AgdaPkt 2017-09-25 Closed and Joint SA PFA

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The Effects of a $15 Minimum Wage by 2019 in Santa Clara County and San Jose 38 holds whether one company raises its wage above the market-clearing level, or whether all do (Akerlof and Yellen 1986). Reduced employee turnover means that workers will have more tenure with the same employer, which creates incentives for both employers and workers to increase training and therefore worker productivity. A large scholarly literature makes this point, and it has been emphasized recently by firms such as Walmart, TJ Maxx, and The Gap as principal reasons underlying their announced policies to increase their minimum wages nationally to $10. However, because of the lack individual- or firm-level productivity data, the earlier efficiency wage literature does not provide a reliable quantitative assessment of the importance of the effect on worker productivity among low-wage workers. A new paper by Burda, Gedanek and Hamermesh (2016) does just that. Using microdata for 2003- 2012 from the American Time Use Study, Burda et al. find that working time while on the job increases when wages are higher. Their results imply that an increase in hourly pay from $10 to $15 increases the level of productivity by 0.05 percent. Burda et al.’s estimate may be too high, given the difficulty of disentangling cause from effect in their loafing data. On the other hand, they do not have measures of worker engagement while working, which could make the actual worker productivity improvement potentially twice as large. To capture this range of productivity effects in our model, we use the Burda et al. estimate of 0.05 percent.19 Another relevant new paper (Card et al. 2016) appeared after the analysis for this report was completed. This paper uses firm-based data on value added per worker and pay to examine how much the rise of wage inequality derives from increases in firm-based productivity differences. The results in this paper (Card, personal communication) imply that a one percent wage increase leads to a 0.04 percent increase in log of productivity, which translates into a productivity increase of 0.1 percent. Consequently, our productivity estimate may be too low, which offsets our automation estimates, which may be too high. A recent study by John Abowd et al. (Abowd et al. 2012) demonstrates the substantial room for productivity and wage growth in low-wage industries in the U.S. Using longitudinally linked employer-employee data, Abowd et al. disentangle wage differentials among industries that are attributable to individual heterogeneity (such as the demographic, educational, and work experience characteristics of workers in the industry), which they label person effects, from the characteristics of the product market and bargaining power of firms in the industry, which they label industry effects. Abowd et al. can observe wage changes when individual workers move from one employer to another. They find very strong industry average firm effects, particularly for industries that have high average pay and low average pay. Among restaurants, for example, they find that 70 percent of the relatively low wages in the industry are attributable to firm effects, and only 30 percent to 8.A. - Page 52