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Before and After Study Designs

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Abstract

In this chapter, we investigate three methods for estimating quasi-experimental models: (1) Interrupted Time Series; (2) Regression Discontinuity Approach; (3) Difference in Difference. We provide examples and a step-by-step guide to show how to estimate these different types of model specifications. We outline how to interpret the results from these different models in light of the underlying assumptions, and what this means for drawing conclusions on causality.

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References and Further Reading

Interrupted Time Series

  • Bernal, J. L., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: A tutorial. International Journal of Epidemiology, 46(1), 348–355.

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  • Kontopantelis, E., Doran, T., Springate, D. A., Buchan, I., & Reeves, D. (2015). Regression based quasi-experimental approach when randomisation is not an option: Interrupted time series analysis. BMJ, 350, h2750.

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Regression Discontinuity

  • Imbens, G. W., & Lemieux, T. (2008). Regression discontinuity designs: A guide to practice. Journal of Econometrics, 142(2), 615–635.

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  • Jacob, R., Zhu, P., Somers, M. A., & Bloom, H. (2012). A practical guide to regression discontinuity. MDRC.

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  • Lee, D. S., & Lemieux, T. (2010). Regression discontinuity designs in economics. Journal of Economic Literature, 48, 281–355.

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Difference in Difference

  • Cameron, A. C., & Miller, D. L. (2015). A practitioner’s guide to cluster-robust inference. Journal of Human Resources, 50(2), 317–372.

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  • Hall, P., Horowitz, J. L., & Jing, B. Y. (1995). On blocking rules for the bootstrap with dependent data. Biometrika, 82(3), 561–574.

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  • Heckman, J. J., & Smith, J. A. (1999). The pre-programme earnings dip and the determinants of participation in a social programme. Implications for simple programme evaluation strategies. The Economic Journal, 109(457), 313–348.

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  • Kloek, T. (1981). OLS estimation in a model where a microvariable is explained by aggregates and contemporaneous disturbances are equicorrelated. Econometrica: Journal of the Econometric Society, 49(1), 205–207.

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  • Moulton, B. R. (1986). Random group effects and the precision of regression estimates. Journal of Econometrics, 32(3), 385–397.

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  • Rosenbaum, P. R. (1987). Sensitivity analysis for certain permutation inferences in matched observational studies. Biometrika, 74(1), 13–26.

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  • Wooldridge, J. (2007). What’s new in econometrics? Lecture 10 difference-in-differences estimation. NBER Summer Institute. Retrieved October 9, 2017, from www.nber.org/WNE/Slides7–31–07/slides_10_diffindiffs.pdf

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Brown, H. (2018). Before and After Study Designs. In: The Economics of Public Health. Palgrave Pivot, Cham. https://doi.org/10.1007/978-3-319-74826-9_5

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