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

Social scientific theories frequently posit that multiple causalmechanisms may produce the same outcome. Unfortunately, it isnot always possible to observe which mechanism was responsible.For example, IMF scholars conjecture that nations enter IMFagreements both out of economic need and for discretionary domesticpolitical reasons. Typically, though, all we observe is thefact of agreement, not its cause. Partial observability probitmodels (Poirier 1980, Journal of Econometrics 12:209–217;Braumoeller2003, Political Analysis 11:209–233) provide one methodfor the statistical analysis of such phenomena. Unfortunately,they are often plagued by identification and labeling difficulties.Sometimes, however, qualitative studies of particular casesenlighten us about causes when quantitative studies cannot.We propose exploiting this information to lend additional structureto the partial observability approach. Monte Carlo simulationreveals that by anchoring "discernible" causes for a handfulof cases about which we possess qualitative information, weobtain greater efficiency. More important, our method provesreliable at recovering unbiased parameter estimates when thepartial observability model fails. The paper concludes withan analysis of the determinants of IMF agreements.

A member shall be entitled to purchase the currencies of othermembers from the Fund ...[provided] the member represents thatit has a need to make the purchase because of its balance ofpayments or its reserve position or developments in its reserves. —InternationalMonetary Fund Articles of Agreement [IMF] negotiations sometimesenable government leaders to do what they privately wish todo, but are powerless to do domestically. —RobertPutnam(1988, p. 457)