A new document has been added to the Society for Political Methodology Website.

 Title:     The Perils of Failed Randomization: Investigating Regression Adjustment of Regionally Confounded Cross-National Data

Author(s):     Jack Paine

Entry Date:     2013-07-18

Keyword(s):     Natural experiment, Regression, Causal Inference, Political Regimes

Abstract:      Many important papers studying cross-national outcomes such as political regime type or economic development exploit treatment variables generated by either geological or pre-modern historical processes. A general and major problem with these treatments, however, derives from their heavy regional concentration. Despite not being caused by other variables that independently affect the dependent variable, due to geological or historical accidents, variables such as oil or settler mortality claimed to be exogenous are nonetheless highly correlated with potential confounders that impede drawing causal inferences. With the goal of eliminating bias by controlling for observables, many papers studying variables such as these use parametric procedures to control for regional dummies. While estimation techniques such as ordinary least squares (OLS) provide a seemingly straightforward methodological fix, OLS also obscures particular shortcomings of the data, and imposes!
 
  strong assumptions to combine information across regions. The current paper takes a closer look at these assumptions and provides examples from top political science and economic journals to show how disaggregating the data can either help to support or to severely qualify existing results.

http://polmeth.wustl.edu/mediaDetail.php?docId=1405

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