Stanford University
POLISCI 353: Workshop in Statistical Modeling

Supplementary Reading List for Causal Inference by Jonathan Wand

Overview:

Cox, D.R. (1992). "Causality: Some Statistical Aspects." Journal of the Royal Statistical Society, Series A 155 291-301.

Holland, P.W. (1986). "Statistics and Causal Inference (with discussion)." Journal of the American Statistical Association 81, as945-970. JSTOR

Freedman, David A. (1991). "Statistical Models and Shoe Leather." With discussion by Richard A. Berk, Hubert M. Blalock, Jr., William M. Mason. Pp. 291-358 in Sociological Methodology 1991.

Winship, Christopher and Stephen Morgan. (1999) "The estimation of causal effects from observational data". Annual Review of Sociology. 25:659--707
http://www.wjh.harvard.edu/~winship/cfa.html

Matching

Donald B. Rubin. Matching to Remove Bias in Observational Studies
Biometrics, Vol. 29, No. 1. (Mar., 1973), pp. 159-183. JSTOR

Rubin, D. B., (1977), "Assignment to a Treatment Group on the Basis of a Covariate", Journal of Educational Statistics, 2, 1-26.

Abadie, A., and G. Imbens, (2004), A Simple and Bias-corrected Matching Estimator for Average Treatment Effects"

Propensity Score Matching

Paul R. Rosenbaum; Donald B. Rubin. "The Central Role of the Propensity Score in Observational Studies for Causal Effects"
Biometrika, Vol. 70, No. 1. (Apr., 1983), pp. 41-55. JSTOR

Paul R. Rosenbaum; Donald B. Rubin. "Reducing Bias in Observational Studies Using Subclassification on the Propensity Score (in Applications)"
Journal of the American Statistical Association, Vol. 79, No. 387. (Sep., 1984), pp. 516-524. JSTOR

Paul R. Rosenbaum; Donald B. Rubin. "Constructing a Control Group Using Multivariate Matched Sampling Methods That Incorporate the Propensity Score"
The American Statistician, Vol. 39, No. 1. (Feb., 1985), pp. 33-38. JSTOR

J. Hahn. "On the Role of the Propensity Score in Efficient Estimation of Average Treatment Effects,"
Econometrica 66, March 1998.

Guido Imbens
Semiparametric Estimation of Average Treatment Effects Under Exogeneity: A Review (local copy)

Instrumental Variables and Structural Models

Joshua D. Angrist; Guido W. Imbens; Donald B. Rubin. "Identification of Causal Effects Using Instrumental Variables"
Journal of the American Statistical Association, Vol. 91, No. 434. (Jun., 1996), pp. 444-455. JSTOR

J.J. Heckmand Edward Vytlacil. (2003).
Structural Equations, Treatment Effects, and Econometric Policy Evaluation

Pedro Carneiro James J. Heckman, and Edward Vytlacil. (2000)
"Understanding What Instrumental Variables Estimate: Estimating Marginal and Average Returns to Education

Angrist, J., (1990)
"Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records"
American Economic Review, 80, 313-335.

Propensity vs IV

James Heckman and Salvador Navarro-Lozanno. (2003) "Using matching, instrumental variables and control functions to estimate economic choice models"

Regression Discontinuity Design

Jinyong Hahn, Petra Todd, Wilbert Van der Klaauw.
"Identification and estimation of treatment effects with a regression-discontinuity design" Econometrica. Jan 2001. Vol. 69, Iss. 1

David Lee's working papers:

Randomized Experiments from Non-random Selection in U.S. House Elections

Do Voters Affect or Elect Policies? Evidence from the U.S. House

Political Science Applications

Jonathan Wand, Kenneth W. Shotts, Jasjeet S. Sekhon, Walter R. Mebane, Jr., Michael C. Herron and Henry E. Brady. 2001.
The Butterfly Did It: The Aberrant Vote for Buchanan in Palm Beach County, Florida.
American Political Science Review 95 (4): 793 810.

Jasjeet S. Sekhon. 2004 Updating Voters: How voters act as if they are informed
American Political Science Review 95 (4): 793 810.

Steven D. Levitt and James M. Snyder, Jr. 1997. "The Impact of Federal Spending on House Election Outcomes." Journal of Political Economy 105(1): 30?53.

Gerber, Alan S. and Donald P. Green. 2000. "The Effects of Canvassing, Telephone Calls, and Direct Mail on Voter Turnout: A Field Experiment." American Political Science Review 94(3): 653 663.

Imai, Kosuke. "Do Get-Out-The-Vote Calls Reduce Turnout? The Importance of Statistical Methods for Field Experiments." American Political Science Review. Forthcoming.

Software for causal inference

Propensity score matching by Jas Sekhon, R software library

Matching estimators by Guido Imbens, Stata or Matlab

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Jonathan Wand's homepage: http://wand.stanford.edu

Revised January 11, 2004