The basic model is: Inw; = 81 + Baxo; + -+ + Brxri + ac; + &4, where Inw; is natural logarithm of wage and ; is a dummy variable equal to one if the worker uses the computer at work and equal to zero otherwise. We focus on the October 1989 results in Table II (columns 4 to 6). When determining the number of parameters in each model, also look at the footnote to the table. (a) Give the formula for the equation estimated in column (4) of table II. (b) It is claimed that computer use is associated with higher wages. Perform an appropriate one-sided test at a = .05 of the statistical significance of the computer dummy variable in model (4) in table II. (c) What is the size of the estimated difference between workers who use computers on the job and those who do not given the estimate in column (4) of table II. (d) Is computer use associated with higher wages after controlling for individual charac- teristics? Perform an appropriate one-sided test at a = .05 of the statistical significance of the computer dummy variable in model (6) in table II. (e) What is the effect of education on wage given the estimates in column (6) of table II. (f) Perform an F test at a = .05 of the overall goodness of fit of model (6) in table II. (g) According to the estimates in model (6) in table II, what is the difference between wages with and without use of computer, controlling for other regressors that might determine wages? (h) Which model do you prefer on the basis of adjusted R?, model (5) or model (6)? i) Do the results in Table II prove that using a computer at work causes higher wages? g g g Explain. 38 QUARTERLY JOURNAL OF ECONOMICS Independent variable Intercept Years of education Experience Experience-squared + 100 Black (1 = yes) Other race (1 = yes) Part-time (1 = yes) Lives in SMSA (1 = yes) Veteran (1 = yes) Female (1 = yes) Married (1 = yes) Married+*Female Union member (1 = yes) 8 Occupation dummies R 2 TABLE I1 OLS REGRESSION EsSTIMATES OF THE EFrECT OF COMPUTER USE ON PAY (DEPENDENT VARIABLE: In (HOURLY WAGE)) October 1984 (1) 1.937 No 0.051 (2) (3) 0.750 0.069 0.048 (0.001) (0.002) 0.027 0.025 (0.001) (0.001) 0.041 -0.040 (0.002) (0.002) 0.098 0.066 (0.013) (0.012) -0.105 -0.079 (0.020) (0.019) -0.256 0.216 (0.010) (0.010) 0.111 0.105 (0.007) (0.007) 0.038 0.041 (0.011) (0.011) -0.162 -0.135 (0.012) (0.012) 0.156 0.129 (0.011) (0.011) -0.168 -0.151 (0.015) (0.015) 0.181 0.194 (0.009) (0.009) No Yes No 0.446 0.491 0.082 (4) 0928 2.086 0.905 (0.005) (0.023) (0.026) (0.006) (0.024) (0.026) Uses computer at work (1 = yes) 0.276 0.170 0.140 0.325 0.188 (0.010) (0.008) (0.008) (0.009) (0.008) (0.008) October 1989 (5) (6) 1.094 0.162 0.075 0.055 (0.002) (0.002) 0.027 0.025 (0.001) (0.001) -0.041 -0.040 (0.002) (0.002) -0.121 -0.092 (0.013) (0.012) -0.029 -0.015 (0.020) (0.020) -0.221 -0.183 (0.010) (0.010) 0.138 0.130 (0.007) (0.007) 0.025 0.031 (0.012) (0.011) -0.172 -0.151 (0.012) (0.012) 0.159 0.143 (0.011) (0.011) -0.141 -0.131 (0.015) (0.015) 0.182 0.189 (0.010) (0.010) No Yes 0.451 0.486 Notes. Standard errors are shown in parentheses. Sample size is 13,335 for 1984 and 13,379 for 1989. Columns (2), (3), (5), and (6) also include three region dummy variables. HOW COMPUTERS HAVE CHANGED THE WAGE STRUCTURE: EVIDENCE FROM MICRODATA, 1984-1989* ALAN B. KRUEGER This paper uses Current Population Survey data to examine whether workers who use a computer at work earn a higher wage rate than otherwise similar workers who do not use a computer at work. A variety of models are estimated to try to correct for unobserved variables that might be correlated with job-related computer use and earnings. Estimates suggest that workers who use computers on their job earn 10 to 15 percent higher wages. Additionally, the expansion in computer use in the 1980s can account for one-third to one-half of the increase in the rate of return to education. INTRODUCTION Several researchers have documented that significant changes in the structure of wages took place in the United States in the 1980s.1 For example, the rate of return to education has increased markedly since 1979, with the earnings advantage of college graduates relative to high school graduates increasing from 34 percent in 1979 to 56 percent in 1991 [Mishel and Bernstein, 1992, Table Bl]. In addition, wage differentials based on race have expanded while the male-femalewage gap has narrowed, and the reward for experience appears to have increased. These changes in the wage structure do not appear to be a result of transitory cyclical factors. In contrast to the near consensus of opinion regarding the scope and direction of changes in the wage structure in the 1980s, the root causes of these changes remain controversial. The two leading hypotheses that have emerged to explain the rapid changes in the wage structure in the 1980s are (1) increased international competition in several industries has hurt the economic position of low-skilled and less-educated workers in the United States (e.g., Murphy and Welch [1991]); (2) rapid, skill-biased technological change in the 1980s caused profound changes in the relative productivity of various types of workers (e.g., Bound and Johnson *I am grateful to Kainan Tang and Shari Wolkon for providing excellent research assistance, and to Joshua Angrist, David Card, Lawrence Katz, and participants at several seminars for helpful comments. Financial support from the National Science Foundation (SES-9012149) is gratefully acknowledged. 1. Excellent examples of this literature include Blackburn, Bloom, and Free- man [1990], Murphy and Welch [1992], Katz and Revenga [1989], Katz and Murphy [1992], Bound and Johnson [1992], Juhn, Murphy, and Pearce [1989], Levy [1989], Mincer [1991], and Davis and Haltiwanger [1991]. 1993 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology. The Quarterly Journal of Economics, February 1993