An NBER conference on Labor Demand and Older Workers took place November 15 in Cambridge. Research Associate Kevin S. Milligan of University of British Columbia organized the meeting, sponsored by Alfred P. Sloan Foundation. These researchers' papers were presented and discussed:
Catherine Maclean, Temple University and NBER; Stefan Pichler, ETH Zurich; and Nicolas R. Ziebarth, Cornell University
Mandated Sick Pay: Coverage, Utilization, and Welfare Effects
Maclean, Pichler, and Ziebarth evaluate the effects of employer sick pay mandates on sick pay coverage, utilization, and labor costs in the US. Using the National Compensation Survey, the researchers estimate difference-in-differences models in an event study design. Sick pay coverage increases significantly by 9 percentage points from a baseline level of 64 percent in the first two years, but then plateaus over the next four years. Newly covered employees take two additional sick days in the first quarter of the year, increasing labor costs by 23 cents per hour worked for marginal firms. However, the researchers find little evidence that mandated sick pay crowds-out other non-mandated paid leave benefits. Finally, the researchers develop a model of optimal sick pay provision along with a welfare analysis. Mandating sick pay likely increases welfare.
Joseph Marchand, University of Alberta, and Kevin S. Milligan, University of British Columbia and NBER
Natural Resource Booms and Older Workers
White, lower-educated, males, in middle-age (WLEMMAs), have seen broadly-based declines in employment and health in the 21st century, sparking a debate about the role of economic and social factors driving the decline. Marchand and Milligan look for evidence of symmetric effects by studying an industry that has undergone a strong positive and negative economic shock over this same era: the shale oil boom (and bust). Evidence of a symmetric effect would bolster the case for economic factors driving the outcomes of WLEMMAs. Using geological variation across the United States, the researchers form instruments to predict the strength of the oil boom across regions and find that WLEMMAs, particularly those aged 45 to 54, significantly benefited from the recent shale boom with higher employment and earnings, as well as lower poverty and disability rates. The researchers also find starkly different effects on mortality across ages, with younger ages showing an increase and older ages a decrease in mortality.
Marco Angrisani and Erik Meijer, University of Southern California, and Arie Kapteyn, University of Southern California and NBER
Sorting into Jobs and Labor Supply and Demand at Older Ages
Angrisani, Kapteyn, and Meijer document considerable heterogeneity in the fraction of older workers across occupations, and show that this is related to occupational characteristics. For example, occupations that have larger fractions of older workers tend to be less physically demanding and more cognitively demanding. Average workers' characteristics such as cognition and health are strongly correlated with these occupational characteristics, although there is considerable within-occupation heterogeneity. Based on these observations, and a Bartik-type argument, the researchers argue that an increase in the employment share of an occupation with a high fraction of older workers implies an increased demand for older workers. This leads to a prediction that the wages of workers in such occupations may have increased in order to lower retirement rates. Using difference-in-difference methods, the researchers do find evidence for the former, but they do not see a direct relation with retirement. However, an indirect effect through wages is consistent with the results.
Daron Acemoglu, MIT and NBER, and Pascual Restrepo, Boston University
Demographics and Automation (NBER Working Paper No. 24421)
Acemoglu and Restrepo argue theoretically and document empirically that aging leads to greater (industrial) automation, and in particular, to more intensive use and development of robots. Using US data, they document that robots substitute for middle-aged workers (those between the ages of 21 and 55). They show that demographic change — measured by an increase in the ratio of older to middle-aged workers — is associated with greater adoption of robots and other automation technologies across countries and with more robotics-related activities across US commuting zones. The researchers also provide evidence of more rapid development of automation technologies in countries undergoing greater demographic change. The directed technological change model predicts that the induced adoption of automation technology should be more pronounced in industries that rely more on middle-aged workers and those that present greater opportunities for automation. Both of these predictions receive support from country-industry variation in the adoption of robots. The model also implies that the productivity implications of aging are ambiguous when technology responds to demographic change, but one should expect productivity to increase and the labor share to decline relatively in industries that are more amenable to automation, and this is indeed the pattern found in the data.
Simon Jäger, MIT and NBER, and Benjamin Schoefer, University of California, Berkeley
Wages and the Value of Nonemployment (NBER Working Paper No. 25230)
Nonemployment is often posited as a worker's outside option in wage setting models such as bargaining and wage posting. The value of nonemployment is therefore a key determinant of wages. Jäger and Schoefer measure the wage effect of changes in the value of nonemployment among initially employed workers. The quasi-experimental variation in the value of nonemployment arises from four large reforms of unemployment insurance (UI) benefit levels in Austria. The researchers document that wages are insensitive to UI benefit changes: point estimates imply a wage response of less than $0.01 per $1.00 UI benefit increase, and the researchers can reject sensitivities larger than $0.03. The insensitivity holds even among workers with low wages and high predicted unemployment duration, and among job switchers and recently unemployed workers. The insensitivity of wages to the nonemployment value presents a puzzle to the widely used Nash bargaining model, which predicts a sensitivity of $0.24-$0.48. The evidence supports wage-setting models that insulate wages from the value of nonemployment.