assignment3_solution

# Assignment3_solution - University of California Santa Barbara Department of Economics Olivier Deschenes Winter 2011 Economics 140B Individual

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University of California, Santa Barbara Olivier Deschenes Department of Economics Winter 2011 Economics 140B Individual Assignment 3: Answer Key Due in class 02/15/11 Question 1: The standard model for estimating the return to education is the log-linear wage equation: i i i i i u EXP EXP ED y 2 2 1 1 0 ) 1 (   Where y i is the log hourly wage of worker i , ED i is years of education, and EXP i is the labor market experience (measured in years). This equation is often called the “Mincer equation” in honor of the labor economist Jacob Mincer, who pioneered its usage. Since actual labor market experience is rarely measured in data sets, labor economists proxy it with “years of potential labor market experience” (defined as age-education-6). While potential experience is an error- ridden measure of true labor market experience, we will ignore this issue in this exercise. The parameter of central interest is β 1 , which is interpreted as the “return to education” (since it measures the percent increase in hourly wages associated with an additional year of education). Note that we typically include other variables in the Mincer equation (e.g. sex, race, marital status, etc.). A major concern in the estimation of equation (1) is the presence of omitted variables that are correlated with both education and wages. Labor economists often refer to such omitted variables as “ability”, and the resulting bias in the OLS estimates as the “ability bias” In this exercise, you will investigate different approaches to resolve the ability bias problem, using two different data sets. The description and questions related to the first data set follow immediately in “Part I”, while the description and questions related to the second data set are in “Part II” at the end. PART I The first approach is to include “proxy” measures of ability directly in the wage equation and to make use of panel data on wages and education of workers, and use fixed effect and random effect models to account for unobserved ability. The file “nlsy.dta” contains data on 1410 young white workers during their first five years in the labor market (these are not the same years for every worker). The data were compiled from the National Longitudinal Survey of Youth (NLSY) that we discussed in class. There are 5 observations on each worker (denoted by the variable “id”) observed over the years 1980-1991. The key variables for the analysis are: log hourly wages (lnwage), years of education (educ), age (age), marital status (married), and union coverage (ucov). In addition, the NLSY contains a measure of “ability”, derived from the worker’s score on the Armed Forces Qualifying Test (AFQT). The AFQT is the average of four scores from the Armed Forces Vocational Aptitude Battery (AFVAB), which is designed to summarize aptitude and ability along various dimensions. It is not a measure of IQ.

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(A) Estimate the wage regression using OLS, and including potential experience, potential
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## This note was uploaded on 09/04/2011 for the course ECON 140b taught by Professor Staff during the Winter '08 term at UCSB.

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Assignment3_solution - University of California Santa Barbara Department of Economics Olivier Deschenes Winter 2011 Economics 140B Individual

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