Readings List

Books and Literature

Author

Kevin Hu(胡华平)

Lecture Handouts

Text and Books

  1. Wooldridge, J.M. Introductory econometrics: a modern approach[M]. Seventh edition. Australia: Cengage, 2020. You can download the following book chapters (View PDF).

This book is easy for reading and understanding and has lots pratical examples.

  • Chapter 15: Instrumental Variables Estimation and Two-Stage Least Squares.

  • Chapter 16: Simultaneous Equations Models.

  1. Gujarati, D.N, Porter, D.C. Basic econometrics[M]. fifth edition. Boston: McGraw-Hill, 2009. You can download the following book chapters (View PDF).

The writing language of this textbook is very simple and easy to understand.

  • Chapter 18: Simultaneous-Equation Models.

  • Chapter 19: The Identification Problem.

  • Chapter 20: Simultaneous-Equation Methods.

  1. Hansen, B. Econometrics[M]. Princeton: Princeton University Press, 2022. You can download the following book chapters (View PDF).

The content of this textbook is very comprehensive and profound, but it is difficult to understand and requires a lot of statistical and mathematical knowledge.

  • Chapter 12: Instrumental Variables.
  1. Hill C, Griffiths W E, Lim G C. Principles of econometrics[M]. Fifth edition. NJ: John Wiley & Sons, 2018. (PDF file supplied if asked.)

  • Chapter 15: Instrumental Variables Estimation and Two-Stage Least Squares

  • Chapter 16: Simultaneous Equations Models

Note

There is an accompany Online Free Book(bookdown website) for this text book by using R programming language: Colonescu C. Principles of Econometrics with R (2016) https://bookdown.org/ccolonescu/RPoE4/

Journal Articles

TipReadings guide

For a concise introduction, critical commentary, and R/Stata reproducibility notes for each paper below, see IV & Endogeneity: Readings Guide.

  • Abadie, A., J. Angrist, and G. Imbens. Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings[J]. Econometrica, 2002, 70(1):91-117. (View PDF)

  • Abadie, A. Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models[J]. Journal of the American Statistical Association, 2002, 97(457):284-292. (View PDF)

  • Abadie, A. Semiparametric Instrumental Variable Estimation of Treatment Response Models[J]. Journal of Econometrics, 2003, 113(2):231-263. (View PDF)

  • Abdulkadiroğlu, A., J. D. Angrist, P. D. Hull, and P. A. Pathak. Charters without Lotteries: Testing Takeovers in New Orleans and Boston[J]. American Economic Review, 2016, 106(7):1878-1920. (View PDF)

  • Angrist, J. D. Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records[J]. The American Economic Review, 1990, 80(3):313-336. (View PDF)

  • Angrist J.D, Krueger A.B. Does Compulsory School Attendance Affect Schooling and Earnings?[J]. The Quarterly Journal of Economics, 1991, 106(4): 979–1014. (View PDF). Note: Win Supanwanid provided the data and STATA scripts <www.github.com/winsup/angrist_krueger_1991>, and Kevin Hu replicated the paper using R code.

  • Angrist, J. D., and A. B. Krueger. The Effect of Age at School Entry on Educational Attainment: An Application of Instrumental Variables with Moments from Two Samples[J]. Journal of the American Statistical Association, 1992, 87(418):328-336. (View PDF)

  • Angrist, J. D., and A. B. Krueger. Split-Sample Instrumental Variables Estimates of the Return to Schooling[J]. Journal of Business & Economic Statistics, 1995, 13(2):225-235. (View PDF)

  • Angrist, J. D., G. W. Imbens, and D. B. Rubin. Identification of Causal Effects Using Instrumental Variables[J]. Journal of the American Statistical Association, 1996, 91(434):444-455. (View PDF)

  • Angrist, J. D., G. W. Imbens, and A. B. Krueger’. Jackknife Instrumental Variables Estimation[J]. Journal of Applied Econometrics, 1999, 14:57-67. (View PDF)

  • Angrist, J. D., P. A. Pathak, and C. R. Walters. Explaining Charter School Effectiveness[J]. American Economic Journal: Applied Economics, 2013, 5(4):1-27. (View PDF)

  • Angrist, J. D., and A. B. Krueger. Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments[J]. Journal of Economic Perspectives, 2021, 15(4):69-85. (View PDF)

  • Angrist, J., and M. Kolesár. One Instrument to Rule Them All: The Bias and Coverage of Just-ID IV[J]. Journal of Econometrics, 2024, 240(2):105398. (View PDF)

  • Bound, J., D. A. Jaeger, and R. M. Baker. Problems with Instrumental Variables Estimation When the Correlation between the Instruments and the Endogenous Explanatory Variable Is Weak[J]. Journal of the American Statistical Association, 1995. (View PDF)

  • Card, D.E. Using Geographic Variation in College Proximity to Estimate the Return to Schooling. Cambridge, MA :National Bureau of Economic Research, 1993.(View PDF)

  • Card D.E. Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems[J]. Econometrica, 2001, 69(5): 1127–1160. (View PDF)

  • Flores‐Lagunes, A. Finite Sample Evidence of IV Estimators under Weak Instruments[J]. Journal of Applied Econometrics, 2007, 22(3):677-694. (View PDF)

  • Heckman, J. J., and E. Vytlacil. Structural Equations, Treatment Effects, and Econometric Policy Evaluation[J]. Econometrica, 2022, 73(3):669-738. (View PDF)

  • Hudson, S., P. Hull, and J. Liebersohn. Interpreting Instrumented Difference-in-Differences[J]. MIT, 2017. (View PDF)

  • Imbens, G. W., and D. B. Rubin. Estimating Outcome Distributions for Compliers in Instrumental Variables Models[J]. The Review of Economic Studies, 1997, 64(4):555-574. (View PDF)

  • Kitagawa, T. A Test for Instrument Validity[J]. Econometrica, 2015, 83(5):2043-2063. (View PDF)

  • Keane, M. P., and T. Neal. A Practical Guide to Weak Instruments[J]. Annual Review of Economics, 2024, 16:185-212. (View PDF)

  • Lee, D. S., J. McCrary, M. J. Moreira, and J. Porter. Valid T-Ratio Inference for IV[R]. 2020. (View PDF)

  • Mogstad, M., A. Santos, and A. Torgovitsky. Using Instrumental Variables for Inference About Policy Relevant Treatment Parameters[J]. Econometrica, 2018, 86(5):1589-1619. (View PDF)

  • Mogstad, M., and A. Torgovitsky. Identification and Extrapolation of Causal Effects with Instrumental Variables[J]. Annual Review of Economics, 2018, 10:577-613. (View PDF) . Note: Reproducible github R package ivmte https://github.com/jkcshea/ivmte?tab=readme-ov-file#references

  • Mogstad, M., A. Torgovitsky, and C. R. Walters. The Causal Interpretation of Two-Stage Least Squares with Multiple Instrumental Variables[J]. American Economic Review, 2021, 111(11):3663-3698. (View PDF)

  • Olea, J. L. M., and C. Pflueger. A Robust Test for Weak Instruments[J]. Journal of Business & Economic Statistics, 2013, 31(3):358-369. (View PDF)

  • Staiger, D., and J. H. Stock. Instrumental Variables Regression with Weak Instruments[J]. Econometrica, 1997, 65(3):557-586. (View PDF)

  • Stock, J. H., and M. Yogo. Testing for Weak Instruments in Linear IV Regression[R]. SSRN Scholarly Paper, 2002. (View PDF)