COMPUTERS HAVE CHANGED THE WAGE STRUCTURE 41 of possible nonrandom selection of the workers who use computers. Companies are likely to provide computer training and equipment first to the workers whose productivity is expected to increase the most from using a computer.This would pose a problem for the interpretation of the OLS estimates if these workers would have earned higher wages in the absence of computer use.The large increase in the number of workers who used computers at work between 1984 and 1989 is likely to have reduced the average quality of workers who work with computers,which would be expected to drive down the average wage differential associated with computer use.However,the slight increase in the computer wage premium between 1984 and 1989 suggests that nonrandom selection of the workers who use computers is not the dominant factor behind the positive association between computer use and wages. The other variables in Table II generally have their typical effects on wages,and their coefficients are relatively stable between 1984 and 1989.One notable exception is the rate of return to education,which increased by 0.6 percentage points between 1984 and 1989,even after holding computer use constant.And the black-white wage gap increased,while the wage gap between whites and other races declined in these years. C.Specific Computer Tasks The 1989 CPS asked workers what tasks they use their computer for.Respondents were allowed to indicate multiple tasks. Table III presents estimates of the coefficients on the specific computer tasks for a wage regression that also includes the covariates listed in column (6)of Table II (including occupation dummies).Importantly,the regression includes a dummy that equals one if the individual used a computer for any task at all,as well as dummies for the specific tasks.Thus,the coefficients on the specific tasks should be interpreted as indicating the additional payoff associated with a specific task relative to any computer use at all. Interestingly,these results show that the most highly re- warded task computers are used for is electronic mail,probably reflecting the fact that high-ranking executives often use E-mail. On the other hand,the results indicate a negative premium for individuals who use a computer for playing computer games.In fact,the-0.11 coefficient on computer games virtually negates the 0.145 coefficient for using computers at all.This result is signifi-COMPUTERS HAVE CHANGED THE WAGE STRUCTURE 41 of possible nonrandom selection of the workers who use computers. Companies are likely to provide computer training and equipment first to the workers whose productivity is expected to increase the most from using a computer. This would pose a problem for the interpretation of the OLS estimates if these workers would have earned higher wages in the absence of computer use. The large increase in the number of workers who used computers at work between 1984 and 1989 is likely to have reduced the average quality of workers who work with computers, which would be expected to drive down the average wage differential associated with computer use. However, the slight increase in the computer wage premium between 1984 and 1989 suggests that nonrandom selection of the workers who use computers is not the dominant factor behind the positive association between computer use and wages. The other variables in Table I1 generally have their typical effects on wages, and their coefficients are relatively stable between 1984 and 1989. One notable exception is the rate of return to education, which increased by 0.6 percentage points between 1984 and 1989, even after holding computer use constant. And the black-white wage gap increased, while the wage gap between whites and other races declined in these years. C. Specific Computer Tasks The 1989 CPS asked workers what tasks they use their computer for. Respondents were allowed to indicate multiple tasks. Table I11 presents estimates of the coefficients on the specific computer tasks for a wage regression that also includes the covariates listed in column (6) of Table I1 (including occupation dummies). Importantly, the regression includes a dummy that equals one if the individual used a computer for any task at all, as well as dummies for the specific tasks. Thus, the coefficients on the specific tasks should be interpreted as indicating the additional payoff associated with a specific task relative to any computer use at all. Interestingly, these results show that the most highly re￾warded task computers are used for is electronic mail, probably reflecting the fact that high-ranking executives often use E-mail. On the other hand, the results indicate a negative premium for individuals who use a computer for playing computer games. In fact, the -0.11 coefficient on computer games virtually negates the 0.145 coefficient for using computers at all. This result is signifi-