The Impacts of Trade on Gender: What Have We Learned and What Tools Are Used

1. The Impacts of Trade on Gender: What Have We Learned and What Tools Are Used?  Mohamed Abdelbasset CHEMINGUI Trade, Finances and Economic Development Division, UN-ECA

2. Context Gender economics is attaining increased prominence in the debates over development policy. There is a growing body of evidence and experience linking gender awareness in policies to equitable, efficient, and sustainable outcome in development. However these links are still not widely understood nor have these lessons been fully integrated by national policymakers. The assumption that open markets will lead to higher growth that benefit all members of a country is no more fully shared by economists. Many recent studies show that trade liberalization has lead to increase in subcontracting of women, a decrease in the prices of agricultural products produced by women, and a masculinisation of typically female employment

3. Impacts of Trade on Gender: What Have We Learned? The neoclassical theory supports a positive correlation between openness to trade on one side and employment and wages on the other side. The reasoning is as follows: trade liberalization, often embodied in the expansion of exports, stimulates growth. This creates a demand for greater workload, and given the law of supply and demand, this must be accompanied by an increase in real wages. Some studies put in doubt these outcomes by showing that increased trade openness in developing economies may have negative effects on both employment and real wages. Other studies admit that in best cases trade liberalization policy can be without effects on employment and real wages in developing economies.

4. Impacts of Trade on Gender: What Have We Learned?(Cont.) Trade liberalization influences the employment, wages, consumption prices, incomes and government expenditures. Tariff reduction may restrict the short-term ability of government to finance social programs, leading to cuts in services and privatization. Through these channels, trade has an incidence on men-women inequalities. Comparatively to men, women profit less from the new economic opportunities and their adaptation process is more difficult because they have less time and mobility with regards to their domestic tasks.

5. Impacts of Trade on Gender: What Have We Learned?(Cont.) Moreover, trade policies affect men and women differently due to gender inequalities in access to and control of economic and social resources and decision-making. Their impact is also mediated by the different roles that men and women have within societies – in particular, the gendered division of labor. Thus, trade liberalization may be positive or negative for women and men, depending on their individual (e.g. education and skills…) and social group characteristics (e.g. net producers or net consumers, urban/rural…). However, there is an agreement among economists that trade liberalization is likely to increase the employment opportunities for women particularly in export oriented sectors such as textiles.

6. Impacts of Trade on Gender: What Have We Learned?(Cont.) Trade liberalization can also lead to unemployment and the restructuring of the labor markets. This situation can affect more severely poor and marginalized groups of women more than men. The need for flexible workers to respond to market fluctuations can lead to a rise in the numbers of informal sector workers, of which a high percentage are women. Overall, the empirical studies distinguish the impacts of trade liberalization on gender employment gaps from gender wage gaps. In the next slides, the main results of some empirical analysis on the effects of trade liberalization on employment and wage gaps are highlighted.

7. Impacts of Trade on Gender: What Have We Learned on the effect on gender wage gap? Artecona and Cunningham (2002) found that trade liberalization is associated with higher gender wage gaps in the Mexican manufacturing sector. This is likely due to an increased premium to men’s higher skills while the discrimination component of wage differentials seems to fall with the increase in international competition. These results are confirmed by Gordon and Harrison (1999) for their analysis of a sample of developing countries. In particular, they found that in the industries that were forced to become competitive due to trade liberalization, the gender wage gap fell.

8. Impacts of Trade on Gender: What Have We Learned on the effect on gender wage gap? (Cont.) Becker (1971) already pointed out that competitive firms do not have the profits to wage discrimination. Black and Brainerd (2002) used data to test whether increased openness in the period 1977-94 induced employers to reduce discrimination against women, by estimating the differential effect of increased imports on concentrated versus competitive industries. Berik et al. (2003) found the opposite effect for the republic of Korea and Taiwan, in the sense that an increase in international competitiveness between 1980 and 1999 in concentrated industries was associated with a wide gender wage gap.

9. Impacts of Trade on Gender: What Have We Learned on the effect on gender employment gap? Women also experience more churning that is, more frequent hiring, firing, and relocation from one job to another (World Bank, 2004). A study on Chile by Levinshon (1999) covering a period of rapid adjustment, including trade liberalization, shows that firms tend to lay off a slightly higher proportion of female workers when business declines and to hire more women when business recovers. These results are confirmed by the study on Turkey (Ozler, 2001), which founds that female employees also had significantly higher job relocation rates.

10. The needs for in depth analysis of the impact of trade agreements on gender Despite the different obtained results, studies on trade and gender revealed that trade has different impact on different group of population, thus making a gendered analysis of international trade policy a priority (UNCTAD, 2003). These mixed results indicate that the effect of trade liberalization on women depends on the diversification level of the concerned countries, the liberalization process itself, initial conditions in terms of economic policies, and the structure of labor markets. Thus, the impacts of trade on women’s or men’s or even across industries within a country should be made on a case-by-case level.

11. Measuring the Impact of Trade on Gender: Which Tools? In Africa, there are various levels of advancements in trade liberalization. Some countries are already embarked in trade reforms since the adoption of structural adjustment programs in the middle of the 80s while some others still negotiating major trade agreements. Two alternative approaches are usually used in measuring the impact of trade on gender: the ex-post and ex-ante analysis. For countries already advanced in trade openess, the purpose could be to identify whether or not there is change in the structure of employment and wage by gender as result of trade liberalization. If yes, are these changes attributed to trade liberalization? For those countries, not yet opened, the objective is quite different. It consists to evaluate the effects of trade liberalization scenarios on employment and wage by gender.

12. What we means by Trade Reforms Here we are considering formal trade and not-informal trade. Formal trade is directly impacted by trade agreements while informal trade is out of the control of most of governments Informal trade such as cross-border trade is not governed by trade agreements and none by domestic economic policies. The purpose is to measure or evaluate the impact of trade agreements on a given economy with special focus on gender issues

13. What Kind of Trade Agreements? Globalization: agreements under the GATT/WTO Accession to WTO, WTO’s agreement (Uruguay Round, Doha Round) Sectoral coverage of the WTO’s agreements (agriculture, NAMA, service…) 2. Regional trade agreements Customs unions: RECs FTA’s: Agadir, EU-ACP, etc. Preferential access: Cotonou, AGOA,et 3. Reforms in Developed Countries: Reform of CAP or OECD agricultural policies and its impact on African countries 4. National Trade Reforms Reform of NTBs and TBTs Custom valuation, etc…

14. What tools should be used? Ex-post analysis: specific indicators and econometric estimations Ex-Ante analysis: simulations models Forecasting Analysis: econometric models

15. Models Simulation models. Goal is to simulate “how” the economy works. Inherently a structural model. Use for “counterfactual” analysis. Forecasting models. Goal is to forecast endogenous variables, given projections of exogenous variables. Less interested in “how” the economy works. May use either a reduced-form or structural model. Need not be able to identify the structural model.

16. Simulation models If interested to one sector of the economy: a sectoral partial equilibrium model is the more appropriate If interested to few sectors with a small effects on the national economy: a multi-market partial equilibrium model is the more appropriate If interested to the whole economy with the feedback and interaction effects: a computable general equilibrium model is the best tool

17. CGE models: General Features CGE models: Computable ? solvable numerically General ? economy-wide Equilibrium ? optimizing agents have found their best solutions subject to their budget constraints quantities demanded = quantities supplied in factor and commodity markets macroeconomic balance Dynamic-recursive ? the solution in any time period depend on current and past periods, not the future.

18. CGE models Actors: producers, consumers, government, rest of the world Motivation: profit maximization, utility maximization Institutions and signals: competitive markets and prices Agent constraints: technology, endowments (budget constraints) System constraints: Resources (land, labor, capital), Macro (trade balance) Equilibrium conditions: Supply-demand balance in all markets Macro balances (trade balance, savings-investment, government

20. Basic Structure of a CGE Model Standard CGE models are made up of two different parts: The social accounting matrix + other data The equations The social accounting matrix (SAM): Generalizes the input-output principle to all transactions in the economy The equations Specification of agent behavior Equilibrium in all markets for goods and factors Macroeconomic constraints

21. SAM Structure

22. Construction and Calibration of a CGE Model Model solution: uses of specific algorithm Calibration : equivalent to a “backward” solution of the model in order to determine the set of parameter values consistent with the initial structure of the economy. Simulations: Evaluate the specific effect of changing an exogenous variable on the economy: Example of simulation with a special focus on gender: The database and the model should includes males and females in the labor market by skill or areas and sector of occupation. It can also includes many types of households according the gender of the head. Removing tariff barriers on imports from the European Union over a period of 10 years (example of EPA agreement): Model’s results: changes in sectoral GDP and trade, consumption by household type and product, government revenue, sectoral wage and employment, wage and employment by labor type, welfare by household’s type…

23. Ex-ante analysis: the case of Kenya (work in progress) The methodology is based on a CGE model with detailed treatment of labor market, manufacturing and agricultural productions, government fiscal policy, and income distribution. Labor market is being disaggregated into female and male, paid and non-paid, and skilled and unskilled. The model will distinguish the following 8 labor categories: skilled paid male, skilled unpaid male, unskilled paid male, unskilled unpaid male, skilled paid female, skilled unpaid female, unskilled paid female, and unskilled unpaid female.

24. Ex-ante analysis: the case of Kenya (cont.) The model is a recursive dynamic CGE model built on a base SAM for the year 2003. The SAM will includes 8 labor categories, 40 household types classified by quintile, gender and areas, two trade partners (European Union and the Rest of the World), and government fiscal policies. The model will provide a simulation laboratory for doing controlled experiments - changing trade policies and other exogenous conditions such as government taxes, and measuring the impact of these changes on the structure of production and trade, and distribution of income among households. Simulation results will provide policy makers guidelines for long term planning.

25. Ex-ante analysis: the case of Kenya (cont.) The trade policies to be analyzed include, the conclusion of the Free Trade Agreement with the European Union. The nature of the simulations will be based on those identified in the World Bank’s document (2004). Complementary policies compensating losers from trade liberalization will also be simulated.

26. Ex-post analysis: the Tunisian case study (work in progress) Tunisia started its economic reform with the application of the structural adjustment program since 1986. The conclusion of the Uruguay agreement in 1995 represented the most important step of trade liberalization in Tunisia where Non-tariff barriers are removed and tariff rates are bound. The partnership agreement signed with the European Union and implemented over a twelve years period (1996-2008) represents another major change in the Tunisian trade policy. Currently, almost all industrial products imported from Europe are duty free. Since 1996, many other preferential trade agreements are signed and being implemented by Tunisia (EFTA, GAFTA, AGADIR…)

27. Ex-post analysis: the Tunisian case study (cont.) The first step in assessing the effects of trade liberalization on gender in Tunisia consists of calculating some relevant indicators such as: 1.trends in the share of female workers to total labor force in the economy, 2. share of female to total workers in some key sectors, 3. average female-wage by type compared to male… The estimation of these indicators should covers both the pre-trade phase (1985-1995) and the post-trade phase (1996-2008) If some changes are observed between the two periods in term of employment and wage by gender, the second step in assessing the role of trade liberalization in these changes should be carried out: the econometric analysis.

28. Ex-post analysis: the Tunisian case study (cont.) Two steps form the econometric analysis in order to identify whether or not conditional gender wage gaps changed as Tunisia opened its economy to international competition. In the first step, a Mincer earnings equation will be estimated to explain the log wages of men and women and the residuals are preserved. The difference between the average male and female residual log wages in each economic activity in the sample is calculated, thereby omitting observable productivity characteristics..

29. Ex-post analysis: the Tunisian case study (cont.) In the second step, this residual will be used as the dependent variable in an OLS equation that controls for changes over time, industry concentration, and exposure to trade openness. For employment gap, the same approach will be followed with employment gap as dependent variable in an OLS equation. Finally, the two estimated OLS equations will be used to make forecasts on the expected changes in gender employment and wage as result of more integration of Tunisia in the word economy in the form of a potential conclusion of Doha Round and a deeper integration with the European Union in the forms of free trade of agricultural and services