COMPUTERS HAVE CHANGED THE WAGE STRUCTURE 39 1989.5 Even after including these covariates,however,the com- puter dummy variable continues to have a sizable and statistically significant effect on wages,with t-ratios of 21.3 in 1984 and 23.1 in 1989. It is not clear whether occupation dummies are appropriate variables to include in these wage regressions because computer skills may enable workers to qualify for jobs in higher paying occupations and industries.For example,one would probably not want to control for whether a worker is in the computer program- ming occupation while estimating the effect of computer use on earnings.Nevertheless,columns (3)and(6)include a set of eight one-digit occupation dummies.These models still show a sizable pay differential for using a computer at work.In 1989,for example, employees who use computers on the job earn 17.6 percent higher pay than employees who do not use computers on the job,holding education,occupation,and other characteristics constant.If 44 two-digit occupation dummies are included in the model in column (6)instead of the 8 one-digit occupation dummies,the computer- use wage differential is 13.9 percent,with a t-ratio of 15.5. A.Employer Characteristics Although I am mainly concerned about bias because of omitted employee characteristics that are correlated with computer use at work,it is possible that characteristics of employers are correlated with the provision of computers and the generosity of compensa- tion.Such a relationship might exist in a rent-sharing model,in which employees are able to capture some of the return to the employer's capital stock.Unfortunately,there is only a limited amount of information about employer characteristics in the CPS. However,if 48 two-digit industry dummies are included in a model that includes two-digit occupation dummies and the covariates in column (6),the computer-use wage differential is 11.4 percent, with a t-ratio of 13.0.6 Information on employer size is not available in the October CPS,but two findings suggest that the computer differential is not merely reflecting the effect of (omitted)employer size.First, establishment-level surveys do not show a strong relationship 5.The computer differential is about the same for men and women.For example,in 1989 the coefficient (and standard error)for computer use is 0.197 (0.012)for men and 0.185 (0.011)for women. 6.Results for 1984 are similar:the wage differential falls to 11.3 percent if 44 occupation dummies are included,and to 9.0 percent if 48 two-digit industry dummies are included.COMPUTERS HAVE CHANGED THE WAGE STRUCTURE 39 1989.5 Even after including these covariates, however, the com￾puter dummy variable continues to have a sizable and statistically significant effect on wages, with t-ratios of 21.3 in 1984 and 23.1 in 1989. It is not clear whether occupation dummies are appropriate variables to include in these wage regressions because computer skills may enable workers to qualify for jobs in higher paying occupations and industries. For example, one would probably not want to control for whether a worker is in the computer program￾ming occupation while estimating the effect of computer use on earnings. Nevertheless, columns (3) and (6) include a set of eight one-digit occupation dummies. These models still show a sizable pay differential for using a computer at work. In 1989, for example, employees who use computers on the job earn 17.6 percent higher pay than employees who do not use computers on the job, holding education, occupation, and other characteristics constant. If 44 two-digit occupation dummies are included in the model in column (6) instead of the 8 one-digit occupation dummies, the computer￾use wage differential is 13.9 percent, with a t-ratio of 15.5. A. Employer Characteristics Although I am mainly concerned about bias because of omitted employee characteristics that are correlated with computer use at work, it is possible that characteristics of employers are correlated with the provision of computers and the generosity of compensa￾tion. Such a relationship might exist in a rent-sharing model, in which employees are able to capture some of the return to the employer's capital stock. Unfortunately, there is only ;I limited amount of information about employer characteristics in the CPS. However, if 48 two-digit industry dummies are included in a model that includes two-digit occupation dummies and the covariates in column (6), the computer-use wage differential is 11.4 percent, with a t-ratio of 13.0.6 Information on employer size is not available in the October CPS, but two findings suggest that the computer differential is not merely reflecting the effect of (omitted) employer size. First, establishment-level surveys do not show a strong relationship 5. The computer differential is about the same for men and women. For example, in 1989 the coefficient (and standard error) for computer use is 0.197 (0.012)for men and 0.185 (0.011) for women. 6. Results for 1984 are similar: the wage differential falls to 11.3 percent if 44 occupation dummies are included, and to 9.0 percent if 48 two-digit industry dummies are included