JSIT19-01: The Effect of Opioids on Labor Market Outcomes and Use of Social Security Disability Insurance

Researchers

  • Adibah Abdulhadi

Abstract

This project investigates the effect of the rate of opioid prescriptions on labor market outcomes (e.g. labor force participation, employment) and Social Security Disability Insurance (SSDI) application and enrollment. While media coverage suggests a devastating impact of opioid abuse on rural communities, there is an important and legitimate medical use for opioids by workers. For example, opioids can help a person who has a medical condition to manage pain, be gainfully employed rather than seeking SSDI, and subsequently pay the Social Security FICA payroll contributions. On the other hand, opioid use can be harmful as it is known to be an addictive substance and might lead to exiting of labor force. The efficacy of opioids in treating chronic pain is unclear, and opioid use could lead to untreated medical conditions that impair work and ultimately lead people to claim SSDI. Given that SSDI is primarily financed by FICA payroll contributions, the effect of opioids on labor force participation is a particularly relevant issue. This project explores whether opioids influence labor market outcomes, and eventually enrollment in SSDI. The main challenge in quantifying the effect of opioid prescription on labor market outcomes and SSDI is that workers who are prescribed an opioid medication may be different from those who are not. For example, the former may have more severe medical conditions which prevent them from working and increase the likelihood of claiming SSDI. An empirical approach that does not take the selection bias into account would overstate the effects of opioids. This project aims to address this issue by using local area payments from pharmaceutical companies to physicians for opioid marketing, as instrument to predict opioid use. The idea is that holding other factors constants (e.g. health conditions), doctors who receive marketing dollars are more likely to prescribe opioids than those who do not. This method has the potential to produce causal estimates of the effect of opioid prescription rates on labor market outcomes and SSDI. The analysis will be done at the county level primarily using publicly available data.

Publications

Project Year

2019