million) of the South African population (Census 2011). The province contributed 2,2% to the country’s GDP and 2,1% to total employment in 2011;, down from a contribution of 2,5% in 2003. The highest contribution to the Northern Cape’s GDP was Mining in both 2003 and 2011 (24,8% and 26,7%). However the industry’s contribution to total employment in the province was the third lowest and has declined over the period 2003 to 2011 (7,8% in 2003 and 3,6% in 2011).

Figure 1: Trends in key labour market indicators in Northern Cape, 2003–2013

RHS refers to read values on the right-hand side. The results for 2003-2007 are based on the September LFSs while those for subsequent years are based on the Q3: QLFS.

In 2013, 306 000 persons were employed in the Northern Cape, this level of employment is slightly higher compared to the level observed in 2003 (305 000). About a fifth of the population in Northern Cape were unemployed between 2003 and 2008; after the global recession the rate increased, with the lowest unemployment rate observed in 2010 at 25,8% and the highest in 2012 at 30,0%. In 2009, the level of employment reached a low where 51,8% of the working age population participated in the labour market, and 36,4% were employed. Figure 2: Labour market rates Figure 3: Labour market indicators (official)



The working age population and the labour force increased between 2003 and 2013; unemployment and the not economically active population increased (by 37 000 and 26 000 respectively), while employment remained virtually unchanged (Figure 3).The increase in unemployment resulted in an increase of 6,8 percentage points in the official unemployment rate, while the increase in the number of persons not economically active yielded a 3,0 percentage increase in the expanded unemployment rate (Figure 2 and Figure 3). The official labour force participation rate (LFPR) remained virtually unchanged over the period, while absorption rate decreased by 3,9 percentage points


Figure 4 shows the following:

Lower unemployment rates were recorded in 2003 within each group compared to 2013.

The increase in unemployment rate for men was almost twice the increase in the unemployment

rate for women, however the gap between the unemployment rates for men and women is still high in 2013 (6,5 percentage points).

Youth continue to be disadvantaged in the labour market compared to adults, the gap in the unemployment rate of the two groups widened from 20,2 percentage points in 2003 to 23,5 percentage points in 2013.

Though the unemployment rates for both coloured people and black Africans increased over the periods, the increase in unemployment rate among blackAfrican was 3,5 times the increase in unemployment rate among coloured people.

33,7

25,5

15,6

39,1

25,1

31,6

25,9

23,3

10,5

30,7

16,9

26,8

0,0 10,0 20,0 30,0 40,0

Black African

Coloured

Adults

Youth

Men

Women

%

2003 2013



Figure 5: Trends in employment by industry, 2003-2013

Due to small sample size, Utilities industry has been removed; the sample is too small for reliable estimates.

In 2003 high levels of employment were observed in four of the ten industries, Agriculture (68 000), Community and social services (62 000), Trade (57 000) and Private households (46 000).Community and social services was the only industry which created jobs after the global recession both. By 2013 Private households had lost 16000 jobs leaving only three industries with employment levels higher than 40 000.

Figure 6: Share of employment by industry Figure 7: Employment by industry


Community and social services, Trade and Agriculture were the largest employers in 2003 and 2013 (Figure 6).Between 2003 and 2013 the share of employment increased in community and social services, while it decreased in Agriculture and Trade industries.The share of employment was the lowest in Utilities, Transport and Manufacturing industries Employment declined in five of the 10 industries, with the highest decrease observed in Agriculture (22 000) and Private household (16 000); at an annual rate of 3,9% and 4,1% each .(Figure 7)





Figure 9 shows that on average the proportion of persons with less than matric education level had decreased by 12,3 percentage points to 55,6% in 2013, this decrease was mainly due to decreases observed among those in secondary industries (5,8 percentage points). Figure 8 shows that the proportions of low skilled employees decreased among those in the secondary and tertiary industries, resulting increases in the proportions of semiskilled workers. The proportion persons in high skilled jobs increased by 3,4 percentage points over a ten year period and those with tertiary education increased by 5,8 percentage points.


About 80% of the employed population was in the formal sector and private household. Over a ten year period from 2003, the share of employment was observed in the formal sector and Agriculture; where the formal sector share increased by 8,9 percentage points to 65,7% and the share in Agriculture increased by 3,5 percentage points to 9,6%. Private households and informal sector recorded a decrease in the share of employment between 2003 and 2013 (7,3 and 5,2 percentage points respectively).



Figure 11: Trade union membership by industry


In 2013, 31,5% of employees belonged to a trade union in Northern Cape, compared with 30,4% members in 2003. This is an increase of 1,2 percentage points. Highest proportions of employees who were affiliated in a union membership in 2013 were among those in Mining, community and social services and transport (78,5% and 58,9% respectively). This is in line with the national picture where the two industries had the highest proportion of employees who were trade union members.

Hard Facts

Northern Cape has the largest land area (362 599 km2) with the smallest population (1,1 million)

The participation rate and absorption rate of the province is in line with the national rates, however the unemployment rate of the province has been higher than the national rate since 2009.

Close to 90% of the working age population in the province are blackAfrican and coloured people.

Employment is dominated by Community and social services, Agriculture and Trade industries.

High skilled occupations remained the lowest, even after ten years.

Union membership is at its highest among employees in the Mining and community and social services industries.

0,0

0,9

8,5

14,2

19,5

23,8

46,9

58,9

78,5

31,5

4,2

0,0

15,5

21,6

17,2

34,2

39,1

59,9

56,2

30,4

0,0 20,0 40,0 60,0 80,0

Agiculture

Private households

Construction

Finance

Trade

Manufacturing

Transport

Community and social services

Mining

Total

%

2003 2013

Free State labour market trends over the last decade

2003 - 2013

Statistics South Africa Free State-1 P0211.4

Free State labour market trends, 2003-2013

Free State

Free State, with its capital known as Bloemfontein, is also South Africa's judicial capital. Its historical origins lie in the Orange Free State Boer Republic and later Orange Free State Province. It is the only province of the former provinces of South Africa not to undergo border changes, excluding the incorporation of Bantustans.

The Free State lies in the heart of South Africa, with the Kingdom of Lesotho nestling in the hollow of its bean-like shape. It borders more districts of Lesotho and more provinces of South Africa than any other province. Situated between the Vaal River in the north and the Orange River in the south, the region is one of flat, rolling grassland and crop fields, rising to lovely sandstone mountains in the northeast.

The province is the granary of South Africa, with its rich soil and pleasant climate allowing for a thriving agricultural industry which is central to its economy. With more than 30 000 farms which produce over 70% of the country's grain, it is known locally as South Africa's breadbasket and contributed 5,3% to the country’s GDP in 2011. The province covers a total area of 129 825 square kilometers. It's the country's third-largest province – only slightly larger than the Western Cape – taking up 10,6% of South Africa's land area.

It is estimated to have a population of 2,7 million people according to Census 2011. The top 2 industries in terms of number employed in Community and social services as well as in Trade. Employment decreased by 98 000 over the ten-year period (2003–2013), while Mining lost 59 000 jobs over the same period.

Figure 1: Trends in key labour market indicators in Free State, 2003–2013

RHS refers to read values on the right-hand side. The results for 2003-2007 are based on the September LFSs, while those for subsequent years are based on Q3:QLFS

Figure 1 reveals that the highest number of people were employed in 2007 (846 000) and the lowest (736 000) in 2012. At 34,0%,the official unemployment rate was at its highest in 2013 and at its lowest in 2007 at 21,4%. The highest expanded unemployment rate was observed in 2013 (41,2%) and the lowest in 2008 (30,8%).The highest increase in the official unemployment rate between two consecutive years was observed between 2011 and 2012 (6,5 percentage points) and the largest decline between 2005 and 2006 (4,2 percentage points).

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Employed 838 792 826 816 846 825 757 768 826 736 740





5,0

15,0

25,0

35,0

45,0

55,0

65,0

0

100

200

300

400

500

600

700

800

900% (Broken scale)

Thousand

http://en.wikipedia.org/wiki/Breadbasket



Figure2: Labour market rates Figure 3: Labour market indicators (official)

The unemployment rate increased by 10,5 percentage points, while the expanded unemployment rate increased by 5,0 percentage points between 2003 and 2013. The absorption rate decreased by 8,2 percentage points. The official participation rate decreased by 2,6 percentage points while the expanded labour force participation rate decreased by 7,7 percentage points. The number of persons of working age increased by 112 000 between 2003 and 2013, while the number of employed persons decreased by 98 000 (Figure 3). Figure 4: Unemployment rates (official) for key groups

Figure 4 shows that unemployment rates for both women and men have been increasing since 2003. The unemployment rate increased by 7,6 and 10,8 percentage points between 2003 and 2013 for women and men respectively. Figure 4 also shows that the unemployment rate has been consistently higher for women compared to men. The youth unemployment rate was higher than that of adults by 26,5 and 25,7 percentage points in 2003 and 2013 respectively. In 2013, the highest unemployment rate among population groups was observed among black Africans (37,3%).Coloureds recorded the lowest decrease in the unemployment rate (1,3 percentage points) between 2003 and 2013.

66,2

59,0

38,9

41,2

34,0

73,9

61,6

47,1

36,2

23,5

0,0 20,0 40,0 60,0 80,0


Labour force participation rate_Official

Absorption rate



%

2003 2013

740

381

780

1 121

1 901

838

257

684

1 095

1 779

98

-124

-96

-26

-122

0 1 000 2 000

Employed

Unemployed


Labour force

Working age

Thousand

2003 2013 Change 2003-2013

34,0

31,7

36,6

21,0

46,7

37,3

26,7

7,2

0,1

23,5

18,6

29,6

10,1

36,6

27,5

28,0

3,5

4,3

0,0 10,0 20,0 30,0 40,0

Free state

Men

Women

Adults

Youth

Black African

Coloured

White

Indian

%

2003 2013



Figure 5: Trends in employment by industry, 2003–2013

Between 2012 and 2013, employment in the province grew by 4 000. This was driven by employment gains in industries such as Community and social services (25 000), followed by Transport (3 000), and Construction (2 000). Results in Figure 5 show that since 2003 employment in Community and social services and Trade has been consistently higher than in other industries, and lowest in Utilities. Although Trade is the second largest contributor to employment in the province, the industry has been consistently losing jobs since 2003; employment in Trade declined by 26 000 over the ten-year period. Agriculture, which produces over 70% of the country’s grain, shed 39 000 jobs between 2003 and 2013. Community and social services gained 31 000 jobs between 2003 and 2013.


Changes in employment as well as the average rate of change in employment are depicted in Figure 7. The highest gains in employment were observed in Community and social services (32 000), while Mining, Agriculture, and Trade lost 59 000, 40 000 and 26 000 jobs respectively. The highest decrease in the

0,7

4,8

7,1

8,9

7,9

3,1

8,9

11,4

19,6

27,7

0,6

3,6

4,4

5,2

9,7

9,7

12,6

13,1

20,4

20,7

0,0 5,0 10,0 15,0 20,0 25,0

Utilities

Transport

Construction

Finance

Manufaturing

Mining

Agriculture

Private hholds

Trade

Services

%

2003 2013

5

23

35

53

58

66

66

84

145

205

5

81

30

37

81

105

43

110

171

174

-3,3

-4,6

-1,7

0,0

-12,0

-1,2

1,7

1,7

3,7

4,3

-0,3

0

-59

5

16

-23

-40

23

-26

-26

32

-98

-100 -50 0 50 100 150 200 250 300

Utilities

Mining

Transport

Construction

Manufacturing

Agriculture

Finance

Phholds

Trade

Services

Total

Thousand

2003 2013 Change %Annual 2003-2013



average annual rate of change was observed in Manufacturing (12,0%), followed by Mining which declined by 4,6%. The highest average annual growth was observed in Services at 4,3%, followed by Trade at 3,7%, while the largest decline in average annual growth was observed in Manufacturing at 12,0%. The results from Figure 6 shows that Community and social services, Trade, and Private households contributed the largest share to employment in the province between 2003 and 2013,while Utilities reflected the smallest contribution to employment over the period. The results further show a significant decrease in the share of employment in the Mining sector (6,6 percentage points), while the share of employment in Community and social services increased by 7,0 percentage points for the period under review. Figure 8: Employment by industry and occupation


Over the 10 year period the skills profile of the province remained relatively unchanged. The share of persons in skilled occupations declined from 20,2% to 20,1%, while the share of persons in semi-skilled occupations increased from 47,6% to 48,3% (Figure 8). In all industry groups, except secondary industries the share of those who were better educated declined. The share of those with a tertiary qualification in secondary industries increased from 7,1% to 17,3%, while those with less than a matric qualification declined from 68,6% to 55,2%. The largest decline in the share of those with a tertiary qualification, occurred in primary industries, from13,2% to 5,7% between 2003 and 2013. Figure 10: Share of employment by sector

20,1

20,2

25,5

23,4

13,9

11,2

8,9

12,9

48,3

47,6

38,3

44,7

70,9

65,5

61,7

41,4

31,6

32,2

36,2

31,9

15,3

23,2

29,3

45,7

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

2003

2013

All industries

2003

2013

Tetiary industries

2003

2013


2003

2013

Primary industriesSkilled Semi-skilled Unskilled

51,8

63,0

45,2

46,9

68,6

55,2

70,4

82,2

27,4

23,8

29,8

31,2

24,2

27,2

16,4

11,9

20,2

13,1

24,1

21,8

7,1

17,3

13,2

5,7

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

2003

2013

All industries

2003

2013

Tertiary industries

2003

2013


2003

2013

Primary industries




Employment in Free State is mostly concentrated in the formal sector which has contributed around 63% over the past ten years. Furthermore, the formal sector increased its share of employment by 4,4 percentage points (from 61,2% in 2003 to 65,6% in 2013) over the ten-year period. The results further show that private households and the agricultural sectors recorded decreases of 1,7 and 3,9 percentage points respectively over the same period. Figure 11: Trade union membership by industry

In 2013, 43,5% of employees belonged to a trade union in the Free State, compared to 34,5% members in 2003. This is an increase of 9,0 percentage points. Industries which had the highest proportion of employees belonging to a trade union in the province were Mining (86,1%), Community and social services (66,4%), and Utilities (46,1%) in 2013. This is in line with the national picture where the three industries had the highest proportion of employees with trade union membership. The number of employees who were trade union members declined in all industries except in Community and social services, and Manufacturing.

Hard Facts

Between 2003 and 2013, the number of persons of working age in the Free State increased by

112 000, while those that were employed decreased by 98 000.

The highest number of people (846 000) were employed in 2007 and the lowest (736 000) in 2012.

Employment in Community and social services and Trade has been consistently higher since 2003,

and lowest in Utilities.

The most skilled workers in the province were found in tertiary industries. Between 2003 and 2013,

the highest percentage decrease was found among semi-skilled workers who were concentrated in

primary industries.

At 34,0%,the official unemployment rate was at its highest in 2013 and its lowest in 2007 at 21,4%.

1,3

3,8

10,4

20,6

22,2

27,9

41,4

46,1

66,9

86,1

34,5

5,7

6,1

11,9

23,6

27,5

28,1

41,4

81,3

66,4

90,6

43,5

0,0 20,0 40,0 60,0 80,0 100,0

Private hholds

Agriculture

Construction

Trade

Finance

Transport

Manufacturing

Utilities

Services

Mining

Total

%

2003 2013

KwaZulu-Natal labour market trends over the last decade

2003–2013

Statistics South Africa KwaZulu-Natal-1 P0211.4

KwaZulu-Natal labour market trends, 2003-2013

KwaZulu-Natal

At around 92 100 km2 in area, KwaZulu-Natal (KZN) is roughly the size of Portugal (92 090 km2). While it is the country's third-smallest province, taking up 7,7% of South Africa's land area, it has the second-largest population, with 10,3 million people living in the province according to the 2011 Population Census. The number of employed persons in the province increased by 429 000 between Q3: 2003 and Q3: 2013 with the largest job gains in the Community and social services industry (176 000). KwaZulu-Natal was also the second largest contributor to GDP (15,7%) or R458 841 million in 2011 with the Agriculture, Transport and Manufacturing industries contributing the most.

1. Results

Figure 1: Trends in key labour market indicators in KwaZulu-Natal, 2003–2013


The highest number of people who were employed was reported in Q3: 2013 (2,7 million),while the lowest was in Q3: 2003 (2,2 million). The unemployment rate in KwaZulu-Natal was highest in 2005 (24,7%) and lowest in 2009 (18,7%). The latest unemployment rate (Q3: 2013) was 3,8 percentage points lower than the national unemployment rate of 24,7%. The highest labour force participation rate (LFPR) was observed in 2006 at 53,2%. The absorption rate reached a peak in 2006 at 43,0%, and was lowest in 2010 at 36,0%. Figure 2: Labour market rates Figure 3: Labour market indicators (official)

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Employed 2 238 2 255 2 369 2 626 2 471 2 641 2 526 2 401 2 510 2 533 2 667


U Rate_official(RHS) 23,5 20,6 24,7 19,1 22,3 22,1 18,7 19,7 19,1 21,3 20,9

LFPR (RHS) 50,3 48,0 52,3 53,2 51,2 52,6 47,5 44,9 45,8 46,8 48,3


0,0

10,0

20,0

30,0

40,0

50,0

60,0

0

500

1 000

1 500

2 000

2 500

3 000 %

Thousand

61,2

48,3

38,2

37,6

20,9

64,2

50,3

38,5

40,0

23,5

0,0 20,0 40,0 60,0



Absorption rate



%

2003 2013

2667

705

3 608

3 372

6 980

2 238

686

2 894

2 925

5 819

429

18

714

447

1 161

0 2000 4000 6000 8000

Employed

Unemployed


Labour force

Working age

Thousand

2003 2013 Change 2003-2013

http://en.wikipedia.org/wiki/Portugal



The working age population in KwaZulu-Natal increased from 5,8million in 2003 to almost 7,0 million in 2013. Over the same period, employment increased by 429 000 and unemployment increased by 18 000, resulting in a net increase of 447 000 in the labour force over the 10-year period. The official unemployment rate for KwaZulu-Natal was lower than the national unemployment rate both in 2003 and in 2013, but the expanded unemployment rate for the province was higher than the national rate in both years. All the key labour market rates for KwaZulu-Natal were higher in 2003 than in 2013. Over the ten-year period, the official unemployment rate declined by 2,6 percentage points and the expanded rate decreased by 2,4 percentage points. The biggest decline occurred in the expanded labour force participation rate (LFPR) which declined from 64,2% to 61,2% (down by 3,0 percentage points).


The unemployment rate for women remained higher than the provincial rate in both 2003 and 2013. The rate among women was 26,8% compared to 20,4% among men (6,4 percentage difference) in 2003. However, by Q3: 2013 the gap has narrowed to 0,9 of a percentage point.

In 2013, youth in KZN were 2,7 times more likely to be unemployed than adults, with an unemployment rate of 29,8%. While the unemployment rate of adults increased by 0,5 of a percentage point in 2013, the rate among youth was 4,4 percentage points lower than it was ten years ago.

The unemployment rate was higher among black Africans than among other population groups.

23,6

14,7

9,0

4,2

29,8

11,0

20,5

21,4

20,9

26,1

22,9

17,2

5,5

34,1

10,5

20,4

26,8

23,5

0,0 10,0 20,0 30,0 40,0

Black African

Coloured

Indian/Asian

White

Youth

Adults

Men

Women

KwaZulu-Natal

%

2003 2013



Figure 5: Trends in employment by industry, 2003 - 2013

A large number of people in KwaZulu-Natal were employed in the Trade industry from 2003–2011, with a peak observed in 2006 where 690 000 people were employed in this industry. In 2012 and 2013, Community and social services industry employed the most people followed by the Trade industry. Between 2003 and 2013 KwaZulu-Natal created 428 000 jobs, and the Community and social services industry contributed the most to this increase with 176 000 jobs. In KwaZulu-Natal, the Mining and Utilities industries employ the least number of people. Figure 6: Share of employment by industry

Figure 7: Employment by industry

Note: Due to small sample size, Mining industry was removed in Figure 7

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Agriculture 166 151 151 198 174 155 116 119 97 89 110

Mining 0 4 6 5 13 8 6 7 16 18 22

Manufacturing 390 407 415 433 406 405 407 371 400 392 370

Utilities 19 14 21 15 9 14 4 9 8 10 15

Construction 132 134 163 200 174 232 244 231 234 215 230

Trade 503 515 634 690 608 632 532 509 605 524 594

Transport 136 160 156 165 138 174 177 194 156 206 207

Finance 196 169 197 209 230 269 313 279 287 298 294

Services 427 420 430 484 502 484 489 470 486 560 604

Private households 268 282 198 226 218 267 236 213 220 222 221

0

100

200

300

400

500

600

700

800

Thousand

0,5

0,8

4,1

7,8

8,3

8,6

11,0

13,9

22,3

22,6

0,8

0,0

7,4

6,1

12,0

5,9

8,8

17,4

22,5

19,1

0,0 5,0 10,0 15,0 20,0 25,0

Utilities

Mining

Agriculture

Transport

Private households

Construction

Finance

Manufacturing

Trade

Services

%

2003 2013

15

110

207

221

230

294

370

594

604

19

166

136

268

132

196

390

503

427

-4

-56

71

-48

98

98

-20

90

176

-2,6

-4,0

4,3

-1,9

5,7

4,1

-0,5

1,7

3,5

0 100 200 300 400 500 600 700

Utilities

Agriculture

Transport

Private hholds

Construction

Finance

Manufacturing

Trade

Services

Thousand

2003 2013 Annual rate of change Change in employment



Figure 6 shows that in 2013, Community and social services had the largest share of employment, followed by the Trade and Manufacturing industries. Mining, Utilities and Agriculture, had the lowest share of employment. As depicted in Figure 7, six out of ten industries had an increase in employment over the ten-year period. Out of the six industries that showed increases, Community and social services, Construction and Finance and other businesses services had the biggest increases (176 000, 98 000 and 98 000 more jobs respectively). Most jobs were lost in Agriculture and Private households. Figure 8: Employment by industry and occupation


In both 2003 and 2013, more than 47% of employed persons were in semi-skilled occupations, followed by those in low-skilled occupations. Among those employed in the secondary industries, a large proportion (more than 65,0%) were in semi-skilled occupations in 2003 and 2013, though there was a decrease of 6,7 percentage points over the 10-year period. A large proportion of people in low-skilled occupations were employed in the primary industries - this includes the Mining and Agriculture industries. Individuals in the skilled occupation category accounted for the smallest share of employment in the primary industries. Figure 9 shows that in both 2003 and 2013, the highest level of education for the majority of the employed across all industries was below matric. People with tertiary education were more likely to be employed in the tertiary industries, and less likely to be in the primary industries. In 2003, 92,4% of those employed in the primary industries did not have matric. Ten years later this group still accounted for the biggest share of employment in this industry category but the share had declined by 9,5 percentage points to 82,9%. Figure 10: Share of employment by sector

4,9

3,8

15,8

13,5

27,3

27,1

23,5

22,1

31,1

37,4

65,2

71,9

42,8

39,4

47,4

47,1

64,0

58,8

19,0

14,6

29,9

33,5

29,1

30,8

0,0 20,0 40,0 60,0 80,0 100,0

2013

2003

Primary industries

2013

2003


2013

2003

Tertiary industries

2013

2003

All industries

%

Skilled Semi skilled Low skilled

92,4

82,9

61,8

55,1

51,9

45,0

57,3

49,2

5,1

15,1

30,0

33,8

31,5

34,9

29,2

33,7

2,5

2,1

8,0

11,0

16,4

19,5

13,3

16,6

0,0 20,0 40,0 60,0 80,0 100,0

2013

2003

Primary industries

2013

2003


2013

2003

Tertiary industries

2013

2003

All industries

%


62,570,8

18,1

16,87,4

4,112,0 8,3

0

20

40

60

80

100

2003 2013

%

Private houuseholds

Agriculture

Informal sector

Formal sector



More than 60% of the employed had jobs in the formal sector both in 2003 and 2013. It is also the only sector that showed an increase in employment share between 2003 and 2013. The informal sector had the second largest share of employment although its share was less than 20%. A small proportion were employed in the agriculture sector in 2003 (7,4%) and 2013 (4,1%) - the proportion in 2013 was almost half that of 2003. Figure 11: Trade union membership by industry

About 26,2% of employees were members of a trade union in 2013 – reflecting a 2,0 percentage point decrease from 2003. Among those employed in Mining, 58,6% were members of a trade union in 2013 compared to just 13,4% in 2003 – a 45,2 percentage point increase. The Utilities industry had the second highest proportion of employees that were members of a trade union in 2013 (56,4%) compared to 32,4% in 2003. Over the 10-year period, trade union membership among employees in the Mining and Utilities industries increased by the largest amount and declined the most in Trade and Finance and other business services industries (by 9,3 percentage points and 7,8 percentage points respectively). Employees in Agriculture and Private households are less likely to be members of a trade union.

2. Hard facts

The number of employed persons in KZN was highest in Q3: 2013 at 2,7 million.

KwaZulu-Natal’s unemployment rate has been consistently lower than the national rate since 2008.

The youth unemployment rate in the province was 18,8 percentage points higher than that of adults

in 2013.

The Trade, Community and social services and Manufacturing industries provide the most jobs

while the Mining and Utilities industries provide the least.

Similar to the national results, the majority of employed persons worked in the formal sector.

Trade union membership in the Mining industry increased the most over the ten-year period.

Almost half of the employed were in semi-skilled occupations.

1,9

4,5

5,5

9,6

22,6

26,5

37,0

52,7

56,4

58,6

26,2

0,0

2,8

11,8

18,9

30,7

25,6

40,4

54,8

32,3

13,4

32,8

0,0 10,0 20,0 30,0 40,0 50,0 60,0

Private households

Agriculture

Construction

Trade

Finance

Transport

Manufacturing

Services

Utilities

Mining

Total

%

2003 2013

North West labour market trends over the last decade

2003 - 2013

Statistics South Africa North West-1 P0211.4

North West labour market trends, 2003-2013

North West North West province is located in the north western part of South Africa and hence the name. It is also known as the "Platinum province" because of its underground wealth in metals. The province covers a land area of 104 882 square kilometers. According to Census 2011, the population of North West is 3,2 million of which the majority (about 90%) are black African and the average annual household income in the province is R69 914. The province contributed 6,4% to the national GDP in 2011. Figure 1: Trend in key labour market indicators in North West, 2003-2013


Over the 10-year period under review, the number of employed people peaked at 860 000 in 2005 and remained above 800 000 until the onset of the global recession when it declined to 729 000 in 2009. Employment levels declined further in both 2010 and 2011 before recovering to 745 000 and 746 000 in 2012 and 2013 respectively. Unemployment was at its highest before the recession where it reached 390 000 in 2006. Since 2006, the number of unemployed people declined for six successive years reaching 248 000 in 2012. As a result, the unemployment rate was at its highest level in 2006 at 32,1%.The rate increased steadily from 26,5% in 2008 to 28,5% in 2011 before declining to 25,0% in 2012 – the lowest rate over the 10-year period. Reflecting the trend in employment, the absorption rate was highest in 2005 at 40,7%. Since 2009 the rate has declined every year until 2011. The expansion of employment in 2012 resulted in an increase in the absorption rate to 36,0% that year. The labour force participation rate (LFPR) declined from a peak of 56,9% in 2006 to a low of 46,6% in 2011. It rose for two successive years thereafter – reaching 49,0% in 2013.

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Employed 728 790 860 824 857 789 729 714 680 745 746





5,0

15,0

25,0

35,0

45,0

55,0

65,0

0

100

200

300

400

500

600

700

800

900

1000 % (Broken scale)

Thousand



Figure 2:Labour market rates Figure 3:Labour market indicators: 2003 and 2013

Figure 2 shows that working age population in North West increased by 29 000 over the period 2003 to 2013. Over the same period, employment increased by 18 000 and unemployment decreased by 60 000 resulting in a decline in the official unemployment rate by 4,7 percentage points to 26,6% in 2013 (Figure 3). The number of not economically active people also increased - by 71 000. Almost all the key labour market rates for North West were higher in 2003 than in 2013 except for the absorption rate which increased by 0,4 of a percentage point in 2013. Figure 3 shows that based on the official definition, over the 10-year period, the LFPR decreased to 49,0%, a decrease of 2,4 percentage points. In addition, both the expanded LFPR and unemployment rates decreased - by 5,5 and 5,2 percentage points respectively over the period 2003 to 2013.

Figure 4: Unemployment rates (Official) for key groups: 2003 and 2013

Figure 4, shows that the unemployment rate for women was higher than that of men in both 2003 and 2013. In 2003, the rate among women was 36,0% compared to 27,9% among men (8,1 percentage points higher). However, by 2013 the gap narrowed to 2,8 percentage points, as the rate among women declined to 28,3% while among men it declined by a smaller margin to 25,5%. In 2013, the youth in North West were

746

271

1 074

1 017

2 091

728

331

1 003

1 059

2 062

18

-60

71

-42

29

0,2

-2,0

0,7

-0,4

0,1

-65 435 935 1435 1935 2435

Employed

Unemployed


Labour force

Working age

Thousand

2003 2013 %Annual Change 2003-2013

62,5

49,0

35,9

42,9

26,6

68,0

51,4

35,3

48,1

31,3

0,0 20,0 40,0 60,0 80,0

Labour force participation rate _Expanded


Absorption rate



%

2003 2013

25,5

28,3

16,7

37,1

5,1

28,6

27,9

36,0

15,8

47,2

6,5

33,6

-2,4

-7,7

-10,1

0,9

-1,4

-5,0

0,0 10,0 20,0 30,0 40,0 50,0

Men

Women

Adults

Youth

Other

Black African

%

2003 2013 Change



2 times more likely than adults to be unemployed, with an unemployment rate of 37,1% compared with 16,7% among adults. While the unemployment rate of adults increased by 0,9 of a percentage point in 2013, the rate among youth was 10,1 percentage points lower than it was ten years ago. The black African population group were more likely to be unemployed than other population groups but the unemployment rate among the black African group declined over the 10-year period by 5,0 percentage points.

Figure 5: Trends in employment by industry, 2003 and 2013

Figure 5 indicates that in 2003 the Trade industry had the highest number of employed persons (153 000) followed by Community and social services (139 000), Mining (110 000) and Private households (107 000). Over the period 2011 to 2013, employment in the Community and social services industry bypassed that of the Trade industry. By 2013, the Trade industry was the third largest contributor to employment in the province - with 129 000 employed persons. The Utilities and Transport industries employed the least number of persons throughout the 10-year period. Figure 6: Share of employment by industry Figure 7: Employment by industry

Due to small sample size, Utilities industries have been removed in Figure 6; the sample is too small for reliable estimates.

Figure 6 shows that in 2003 the Trade industry accounted for the largest share of employment at 21,1%, followed by Community and social services (19,1%) and Mining (15,2%). Over the 10-year period, the

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Agriculture 59 59 61 56 52 56 35 35 31 31 37

Mining 110 104 109 127 117 128 105 106 114 115 141

Manufacturing 69 75 68 58 81 68 83 69 67 55 64

Utilities 3 4 3 3 3 5 3 2 3 8 4

Construction 30 41 52 60 48 54 55 38 41 42 47

Trade 153 182 209 176 192 164 135 164 130 151 129

Transport 25 27 31 28 27 26 19 22 22 31 23

Finance 34 64 63 48 72 62 67 62 63 64 63

Services 139 134 157 157 154 145 158 146 151 175 182

Private hholds 107 100 108 111 111 81 68 71 59 73 55

0

50

100

150

200

250

Thousand

3,1

6,4

7,5

8,2

8,5

8,7

17,4

18,9

24,5

3,4

4,1

14,7

5,0

4,6

9,5

21,1

15,2

19,1

0,0 5,0 10,0 15,0 20,0 25,0 30,0

Transport

Construction

Private hholds

Agriculture

Finance

Manufaturing

Trade

Mining

Services

%

2003 2013

3

25

59

30

107

34

69

153

110

139

4

23

37

47

55

63

64

129

141

182

1

-1

-22

17

-51

30

-4

-24

30

43

18

4,7

-0,6

-4,6

4,7

-6,4

6,5

-0,7

-1,7

2,4

2,7

0,2

0 50 100 150 200

Utilities

Transport

Agriculture

Construction

Ph holds

Finance

Manufaturing

Trade

Mining

Services

Total

Thousand

2013 2003 Change %Annual 2003-2013



Community and social services and the Mining industries had the largest increases in their shares of total employment (by 5,4 and 3,7 percentage points respectively). Figure 7 illustrates that over the 10-year period Community and social services had the highest increase in employment at 43 000 followed by Finance and other business services and Mining each of which increased by 30 000. Private households lost 51 000 jobs followed by Trade and Agriculture (down by 24 000 and 22 000 jobs respectively). The average annual rate of growth in employment was highest in the Finance and other business services industry (6,5%) and in Construction (4,7%).

Figure 8: Employment by industry by occupation

Figure 9: Employment industry by level of education

Figure 8 above shows that semi-skilled and unskilled occupations dominate all industry groupings. In both 2003 and 2013 these occupation groups accounted for over 80% of all employment opportunities in the province. In the primary and secondary industries the percentage of such occupations rises to over 90%. Figure 9 shows that across all industry groups, the level of education has generally improved over the 10-year period. The largest improvement occurred in the primary industries where the percentage of those with education levels below matric declined from 76,5% in 2003 to 59,9% in 2013 while the share in employment of those with Tertiary education rose from 4,8% to 8,6% over the same period.


18,0

16,8

23,5

23,2

9,9

8,9

8,0

5,6

49,9

51,5

36,5

44,4

73,0

72,3

72,3

56,1

32,0

31,7

39,9

32,5

17,1

18,8

19,7

38,4

0% 20% 40% 60% 80% 100%

2003

2013

All industries

2003

2013

Tetiary industries

2003

2013


2003

2013

Primary industries


64,4

54,2

58,7

50,1

69,4

61,6

76,5

59,9

21,8

31,9

23,4

32,4

20,9

31,0

17,9

31,0

12,5

13,5

16,3

17,3

8,2

6,3

4,8

8,6

0% 20% 40% 60% 80% 100%

2003

2013

All industries

2003

2013

Tertiary industries

2003

2013


2003

2013

Primary industries


62,174,6

15,0

13,08,2

5,014,77,4

0%

20%

40%

60%

80%

100%

2003 2013

Private hholds

Agriculture

Informal sector

Formal sector



Figure 10 shows that the formal sector accounted for the largest share of total employment in the province, and in 2013 the share increased to 74,6% from the 62,1% in 2003 - an increase of 12,5 percentage points. Over the same period, the informal sector declined by 2,0 percentage points to 13,0% in 2013.

Figure 11: Trade union membership of by industry

Over the ten year period, in the North West, the proportion of employees with trade union membership increased by 2,0 percentage points to 42,3% in 2013. Utilities and Minning were the industries with the largest trade union membership at 92,5% and 87,8% respectively in 2013. In both industries membership increased over the period 2003 to 2013 - by 25,9 and 19,0 percentage points respectively. Finance and other business services as well as Trade recorded the biggest declines in membership at 3,5 and 3,4 percentage points respectively.

Hard facts

Over the ten-year period, the analysis showed that the official unemployment rate decreased by 4,7 percentage points from 31,3% in 2003 to 26,6% in 2013.

The unemployment rate among youth in the province is twice that of adults.

In 2013, the Community and social services industry provided the most job opportunities in the province followed by Mining and Trade. This compares to 2003 when the Trade industry provided the most jobs, with the Community and social services, and Mining industries in second and third place.

Employment in all industries in the province is primarily dependent on semi-skilled and unskilled occupations.

Most of the jobs gains over the ten-year period were in the formal sector which contributed 74,6% to the total employment of the province in 2013.

0,0

13,8

15,2

17,4

27,0

48,7

55,2

87,8

92,5

42,3

6,0

6,4

18,7

20,9

27,9

34,1

60,0

68,9

66,6

40,3

-6,0

7,5

-3,4

-3,5

-0,9

14,6

-4,8

19,0

25,9

2,0

0,0 20,0 40,0 60,0 80,0

Private hholds

Construction

Trade

Finance

Transport

Manufacturing

Services

Mining

Utilities

Total

%

2003 2013 Change

Gauteng labour market trends over the last decade

2003–2013

Statistics South Africa Gauteng-1 P0211.4

Gauteng labour market trends, 2003-2013

Introduction

Situated in the Highveld, Gauteng is the smallest province in terms of land size in South Africa. It is home to 12,2 million people and the fastest growing province, experiencing a population growth of over 33% between the 1996 and 2011. Gauteng now has the largest population in South Africa, although it is has the smallest land size in terms of square meters at 18 178 according to Census 2001. The province is highly urbanised, and considered to be the economic hub of South Africa. It is responsible for a third of the country’s Gross Domestic Product. It contributes heavily in the Financial, Manufacturing and Transport industries, among others.

Figure 1: Trends in key labour market indicators Gauteng, 2003 - 2013

RHS refers to read values on the right-hand side. The results for 2003-2007 are based on the September LFSs while those for subsequent years are based on the Q3: QLFSs.

Figure 1 shows that between 2003 and 2013 employment in Gauteng increased by 783 000. Employment peaked in 2008 at 4,3 million after which it declined by 319 000 in the subsequent year due to the global

economic recession. Since 2010 employment has been on an increase in the province, reaching 4,2 million in 2013. The number of unemployed people increased from 1,1 million in 2003 to 1,4 million in 2013. In 2013 the unemployment rate was 24,3% - 0,7 of a percentage point lower than in 2003 and 2,7 percentage points higher than in 2008 when employment was at a peak. The absorption rate was highest in 2007 at 57,8% and the highest labour force participation rate was observed in 2008 at 73,2% – 3,6 percentage point higher than in Q3: 2013.

Figure 2: Labour market indicators (Official) Figure 3: Labour market rates

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Employed 3 450 3 552 3 894 4 029 4 054 4 271 3 952 3 958 3 983 4 194 4 234



LFPR (RHS) 69,8 68,5 71,7 72,5 70,4 73,2 70,0 70,1 70,5 70,3 69,6


0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

0

500

1 000

1 500

2 000

2 500

3 000

3 500

4 000

4 500 %

Thousand

4 234

1359

2 445

5 592

8 037

3 450

1148

1 991

4 598

6 589

783

211

455

994

1 449

0 2 000 4 000 6 000 8 000 10 000

Employed

Unemployed

Not economically

active

Labour force

Working age

Thousand

2003 2013 Change 2003-2013

74,2

69,6

52,7

34,8

24,3

78,5

69,8

52,4

33,3

25,0

0,0 20,0 40,0 60,0



Absorption rate



%

2003 2013



Figures 2 shows that there was an increase in all key labour market indicators over the period 2003 to 2013 with the working age population increasing by 1,4 million people and the labour force by 994 000 people. The employed also increased by 784 000, the number of unemployed people increased by 211 000, while

the not economically active population increased by 1, 2 million.

According to Figure 3, the official unemployment rate decreased by 0,7 of a percentage point between 2003 and 2013 to 24,3%, while the expanded unemployment rate decreased by 4,3 percentage points in the same period to 29,0%. The absorption rate increased by 0,3 of a percentage point to 52,7% in 2013. The official labour force participation rate (LFPR) decreased by 0,3 of a percentage point in 2013 to 69,6% and the expanded LFPR declined by 4,3 percentage points to 74,2% in 2013.


The unemployment rate was higher among black Africans and coloured population than among Indian/Asian and white population both in 2003 and 2013. However, there was a decline of 5,8 percentage points among the coloured population and a decline of 2,8 percentage points among black Africans while the rate increased among the white and Indian/Asian population over the 10-year period.

The youth (15-34 years) unemployment rate in 2013 was twice that of adults (35-64 years). The unemployment rate among the youth remained unchanged over the period 2003 to 2013, while it increased by 2,0 percentage points to 15,9% among adults.

The unemployment rate among women was higher than among men, and it decreased from 29,7% in 2003 to 27,6% in 2013, while among men it increased by 0,2 of a percentage point to 21,5% in the same period.

21,5

27,6

15,9

35,0

28,2

25,3

16,3

8,6

21,3

29,7

13,9

35,0

31,0

31,1

14,2

3,9

0,2

-2,1

2,0

0,0

-2,8

-5,8

2,1

4,7

0,0 10,0 20,0 30,0 40,0

Men

Women

Adults

Youth

Black African

Coloured

Indian/Asian

White

%

2003 2013 Change



Figure 5: Trends in employment by industry, 2003 – 2013

The industries that employed the most people in Gauteng over the period 2003 to 2013 were Trade, Community and social services and Finance and other business services. The Trade industry employed more than 1,0 million people in 2007 and 2008 after which employment decreased to 952 000 in the following year. Employment in the Finance and other business services industry increased over time, reaching the highest level of 862 000 in 2013. The same trend was observed in the Community and social services industry, with the peak reached in 2012 at 899 000.


Figures 6 shows that Trade accounted for the biggest share of employment in Gauteng both in 2003 and 2013. In 2013 this industry accounted for 21,3% of total employment in the province, followed by Finance and other business services (20,4%) and Community and social services (20,4%). Although Mining accounted for a small share of employment in the province, the share decreased from 2,9% in 2003 to 0,8% in 2013.

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Agriculture 21 58 48 51 44 69 45 34 39 49 33

Mining 102 33 30 34 37 30 33 38 25 30 32

Manufacturing 590 596 599 629 739 724 597 630 600 607 594

Utilities 27 33 27 42 29 33 44 42 24 28 34

Construction 146 255 345 323 271 308 283 308 259 279 251

Trade 824 819 982 1 074 1 031 952 886 907 894 910 903

Transport 214 229 248 233 297 290 272 256 278 293 310

Finance 580 574 637 617 584 744 745 677 744 804 863

Services 664 626 599 617 662 752 718 744 805 899 862

Private households 283 330 380 408 362 367 324 322 312 296 350

0

200

400

600

800

1 000

1 200

Thousand

0,8

0,8

0,8

5,9

7,3

8,3

14,0

20,4

20,4

21,3

2,9

0,6

0,8

4,2

6,2

8,2

17,1

19,2

16,8

23,9

0,0 5,0 10,0 15,0 20,0 25,0 30,0

Mining

Agriculture

Utilities

Construction

Transport

Ph holds

Manufaturing

Services

Finance

Trade

%

2003 2013

33

32

594

34

251

903

310

863

862

350

21

102

590

27

146

824

214

580

664

283

13

-70

4

7

104

79

96

283

198

67

0

4,8

-10,9

0,1

2,4

5,5

0,9

3,8

4,1

2,6

2,1

0,0

0 100 200 300 400 500 600 700 800 900 1000

Agriculture

Mining

Manufaturing

Utilities

Construction

Trade

Transport

Finance

Services

Ph holds

Total

Thousand

2003 2013 Change %Annual 2003-2013



As depicted in Figure 7, over 900 000 people were employed in the Trade industry in Gauteng, followed by Finance and other business services and Community and social services with 863 000 and 862 000 respectively. Of the 784 000 jobs created over the 10-year period, the majority were in these three

industries. Only the mining industry shed jobs in 2013 compared to 2003 (down by 70 000).


Figure 9: Employment by Industry and level of education

In both 2003 and 2013, more than 42% of employed persons were in semi-skilled occupations, followed by those in high-skilled occupations. Among those employed in the secondary industries, a large proportion (more than 54,0%) were in semi-skilled occupations in 2003 and 2013, though there was an increase of 10,0 percentage points over the 10-year period. A large proportion of people in low-skilled occupations were employed in the primary industries - this includes the Mining and Agriculture industries. Individuals in the skilled occupation category accounted for the smallest share of employment in the primary industries in 2003 (Figure 8).

Figure 9 shows that both in 2003 and 2013, the majority of the employed people across all industries did not have matric. People with tertiary education were more likely to be employed in the tertiary industries, and less likely to be in the primary industries. In 2003, 78,6%of those employed in the primary industries did not have matric. Ten years later this group still accounted for the biggest share of employment in primary industries but the share had declined by 25,4 percentage points to 53,2%.

Figure 10: Share of employment by sector Figure 11: Trade union membership by industry

28,5

33,3

31,0

34,3

23,3

30,3

8,8

25,5

48,5

46,0

42,7

43,7

64,3

54,3

71,1

49,6

23,0

20,7

26,3

22,0

12,4

15,5

20,1

24,9

0% 20% 40% 60% 80% 100%

2003

2013

All industries

2003

2013

Tetiary industries

2003

2013


2003

2013

Primary industries


45,8

35,8

42,4

34,1

51,9

40,6

78,6

53,2

34,3

34,0

35,5

33,9

33,4

34,9

14,0

28,3

19,0

29,0

21,1

30,8

13,9

23,2

5,7

17,8

0% 20% 40% 60% 80% 100%

2003

2013

All industries

2003

2013

Tertiary industries

2003

2013


2003

2013

Primary industries


76,4 79,2

14,7 11,7

0,6 0,88,2 8,3

0,0

20,0

40,0

60,0

80,0

100,0

2003 2013%

Private households

Agriculture

Informal sector

Formal sector

0,0

2,2

11,1

16,7

18,7

26,9

28,1

44,8

45,1

68,9

24,2

4,3

35,4

11,9

19,2

17,2

28,4

36,3

48,7

30,1

78,4

30,9

-4,3

-33,1

-0,8

-2,5

1,6

-1,4

-8,2

-3,8

15,1

-9,6

-6,7

0,0 20,0 40,0 60,0 80,0

Ph holds

Agriculture

Construction

Finance

Trade

Manufacturing

Transport

Services

Utilities

Mining

Total

%

2003 2013 Change



Figure 10 shows that more than 75% of the employed people had jobs in the formal sector for in 2003 as well as in 2013. Formal sector employment increased by 2,8 percentage points to 79,2% in 2013 compared to 2003. The informal sector accounted for 14,7% of total employment in Gauteng in 2003 and by 2013 the share had declined to 11,7% - 3,0 percentage points lower.

According to Figure 11, almost a quarter (24,2%) of employees in Gauteng belonged to a trade union in 2013. This is lower than the 30,9% observed in 2003. The industries that had the highest proportion of employees who belonged to a trade union were Mining (68,9%), Utilities (45,1%) and Community and social services (44,6%) and in 2013.

Hard Facts

Employment levels have not recovered to the 4,3 million reached in 2008 after the economic recession, but have been on a steady increase resulting in 4,2 million employed people in 2013.

In both 2013 and 2003, the unemployment rate was highest amongst women, the youth and Black Africans.

The Trade industry accounted for the largest share of total employment both in 2003 and 2013 in Gauteng.

The majority of the employed people across all industries did not have matric. People with tertiary education were more likely to be employed in the tertiary industries, and less likely to be in the primary industries.

The proportion of those with tertiary education increased by 10,0 percentage points over the 10-year period in the province – increased from 19,0% in 2003 to 29,0% in 2013.

Mpumalanga labour market trends over the last decade

2003 - 2013

Statistics South Africa Mpumalanga-1 P0211.4

Mpumalanga labour market trends, 2003-2013

Mpumalanga

According to Census 2011, Mpumalanga had an estimated population of 4 million people, covering a total of 76 495 square kilometers of land in South Africa. Mpumalanga’s economy grew by 2,7% during 2010, and 2,5% in 2011. The province’s economy is estimated to be worth R205,6 billion and contributes around 7,0% to the national GDP. In 2011, the largest industries contributing to employment in the province were Mining and quarrying at 24,9% respectively, Manufacturing (11,5%), and Finance and other business services (10,9%). Agriculture made the lowest contribution (2,8%) to the GDP. Figure 1: Trends in key labour market indicators in Mpumalanga, 2003–2013

Figure 1 shows that employment reached a peak in 2008 at 947 000, declining to 890 000 in 2010. Since 2011, the number of employed persons has been steadily increasing to reach 1 032 000 employed in 2013. The official unemployment rate was the lowest in 2003 (17,9%) with noticeable declines in the levels of unemployment observed between 2006 and 2007 (down by 54 000) as well as between 2012 and 2013 (down by 44 000). The labour force participation rate (LFPR) increased by 7,7 percentage points between 2003 and 2013, and by 1,6 percentage points between 2012 and 2013 (Figure 2). The absorption rate also increased over the same period (2003 and 2013, and 2012 and 2013) but at a slower pace compared to LFPR. The official unemployment rate increased from 17,9% in 2003 to 26,6% in 2013 (an increase of 8,7 percentage points), while a decline of 4,4% percentage points between 2012 and 2013 was observed.

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Employed 837 834 875 897 943 947 908 890 911 928 1032





5,0

15,0

25,0

35,0

45,0

55,0

65,0

0

200

400

600

800

1 000


Thousand




Figure 3 outlines an increase in all labour market indicators. The number of the working age population increased by 398 000, from 2 million in 2003 to 2,4 million in 2013. Between 2003 and 2013 (as shown in Figure 2), the official LFPR increased by 7,7 percentage points (an increase of 387 000 persons in the labour force).Figure 2 shows that the unemployment rate rose from 17,9% in 2003 to 26,6% in 2013, up by 8,7 percentage points (191 000 unemployed persons in Figure 3). The unemployment rate in Mpumalangawas 1,9 percentage point lower than the national unemployment rate (24,7%). The expanded unemployment rate increased by 2,7 percentage points (from 37,8% in 2003 to 40,5% in 2013). The official unemployment rate percentage increase was 4,3 times higher than the expanded unemployment rate. Figure 4: Unemployment rates (official) for key groups

The unemployment rate for women has consistently been above that of men. In 2003, the unemployment rate for women was 3,0 percentage points higher than the provincial rate of 17,9%, and 6,8 percentage points higher than the provincial unemployment rate of 26,6% in 2013. Similarly in 2003, the unemployment rate for men was 2,7 percentage points lower than the provincial unemployment rate.

71,8

58,2

42,7

40,5

26,6

66,7

50,5

41,5

37,8

17,9

0,0 20,0 40,0 60,0 80,0



Absorption rate



%

2003 2013

837

183

999

1 019

2 018

1 032

374

1 010

1 406

2 416

196

191

11

387

398

0 1 000 2 000 3 000

Employed

Unemployed


Labour force

Working age

Thousand

2003 2013 Change 2003-2013

26,6

21,2

33,4

14,7

36,9

28,5

7,6

17,9

15,2

20,9

8,4

27,2

19,4

7,4

0,0 10,0 20,0 30,0 40,0

Total

Men

Women

Adults

Youth

Black African

Other

%

2003 2013



2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Agriculture 93 91 79 88 95 84 75 74 75 87 90

Mining 57 24 29 31 36 56 61 58 72 60 79

Manufacturing 103 114 122 101 96 87 75 81 77 77 83

Utilities 13 12 10 15 11 17 14 21 14 22 26

Construction 47 82 76 84 94 84 88 72 76 66 84

Trade 231 210 223 228 256 254 214 214 222 224 229

Transport 35 40 46 48 46 45 40 42 42 47 45

Finance 47 48 71 70 79 88 81 89 81 97 107

Services 135 118 116 131 137 144 163 168 163 158 203

Private hholds 75 95 103 103 91 87 97 71 90 88 87

0

50

100

150

200

250

300

Thousand

The youth unemployment rate increased from 27,2% in 2003 to 36,9,0% in 2013, an increase of 9,7 percentage points, while adults’ unemployment rate increased by 6,3 percentage points, reaching 14,7% in 2013. The rate of increase for adults was not as high as that for the youth. The unemployment rate for black Africans rose from 19,4% to 28,5%, higher than the national unemployment rate by 3,8 percentage points. The unemployment rate for other population groups increased by 0,2of a percentage point (from 7,4% in 2003 to 7,6% in 2013), lower than the national unemployment rate by 17,1 percentage points.

Figure 5: Trends in employment by industry, 2003–2013

Figure 5 shows that Trade has been the main job contributor in the province since 2003, whereas Utilities maintained the lowest job contribution. Between 2012 and 2013, Transport and Private Households were the only industries to shed jobs (2 000 and 1 000 jobs respectively). Figure 6: Share of employment by industry, 2003 and 2013

Figure 7: Employment by industry

2,5

4,3

7,7

8,1

8,1

8,4

8,7

10,3

19,6

22,2

1,5

4,2

6,8

12,3

5,6

8,9

11,2

5,7

16,2

27,6

0,0 5,0 10,0 15,0 20,0 25,0

Utilities

Transport

Mining

Manufacturing

Construction

Private hholds

Agriculture

Finance

Services

Trade

%

2003 2013

26

45

79

83

84

87

90

107

203

229

13

35

57

103

47

75

93

47

135

231

3,3

-1,5

3,0

0,8

-0,6

-0,1

2,1

0,5

2,7

-1,4

1,8

13

10

22

-20

37

12

-4

59

67

-1

166

0 50 100 150 200 250 300 350

Utilities

Transport

Mining

Manufacturing

Construction

Phholds

Agriculture

Finance

Services

Trade

Total

Thousand

2003 2013 Change %Annual 2003-2013



Figures 6 and 7 highlight the share of employment over the ten-year period in Mpumalanga. The Trade industry had the highest share of employment. However, the industry saw the highest decline (of 5,4 percentage points) in the share of employment compared to Agriculture, Manufacturing, and Private households between 2003 and 2013. Community and social services maintained the second highest share of employment in the province across all years, increasing by 3,4 percentage points between 2003 and 2013. The industry also grew at an average annual rate of 2,7%. The Utilities industry on the other hand, had the lowest share of employment despite gaining 13 000 jobs between 2003 and 2013 (Figure 7). Figure 8: Employment by industry and occupation Figure 9: Employment by industry and level of education

Figure 8 illustrates the share of employment by industry and occupation over the period 2003 and 2013. Overall there was a deterioration in the skills profile of the province. While the share of persons in higher skilled occupations increased modestly from 17,8% to 18,0%, the share of persons in unskilled occupations increased from 36,3% to 47,5%. The deterioration in the share of unskilled occupations was most pronounced in secondary industries where the share increased from 13,9% to 60,9% over the 10 year period. A decline of 9,0 percentage points in the share of employed persons with less than matric was observed between 2003 and 2013 (Figure 9). In all industry groupings the share of those who are better educated increased over the period. In secondary industries the share of those with a tertiary qualification increased from 10,2% to 20,4%. Figure 10: Share of employment by sector

Figure 10 outlines that the formal sector has the highest share of employed persons in the province, reflecting an increase in its share of 7,3 percentage points between 2003 and 2013. The informal sector remained the second highest employer in 2003 and 2013. However, the sector saw a decline of 4,3

18,0

17,8

21,1

23,3

19,3

11,8

4,2

5,3

34,5

45,9

35,5

35,9

19,8

74,3

47,6

49,8

47,5

36,3

43,4

40,8

60,9

13,9

48,1

44,9

0% 20% 40% 60% 80% 100%

2013

2003

All industries

2013

2003

Tetiary industries

2013

2003


2013

2003

Primary industries


54,8

64,1

52,6

60,7

50,3

59,3

68,6

80,9

25,9

24,1

26,6

24,8

27,0

30,3

21,8

15,1

17,4

11,6

19,1

14,3

20,4

10,2

7,5

4,0

0% 20% 40% 60% 80% 100%

2013

2003

All industries

2013

2003

Tertiary industries

2013

2003


2013

2003

Primary industries


54,361,6

25,621,3

11,2 8,7

8,9 8,4

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

90,0

100,0

2003 2013

%

Private households

Agriculture

Informal sector

Formal sector



percentage points in its share of employment over the period. Private households lost 0,5 of a percentage point between 2003 and 2013. The Agricultural sector’s share of employment declined from 11,2% to 8,7% by 2,5 percentage points between 2003 and 2013. Figure 11: Trade union membership by industry

In 2013, 31,8% of employees belonged to a trade union in Mpumalanga, compared to 40,9% members in 2003, an increase of 9,1 percentage points over ten years. In 2013, industries showing the highest proportion of employees belonging to a trade union in the province were Utilities (71,1%), Mining(69,3%), and Community and social services (56,1%). This is in line with the national picture where the three industries had the highest proportion of employees who were trade union members. The number of employees who were trade union members declined in most industries except in Construction, Utilities, Transport, and Private households. The greatest decline was noticed in Manufacturing at 14,7 percentage points, followed by Mining and Finance at 13,3 and 12,4 percentage points respectively.

Hard Facts

The number of the working age population in the province increased by 398 000 between 2003 and 2013; this is reflected in the increase of the labour force by 387 000 persons.

The unemployment rate rose from 17,9% in 2003 to 26,6% in 2013, an increase of 8,7 percentage points (191 000 unemployed persons). The rate was 1,9 percentage point lower than the national rate (24,7%).

The number of employed persons increased by 196 000 between 2003 and 2013.

The Trade and Community and social services industries have been the main employers in the province.

Although the formal and informal sectors were the highest job contributing sectors in the province, both sectors lost jobs to Agriculture over the ten years of reporting.

Limpopo labour market trends over the last decade

2003 - 2013

Statistics South Africa Limpopo-1 P0211.4

Limpopo labour market trends, 2003-2013

Limpopo Limpopo, South Africa's northern-most located province, borders onto Mozambique, Zimbabwe and Botswana, making it the ideal gateway to Africa. According to Population Census 2011, about 5,4 million people lived on about 125 754 km2 of land in Limpopo. The province contributed 7,1% to the national Gross Domestic Product (GDP) in 2011 – an increase from the 6,6% it contributed in 2003. In 2013, the labour force of South Africa comprised 18,6 million people, of which 1,4 million were in Limpopo. The industries that employed the most people in Limpopo in 2003 were Trade, Community and social services, and Agriculture. In 2013, these were still the industries that accounted for the biggest shares of employment in the province.

Figure 1: Trends in key labour market indicators in Limpopo, 2003–2013

Figure 1 shows that the number of employed people increased by 344 000 between 2003 and 2013, while the number of unemployed people decreased by 73 000 over the same period, resulting in a decrease in the unemployment rate from 28,8% in 2003 to 17,8% in 2013. The official unemployment rate for Limpopo was 7,8 percentage points lower than the national unemployment rate in 2013.


2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Employed 777 867 847 851 928 926 936 905 1 026 1 084 1 121



LFPR (RHS) 39,3 40,5 40,5 39,1 41,0 41,3 38,9 36,7 37,8 40,7 39,1


5,0

10,0

15,0

20,0

25,0

30,0

35,0

40,0

45,0

0

200

400

600

800

1 000


Thousand

28,8

54,8

27,9

39,3

61,8

17,8

40,1

32,2

39,1

53,7

0,0 20,0 40,0 60,0 80,0



Absorption rate



%

2003 2013

1121

242

2124

1363

3487

777

315

1689

1091

2780

345

-73

435

272

707

3,7

-2,6

2,3

2,2

2,3

0 1000 2000 3000 4000

Employed

Unemployed


Labour force

Working age

Thousand

2003 2013 Annual Rate of Change Change 2003-2013

http://www.golimpopo.com/



Figure 2 shows that all the key labour market rates except the absorption rate were higher in 2003 than in 2013.Between 2003 and 2013, the official unemployment rate decreased by 11,0 percentage points while the expanded unemployment decreased by 14,7 percentage points. The official labour force participation rate and expanded labour force participation rate decreased by 0,2 of a percentage point and 8,1 percentage points, respectively over the 10-year period. The absorption rate on the other hand increased by 4,3 percentage points over the same period. As shown in Figure 3, there was an increase in the number of people in the labour force resulting from an increase in employment and a decline in unemployment. The number of people who were not in the labour force increased from 1,7 million to 2,1 million between 2003 and 2013.

Figure 4: Unemployment rates (Official) for key groups

Due to the small numbers, coloured and Indian/Asian population groups were omitted

There was a decrease in unemployment rates for both women and men between 2003 and 2013. Figure 4 indicates that the unemployment rate for women was higher than that for men both in 2003 and 2013. However, the unemployment rate among women decreased from 30,8% in 2003 to 17,6% in 2013 (down by 13,2 percentage points) while it decreased among men from 26,5% to 17,9% over the same period. Among youth, the unemployment rate declined from 42,6% to 26,7% over the period 2003 to 2013. Among the black African population group, the unemployment rate declined by 1,7 percentage points (from 29,8% in 2003 to 28,1% in 2013) while among the white population it increased by 0,5 of a percentage point over the period under review.

28,1

6,6

26,7

9,2

17,9

17,6

17,8

29,8

6,1

42,6

15,7

26,5

30,8

28,8

0,0 10,0 20,0 30,0 40,0 50,0

Black African

White

Youth

Adults

Men

Women

Limpopo

%

2003 2013



Figure 5: Trend in employment by industry, 2003–2013

Figure 5 shows that employment in all industries fluctuated over the period 2003 to 2013. Since 2010 there was a steady increase in employment each year in Trade, Agriculture, Utilities and Manufacturing.


Figures 6 and 7 show that between 2003 and 2013 the Community and social services and Trade industries had the highest share of employment. However, over the 10-year period, their share of employment declined by 1,8 percentage points in and 6,4 percentage points respectively. Although Utilities accounted for the lowest share of employment in both years, employment in this industry increased by 13 000 over the 10-year period. The biggest rate of increase in employment in Limpopo occurred in the Mining industry at 14,7%, followed by Utilities industry with 13,5% over the period 2003 to 2013. The share of Agriculture and Private households also decreased (by 1,6 and 1,9 percentage points) between 2003 and 2013.

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Agriculture 90 93 66 61 69 73 65 58 87 109 113

Mining 18 44 49 44 48 48 53 46 58 78 73

Manufacturing 50 65 77 55 54 70 75 66 67 76 75

Utilities 5 6 5 5 7 6 8 7 5 9 18

Construction 48 51 44 59 84 91 91 94 111 101 105

Trade 234 279 285 272 283 233 249 233 252 259 266

Transport 26 29 30 33 23 36 35 42 35 54 44

Finance 23 46 45 46 45 57 57 64 69 61 61

Service 205 181 180 202 218 222 218 198 257 242 276

Private Hhoulds 76 75 67 74 98 90 85 96 84 96 89

0

50

100

150

200

250

300Thousand

1,6

3,9

5,5

6,5

6,7

7,9

9,4

10,0

23,7

24,6

0,7

3,4

2,9

2,4

6,5

9,8

6,2

11,6

30,1

26,4

0,0 10,0 20,0 30,0 40,0

Utilities

Transport

Finance

Mining

Manufacturing

Private Housholds

Construction

Agriculture

Trade

Services

%

2003 2013

18

44

61

73

75

89

105

113

266

276

5

26

23

18

50

76

48

90

234

205

13

18

38

55

25

13

57

23

32

71

344

13,5

5,3

10,3

14,7

4,1

1,6

8,1

2,3

1,3

3,0

3,7

0 50 100 150 200 250 300

Utilities

Transport

Finance

Mining

Manufacturing

Private Hholds

Construction

Agriculture

Trade

Services

Total

Thousand

2003 2013 %Average annual rate Change in Employment





There was a marked improvement in the skills profile of the province over the period 2003 to 2013. The share of persons in higher skilled occupations increased from 18,8% to 25,6% while those in low skilled occupations declined from 42,3% to 28,3% (Figure 8). In terms of the level of education attainment, over the 10-year period, there was an improvement in the education profile of employed persons both in the province and nationally since the number of those with tertiary education increased. Across all industries, those that had less than matric had the highest share of employment while those with tertiary education had the least share (Figure 9).


Figure 10 indicates that the share of formal sector employment increased by 4,7 percentage points from 48,6% in 2003 to 53,3% in 2013. This was accompanied by a decrease in the informal sector share in total employment – decreased by 1,2 percentage points from 29,9% in 2003 to 28,7% in 2013.

2,9

7,1

2,6

20,0

24,8

29,2

18,8

25,6

26,5

38,1

80,0

59,0

33,8

43,3

38,9

46,1

70,6

54,8

17,4

21,0

41,5

27,5

42,3

28,3

Primary industries

2003

2013


2003

2013

Tertiary industries

2003

2013

All industries

2003

2013%

Skilled Semi-skilled Low skilled

83,8

73,6

62,2

53,7

50,9

43,1

56,8

47,7

11,7

18,7

27,9

31,1

30,4

32,6

27,9

31,2

4,5

7,8

9,9

15,1

18,7

24,2

15,3

21,1

Primary industries

2003

2013


2003

2013

Tertiary industries

2003

2013

All industries

2003

2013%

Below Matric Matric only Tertiary education

48,653,3

29,928,7

11,610,0

9,8 7,9

0%

20%

40%

60%

80%

100%

2003 2013

Private Households

Agriculture

Informal

formal



Figure 11: Trade union membership by industry

Trade union membership of employees over the 10-year period declined from 34,5% in 2003 to 28,1% in 2013 amounting to a loss of 6,4 percentage points. Some industries showed growth of membership in the past 10 years, others showed a decrease. Unionisation among employees in the Mining industry increased from 61,9% in 2003 to 79,7% in 2013 – the largest increase. Utilities had the second largest rise –from 28,1% in 2003 to 64,9% in 2013. Over the same period, the number of employees who were members of a trade union declined in the Services industry (21,5 percentage points), Construction (3,5 percentage points) and Trade (2,5 percentage points).

Hard facts

Over the 10-year period (2003–2013) the unemployment rate in Limpopo has decreased by 11,0 percentage points. In contrast, there was an increase in the national rate of 0,8 of a percentage point.

The number of the employed has increased by 344 000, while the number of the unemployed decreased by 73 000 over the period of 2003 to 2013.

The formal sector supports jobs creation - there has been an increase in the formal sector share of total employment - up 4,7 percentage points from 48,6% in 2003 to 53,3% in 2013.

There was an improvement in education levels both in the province and nationally since the number of those with tertiary education increased over the period 2003 to 2013.

Limpopo followed the national trend regarding unskilled occupations in the primary industries, which accounted for the largest share in both 2003 and 2013.

34,5

71,9

61,9

28,1

23,0

21,0

20,7

14,3

13,7

6,7

0,0

28,1

50,4

79,7

64,9

16,8

17,9

19,1

10,8

11,2

5,1

0,8

0,0 20,0 40,0 60,0 80,0

Total

Services

Mining

Utilities

Manufacturing

Finance

Transport

Construction

Trade

Agriculture

Private Hholds

%

2003 2013

Statistics South Africa A1 -1 P0211.4

Appendix 1 - Technical notes


Missing values

These were imputed in the QLFS but not in the LFS. As a result, some of the historically linked variables in the LFS may sometimes include an unspecified category. This category will always be included in the totals but, depending on the size, it may not necessarily be itemised separately.

Differences between the QLFS and LFS questionnaires

A detailed report on the differences pertaining to the questions and the structure of the questionnaire is available at www.statssa.gov.za/qLFS/index.asp

Breaks in series

As noted under the heading 'Linking the LFS and the QLFS', many of the series published by the LFS have been adjusted to make them comparable to the QLFS data. However, not all series could be linked for two reasons:

Any of the questions common to both the LFS and QLFS questionnaires had the potential to be linked;

that is, the LFS series could be adjusted to make them comparable to their QLFS counterparts.

However, the linkage methodology strictly limited the number of series that could be directly linked.

Priority was given to linked series related to the employed, unemployed, not economically active,

sector, industry, occupation, sex, population group, province, and age. Thus, while the not economically

active were controlled to enable historical continuity with the LFS, its components were not – hence, the

break in series for discouraged work-seekers.

Other variables, including hours worked, formal/informal sector employment, and duration of

unemployment, were not adjusted directly but are nevertheless available as LFS historically adjusted

data. See 'Linking the LFS and the QLFS' for more information on the distinction between directly and

indirectly historically revised LFS data.

The results presented in this report are based on the 2003-2007 September LFSs while those for subsequent years are based on the quarter 3 QLFSs.

Rounding

Totals may sometimes differ from the sum of the constituent parts by small amounts due to rounding.

Master sample design

The Labour Force Survey (LFS) and the Quarterly Labour Force Survey (QLFS) are based on a master sample of which there have been three so far. The design of each is outlined below.

1999 master sample

For the LFSs of February 2000 to March 2004, a rotating panel sample design was used to allow for measurement of change in people’s employment situation over time. The same dwellings were visited on, at most, five different occasions. After this, new dwelling units were included for interviewing from the same PSU in the master sample. This means a rotation of 20% of dwelling units each time.

The database of enumerator areas (EAs) established during the demarcation phase of Census 1996 constituted the sampling frame for selecting EAs for the LFS. Small EAs consisting of fewer than 100 dwelling units were combined with adjacent EAs to form primary sampling units (PSUs) of at least 100 dwelling units, to allow for repeated sampling of dwelling units within each PSU.

http://www.statssa.gov.za/qlfs/index.asp



The sampling procedure for the master sample involved explicit stratification by province and within each province, by urban and non-urban areas (using Census 1996 definitions). Independent samples of PSUs were drawn for each stratum within each province. The smaller provinces (in terms of population size) were given a disproportionately large number of PSUs compared to the bigger provinces. Simple random sampling was applied to select 10 dwelling units to visit in each PSU as ultimate sampling units. If more than one household was found in the same dwelling unit, all such households were interviewed.

2004 master sample

The 2004 master sample was used in the LFSs of September 2004 to September 2007. Enumeration areas (EAs) that had a household count of less than twenty-five were omitted from the census frame that was used to draw the sample of PSUs for the master sample. Other omissions from the frame included all institution EAs except workers’ hostels, convents and monasteries. EAs in the census database that were found to have fewer than sixty dwelling units during listing were pooled.

This master sample was a multi-stage stratified sample. The overall sample size of PSUs was 3 000. The explicit strata were the 53 district councils. The 3 000 PSUs were allocated to these strata using the power allocation method. The PSUs were then sampled using probability proportional to size principles. The measure of size used was the number of households in a PSU as counted in the census.

The sampled PSUs were listed with the dwelling unit as the listing unit. From these listings, systematic samples of dwelling units per PSU were drawn. These samples of dwelling units formed clusters. The size of the clusters differed depending on the specific survey requirements. The LFS used one of the clusters that contained ten dwelling units.

Current master sample

The QLFS frame has been developed as a general-purpose household survey frame that can be used by all other household surveys irrespective of the sample size requirement of the survey. The sample size for the QLFS is roughly 30 000 dwellings per quarter.

The sample is based on information collected during the 2001 Population Census conducted by Stats SA. In preparation for Census 2001, the country was divided into 80 787 enumeration areas (EAs). Stats SA’s household-based surveys use a master sample of primary sampling units (PSUs) which comprise EAs that are drawn from across the country.

The sample is designed to be representative at provincial level and within provinces at metro/non-metro level. Within the metros, the sample is further distributed by geography type. The four geography types are: urban formal, urban informal, farms and tribal. This implies, for example, that within a metropolitan area the sample is representative at the different geography types that may exist within that metro.

The current sample size is 3 080 PSUs. It is divided equally into four subgroups or panels called rotation groups. The rotation groups are designed in such a way that each of these groups has the same distribution pattern as that which is observed in the whole sample. They are numbered from one to four and these numbers also correspond to the quarters of the year in which the sample will be rotated for the particular group.

The sample for the redesigned labour force survey (i.e. the QLFS) is based on a stratified two-stage design with probability proportional to size (PPS) sampling of primary sampling units (PSUs) in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.

Each quarter, a ¼ of the sampled dwellings rotate out of the sample and are replaced by new dwellings from the same PSU or the next PSU on the list. Thus, sampled dwellings will remain in the sample for four consecutive quarters. It should be noted that the sampling unit is the dwelling, and the unit of observation is the household. Therefore, if a household moves out of a dwelling after being in the sample for, say two quarters, and a new household moves in, then the new household will be enumerated for the next two



quarters. If no household moves into the sampled dwelling, the dwelling will be classified as vacant (unoccupied).

Linking the LFS and the QLFS

To preserve historical continuity with the QLFS, link factors were computed on the basis of an overlap of the QLFS and the LFS in March and September 2008. A detailed report regarding the methodology used to derive the link factors is available at www.statssa.gov.za/qLFS/indes.asp.

The historical adjustment methodology involved re-weighting the LFS unit record (micro data) files. In doing this re-weighting, a substantial number of variables were set as control totals. This was done using the QLFS/LFS ratios from the estimates for these variables for Q1: 2008/March 2008 and Q3: 2008/September 2008. These variables (employed, unemployed, not economically active, industry, occupation, etc.) can be said to have been adjusted directly.

However, it is possible to tabulate other variables on the LFS files. Because these variables did not enter directly into the revision process, less confidence can be put in the consistency of these data with the corresponding data from the QLFS.

In the case of variables with vastly different definitions in the LFS and QLFS, such as discouraged work-seekers, the indirect method of historical adjustment yields LFS data that are clearly inconsistent with the QLFS estimates.

Survey requirements and design

The Quarterly Labour Force Survey (QLFS) frame has been developed as a general-purpose household survey frame that can be used by all other household surveys, irrespective of the sample size requirement of the survey. The sample size for the QLFS is roughly 30 000 dwellings per quarter.

The sample is based on information collected during the 2001 Population Census conducted by Stats SA. In preparation for the 2001 Census, the country was divided into 80 787 enumeration areas (EAs). Stats SA’s household-based surveys use a master sample of primary sampling units (PSUs) which comprise EAs that are drawn from across the country.

The sample is designed to be representative at provincial level and within provinces at metro/non-metro level. Within the metros, the sample is further distributed by geography type. The four geography types are: urban formal, urban informal, farms, and tribal. This implies, for example, that within a metropolitan area the sample is representative of the different geography types that may exist within that metro.

The current sample size is 3 080 PSUs. It is divided equally into four subgroups or panels called rotation groups. The rotation groups are designed in such a way that each of these groups has the same distribution pattern as that which is observed in the whole sample. They are numbered from one to four and these numbers also correspond to the quarters of the year in which the sample will be rotated for the particular group.

The sample for the redesigned Labour Force Survey (i.e. the QLFS) is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.

Sample rotation

Each quarter, a ¼ of the sampled dwellings rotate out of the sample and are replaced by new dwellings from the same PSU or the next PSU on the list. Thus, sampled dwellings will remain in the sample for four consecutive quarters. It should be noted that the sampling unit is the dwelling, and the unit of observation is the household. Therefore, if a household moves out of a dwelling after being in the sample for, say two quarters, and a new household moves in, the new household will be enumerated for the next two quarters. If no household moves into the sampled dwelling, the dwelling will be classified as vacant (unoccupied).

http://www.statssa.gov.za/qlfs/indes.asp



Weighting

The sampling weights for the data collected from the sampled households are constructed in such a manner that the responses could be properly expanded to represent the entire civilian population of South Africa. The weights are the result of calculations involving several factors, including original selection probabilities, adjustment for non-response, and benchmarking to known population estimates from the Demographic division of Stats SA.

Non-response adjustment

In general, imputation is used for item non-response (i.e. blanks within the questionnaire) and edits failure (i.e. invalid or inconsistent responses). The eligible households in the sampled dwellings can be divided into two response categories: respondents and non-respondents; and weight adjustment is applied to account for the non-respondent households (e.g. refusal, no contact, etc.).

Final survey weights

The final survey weights are constructed using regression estimation to calibrate to the known population counts at the national level population estimates (which are supplied by the Demography division) cross-classified by 5-year age groups, gender and race, and provincial population estimates by broad age groups. The 5-year age groups are: 0–4, 5–9, 10–14, etc., and 65 years and above. The provincial level age groups are: 0–14, 15–34, 35–64, and 65 years and over. The calibrated weights are constructed such that all persons in a household would have the same final weight.

Estimation

The final survey weights are used to obtain the estimates for various domains of interest, e.g. number of persons employed in agriculture in Western Cape, number of females employed in manufacturing, etc.

Reliability of the survey estimates

Since estimates are based on sample data, they differ from figures that would have been obtained from complete enumeration of the population using the same instrument. Results are subject to both sampling and non-sampling errors. Non-sampling errors include biases from inaccurate reporting, processing, and tabulation, etc., as well as errors from non-response and incomplete reporting. These types of errors cannot be measured readily. However, to some extent, non-sampling errors can be minimised through the procedures used for data collection, editing, quality control, and non-response adjustment. The variances of the survey estimates are used to measure sampling errors. The variance estimation methodology is discussed below.

(i) Variance estimation

The most commonly used methods for estimating variances of survey estimates from complex surveys such as the QLFS, are the Taylor-series Linearization, Jackknife Replication, Balanced Repeated Replication (BRR), and Bootstrap methods (Wolter, 2007)1. The Fay’s BRR method has been used for variance estimation in the QLFS because of its simplicity.

(ii) Coefficient of variation

It is more useful in many situations to assess the size of the standard error relative to the magnitude of the characteristic being measured (the standard error is defined as the square root of the variance). The

coefficient of variation provides such a measure. It is the ratio of the standard error of the survey

estimate to the value of the estimate itself expressed as a percentage. It is very useful in comparing the precision of several different survey estimates, where their sizes or scale differ from one another.

(iii) P-value of an estimate of change

The p-value corresponding to an estimate of change is the probability of observing a value larger than the particular observed value under the hypothesis that there is no real change. If p-value <0,01, the difference

1Wolter KM, 2007.Introduction to Variance Estimation, 2

ndEdition.New York: Springer-Verlag.

cv



is highly significant; if p-value is between 0,01 and 0,05, the difference is significant; and if p-value >0,05, the difference is not significant.

Statistics South Africa A -1 P0211.4

Appendix 2 - Definitions

Definitions

Economic activities are those that contribute to the production of goods and services in the country. There are two types of economic activities, namely: (1) Market production activities (work done for others and usually associated with pay or profit); and (2) Non-market production activities (work done for the benefit of the household, e.g. subsistence farming).

Employed persons are those aged 15–64 years who, during the reference week, did any work for at least one hour, or had a job or business but were not at work (temporarily absent).

Employment-to-population ratio (labour absorption rate) is the proportion of the working-age population that is employed.

Informal sector: The informal sector has the following two components:

i) Employees working in establishments that employ less than five employees, who do not deduct income tax from their salaries/wages; and

ii) Employers, own-account workers and persons helping unpaid in their household business who are not registered for either income tax or value-added tax.

The labour force comprises all persons who are employed plus all persons who are unemployed.

Labour force participation rate is the proportion of the working-age population that is either employed or unemployed.

Not economically active: Persons aged 15–64 years who are neither employed nor unemployed in the reference week.

Unemployed (strict/official) persons are those (aged 15–64 years) who:

a) Were not employed in the reference week and;

b) Actively looked for work or tried to start a business in the four weeks preceding the survey interview and;

c) Were available for work, i.e. would have been able to start work or a business in the reference week or;

d) Had not actively looked for work in the past four weeks but had a job or business to start at a definite date in the future and were available.

Unemployed (Expanded) persons are those (aged 15–64 years) who:

a) Were not employed in the reference week and;

b) Were available for work, i.e. would have been able to start work or a business in the reference week

Unemployment rate (strict/official) is the proportion of the labour force that is unemployed according to the strict/official definition.

Unemployment rate (expanded) is the proportion of the labour force that is unemployed according to the expanded definition.

The working-age population comprises all persons aged 15–64 years.

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