On Trade Policy and Wages Inequality in Egypt: Evidence from Microeconomic Data

Transcription

1 On Trade Policy and Wages Inequality in Egypt: Evidence from Microeconomic Data Population Council March, 2010

2 Motivation Egypt has undertaken numerous policies that affected trade and in turn, labor market. High cost of red tape barriers and non-tariff barriers despite a significant liberalization. Persistent inequalities on geographic, qualification and gender levels are observed on the Egyptian labor market. Empirical literature (Gaston and Trefler (1994) for USA, Attanasio et al (2004) for Columbia and Said and El Azawi (2009) for Egypt) has shed the light on the impact of tariffs on wages. NTB as well as red tape barriers have never been taken into account.

3 Contribution What I do?: 1 I estimate a wage equation taking into account individual characteristics (age, education, parental background, etc.). 2 I determine the impact of different trade policy variables (tariffs, NTB and red tape costs) on wage inequality, on wage premium and on employment. What I found?: 1 Tariffs have a lower negative effect than NTBs and administrative barriers on wages. 2 Skilled and urban workers as well as females are more affected by such impediments.

4 1 Stylized Facts 2 Theory 3 Methodology 4 Results 5 Conclusion

5 Tariff Barriers in Egypt

6 Non Tariff Barriers in Egypt

7 Administrative Barriers to Trade in Egypt Table: Export procedures in Egypt, 2007 Nature of Export Duration US$ Cost Procedures (days) Documents preparation Inland transportation and handling Customs clearance and technical control 1 10 Ports and terminal handling 3 50 Totals: 20 1,014 Table: Import procedures in Egypt, 2007 Nature of Import Procedures Duration (days) US$ Cost Documents preparation Customs clearance and technical control 2 10 Ports and terminal handling Inland transportation and handling Totals: 25 1,049

8 Inequality in Egypt General: The income share held by the lowest 10% of the population is 3.7% and the one held by the lowest 20% is 9%. Those figures are much higher for the highest 20% and 10% (44% and 30% respectively) Gender: El Hamidi (2008) has also shown that, during trade liberalization periods, tradable sectors experienced higher levels of wage differences between men and women than non-tradable ones. Regional: Said (2007) has shown that living outside greater Cairo is associated with a wage disadvantage for all sector and gender groups. Urban and rural low-egypt areas still suffer from the greatest disadvantage.

9 Theory Classic trade theory (HOS and Stolper-Samuelson, 1934): wages increase more than proportionally than prices of the products (having a comparative advantage). Sector Specific model (Viner, 1951): workers in exporting sectors earn higher wages than importing ones New trade theory: More productive firms (Melitz, 2003) higher wages. The nearer firms are from their markets or their suppliers (Redding and Venables, 2004) higher wages.

10 Estimation The wage Log(w igs ) of individual i living in region g and working in sector s are regressed on individual characteristics, (education attainment, age, marital status, household size) and other dummies capturing some specific individual f i, industries wp s and regional f g characteristics: Log(w igs ) = α i + β i.x i + α is wp s + γ 1 Tar s + γ 2 NTM s +γ 3 TimM s + γ 4 TimX s + ε igs (1) Industry wage premia wp s are obtained by filtering out the effects of observable worker characteristics: (wp s ) = η s + η 1 Tar s + η 2 NTM s +η 3 TimM s + η 4 TimX s + ɛ s (2)

11 Data Micro: Macro: All individuals aged between 15 and , 072 individuals, 50% males and 50% females. Only those who are working in manufacturing sector are taken into account (almost 9% of the sample). 1, 176 individuals working in 20 sectors. Tariffs are taken from the Egyptian Ministry of Trade and Industry. Trade and Production for Non Tariff Barriers. AVEs of administrative barriers (bureaucracy, corruption, Internet widespread, etc.) are taken from Zaki (2009)

12 Wage Equation by Gender 2006 Males Females Ln (Hr. Wage) Ln (Hr. Wage) Tariff *** ( ) ( ) Non Tariff 0.118** (0.0544) (0.374) AVE Time Exp ** ( ) (0.0192) AVE Time Imp *** ( ) ( ) Industry dummies YES YES Observations R-squared

13 Wage Equation by Skill 2006 Unskilled Skilled Ln (Hr. Wage) Ln (Hr. Wage) Tariff ** ( ) ( ) Non Tariff *** *** (0.0823) (0.0917) AVE Time Exp *** ( ) ( ) AVE Time Imp *** *** ( ) ( ) Industry dummies YES YES Observations R-squared

14 Wage Equation by Region 2006 Urban Rural Ln (Hr. Wage) Ln (Hr. Wage) Tariff *** *** ( ) ( ) Non Tariff *** (0.0323) (0.206) AVE Time Exp *** ( ) ( ) AVE Time Imp *** ( ) ( ) Industry dummies YES YES Observations R-squared

15 Wage Premium 2006 Wage Premium Tariff *** ( ) Time to Imp ( ) Time to Exp * (0.0103) Non Tariff * (0.174) Share of females (0.712) Constant 1.300*** (0.198) Observations 20 R-squared 0.941

16 Trade and Employment 2006 Total Rural Urban Males Females Unskilled Skilled Tariff * ( ) ( ) ( ) ( ) ( ) ( ) ( ) Time Imp ( ) ( ) ( ) ( ) ( ) ( ) ( ) Time Exp * * ** * ( ) ( ) ( ) ( ) ( ) ( ) ( ) Non-Tar 0.117** 0.124* 0.113*** * 0.249*** 0.111** 0.135*** (0.0420) (0.0597) (0.0375) (0.0473) (0.0566) (0.0461) (0.0420) Constant * * * ** (0.0272) (0.0387) (0.0243) (0.0307) (0.0367) (0.0299) (0.0272) Observations R-squared

17 Conclusion Policy implication: To protect unskilled workers, education policy should be established to reduce this skill premium. Egypt still needs further improvement in border-related procedures and in eliminating non-tariff barriers. Further Research Apply the same analysis for services and agriculture Effect of trade policy on the informal sector Make use of the panel dimension

18 THANK YOU FOR YOUR ATTENTION