Guides: PADM 5510/6710: Administrative Research Methods II: Course readings

Reading List

Alvarez, R. M., & Brehm, J. (1998). Speaking in Two Voices: American Equivocation about the Internal Revenue Service. American Journal of Political Science, 42(2), 418–452. https://doi.org/10.2307/2991765
Amrhein, V., Trafimow, D., & Greenland, S. (2019). Inferential Statistics as Descriptive Statistics: There Is No Replication Crisis if We Don’t Expect Replication. The American Statistician, 73(sup1), 262–270. https://doi.org/10.1080/00031305.2018.1543137
Borsboom, D. (2006). The attack of the psychometricians. Psychometrika, 71(3), 425–440. https://doi.org/10.1007/s11336-006-1447-6
Briggs, A. H., Wonderling, D. E., & Mooney, C. Z. (1997). Pulling cost-effectiveness analysis up by its bootstraps: A non-parametric approach to confidence interval estimation. Health Economics, 6(4), 327–340. https://doi.org/10.1002/(SICI)1099-1050(199707)6:4<327::AID-HEC282>3.0.CO;2-W
Clarke, K. R. (1993). Non-parametric multivariate analyses of changes in community structure. Australian Journal of Ecology, 18(1), 117–143. https://doi.org/10.1111/j.1442-9993.1993.tb00438.x
Cook, P. J., & Kang, S. (2016). Birthdays, Schooling, and Crime: Regression-Discontinuity Analysis of School Performance, Delinquency, Dropout, and Crime Initiation. American Economic Journal: Applied Economics, 8(1), 33–57. https://doi.org/10.1257/app.20140323
Coviello, D., & Mariniello, M. (2014). Publicity requirements in public procurement: Evidence from a regression discontinuity design. Journal of Public Economics, 109, 76–100. https://doi.org/10.1016/j.jpubeco.2013.10.008
DeHart-Davis, L. (2009). Green Tape and Public Employee Rule Abidance: Why Organizational Rule Attributes Matter. Public Administration Review, 69(5), 901–910. https://doi.org/10.1111/j.1540-6210.2009.02039.x
Gao, X., Canfield, C., Tang, T., Hill, H., Higman, M., & Cornwell, J. (2022). Encouraging voluntary government action via a solar-friendly designation program to promote solar energy in the United States. Proceedings of the National Academy of Sciences, 119(11), e2106201119. https://doi.org/10.1073/pnas.2106201119
Huebner, M., le Cessie, S., Schmidt, C. O., & Vach, W. (2018). A Contemporary Conceptual Framework for Initial Data Analysis. Observational Studies, 4(1), 171–192. https://doi.org/10.1353/obs.2018.0014
Kim, Y., & Steiner, P. (2016). Quasi-Experimental Designs for Causal Inference. Educational Psychologist, 51(3–4), 395–405. https://doi.org/10.1080/00461520.2016.1207177
Kline, R. B. (2010). Principles and Practice of Structural Equation Modeling, Third Edition—Chapter 5 Specifications (3rd edition). The Guilford Press.
Liang, J., & Langbein, L. (2015). Performance Management, High-Powered Incentives, and Environmental Policies in China. International Public Management Journal, 18(3), 346–385. https://doi.org/10.1080/10967494.2015.1043167
Munshi, K. (2003). Networks in the Modern Economy: Mexican Migrants in the U. S. Labor Market. The Quarterly Journal of Economics, 118(2), 549–599. https://doi.org/10.1162/003355303321675455
Munshi, K., & Rosenzweig, M. (2016). Networks and Misallocation: Insurance, Migration, and the Rural-Urban Wage Gap. The American Economic Review, 106(1), 46–98.
Nonparametric Tests. (n.d.). Retrieved August 17, 2023, from https://sphweb.bumc.bu.edu/otlt/MPH-Modules/BS/BS704_Nonparametric/BS704_Nonparametric_print.html
Thinking for Observational Studies, http://www.stratos-initiative.org), Huebner, M., Vach, W., Le Cessie, S., Schmidt, C. O., & Lusa, L. (2020).
Huebner, Marianne, Werner Vach, Saskia Le Cessie, Carsten Oliver Schmidt, Lara Lusa, Dianne Cook, Marianne Huebner, et al. 2020. "Hidden Analyses: A Review of Reporting Practice and Recommendations for More Transparent Reporting of Initial Data Analyses." BMC Medical Research Methodology 20 (1): 61-61
Park, S., & Liang, J. (2021). A Comparative Study of Gender Representation and Social Outcomes: The Effect of Political and Bureaucratic Representation. Public Administration Review, 81(2), 321–332. https://doi.org/10.1111/puar.13092
Stuart, E. A., Huskamp, H. A., Duckworth, K., Simmons, J., Song, Z., Chernew, M. E., & Barry, C. L. (2014). Using propensity scores in difference-in-differences models to estimate the effects of a policy change. Health Services and Outcomes Research Methodology, 14(4), 166–182. https://doi.org/10.1007/s10742-014-0123-z
Vigoda-Gadot, E., & Vashdi, D. R. (2020). Handbook of Research Methods in Public Administration, Management and Policy—Chapter 8—The use of difference-in-differences in public administration research. Edward Elgar Publishing.
Ye, F., & Lord, D. (2011). Investigation of Effects of Underreporting Crash Data on Three Commonly Used Traffic Crash Severity Models: Multinomial Logit, Ordered Probit, and Mixed Logit. Transportation Research Record, 2241(1), 51–58. https://doi.org/10.3141/2241-06
Ye, F., & Lord, D. (2014). Comparing three commonly used crash severity models on sample size requirements: Multinomial logit, ordered probit and mixed logit models. Analytic Methods in Accident Research, 1, 72–85. https://doi.org/10.1016/j.amar.2013.03.001
Yi, H., & Cui, C. (2019). Coping with functional collective action dilemma: Functional fragmentation and administrative integration. Public Management Review, 21(7), 1052–1075. https://doi.org/10.1080/14719037.2018.1544271

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