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From a new NBER Working Paper "U.S. Employment and Opioids: Is There a Connection?" by Janet Currie, Jonas Y. Jin and Molly Schnell.
Abstract:
This paper uses quarterly county-level data to examine the relationship between opioid prescription rates and employment-to-population ratios from 2006-2014. We first estimate models of the effect of opioid prescription rates on employment-to-population ratios, instrumenting opioid prescriptions for younger ages using opioid prescriptions to the elderly. We also estimate models of the effect of employment-to-population ratios on opioid prescription rates using a shift-share instrument. We find that the estimated effect of opioids on employment-to-population ratios is positive but small for women, but there is no relationship for men. These findings suggest that although they are addictive and dangerous, opioids may allow some women to work who would otherwise leave the labor force. When we examine the effect of employment-to-population ratios on opioid prescriptions, our results are more ambiguous. Overall, our findings suggest that there is no simple causal relationship between economic conditions and the abuse of opioids. Therefore, while improving economic conditions in depressed areas is desirable for many reasons, it is unlikely to curb the opioid epidemic.
The working paper is available here, (gated).
We live in an age of paradox. Systems using artificial intelligence match or surpass human-level performance in more and more domains, leveraging rapid advances in other technologies and driving soaring stock prices. Yet measured productivity growth has declined by half over the past decade, and real income has stagnated since the late 1990s for a majority of Americans. We describe four potential explanations for this clash of expectations and statistics: false hopes, mismeasurement, redistribution, and implementation lags. While a case can be made for each, we argue that lags have likely been the biggest contributor to the paradox. The most impressive capabilities of AI, particularly those based on machine learning, have not yet diffused widely. More importantly, like other general purpose technologies, their full effects won't be realized until waves of complementary innovations are developed and implemented. The required adjustment costs, organizational changes, and new skills can be modeled as a kind of intangible capital. A portion of the value of this intangible capital is already reflected in the market value of firms. However, going forward, national statistics could fail to measure the full benefits of the new technologies and some may even have the wrong sign.
We try to explain why Italy's labor productivity stopped growing in the mid-1990s. We find no evidence that this slowdown is due to trade dynamics, Italy's inefficient governmental apparatus, or excessively protective labor regulations. By contrast, the data suggest that Italy's slowdown was more likely caused by the failure of its firms to take full advantage of the ICT revolution. While many institutional features can account for this failure, a prominent one is the lack of meritocracy in the selection and rewarding of managers. Familyism and cronyism are the ultimate causes of the Italian disease.Read more at NBER Working Papers.
Here's a new paper from labor economist David Neumark:
The literature on the employment effects of minimum wages is about a century old, and includes hundreds of studies. Yet the debate among researchers about the employment effects of minimum wages remains intense and unsettled. This essay discussed the key questions that have arisen in the past research that, if we can answer them, may prove most useful in making sense of the conflicting evidence. I also focus on additional questions we should consider to better inform the policy debate, in particular in the context of the very high minimum wages coming on line in the United States, about which past research is quite uninformative.Certain to add to the debate on how we think about minimum wages in the U.S.
Between 1972 and 2012, the fraction of the population with low levels of education has declined dramatically and the fraction with higher levels of education has increased. This change in the composition of educational attainment in the population places downward pressure on disability rates. Our estimates suggest that over the past two decades, the upward pressure on DI rates arising from increasing educational disparities in health, wealth and employment has been roughly offset by the downward pressure arising from the declining fraction of the population with low levels of education.
Participation in flexible contract work has increased dramatically over the last decade, often in settings where new technologies lower the transaction costs of providing labor flexibly. One prominent example of this is the ride-sharing company Uber, which allows drivers to provide (or not provide) rides anytime they are willing to accept prevailing prices for this service. An Uber-style arrangement offers workers flexibility in both setting a customized work schedule and also adjusting it throughout the day. Using high-frequency data of hourly earnings for Uber drivers, we document the ways in which drivers utilize this real-time flexibility and we estimate the driver surplus generated by this flexibility. We estimate how drivers' reservation wages vary in high frequency from hour to hour, which allows us to study the surplus and supply implications of both flexible and traditional work arrangements. Our results indicate that, while the Uber relationship may have other drawbacks, Uber drivers benefit significantly from real-time flexibility, earning more than twice the surplus they would in less flexible arrangements. If required to supply labor inflexibly at prevailing wages, they would also reduce the hours they supply by more than two-thirds. The implications of our findings for the future of flexible work are discussed.It comes down to the willingness to supply more labor.