Stata: 断点回归分析 (RDD) 文献和命令

2018-05-10 本文已影响251人 stata连享会

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Overview

There are several review articles on RD methodology and empirical practice. This course will discuss, and update as appropriate, topics in Imbens and Lemieux (2008) and Lee and Lemieux (2010). Since these reviews do not cover many of the most recent methodological results available in the literature, we are currently working on an up-to-date review on RD methodology (Cattaneo and Titiunik, 2016), which will be the main focus of this workshop. See also Skovron and Titiunik (2015) for a recent, updated review with particular focus on Political Science.

RDD 分析的 Stata 命令

rdrobust: RD inference employing local polynomial and partitioning methods. See Calonico, Cattaneo, and Titiunik (2014a, 2015b) for introductions, and Calonico, Cattaneo, Farrell, and Titiunik (2016b) for the most recent upgrades.
rddensity: RD density test for manipulation testing. See Cattaneo, Jansson, and Ma (2016b) for an introduction.
rdlocrand: RD inference employing randomization inference methods. See Cattaneo, Titiunik, and Vazquez-Bare (2016b) for an introduction
Source：Cattaneo-2018-Handbook

RDD 简明教程 (适于上手操作)

Jacob, R., P. Zhu, M. A. Somers, H. Bloom, 2012, A practical guide to regression discontinuity, Mdrc, - PDF -，模型设定部分的解释非常清晰，基本上没有用复杂的数学公式。

RDD 的适用条件？

Schochet, P., Cook, T., Deke, J., Imbens, G., Lockwood, J.R., Porter, J., Smith, J. (2010). Standards for Regression Discontinuity Designs. -PDF-

RDD 文献清单

Matias D. Cattaneo - Syllabus - 2016, Short Course in Regression Discontinuity Designs, - PDF -, 给出了一份较为完整的 RDD 参考文献清单。

RDD 相关 Stata 命令的介绍性文档

Cattaneo and Titiunik (2018): Regression Discontinuity Designs: A Review, coming soon.
Cattaneo, Idrobo and Titiunik (2018): A Practical Introduction to Regression Discontinuity Designs: Volume I. Cambridge Elements: Quantitative and Computational Methods for Social Science, Cambridge University Press. Replication Files
Cattaneo, Idrobo and Titiunik (2018): A Practical Introduction to Regression Discontinuity Designs: Volume II. Cambridge Elements: Quantitative and Computational Methods for Social Science, Cambridge University Press. Replication Files
Cattaneo, Titiunik and Vazquez-Bare (2017): Comparing Inference Approaches for RD Designs: A Reexamination of the Effect of Head Start on Child Mortality. Journal of Policy Analysis and Management 36(3): 643-681, Summer 2017.
Replication Files
Cattaneo and Vazquez-Bare (2016): The Choice of Neighborhood in Regression Discontinuity Designs.
Observational Studies 2: 134-146, December 2016.

参考文献

Calonico, S., M. D. Cattaneo, and M. H. Farrell (2016): “On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference,” working paper, University of Michigan.
Calonico, S., M. D. Cattaneo, M. H. Farrell, and R. Titiunik (2016a): “Regression Discontinuity Designs Using Covariates,” working paper, University of Michigan.
Calonico, S., M. D. Cattaneo, M. H. Farrell, and R. Titiunik (2016b): “rdrobust: Software for Regression Discontinuity Designs,” working paper, University of Michigan.
Calonico, S., M. D. Cattaneo, and R. Titiunik (2014a): “Robust Data-Driven Inference in the Regression-Discontinuity Design,” Stata Journal, 14(4), 909–946.
Calonico, S., M. D. Cattaneo, and R. Titiunik (2014b): “Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs,” Econometrica, 82(6), 2295–2326.
Calonico, S., M. D. Cattaneo, and R. Titiunik (2015a): “Optimal Data-Driven Regression Discontinuity Plots,” Journal of the American Statistical Association, 110(512), 1753–1769.
Calonico, S., M. D. Cattaneo, and R. Titiunik (2015b): “rdrobust: An R Package for Robust Nonparametric Inference in RegressionDiscontinuity Designs,” R Journal, 7(1), 38–51.
Card, D., D. S. Lee, Z. Pei, and A. Weber (2015): “Inference on Causal Effects in a Generalized Regression Kink Design,” Econometrica, 83(6), 2453–2483.
Cattaneo, M. D., N. Idrobo, and R. Titiunik (2018a): A Practical Introduction to Regression Discontinuity Designs: Part I. In preparation for Cambridge Elements: Quantitative and Computational Methods for Social Science, Cambridge University Press. - PDF -
Cattaneo, M. D., N. Idrobo, and R. Titiunik (2018b): A Practical Introduction to Regression Discontinuity Designs: Part II. In preparation for Cambridge Elements: Quantitative and Computational Methods for Social Science, Cambridge University Press. - PDF -
Cattaneo, M. D., B. Frandsen, and R. Titiunik (2015): “Randomization Inference in the Regression Discontinuity Design: An Application to Party Advantages in the U.S. Senate,” Journal of Causal Inference, 3(1), 1–24.
Cattaneo, M. D., M. Jansson, and X. Ma (2016a): “Simple Local Regression Distribution Estimators with an Application to Manipulation Testing,” working paper, University of Michigan.
Cattaneo, M. D., M. Jansson, and X. Ma (2016b): “rddensity: Manipulation Testing based on Density Discontinuity,” working paper, University of Michigan.
Cattaneo, M. D., L. Keele, R. Titiunik, and G. Vazquez-Bare (2016): “Interpreting Regression Discontinuity Designs with Multiple Cutoffs,” Journal of Politics, forthcoming.
Cattaneo, M. D., and R. Titiunik (2016): “Regression Discontinuity Designs: A Review of Recent Methodological Developments,” manuscript in preparation, University of Michigan.
Cattaneo, M. D., R. Titiunik, and G. Vazquez-Bare (2016a): “Comparing Inference Approaches for RD Designs: A Reexamination of the Effect of Head Start on Child Mortality,” working paper, University of Michigan.
Cattaneo, M. D., R. Titiunik, and G. Vazquez-Bare (2016b): “rdlocrand: Inference in Regression Discontinuity Designs under Local Randomization,” Stata Journal, forthcoming.
Hahn, J., P. Todd, and W. van der Klaauw (2001): “Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design,” Econometrica, 69(1), 201–209.
Imbens, G., and T. Lemieux (2008): “Regression Discontinuity Designs: A Guide to Practice,” Journal of Econometrics, 142(2), 615–635.
Imbens, G. W., and K. Kalyanaraman (2012): “Optimal Bandwidth Choice for the Regression Discontinuity Estimator,” Review of Economic Studies, 79(3), 933–959.
Keele, L. J., and R. Titiunik (2015): “Geographic Boundaries as Regression Discontinuities,” Political Analysis, 23(1), 127–155.
Lee, D. S. (2008): “Randomized Experiments from Non-random Selection in U.S. House Elections,” Journal of Econometrics, 142(2), 675–697.
Lee, D. S., and T. Lemieux (2010): “Regression Discontinuity Designs in Economics,” Journal of Economic Literature, 48(2), 281–355.
Lee, D. S., and T. Lemieux 2014, Chapter 14: Regression discontinuity designs in social sciences[C], in H. Best,C. Wolf eds, The sage handbook of regression analysis and causal inference. PDF
McCrary, J. (2008): “Manipulation of the running variable in the regression discontinuity design: A density test,” Journal of Econometrics, 142(2), 698–714.
Porter, J. (2003): “Estimation in the Regression Discontinuity Model,” working paper, University of Wisconsin.
Skovron, C., and R. Titiunik (2015): “A Practical Guide to Regression Discontinuity Designs in Political Science, with,” working paper, University of Michigan.
Wooldridge, J. (2010): Econometric Analysis of Cross-Section and Panel Data. MIT Press, Cambridge, MA.

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