Inferring causality is an old and standard topic in methodology, taking a number of different forms depending on context.  In 1953, Hood and Koopmans published a social science classic, Studies in Econometric Method.  The book's central focus was on ways to estimate the magnitude of causal relationships from observational studies, relying on both theoretical models and a variety of regression based methods.  These chapters and the discussions they stimulated were deeply and sophisticatedly concerned with causality:  for example, chapter 2 was Herbert Simon's "Causal Ordering and Identifiability."   That book laid the foundations for the econometric revolution of the Sixties and Seventies.  This, in turn, formed the intellectual beginning of the Society for Political Methodology.  

Political methodology has evolved dramatically since the Society's beginning in the early 1980's.  Causal thinking continues to be at the core of this evolution, which has added important new ways to think about causality, new statistical methods, and new types of data.  A natural part of this evolution is an increased awareness of the limitations of the earlier work, just as future scholarship will add perspective to current topics.  Thus in our view, no one school of social science methodology has a monopoly on the term "causal inference."  Lab and field experiments, natural experiments, and observational studies all have strengths and weaknesses, present different challenges and opportunities, and are a vital part of our methodological tool kit used to study a wide range of political phenomena.  
 
For next summer's Polmeth meetings, we are sure that Don and the selection committee will take a capacious view of how quantitative methods can help us understand and estimate cause and effect in political science, as the Society has always striven to do in setting up those meetings.
 
John Jackson, Political Science, Michigan
Chris Achen, Politics, Princeton

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