Quantitative Leverage Through Qualitative Knowledge: Augmenting the Statistical Analysis of Complex Causes

Social scientific theories frequently posit that multiple causal mechanisms may produce the same outcome. Unfortunately, it is not always possible to observe which mechanism was responsible. For example, IMF scholars conjecture that nations enter IMF agreements both out of economic need and for discretionary domestic political reasons. Typically, though, all we observe is the fact of agreement, not its cause. Partial observability probit models (Poirier 1980, Journal of Econometrics 12:209–217; Braumoeller 2003, Political Analysis 11:209–233) provide one method for the statistical analysis of such phenomena. Unfortunately, they are often plagued by identification and labeling difficulties. Sometimes, however, qualitative studies of particular cases enlighten us about causes when quantitative studies cannot. We propose exploiting this information to lend additional structure to the partial observability approach. Monte Carlo simulation reveals that by anchoring “discernible†causes for a handful of cases about which we possess qualitative information, we obtain greater efficiency. More important, our method proves reliable at recovering unbiased parameter estimates when the partial observability model fails. The paper concludes with an analysis of the determinants of IMF agreements. A member shall be entitled to purchase the currencies of other members from the Fund …[provided] the member represents that it has a need to make the purchase because of its balance of payments or its reserve position or developments in its reserves. —International Monetary Fund Articles of Agreement [IMF] negotiations sometimes enable government leaders to do what they privately wish to do, but are powerless to do domestically. —Robert Putnam (1988, p. 457)