Causal Inference

Methods for Observational Data

• Evaluating whether counterfactual questions (predictions, what-if questions, and causal effects) can be reasonably answered from given data, or whether inferences will instead be highly model-dependent; also, a new decomposition of bias in causal inference. These articles overlap (and each as been the subject of a journal symposium):
• • For complete mathematical proofs, general notation, and other technical material, see: Gary King and Langche Zeng. 2006. The Dangers of Extreme Counterfactuals, Political Analysis, Vol. 14, No. 2, Pp. 131-159. (Article: PDF | Abstract: HTML)
  • For more intuitive, but less general, notation, but with additional examples and more pedagogically oriented material, see: Gary King and Langche Zeng. When Can History be Our Guide? The Pitfalls of Counterfactual Inference, International Studies Quarterly, 51 (March, 2007): 183--210. (Article: PDF | Abstract: HTML)
• Matching Methods
• • A unified approach to matching methods as a way to reduce model dependence by preprocessing data and then using any model you would have without matching: Daniel Ho, Kosuke Imai, Gary King, and Elizabeth Stuart. Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference. Political Analysis, Vol. 15 (2007): Pp. 199-236. (Article: PDF | Abstract: HTML)
  • A simple and powerful method of matching: Stefano M. Iacus, Gary King, and Giuseppe Porro. Causal Inference Without Balance Checking: Coarsened Exact Matching. (Paper: PDF | Abstract: HTML)
  • A technical paper that describes a new class of matching methods, of which coarsened exact matching is an example: Stefano M. Iacus, Gary King, and Giuseppe Porro. Multivariate Matching Methods That are Monotonic Imbalance Bounding. (Paper: PDF | Abstract: HTML)
  • Stefano M. Iacus, Gary King, and Giuseppe Porro, "CEM: Software for Coarsened Exact Matching", Journal of Statistical Software, 30, 9 (June 2009) http://gking.harvard.edu/files/abs/cemR-abs.shtml. (Paper: PDF | JSS Version: HTML).
  • Matthew Blackwell, Stefano Iacus, Gary King, and Giuseppe Porro, cem: Coarsened Exact Matching in Stata The Stata Journal 9, 4 (2009): 524--546. (Article: PDF | Abstract: HTML)
• A method to estimate base probabilities or any quantity of interest from case-control data, even with no (or partial) auxilliary information. Discusses problems with odds-ratios. Gary King and Langche Zeng. Estimating Risk and Rate Levels, Ratios, and Differences in Case-Control Studies, Statistics in Medicine, Vol. 21 (2002): Pp. 1409-1427. (Article: PDF | Abstract: HTML)
• Causal inference in qualitative research (Chapter 4). King, Gary; Robert O. Keohane; and Sidney Verba. Designing Social Inquiry: Scientific Inference in Qualitative Research. Princeton: Princeton University Press, 1994. (Website: Book)
• Gary King. 'Truth' is Stranger than Prediction, More Questionable Than Causal Inference, American Journal of Political Science, Vol. 35, No. 4 (November, 1991): Pp. 1047-1053. (Article: PDF | Abstract: HTML)

Experimental Design

• An evaluation of the Mexican Seguro Popular program (designed to extend health insurance and regular and preventive medical care, pharmaceuticals, and health facilities to 50 million uninsured Mexicans), one of the world's largest health policy reforms of the last two decades. The evaluation features the largest randomized health policy experiment in history, a new design for field experiments that is more robust to the political interventions that have ruined many similar previous efforts, and new statistical methods that produce more reliable and efficient results using substantially fewer resources, assumptions, and data. (Articles on the Seguro Popular Evaluation: Website)
• Clarifying serious misunderstandings in the advantages and uses of the most common research designs for making causal inferences. Kosuke Imai, Gary King, and Elizabeth Stuart, Misunderstandings among Experimentalists and Observationalists about Causal Inference, Journal of the Royal Statistical Society, Series A Vol. 171, Part 2, (2008): Pp. 481--502. (Abstract: HTML | Paper: PDF)

Software

• MatchIt: Nonparametric Preprocessing for Parametric Causal Inference (Website: MatchIT)
• CEM: Coarsened Exact Matching (Website: CEM)
• WhatIf: Software for Evaluating Counterfactuals (Website: WhatIf)
• Zelig: Everyone's Statistical Software (Website: Zelig)
• CLARIFY: Software for Interpreting and Presenting Statistical Results (Website: CLARIFY)

Applications

• Epstein, Lee; Daniel E. Ho; Gary King; and Jeffrey A. Segal. The Supreme Court During Crisis: How War Affects only Non-War Cases, New York University Law Review, Vol. 80, No. 1 (April, 2005): 1-116. (Article: PDF | Abstract: HTML)
• A brief summary of the above article for an undergraduate audience: Epstein, Lee; Daniel E. Ho; Gary King; and Jeffrey A. Segal. The Effect of War on the Supreme Court, in Samuel Kernell and Steven S. Smith, eds.(3rd ed). Principles and Practice in American Politics: Classic and Contemporary Readings. Washington, D.C.: Congressional Quarterly Press, 2006. (Article: PDF | Abstract: HTML)