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Published on October 29, 2007

Author: Columbia

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Slide1:  WAGE INEQUALITY AND TRADE LIBERALIZATION IN MPs: EVIDENCE FOR MOROCCO by Silvia Muzi INTERNATIONAL CONFERENCE “Bridging the gap: the role of trade and FDI in the Mediterranean” Naples, 8 June 2006   Slide2:  Trade liberalization and wages: related theoretical and empirical literature Relevance of extending the analysis to the MPs: evidence for Morocco Objectives of the empirical analysis Empirical framework and empirical results Conclusions S. Muzi - University of Rome “La Sapienza” and IPALMO Structure of the Presentation… Slide3:  The analytical framework for the analysis is offered by the emerging literature on the role of inter-industry wage premiums (Dickens and Katz, 1987; Krueger and Summers, 1988; Katz et al., 1989) Industry wage premiums are defined as the portion of individual wages that cannot be explained by worker, firm, or job characteristics, but can only be explained by the worker’s industry affiliation (Krueger and Summers, 1988) The role of wage premiums seems to be particularly relevant in predicting the impact of trade reforms in short and medium-run models of trade and in trade models with imperfect competition Literature on trade liberalization and productivity is also relevant. There is also strong evidence that reduction in trade protection results in productivity improvement (Roberts and Tybout, 1997). Changes in productivity might, then, impact on the labor market Trade liberalization and wages: the theoretical literature S. Muzi - University of Rome “La Sapienza” and IPALMO Slide4:  The relationship between industry wage premiums and trade liberalization has been firstly analyzed by Gaston e Trefler (1997) in the specific case of United States The analysis has then been extended to developing countries with a focus on the Latin American experience. Pavcnik et al. (2004) studied the case of Brazil; Feliciano (2001) the Mexican experience; Goldberg e Pavcnik (2005) the effects of the Colombian trade liberalization At present, the focus is moving towards other geographical regions: Asia (Mishra e Kumar, 2005 for India) and Eastern Europe (Goh e Javorcik, 2005 for Poland) The evidence emerging from these empirical investigations is mixed. Trade liberalization and wages: the empirical literature S. Muzi - University of Rome “La Sapienza” and IPALMO Slide5:  Trade liberalization and wages: related theoretical and empirical literature Relevance of extending the analysis to the MPs: evidence for Morocco Objectives of the empirical analysis Empirical framework and empirical results Conclusions S. Muzi - University of Rome “La Sapienza” and IPALMO Structure of the Presentation… Why MPs? …:  Why MPs? … S. Muzi - University of Rome “La Sapienza” and IPALMO Labor market related issues are crucial for MPs that need to increase employment amongst an active population growing really fast (35 million of new jobs have to be created in the MPs, between 2000 and 2015, in order to maintain unemployment at current levels) Within this context the EU-Med FTA is a relevant tool to support Southern Mediterranean countries in dealing with this challenge as well as with other very important ones such as the need of: shifting from public sector dominated to private-sector driven economy; moving from a closed and passive international role to a more open and active one; overcoming an international specialization model volatile and dominated by oil or by a low degree of diversification to more stable and diversified one Why Morocco?...:  Why Morocco?... S. Muzi - University of Rome “La Sapienza” and IPALMO During the ’90s Morocco not only strongly confirmed the process of trade liberalization started in the previous decade but was also characterized by an impressing magnitude in the degree of tariffs reduction (Femise, 2005) Morocco is, with Tunisia, the most advanced country in the implementation of the Euro-Mediterranean Agreement. It is also a country with little natural resources and a big and increasing labor force Stylized Facts: a quick picture of Moroccan trade liberalization during the ’90s:  Stylized Facts: a quick picture of Moroccan trade liberalization during the ’90s S. Muzi - University of Rome “La Sapienza” and IPALMO Stylized Facts: a quick picture of Moroccan trade liberalization during the ’90s:  Stylized Facts: a quick picture of Moroccan trade liberalization during the ’90s S. Muzi - University of Rome “La Sapienza” and IPALMO Slide10:  Trade liberalization and wages: related theoretical and empirical literature Relevance of extending the analysis to the MPs: evidence for Morocco Objectives of the empirical analysis Empirical framework and results Conclusions S. Muzi - University of Rome “La Sapienza” and IPALMO Structure of the Presentation… Objectives of the analysis :  Objectives of the analysis S. Muzi - University of Rome “La Sapienza” and IPALMO Analyzing the structure and evolution of wages in Morocco before and after the process of trade liberalization implemented during the ‘90s Inequality analysis focused on the overall distribution as well as on specific sub-groups of the population (male/female workers; educational or industry related groups) Investigating the relationship between trade liberalization and changes in wage structure Focus on the role of industry affiliation and on the specific impact of trade liberalization on unskilled workers’ wages Slide12:  Trade liberalization and wages: related theoretical and empirical literature Relevance of extending the analysis to the MPs: evidence for Morocco Objectives of the empirical analysis Empirical framework and empirical results Conclusions S. Muzi - University of Rome “La Sapienza” and IPALMO Structure of the Presentation… DATA :  DATA S. Muzi - University of Rome “La Sapienza” and IPALMO WAGES The analysis is based on two Living Standards Measurement Study (LSMS) household surveys conducted by the Moroccan Direction of Statistics in 1990/91 and 1998/99. The 1990/1991 survey provides data for a sample of over 3,000 households and about 20,000 individuals, while the sample for 1998/1999 survey is of more than 5,000 households and 30,000 individuals. The individual-level sample used has been restricted to those male and woman in wage employment and aged between 15 and 70 years old. The sample was, therefore, restricted to about 1.700 and 3.900 individuals, respectively, in 1990/1991 and 1998/1999 The wage distribution has, then, been trimmed by 0.1% at the top and bottom tails DATA :  DATA S. Muzi - University of Rome “La Sapienza” and IPALMO TRADE Data on international trade are from the United Nations Commodity Trade Statistics Database (UN-COMTRADE) For matching data on trade with data from the LSMS, the ISIC rev2 classification at the 2 digit desegregation level has been considered Data on tariffs are from UNCTAD-TRAINS (Trade Analysis and Information System), a comprehensive computerized information system covering tariff, para-tariff and non-tariff measures as well as import flows by origin for more than 140 countries. Slide15:  The dynamic of wage distribution has been analyzed using a number of inequality measures which differ in their sensitivity to wage differences in different parts of wage distribution. They include: percentile ratios, the Gini coefficient, three Generalized Entropy measures (the mean log deviation (MLD), the Theil index and half the squared coefficient of variation) Inequality analysis: the empirical framework S. Muzi - University of Rome “La Sapienza” and IPALMO Slide16:  Inequality: empirical results…. S. Muzi - University of Rome “La Sapienza” and IPALMO - Kernel density plot for wages 1990/1991 and 1998/1999 Slide17:  Inequality: empirical results Slide18:  …Inequality: empirical results Slide19:  Trade and wages: methodology S. Muzi - University of Rome “La Sapienza” and IPALMO The impact of trade liberalization on wages has been assessed by applying a two stage model by verifying the findings of this model throughout the estimation of a pooled equation Two stage model First stage. Estimation of two separate Augmented Mincerian wage equations. The specification is the following: Second stage. The coefficient on the industry dummy (wpj) are pooled and regressed on tariffs and other trade-related variables. The following WLS regression model has been estimated Slide20:  Trade and wages: methodology S. Muzi - University of Rome “La Sapienza” and IPALMO Pooled equation model The small size of the sample available in the second stage of the analysis ask for checking the robustness of the results of the analysis A reduced form model for all the individuals of age 15-70, employed in the manufacturing and electricity sectors has been estimated by pooling all workers from the 1990/1991 and 1998/1999 LSMS. The specification is the following: Slide21:  Trade and wages: empirical results Two stage model Slide22:  Trade and wages: empirical results Wage premiums and tariffs reduction Slide23:  Trade and wages: empirical results Slide24:  Trade and wages: empirical results Pooled equation model Slide25:  Conclusions… The paper offered a contribution to the analysis on the effect of trade liberalization on MPs focusing on the impact of Moroccan trade reforms on wages It showed a decrease in wage inequality during the ’90 both for the overall distribution and for the sub-groups of male and female. Despite this common trend, wage dispersion is still higher for women at work compared to men The major proportion of wage inequality is accounted for by inequality among individuals within the educational groups as well as by inequality among individuals within the industry groups. The relevance of the within-group inequality increased during the decade Between 1990/1991 and 1998/1999 wage premiums changed widely (increase and less dispersion). The relationship between industry wage premiums and tariffs is negative and statistically significant. This suggests that a reduction in tariffs is associated with an increase in wage premiums The negative and statically significant relationship is confirmed also in the specific case of unskilled labor S. Muzi - University of Rome “La Sapienza” and IPALMO Slide26:  Thanks! Acknowledgments University of Rome “La Sapienza”; Moroccan Direction of Statistics

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