Efficiency wage and union effects in labor demand and wage structure in Mexico

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Efficiency wage and union effects in labor demand and wage structure in Mexico - An application of quantile analysis, Volume 1

Author:	Maloney, William F.; Pontual Ribeiro, Eduardo;	Collection Title:	Policy, Research working paper ; no. WPS 2131
Country:	Mexico;	Date Stored:	1999/09/14
Document Date:	1999/05/31	Document Type:	Policy Research Working Paper
Language:	English	Major Sector:	(Historic)Social Protection
Region:	Latin America & Caribbean	Report Number:	WPS2131
Sub Sectors:	Labor Markets & Employment	SubTopics:	Environmental Economics & Policies; Economic Theory & Research; Banks & Banking Reform; Labor Management and Relations; Health Monitoring & Evaluation; Labor Policies; Public Health Promotion
Volume No:	1

Summary: Applying quantile analysis to detailed firm-level data from Mexico, the authors study determinants of demand and wages for two classes of labor. Unions appear to have a strong impact on how much unskilled labor is employed but not on wages. This suggests an extreme example of "monopoly union" behavior. The impact on productivity is, by definition, negative, but unions could also be said to be forcing firms to use "appropriate technology" (less capital and more workers), increasing the total amount of labor employed in the economy. The only impact on wages appears for the tenth (lowest) quantile of unskilled workers, suggesting that unions prevent workers from being paid too far below the median for their skill level. The authors identify significant efficiency wage effects where firms pay above market clearing to prevent labor turnover both in labor demand and in the wage equations. Since minimum wages are not binding and the union impact on wages is small, this suggests that whatever segmentation exists emerges endogenously and is not due to union - or government - induced distortions. The authors offer the first use of quantile analysis to analyze labor demand at the firm level, and one of the first uses of correct standard errors in two-stage least-squares quantile regression.


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