Does Trade Liberalisation Leave Women Behind in South Africa Presented by Margaret Chitiga-Mabugu,...

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Does Trade Liberalisation Leave Women Behind in South Africa

Presented by Margaret Chitiga-Mabugu, HSRC, EPD unit

J. Cockburn, B. Decaluwé, M .Chitiga-Mabugu, I. Fofana and R. Mabugu

Outline

Background and Motivation

Trade reform experiment and key findings

Policy implications

Background and Motivation

Background and motivation

Macroeconomic policy reforms (and their differentiated impacts on women and men) are of crucial importance to all countries

Macroeconomic policies and gender poverty and inequalities have become a growing concern in developing countries

Background and motivation

Women are more vulnerable to chronic poverty, because of gender inequalities in the distribution of income, access to productive inputs, asset management, and the labor market (World development reports 2000 and 2001)

That is why it is important to integrate household production and gender in the analysis of macroeconomic policies effects

Men Women Children

P0 P1 P2 P0 P1 P2 P0 P1 P2

South Africa 0.44 0.20 0.12 0.51 0.24 0.14 0.63 0.31 0.19

Urban area 0.35 0.15 0.08 0.42 0.18 0.10 0.52 0.23 0.13

Rural area 0.61 0.30 0.18 0.66 0.33 0.20 0.74 0.40 0.25

Male-headed 0.37 0.16 0.09 0.42 0.19 0.11 0.54 0.25 0.15

Female-headed 0.66 0.33 0.20 0.59 0.29 0.17 0.73 0.38 0.24

Black 0.52 0.24 0.14 0.60 0.29 0.17 0.69 0.35 0.21

Colored 0.31 0.12 0.06 0.35 0.14 0.08 0.43 0.18 0.09

Asian 0.06 0.02 0.01 0.03 0.01 0.00 0.12 0.04 0.02

White 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Unspecified 0.00 0.00 0.00 0.08 0.02 0.01 0.22 0.06 0.02

Poverty indexes by gender and age in 2000 IES

Background and motivation

0%

20%

40%

60%

80%

100%

Market w ork Domestic w ork Leisure

Female

Male

Gender Time Allocation in Year 2000

Background and motivation

Male-female Sectoral shares in wage income (%)

ratio Males Females

Health and social work 0.4 0.6 3.5

Textiles industry 0.9 0.8 2.5

Other activities and services 0.9 3.8 10.6

Hotels and restaurants 1.3 1.1 2.2

Financial intermediation 1.5 5.6 9.5

Real estate 1.6 1.7 2.9

Trade services 1.9 15.6 21.0

Business activities 2.0 3.7 4.7

Communications 2.5 3.4 3.6

Telecommunications 2.6 0.3 0.3

Other manufacturing 3.0 2.8 2.4

General government 3.2 24.3 19.9

Agriculture 3.2 2.8 2.3

Footwear 3.3 0.1 0.1

Distribution of male and female market work

Background and motivation

Distribution of male and female market work (continue)

Male-female Sectoral shares in wage income (percent)

ratio Males Females

Food industry 3.4 2.8 2.2

Electrical machinery 4.2 0.5 0.3

Petroleum 4.3 3.3 2.0

Transport services 4.8 6.3 3.4

Non-metallic mineral goods 4.9 0.7 0.4

Electricity 6.2 1.8 0.7

Water 6.3 0.2 0.1

Basic iron and steel 6.7 5.0 2.0

Transport equipment 6.7 1.8 0.7

Construction 6.7 4.4 1.7

Other mining industry 11.4 2.1 0.5

Coal industry 14.2 1.1 0.2

Gold industry 27.7 3.3 0.3

All 2.6 100.0 100.0

Background and motivation

Male Female

All population groups 24.8 28.0

Urban 24.1 28.6

Non urban 26.4 26.9

African 30.0 32.3

Urban 31.0 35.7

Non urban 28.6 27.9

Colored 21.1 22.8

Urban 23.9 23.7

Non urban 8.8 17.1

Asian 13.9 23.0

Urban 13.5 22.9

Non urban 31.4 30.1

White 5.6 7.8

Urban 5.7 8.0

Non urban 4.9 5.4

Unemployment rate (official definition) by race and gender (2001)

Background and motivation

Mean monthly income by gender (1999)

0

2000

4000

6000

8000

10000

12000

14000

Formal White Formal Urban(African)

Informal urban(African)

Informal non-urban(African)

Domestic (urban)(African)

Domestic (non-urban)(African)

Agricultural (formal)(African)

Agricultural ( informal)(African)

Men women

Background and motivation

Trade liberalization scenario and key findings

South Africa is member of World Trade Organization since 1995 and since 1969 participates to the Southern Africa Custom Union

South Africa has also a number of bilateral trade ties, mainly in the form of free trade areas (FTA). The European Union – South Africa FTA (agreed in 2000)

There are other planned FTAs with India, Brazil etc.

Trade liberalization scenario and key findings

Substantial reductions in the number of tariff lines and bands and maximum tariff rates

Tariff barrier constitute the principal protectionist measure in South Africa (Other policy measures against free trade are still in place)

Trade liberalization scenario and key findings

Simulation involves the complete elimination of all import tariffs

Trade liberalization scenario and key findings

Penalize the initially highly protected sectors

Favour the export-intensive and high input-used sectors

ResultsTrade and output effects

Trade liberalization scenario and key findings

Employment and wage effects

Strong gender bias against women with a decrease in their labor market participation, while men supply more labor in the market

Trade liberalization scenario and key findings

Employment and wage effects

Male workers derive substantially more labour income from the expanding sectors (export-oriented and high input used sectors)

Female workers are penalized by their greater participation in garments, as well as health and social work, the contracted sectors

Trade liberalization scenario and key findings

Increase the labour market participation of male workers, while female workers market activities fall

The existing gender bias against women in labour market participation increases

Time re-allocation effects

Trade liberalization scenario and key findings

Male workers increased their labour market participation and reduced their domestic work participation

The existing gender bias towards women performing domestic work accentuates

Trade liberalization scenario and key findings

Men continue to contribute more to household income

Reducing the bargaining power of women in their households

Income distribution effects

Trade liberalization scenario and key findings

Policy implications

Non uniform compensatory taxes that favour female intensive sectors and poor households would help to reduce gender inequalities

Complementary fiscal and non fiscal policies to reduce time burden on women through measures that save time or improve the productivity of time use (access to education, land, credit, information, help centres, and technology)

Policy implications

Thank you!