Christopher J. Cronin
Associate Professor of Economics, University of Notre Dame
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My Google Scholar page is here and Research Statement is here.

Completed Papers

12. The Anatomy of U.S. Sick Leave Schemes: Evidence from Public School Teachers  (with Matthew Harris and Nicolas Ziebarth), Accepted, The Review of Economics and Statistics, NBER working paper 29956 

​​11. What Good are Treatment Effects without Treatment? Mental Health and the Reluctance to use Talk Therapy  (with Matthew Forsstrom and Nicholas Papageorge), Review of Economic Studies 92 (2025), NBER working paper 27711
   Published article: 
https://doi.org/10.1093/restud/rdae061   
   Press: Marginal Revolution


10. Demand for skills training among Medicaid home-based caregivers  (with Ethan Lieber), Journal of Health Economics 95 (2024)
   Published article: https://doi.org/10.1016/j.jhealeco.2024.102877

9. Nursing Home Quality, COVID-19 Deaths, and Excess Mortality (with Bill Evans), Journal of Health Economics 82 (2022) 
   Published article: https://doi.org/10.1016/j.jhealeco.2022.102592
   Press: Bloomberg Businessweek, Las Vegas Review-Journal, Tradeoffs Podcast
​   Circulated as NBER working paper 28012.
   Presentation: NBER


8. Excess mortality from COVID and non-COVID causes in minority populations (with Bill Evans), Proceedings of the National Academy of Sciences 39 (2021).
   Published article: 
https://doi.org/10.1073/pnas.2101386118
   Press: NPR Indianapolis

7. Total Shutdowns, Targeted Restrictions, or Individual Responsibility: How to Promote Social Distancing in the COVID-19 Era? (with Bill Evans), Journal of Health Economics 79 (2021)
​   Published article: https://doi.org/10.1016/j.jhealeco.2021.102497
   Press: NPR Indianapolis (31:00), Notre Dame Research, New York Times, ABC57 
              * Previously circulated as NBER working paper 27531, with the title: "
Private Precaution and Public Restrictions: What Drives Social Distancing and Industry                    Foot Traffic in the COVID-19 Era? " 
 
6. The Labor Market Effects of Antidepressants: Evidence from the 2007 FDA Black Box Warning (with Aline Bütikofer and Meghan Skira), Journal of Health Economics 73 (2020). Web Appendix
   Published article: 
https://doi.org/10.1016/j.jhealeco.2020.102348 


5. Measurement Error in Discrete Health Facility Choice Models: an Example from Urban Senegal (with David Guilkey and Ilene Speizer), Journal of Applied Econometrics 34 (2019): 1102-1120. Web Appendix
   Published article: 
https://doi.org/10.1002/jae.2739

4. Insurance-Induced Moral Hazard: A Dynamic Model of Within-Year Medical Care Decision Making Under Uncertainty, International Economic Review 60 (2019): 187-218. Web Appendix
   Published article: https://doi.org/10.1111/iere.12349

3. The Effects of Health Facility Access and Quality on Family Planning Use in Urban Senegal (with David Guilkey and Ilene Speizer), Health Economics 27 (2018): 576-591.  Web Appendix
   Published article: https://doi.org/10.1002/hec.3615 

2. The Effects of Prospective Mate Quality on Investments in Healthy Body Weight Among Single Women (with Matthew Harris), Economics & Human Biology 24 (2017): 164-183
   Published article: https://doi.org/10.1016/j.ehb.2016.12.002


1. Longitudinal Methods and the Urban Reproductive Health Initiative: A Guide to Program Impact Evaluation, MLE Technical Working Paper 1-2014 (with Gustavo Angeles, David Guilkey, Peter Lance, and Brian Sullivan)

Works in Progress

Sick Leave and Retirement: Dynamic Decision-Making among US Public School Teachers (with Matthew Harris and Nicolas Ziebarth)

Financial Incentives for Therapy Completion: A Randomized Control Trial with US Veterans  (with Ethan Lieber and Meghan Skira)

Information, Attendance, and Achievement: A Randomized Evaluation of Food Pantry Outreach to College Students (with Craig Gundersen)


 Useful Code
 
The following program can be used to determine which of 11 parametric distributions best fits the empirical (conditional or unconditional) distribution of a variable of interest. The distributions mimic those used in Jones, Lomas, and Rice (2014), which are chosen to fit a healthcare expenditure distribution that is characterized by a long right tail. I have attached an edited (publicly available) data file from the 1996 Medical Expenditure Panel Survey (MEPS) as an example of how the code works.



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