References

This guide draws on a handful of textbooks, the original papers behind the estimators discussed, and package documentation. The list below collects the works cited across the chapters.

Textbooks and lecture notes

  • Baltagi, B. H. Econometric Analysis of Panel Data. Wiley.
  • Baum, C. F. An Introduction to Modern Econometrics Using Stata. Stata Press.
  • Davidson, R., and J. G. MacKinnon. Econometric Theory and Methods. Oxford University Press.
  • Greene, W. H. Econometric Analysis. Prentice Hall. Cited by year in places (e.g. the 1993 edition); chapter and page numbers differ across editions.
  • Hamilton, J. D. (1994). Time Series Analysis. Princeton University Press.
  • Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data. 2nd ed. MIT Press.

Core papers

  • Anderson, T. W., and C. Hsiao (1981). “Estimation of Dynamic Models with Error Components.” Journal of the American Statistical Association 76: 598–606.
  • Andrews, D. W. K., M. J. Moreira, and J. H. Stock (2006). “Optimal Two-Sided Invariant Tests for Instrumental Variables Regression.” Econometrica 74(3): 715–752.
  • Angrist, J. D. (1998). “Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants.” Econometrica 66(2): 249–288.
  • Arellano, M., and S. Bond (1991). “Some Tests of Specification for Panel Data.” Review of Economic Studies 58: 277–297.
  • Arkhangelsky, D., S. Athey, D. A. Hirshberg, G. W. Imbens, and S. Wager (2021). “Synthetic Difference-in-Differences.” American Economic Review 111(12): 4088–4118. R package synthdid.
  • Baltagi, B. H., and D. Levin (1992). “Cigarette Taxation: Raising Revenues and Reducing Consumption.” Structural Change and Economic Dynamics 3(2): 321–335.
  • Blundell, R., and S. Bond (1998). “Initial Conditions and Moment Restrictions in Dynamic Panel Data Models.” Journal of Econometrics 87: 115–143.
  • Borusyak, K., X. Jaravel, and J. Spiess (2024). “Revisiting Event-Study Designs: Robust and Efficient Estimation.” Review of Economic Studies 91(6): 3253–3285.
  • Breslow, N. E. (1974). “Covariance Analysis of Censored Survival Data.” Biometrics 30(1): 89–99.
  • Callaway, B., and P. H. C. Sant’Anna (2021). “Difference-in-Differences with Multiple Time Periods.” Journal of Econometrics 225(2): 200–230. R package did.
  • Cameron, A. C., and P. K. Trivedi (2005). Microeconometrics: Methods and Applications. Cambridge University Press.
  • Chabé-Ferret, S. (2015). “Analysis of the Bias of Matching and Difference-in-Difference under Alternative Earnings and Selection Processes.” Journal of Econometrics 185(1): 110–123.
  • Chabé-Ferret, S. (2017). “Should We Combine Difference in Differences with Conditioning on Pre-Treatment Outcomes?” Toulouse School of Economics Working Paper 17-824.
  • Chattopadhyay, A., and J. R. Zubizarreta (2023). “On the implied weights of linear regression for causal inference.” Biometrika 110(3): 615–629. R package lmw.
  • Cochrane, D., and G. H. Orcutt (1949). “Application of Least Squares Regression to Relationships Containing Auto-Correlated Error Terms.” Journal of the American Statistical Association 44(245): 32–61.
  • Cox, D. R. (1972). “Regression Models and Life-Tables.” Journal of the Royal Statistical Society B 34: 187–220.
  • Crump, R. K., V. J. Hotz, G. W. Imbens, and O. A. Mitnik (2009). “Dealing with Limited Overlap in Estimation of Average Treatment Effects.” Biometrika 96(1): 187–199.
  • Daw, J. R., and L. A. Hatfield (2018). “Matching and Regression to the Mean in Difference-in-Differences Analysis.” Health Services Research 53(6): 4138–4156.
  • de Chaisemartin, C., and X. D’Haultfœuille (2020). “Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects.” American Economic Review 110(9): 2964–2996.
  • Donald, S. G., and K. Lang (2007). “Inference with Difference-in-Differences and Other Panel Data.” Review of Economics and Statistics 89(2): 221–233.
  • Doudchenko, N., and G. W. Imbens (2016). “Balancing, Regression, Difference-in-Differences and Synthetic Control Methods: A Synthesis.” NBER Working Paper 22791.
  • Efron, B. (1977). “The Efficiency of Cox’s Likelihood Function for Censored Data.” Journal of the American Statistical Association 72(359): 557–565.
  • Frisch, R., and F. V. Waugh (1933). “Partial Time Regressions as Compared with Individual Trends.” Econometrica 1(4): 387–401.
  • Gibbons, C. E., J. C. Suárez Serrato, and M. B. Urbancic (2018). “Broken or Fixed Effects?” Journal of Econometric Methods 8(1): 1–12.
  • Goodman-Bacon, A. (2021). “Difference-in-Differences with Variation in Treatment Timing.” Journal of Econometrics 225(2): 254–277.
  • Grogger, J. T., and R. T. Carson (1991). “Models for Truncated Counts.” Journal of Applied Econometrics 6(3): 225–238.
  • Hausman, J. A. (1978). “Specification Tests in Econometrics.” Econometrica 46(6): 1251–1271.
  • Hazlett, C., and T. Shinkre (2024). “Demystifying and Avoiding the OLS ‘Weighting Problem’: Unmodeled Heterogeneity and Straightforward Solutions.” arXiv:2403.03299.
  • Hazlett, C., and Y. Xu (2018). “Trajectory Balancing: A General Reweighting Approach to Causal Inference with Time-Series Cross-Sectional Data.” Working paper, SSRN 3214231.
  • Heckman, J. J. (1979). “Sample Selection Bias as a Specification Error.” Econometrica 47: 153–161.
  • Imai, K., I. S. Kim, and E. H. Wang (2023). “Matching Methods for Causal Inference with Time-Series Cross-Sectional Data.” American Journal of Political Science 67(3): 587–605. R package PanelMatch.
  • Imbens, G. W., and J. D. Angrist (1994). “Identification and Estimation of Local Average Treatment Effects.” Econometrica 62(2): 467–475.
  • Judson, R. A., and A. L. Owen (1999). “Estimating Dynamic Panel Data Models: A Guide for Macroeconomists.” Economics Letters 65: 9–15.
  • Knaus, M. C. (2024). “Treatment Effect Estimators as Weighted Outcomes.” arXiv:2411.11559. R package OutcomeWeights.
  • Li, F., K. L. Morgan, and A. M. Zaslavsky (2018). “Balancing Covariates via Propensity Score Weighting.” Journal of the American Statistical Association 113(521): 390–400.
  • Lovell, M. C. (1963). “Seasonal Adjustment of Economic Time Series and Multiple Regression Analysis.” Journal of the American Statistical Association 58: 993–1010.
  • Montiel Olea, J. L., and C. Pflueger (2013). “A Robust Test for Weak Instruments.” Journal of Business & Economic Statistics 31(3): 358–369.
  • Moreira, M. J. (2003). “A Conditional Likelihood Ratio Test for Structural Models.” Econometrica 71: 1027–1048.
  • Moulton, B. R. (1990). “An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Units.” Review of Economics and Statistics 72(2): 334–338.
  • Mundlak, Y. (1978). “On the Pooling of Time Series and Cross Section Data.” Econometrica 46(1): 69–85.
  • Newey, W. K., and K. D. West (1987). “A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix.” Econometrica 55: 703–708.
  • Newey, W. K., and K. D. West (1994). “Automatic Lag Selection in Covariance Matrix Estimation.” Review of Economic Studies 61: 631–653.
  • Nickell, S. (1981). “Biases in Dynamic Models with Fixed Effects.” Econometrica 49: 1417–1426.
  • Peto, R. (1972). Contribution to the discussion of D. R. Cox, “Regression Models and Life-Tables.” Journal of the Royal Statistical Society B 34: 205–207.
  • Prais, S. J., and C. B. Winsten (1954). “Trend Estimators and Serial Correlation.” Cowles Commission Discussion Paper 383.
  • Rambachan, A., and J. Roth (2023). “A More Credible Approach to Parallel Trends.” Review of Economic Studies 90(5): 2555–2591. R package HonestDiD.
  • Roth, J. (2022). “Pretest with Caution: Event-Study Estimates after Testing for Parallel Trends.” American Economic Review: Insights 4(3): 305–322.
  • Sant’Anna, P. H. C., and J. Zhao (2020). “Doubly Robust Difference-in-Differences Estimators.” Journal of Econometrics 219(1): 101–122. R package DRDID.
  • Sargan, J. D. (1958). “The Estimation of Economic Relationships Using Instrumental Variables.” Econometrica 26: 393–415.
  • Singer, J. D., and J. B. Willett (1993). “It’s About Time: Using Discrete-Time Survival Analysis to Study Duration and the Timing of Events.” Journal of Educational Statistics 18: 155–195.
  • Słoczyński, T. (2022). “Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights.” Review of Economics and Statistics 104(3): 501–509.
  • Stock, J. H., and M. Yogo (2005). “Testing for Weak Instruments in Linear IV Regression.” In Identification and Inference for Econometric Models, ed. Andrews and Stock. Cambridge University Press.
  • Sun, L., and S. Abraham (2021). “Estimating Dynamic Treatment Effects in Event Studies with Heterogeneous Treatment Effects.” Journal of Econometrics 225(2): 175–199.
  • Swamy, P. A. V. B., and S. S. Arora (1972). “The Exact Finite Sample Properties of the Estimators of Coefficients in the Error Components Regression Models.” Econometrica 40(2): 261–275.
  • White, H. (1980). “A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity.” Econometrica 48(4): 817–838.
  • Wooldridge, J. M. (1999). “Distribution-Free Estimation of Some Nonlinear Panel Data Models.” Journal of Econometrics 90: 77–97.

Missing data

  • Rubin, D. B. (1987). Multiple Imputation for Nonresponse in Surveys. Wiley.
  • van Buuren, S. (2018). Flexible Imputation of Missing Data. 2nd ed. CRC Press. (MICE.)

Software

  • R Core Team. R: A Language and Environment for Statistical Computing. R packages loaded in the code examples: cobalt, DRDID, fixest, ggfortify, gmm, ivreg, knitr, MASS, OutcomeWeights, plm, sandwich, strucchange, survival, synthdid, WeightIt.
  • StataCorp. Stata Statistical Software.