Kopecky, Karen A.
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Publication Substance Abuse during the Pandemic: Implications for Labor-Force Participation(2022-04-04) Greenwood, Jeremy; Guner, Nezih; Kopecky, Karen A.The labor-force participation rates of prime-age U.S. workers dropped in March 2020—the start of the COVID-19 pandemic—and have still not fully recovered. At the same time, substance-abuse deaths were elevated during the pandemic relative to trend indicating an increase in the number of substance abusers, and abusers of opioids and crystal methamphetamine have lower labor-force participation rates than non-abusers. Could increased substance abuse during the pandemic be a factor contributing to the fall in labor-force participation? Estimates of the number of additional substance abusers during the pandemic presented here suggest that increased substance abuse accounts for between 9 and 26 percent of the decline in prime-age labor-force participation between February 2020 and June 2021.Publication The Wife's Protector: A Quantitative Theory Linking Contraceptive Technology with the Decline in Marriage(2020-05-01) Greenwood, Jeremy; Guner, Nezih; Kopecky, Karen A.The 19th and 20th centuries saw a transformation in contraceptive technologies and their take up. This led to a sexual revolution, which witnessed a rise in premarital sex and out-of-wedlock births, and a decline in marriage. The impact of contraception on married and single life is analyzed here both theoretically and quantitatively. The analysis is conducted using a model where people search for partners. Upon finding one, they can choose between abstinence, a premarital sexual relationship, and marriage. The model is confronted with some stylized facts about premarital sex and marriage over the course of the 20th century. Some economic history is also presented.Publication The Downward Spiral(2022-09-14) Greenwood, Jeremy; Guner, Nezih; Kopecky, Karen A.There have been more than 500,000 opioid overdose deaths since 2000. To analyze the opioid epidemic, a model is constructed where individuals, with and without pain, choose whether to misuse opioids knowing the probabilities of addiction and dying. These odds are functions of opioid use. Markov chains are estimated from the US data for the college and non-college educated that summarize the transitions into and out of opioid addiction as well as to a deadly overdose. A structural model is constructed that matches the estimated Markov chains. The epidemic's drivers, and the impact of medical interventions, are examined.