Wage determination in Northeast Brazil
The author analyzes the labor markets in the Northeast region of Brazil that includes Pernambuco, Bahia, and Ceará states. Her findings show a rather heterogeneous impact pattern of individual characteristics on monthly wages across the wage distribution. That is, the magnitude of the effect of a wage determinant is different depending on whether the worker is placed in the lower, median, or top of the wage distribution. The findings reveal that basic schooling matters for all four geographical areas and across the income distribution. However, poor workers are awarded lower returns than their richer peers, and in Bahia and Ceará, the poor do not obtain any returns to basic schooling. Furthermore, the impact of 5-8 or 9-11 years of education is larger than that of 1-4 years of completed education. The returns obtained by a median worker are higher in Ceará and Pernambuco than in Bahia. Finally, completed tertiary education offers the largest returns of all levels of education. The median worker receives a premium of 105, 249, and 216 percent in Ceará, Pernambuco, and Bahia, respectively. Hence, one direct policy implication is to increase the quality of education, in particular in poorer neighborhoods. Experience impacts positively on wages and it increases with age until workers reach 50 years of age. However, returns to experience are falling significantly across the wage distribution. For the poor and younger generations, experience contributes more to wages than education. The occupation of workers is important for wage determination. All workers in the included occupational groups are paid more than workers engaged in agricultural activities. Workers employed as technicians or administrators obtain the highest returns. The white/nonwhite wage disparity reveals that white workers are paid 17 percent more than their nonwhite co-workers, takinginto account other characteristics. Gender disparities are large in the Northeast and heterogeneous across the wage distribution. The time spent in the current state impacts adversely on wages. That is, those that have stayed earn, on average, less than the newcomers. There are no considerable differences between male and female workers. Union membership has a positive impact on workers'wages.
|Date of creation:||01 Mar 2005|
|Date of revision:|
|Contact details of provider:|| Postal: 1818 H Street, N.W., Washington, DC 20433|
Phone: (202) 477-1234
Web page: http://www.worldbank.org/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Verner, Dorte, 1999. "Are wages and productivity in Zimbabwe affected by human capital investment and international trade?," Policy Research Working Paper Series 2101, The World Bank.
- Juhn, Chinhui & Murphy, Kevin M & Pierce, Brooks, 1993. "Wage Inequality and the Rise in Returns to Skill," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 410-42, June.
- Maloney, William F. & Pontual Ribeiro, Eduardo, 1999. "Efficiency wage and union effects in labor demand and wage structure in Mexico - An application of quantile analysis," Policy Research Working Paper Series 2131, The World Bank.
- Verner, Dorte, 1999. "Wage and productivity gaps - evidence from Ghana," Policy Research Working Paper Series 2168, The World Bank.
- Rama,Martin G., 1998. "Wage misalignment in CFA countries: are labor market policies to blame?," Policy Research Working Paper Series 1873, The World Bank.
- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
- Levy, Frank & Murnane, Richard J, 1992. "U.S. Earnings Levels and Earnings Inequality: A Review of Recent Trends and Proposed Explanations," Journal of Economic Literature, American Economic Association, vol. 30(3), pages 1333-81, September.
- Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
When requesting a correction, please mention this item's handle: RePEc:wbk:wbrwps:3548. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Roula I. Yazigi)
If references are entirely missing, you can add them using this form.