1. 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

2. Outline Background and Motivation Trade reform experiment and key findings Policy implications

3. Background and Motivation

4. 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

5. 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

6. MenWomenChildren P0P1P2P0P1P2P0P1P2 South Africa0.440.200.120.510.240.140.630.310.19 Urban area0.350.150.080.420.180.100.520.230.13 Rural area0.610.300.180.660.330.200.740.400.25 Male-headed0.370.160.090.420.190.110.540.250.15 Female-headed0.660.330.200.590.290.170.730.380.24 Black0.520.240.140.600.290.170.690.350.21 Colored0.310.120.060.350.140.080.430.180.09 Asian0.060.020.010.030.010.000.120.040.02 White0.00 Unspecified0.00 0.080.020.010.220.060.02 Poverty indexes by gender and age in 2000 IES Background and motivation

7. Gender Time Allocation in Year 2000 Background and motivation

8. Male-femaleSectoral shares in wage income (%) ratioMalesFemales Health and social work0.40.63.5 Textiles industry0.90.82.5 Other activities and services0.93.810.6 Hotels and restaurants1.31.12.2 Financial intermediation1.55.69.5 Real estate1.61.72.9 Trade services1.915.621.0 Business activities2.03.74.7 Communications2.53.43.6 Telecommunications2.60.3 Other manufacturing3.02.82.4 General government3.224.319.9 Agriculture3.22.82.3 Footwear3.30.1 Distribution of male and female market work Background and motivation

9. Distribution of male and female market work (continue) Male-femaleSectoral shares in wage income (percent) ratioMalesFemales Food industry3.42.82.2 Electrical machinery4.20.50.3 Petroleum4.33.32.0 Transport services4.86.33.4 Non-metallic mineral goods4.90.70.4 Electricity6.21.80.7 Water6.30.20.1 Basic iron and steel6.75.02.0 Transport equipment6.71.80.7 Construction6.74.41.7 Other mining industry11.42.10.5 Coal industry14.21.10.2 Gold industry27.73.30.3 All2.6100.0 Background and motivation

10. MaleFemale All population groups24.828.0 Urban24.128.6 Non urban26.426.9 African30.032.3 Urban31.035.7 Non urban28.627.9 Colored21.122.8 Urban23.923.7 Non urban8.817.1 Asian13.923.0 Urban13.522.9 Non urban31.430.1 White5.67.8 Urban5.78.0 Non urban4.95.4 Unemployment rate (official definition) by race and gender (2001) Background and motivation

11. Mean monthly income by gender (1999) Background and motivation

12. Trade liberalization scenario and key findings

13. 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

14. 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

15. Simulation involves the complete elimination of all import tariffs Trade liberalization scenario and key findings

16. Penalize the initially highly protected sectors Favour the export-intensive and high input-used sectors Results Trade and output effects Trade liberalization scenario and key findings

17. 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

18. 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

19. 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

20. 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

21. 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

22. Policy implications

23. 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

24. Thank you!