Does Health Behavior Change After Diagnosis? Evidence From Fuzzy Regression Discontinuity

References

Anderson, T., and H. Rubin. 1949. “Estimation of the Parameters of a Single Equation in a Complete System of Stochastic Equations.” Annals of Mathematical Statistics 20 (1): 46–63. https://doi.org/10.1214/aoms/1177730090.Suche in Google Scholar

Angrist, J. D., G. W. Imbens, and D. B. Rubin. 1996. “Identification of Causal Effects Using Instrumental Variables.” Journal of the American Statistical Association 91 (434): 444–55. https://doi.org/10.1080/01621459.1996.10476902.Suche in Google Scholar

Arai, Y., Y. Hsu, T. Kitagawa, I. Mourifié, and Y. Wan. 2019. Testing Identifying Assumptions in Fuzzy Regression Discontinuity Designs, CEMMAP Working Paper.Suche in Google Scholar

Armstrong, T. B., and M. Kolesár. 2020. “Simple and Honest Confidence Intervals in Nonparametric Regression.” Quantitative Economics 11 (1): 1–39. https://doi.org/10.3982/qe1199.Suche in Google Scholar

Calonico, S., M. D. Cattaneo, and R. Titiunik. 2014. “Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs.” Econometrica 82 (6): 2295–326. https://doi.org/10.3982/ecta11757.Suche in Google Scholar

Chern, W. S., E. T. Loehman, and S. T. Yen. 1995. “Information, Health Risk Beliefs, and the Demand for Fats and Oils.” Review of Economics and Statistics 77 (3): 555–64. https://doi.org/10.2307/2109915.Suche in Google Scholar

DiNardo, J., and D. S. Lee. 2011. “Program Evaluation and Research Designs.” Handbook of Labor Economics 4: 463–536. https://doi.org/10.1016/s0169-7218(11)00411-4.Suche in Google Scholar

Dong, Y. 2016. Jump or Kink? Regression Probability Jump and Kink Design for Treatment Effect Evaluation. Working Paper.Suche in Google Scholar

Dufour, J.-M. 1997. “Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models.” Econometrica 65 (6): 1365–88. https://doi.org/10.2307/2171740.Suche in Google Scholar

Dufour, J.-M., and M. Taamouti. 2005. “Projection-based Statistical Inference in Linear Structural Models with Possibly Weak Instruments.” Econometrica 73 (4): 1351–65. https://doi.org/10.1111/j.1468-0262.2005.00618.x.Suche in Google Scholar

Fan, J., and I. Gijbels. 1992. “Variable Bandwidth and Local Linear-Regression Smoothers.” Annals of Statistics 20 (4): 2008–36. https://doi.org/10.1214/aos/1176348900.Suche in Google Scholar

Feir, D., T. Lemieux, and V. Marmer. 2016. “Weak Identification in Fuzzy Regression Discontinuity Designs.” Journal of Business and Economic Statistics 34 (2): 185–96. https://doi.org/10.1080/07350015.2015.1024836.Suche in Google Scholar

Gelman, A., and G. Imbens. 2018. “Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs.” Journal of Business and Economic Statistics: 1–10. https://doi.org/10.1080/07350015.2017.1366909.Suche in Google Scholar

Hahn, J., P. Todd, and W. Van der Klaauw. 2001. “Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design.” Econometrica 69 (1): 201–9. https://doi.org/10.1111/1468-0262.00183.Suche in Google Scholar

He, Y. 2018. Three Essays on Regression Discontinuity Design and Partial Identification. Doctoral dissertation, Iowa State University.Suche in Google Scholar

Imbens, G., and K. Kalyanaraman. 2012. “Optimal Bandwidth Choice for the Regression Discontinuity Estimator.” Review of Economic Studies 79 (3): 933–59. https://doi.org/10.1093/restud/rdr043.Suche in Google Scholar

Imbens, G., and T. Lemieux. 2008. “Regression Discontinuity Designs: A Guide to Practice.” Journal of Econometrics 142 (2): 615–35. https://doi.org/10.1016/j.jeconom.2007.05.001.Suche in Google Scholar

Imbens, G.W., and J.D. Angrist. 1994. “Identification and Estimation of Local Average Treatment Effects.” Econometrica 62: 467–75. https://doi.org/10.2307/2951620.Suche in Google Scholar

Kleibergen, F. 2002. “Pivotal Statistics for Testing Structural Parameters in Instrumental Variables Regression.” Econometrica 70 (5): 1781–803. https://doi.org/10.1111/1468-0262.00353.Suche in Google Scholar

Lee, D. S., and T. Lemieuxa. 2010. “Regression Discontinuity Designs in Economics.” Journal of Economic Literature 48 (2): 281–355. https://doi.org/10.1257/jel.48.2.281.Suche in Google Scholar

Moreira, M. 2003. “A Conditional Likelihood Ratio Test for Structural Models.” Econometrica 71 (4): 1027–48. https://doi.org/10.1111/1468-0262.00438.Suche in Google Scholar

Noack, C., and C. Rothe. 2021. Bias-aware Inference in Fuzzy Regression Discontinuity Designs.Suche in Google Scholar

Oster, E. 2012. “HIV and Sexual Behavior Change: Why Not Africa?” Journal of Health Economics 31 (1): 35–49. https://doi.org/10.1016/j.jhealeco.2011.12.006.Suche in Google Scholar PubMed

Oster, E. 2018. “Diabetes and Diet: Purchasing Behavior Change in Response to Health Information.” American Economic Journal: Applied Economics 10 (4): 308–48. https://doi.org/10.1257/app.20160232.Suche in Google Scholar PubMed PubMed Central

Otsu, T., K.-L. Xu, and Y. Matsushita. 2015. “Empirical Likelihood for Regression Discontinuity Design.” Journal of Econometrics 186 (1): 94–112. https://doi.org/10.1016/j.jeconom.2014.04.023.Suche in Google Scholar

Staiger, D., and J. H. Stock. 1997. “Instrumental Variables Regression with Weak Instruments.” Econometrica 65 (3): 557–86. https://doi.org/10.2307/2171753.Suche in Google Scholar

Van der Klaauw, W. 2008. “Regression–Discontinuity Analysis: A Survey of Recent Developments in Economics.” Labour 22 (2): 219–45. https://doi.org/10.1111/j.1467-9914.2008.00419.x.Suche in Google Scholar

Xu, K.-L. 2020. “Inference of Local Regression in the Presence of Nuisance Parameters.” Journal of Econometrics 218 (2): 532–60. https://doi.org/10.1016/j.jeconom.2020.04.028.Suche in Google Scholar

Zhao, M., Y. Konishi, and P. Glewwe. 2013. “Does Information on Health Status Lead to a Healthier Lifestyle? Evidence from China on the Effect of Hypertension Diagnosis on Food Consumption.” Journal of Health Economics 32 (2): 367–85. https://doi.org/10.1016/j.jhealeco.2012.11.007.Suche in Google Scholar PubMed