The Possibility of Causal Inference in Social Sciences

This lecture attempts to discuss the possibility of causal inference in social sciences. There are four strategies for attempting to derive causal inferences from observational data: (1) cross-tabulation approach, (2) regression approach, (3) methods based on panel data, and (4) counter-factual framework. The lecture discusses these four approaches in detail. The lecture concludes with the discussion of the "heterogeneous causal effect" inherent in the society, the idea introduced by Otis Dudley Duncan, and the "causation as generative process" advanced by John H. Goldthorpe. I argue that these two ideas are complementary, and that the two great sociologists have highlighted important issues which must be confronted by social scientists in the course of causal inference using the observational data.