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This program provides a method of inferring individual behavior from aggregate data. It implements the statistical procedures, diagnostics, and graphics from the book A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data (Princeton: Princeton University Press, 1997), by Gary King. Please read the book prior to trying this program (a sample chapter and other related information is available at my web site). Except where indicated, all references to page, section, chapter, table, and figure numbers in this document refer to the book.
Ecological inference, as traditionally defined, is the process of using aggregate (i.e., ``ecological'') data to infer discrete individual-level relationships of interest when individual-level data are not available. As existing methods usually lead to inaccurate conclusions about the empirical world, the ecological inference problem had been to develop a method that gives accurate answers. Ecological inferences are required in political science research when individual-level surveys are unavailable (e.g., local or comparative electoral politics), unreliable (racial politics), insufficient (political geography), or infeasible (political history). They are also required in numerous areas of major significance in public policy (e.g., for applying the Voting Rights Act) and other academic disciplines ranging from epidemiology and marketing to sociology and quantitative history. Most researchers using aggregate data have encountered some form of the ecological inference problem.
Because the ecological inference problem is caused by the lack of individual-level information, no method of ecological inference, including that introduced in this book and estimated by this program, will produce precisely accurate results in every instance. However, potential difficulties are minimized here by models that include more available information, diagnostics to evaluate when assumptions need to be modified, easy methods of modifying the assumptions, and uncertainty estimates for all quantities of interest. I recommend reviewing Chapter 16 while using this program for actual research.