Essays in health economics and political economy

This dissertation explores various topics in public and health economics and political economy. It studies pathways into deep poverty, substance use disorders, and homelessness, as well as the influence of social media use on societal outcomes. The first chapter is coauthored with Christina Kent and is concerned with family formation among low-income populations. Pregnancy and new parenthood mark formative periods that can influence the social, emotional and economic lives of parents profoundly. In this chapter, we map out how these events shape the living conditions of women with low incomes, focusing on housing stability (including homelessness), social assistance use, mental health, and crime. We use panel data consisting of administrative records from all residents of a large urban US county. Our sample encompasses all births to women of low SES in the county. For identification, we leverage an event study design around pregnancy. We further employ two dynamic difference-in-difference designs: One compares the outcomes of women who do vs. do not experience miscarriages, and one compares the outcomes across events for women who first experience a miscarriage, followed by a live birth in the subsequent years. We find that new parenthood is associated with large, 15-30 percentage point increases in the uptake of Medicaid, SNAP and TANF benefits, with a 44% increase in movement into public housing (on a base of 4% pre-pregnancy), persistent increases in homelessness encounters (30-50%), large reductions in criminal behavior, and short-term increases in treatments of substance use disorder. The second chapter is coauthored with Jonathan Zhang and investigates how physician opioid-prescribing behavior impacts patient outcomes and behavior. In the past two decades, death rates from opioids have seen a fivefold increase and opioid prescribing has emerged as a leading public health problem in the United States. Clinical guidelines leave many opioid prescribing decisions to physician judgement; we study the extent to which a single opioid prescription in an emergency department, for these marginal cases, can induce long-term dependence and impact health and economic outcomes of a patient. We tackle these questions by leveraging quasi-random assignment of patients to physicians, who vary in their propensity to prescribe opioids. We analyze the universe of electronic health record data for a particularly vulnerable population— veterans—and find that a single opioid prescription can have strong adverse effects on a veteran's long-term outcomes. A single opioid prescription induces a 1.2 percentage point (pp) increase in the probability of long-term prescription opioid use, a 0.34pp increase in development of an opioid use disorder, and a 0.075pp increase in opioid overdose mortality. We find suggestive evidence of both use of and death by heroin and synthetic opioids. Moreover, in settings where the supply of legal prescription opioids is restricted, veterans are more likely to resort to illicit opioids, highlighting the complex interdependencies between legal and illicit sources of opioid supply. The third chapter, also coauthored with Jonathan Zhang, builds on the first chapter by expanding into the primary care setting and the broader effects of having a high opioid-prescribing primary care provider (PCP). Primary care is the most frequently utilized health service and is the source for nearly half of all opioids prescribed in the United States. This chapter studies the impact of exposure to high prescribing primary care providers (PCP) on opioid abuse, and physical and mental health among veterans. Using over two decades of electronic health records, we exploit variation in opioid prescribing tendency across providers in the same facility, in conjunction with quasi-random assignment of providers to new patients. We find that assignment to a PCP who prescribes opioids at a 3 percentage point (pp) higher rate (equivalent to the difference between a 90th and 10th percentile prescriber within a facility) is associated with an increase in the probability of long-term opioid use by 0.72pp, development of an opioid use disorder by 0.12pp, and five-year opioid overdose mortality by 0.008pp. Veterans' mental health deteriorates; the three-year likelihood of attempted suicide or self-harm increases by 0.023pp and depression diagnosis increases by 0.18pp. Investigating into the mechanisms, we find evidence consistent with high opioid prescribers being less likely to refer patients to alternative pain management, adhere to clinical recommendations on naloxone distribution, or refer patients to substance use disorder treatment. The final chapter is coauthored with Hunt Allcott, Luca Braghieri, and Matthew Gentzkow and evaluates social media's influence on society. The rise of social media has provoked both optimism about potential societal benefits and concern about harms such as addiction, depression, and political polarization. In a randomized experiment, we find that deactivating Facebook for the four weeks before the 2018 US midterm election (i) reduced online activity, while increasing offline activities such as watching TV alone and socializing with family and friends; (ii) reduced both factual news knowledge and political polarization; (iii) increased subjective well-being; and (iv) caused a large persistent reduction in post-experiment Facebook use. Deactivation reduced post-experiment valuations of Facebook, suggesting that traditional metrics may overstate consumer surplus

Keywords: Economics.
Advisor: Gentzkow Matthew
Duggan Mark G. (Mark Gregory) 
Persson Petra