The dangers of extreme counterfactuals

Political Analysis

Volumn 14, Issue 2, 2006, Pages 131-159

  King, Gary ^a   Zeng, Langche ^b  

^a HARVARD UNIVERSITY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 31344479653     PISSN: 10471987     EISSN: 14764989     Source Type: Journal    
DOI: 10.1093/pan/mpj004     Document Type: Article

References (43)

1. Bishop, Christopher M. 1995. Neural Networks for Pattern Recognition. Oxford: Oxford University Press.
2. Cuadras, C. M., and J. Fortiana. 1995. "A Continuous Metric Scaling Solution for a Random Variable." Journal of Multivariate Analysis 52: 1-14.
3. Cuadras, C. M., J. Fortiana, and E Oliva. 1997. "The Proximity of an Individual to a Population with Applications to Discriminant Analysis." Journal of Classification 14: 117-136.
4. de Berg, Mark, Marc van Krevald, Mark Overmars, and Otfried Schwarzkopf. 1998. Computational Geometry: Algorithms and Applications, 2nd rev. ed. New York: Springer.
5. Esty, Daniel C., Jack Goldstone, Ted Robert Gurr, Barbara Harff, Pamela T. Surko, Alan N. Unger, and Robert S. Chen. 1998. The State Failure Task Force Report: Phase II Findings. McLean, VA: Science Applications International Corporation.
6. Frangakis, Constantine E., and Donald Rubin. 2002. "Principal Stratification in Causal Inference." Biometrics 58: 21-29.
7. Gelman, Andrew, and Gary King. 1994. "Party Competition and Media Messages in U.S. Presidential Election Campaigns." In The Parties Respond: Changes in the American Party System, ed. L. Sandy Maisel. Boulder, CO: Westview, pp. 255-295. (Available from http://gking.harvard.edu/files/abs/partycomp-abs.shtml.)
8. Gower, J. C. 1966. "Some Distance Properties of Latent Root and Vector Methods Used in Multivariate Analysis." Biometrika 53(3/4): 325-388.
9. Gower, J. C. 1971. "A General Coefficient of Similarity and Some of Its Properties." Biometrics 27: 857-872.
10. Greenland, Sander, Judea Pearl, and James M. Robins. 1999. "Causal Diagrams for Epidemiologic Research." Epidemiology 10(1): 37-48.
11. Hastie, Trevor, R. Tibshirani, and J. Friedman. 2001. The Elements of Statistical Learning. New York: Springer Verlag.
12. Heckman, James, H. Ichimura, and P. Todd. 1998. "Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Program." Review of Economic Studies 64: 605-654.
13. Heckman, James J., Hidehiko Ichimura, Jeffrey Smith, and Petra Todd. 1998. "Characterizing Selection Bias Using Experimental Data." Econometrika 66(5): 1017-1098.
14. Ho, Daniel, Kosuke Imai, Gary King, and Elizabeth Stuart. 2005. "Matching as Nonparametric Preprocessing for Parametric Causal Inference." http://gking.harvard.edu/files/matchp.pdf.
15. Hoeting, Jennifer A., David Madigan, Adrian E. Raftery, and Chris T. Volinsky. 1999. "Bayesian Model Averaging: A Tutorial." Statistical Science 14(4): 382-417.
16. Holland, Paul W. 1986. "Statistics and Causal Inference." Journal of the American Statistical Association 81: 945-960.
17. Imai, Kosuke, and David A. van Dyk. 2004. "Causal Inference with General Treatment Regimes: Generalizing the Propensity Score." Journal of the American Statistical Association 99(467): 854-866.
18. Imai, Kosuke, and Gary King. 2004. "Did Illegal Overseas Absentee Ballots Decide the 2000 U.S. Presidential Election?" Perspectives on Politics 2(3): 537-549.
19. Kallay, Michael. 1986. "Convex Hull Made Easy." Information Processing Letters 22(March): 161.
20. King, Gary. 1991. "'Truth' Is Stranger than Prediction, More Questionable than Causal Inference." American Journal of Political Science 35(4): 1047-1053. http://gking.harvard.edu/files/abs/ truth-abs.shtml.
21. King, Gary, Robert O. Keohane, and Sidney Verba. 1994. Designing Social Inquiry: Scientific Inference in Qualitative Research. Princeton, NJ: Princeton University Press.
22. King, Gary, Michael Tomz, and Jason Wittenberg. 2000. "Making the Most of Statistical Analyses: Improving Interpretation and Presentation." American Journal of Political Science 44(2): 341-355. http://gking.harvard.edu/files/abs/making-abs.shtml.
23. King, Gary, and Langche Zeng. 2002. "Improving Forecasts of State Failure." World Politics 53(4): 623-658. http://gking.harvard.edu/files/abs/civil-abs.shtml.
24. Klee, Victor. 1980. "On the Complexity of d-Dimensional Voronoi Diagrams." Archive der Mathematik 34: 75-80.
25. Kuo, Yen-Hong. 2001. "Extrapolation of Association between Two Variables in Four General Medical Journals." Presented at the Fourth International Congress on Peer Review in Biomedical Publication, Barcelona, Spain.
26. Lechner, Michael. 1999. "Identification and Estimation of Causal Effects of Multiple Treatments under the Conditional Independence Assumptions." IZA Discussion Papers no. 91, University St. Gallen.
27. Madych, W. R., and S. A. Nelson. 1992. "Bounds on Multivariate Polynomials and Exponential Error Estimates for Multiquadric Interpolation."Journal of Approximation Theory 70: 94-114.
28. Manski, Charles F. 1995. Identification Problems in the Social Sciences. Cambridge, MA: Harvard University Press.
29. Meng, Xiao-Li, and Marin Romero. 2003. "Discussion: Efficiency and Self-Efficiency." International Statistical Review 71(3): 607-618.
30. O'Rourke, Joseph. 1998. Computational Geometry in C. New York: Cambridge University Press.
31. Pearl, Judea. 2000. Causality: Models, Reasoning, and Inference. Cambridge, UK: Cambridge University Press.
32. Robins, James M. 1999a. "Marginal Structural Models versus Structural Nested Models as Tools for Causal Inference." In Statistical Models in Epidemiology: The Environment and Clinical Trials, vol. 16, eds. M. E. Halloran and D. Berry. New York: Springer-Verlag, pp. 95-134.
33. Robins, James M. 1999b. "Association, Causation, and Marginal Structural Models" Synthese 121: 151-179.
34. Rosenbaum, Paul. 1984. "The Consequences of Adjusting for a Concomitant Variable That Has Been Affected by the Treatment" Journal of the Royal Statistical Society, A 147(5): 656-666.
35. Rosenbaum, Paul R., and Donald B. Rubin. 1983. "The Central Role of the Propensity Score in Observational Studies for Causal Effects" Biometrika 70: 41-55.
36. Rosenbaum, Paul R., and Donald B. Rubin. 1984. "Reducing Bias in Observational Studies Using Subclassification on the Propensity Score." Journal of the American Statistical Association 79: 515-524.
37. Rubin, Donald B. 1974. "Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies." Journal of Educational Psychology 6: 688-701.
38. Schaback, R. 1996. "Approximation by Radia Basis Functions with Finitely Many Centers."Constructive Approximation 12: 331-340.
39. Sisson, Scott A. 2005. "Transdimensional Markov Chains: A Decade of Progress and Future Perspectives." Journal of the American Statistical Association 100(471): 1077-1089.
40. Stoll, Heather, Gary King, and Langche Zeng. 2005. "Whatlf: Software for Evaluating Counterfactuals." http://gking.harvard.edu/whatif/.
41. Valentine, Frederick Albert. 1964. Convex Sets. New York: McGraw-Hill.
42. Winship, Christopher, and Stephen L. Morgan. 1999. "The Estimation of Causal Effects from Observational Data." American Review of Sociology 25: 659-707.
43. Wu, Z., and R. Schaback 1993. "Local Error Estimates for Radial Basis Function Interpolation of Scattered Data." Journal of Numerical Analysis 13: 13-27.