TRADE REFORM: Wage Inequality and Globalization 4


Nevertheless, there are a number of problems associated with estimating (4). Relative wages and value-added both determine and are determined by cost shares. In addition, we would like to know whether shares are changing because wages are responding to technology shocks, or employment levels, or both. Consequently, instead of estimating (4) we estimate a reduced form for both relative wages and relative employment levels separately as a function of both technology shocks and capital stock, the two variables in (4) which are pre-determined. This allows to identify the separate effects of technology shocks on both relative wages and relative employment. More info

Estimation Issues and Results

We have annual data on 2,354 manufacturing plants from the Secretariat of Trade and Industrial promotion (SECOFI) for 1984 through 1990. We proceed to examine the observable characteristics of these plants which are correlated with the relative wages and relative employment of skilled workers. We do so by regressing the log ratio of white-collar to blue-collar wages and the log ratio of white-collar to blue-collar employment on measures of (i) plant and industry export activity, (ii) plant and industry foreign-ownership status, (iii) trade protection, (iv) plant technology characteristics, and (v) characteristics of labor-market institutions observed at the plant level.

Levels regressions include dummy variables for the year, region, and two-digit industry. The sample is all plants for which we a complete set of observations on the variables described below. All regressions are weighted by the plant share of total employment and corrected for arbitrary heteroskedasticity.

Appendix Table A.1 lists the variables included in the analysis and gives variable definitions. The SECOFI sample classifies workers in two categories: obreros, who are equivalent to blue-collar workers, and empleados, who are equivalent to white-collar workers.

The activities of blue-collar workers include machine operation, production supervision, repair, maintenance, and cleaning; those of white-collar workers include management, product development, administration, and general office tasks. We identify white-collar workers as skilled labor and blue-collar workers as unskilled labor. We measure earnings as the average annual salary for each type of worker in a given plant.

Industry variables are defined at the four-digit level and measured excluding the plant on which the observation is taken. Variables that capture export orientation and foreign ownership status are the share of exports in total sales at the industry level, the share of industry employment in foreign-owned plants, a dummy variable that indicates whether a plant has positive exports, and a dummy variable that indicates whether a plant is foreign owned. We also include the industry average tariff rate, the average share of industry production that is covered by import licenses, and the product of the tariff rate and the import-license coverage rate.

Variables that capture technological change — either disembodied or embodied in capital goods — are the plant share of imported machinery in total machinery purchases, the plant share of imported materials in total material purchases, the plant shares of total equipment purchases and transportation equipment purchases in total investment, lagged plant total factor productivity, and royalty payments for patents, and copyrights or trademarks as a share of total plant sales. We also include dummy variables for the plant employment-size category and dummy variables for the plant capital-labor ratio by quintile.

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