In the second model, we add in a basic set of controls, which include the demographic variables included in Table 1—age, age squared, race/ethnicity, education indicators, sex, marital status, urbanicity, an indicator for being an hourly worker, and an indicator for being a full-time worker—in addition to a worker’s major industry and occupation. As with worker characteristics, the industry and occupation mix in the state could affect the average wage. Again, controlling for these differences allows us to better isolate the relationship between RTW status and wages. As expected, the coefficient on the RTW indicator moves closer to zero (as shown in the second column of Table 2), and wages in RTW states are found to be percent lower, on average, after controlling for these worker differences. Again, these results are in line with previous research.