A Random Walk in the History of Economic Thought, 1900–1950
Chapter 2: The Highs and Lows of Bayesian Economic Statistics
Modern financial economics uses probability theory and statistical methods to analyze the risk of an investment. For the most part, the pioneers and the practitioners of modern financial economics investigate financial markets as part of their study of economics. Historians of economic statistics have described how its innovation and diffusion took time and followed an uneven pattern (Morgan 1992; Epstein 1987; and Klein 1997). Of special interest to this study, its early development included a group who followed the Bayesian perspective, and they had an influence on the forerunners of financial economics who form the subject of this book. Consequently, for us to gain an appreciation of how they used statistics we need to have a background in the advancement of Bayesian statistical methods and how they came to be applied to economics. The brief overview of the development of probability theory, statistics, and economic statistics presented in this chapter does little justice to their complex history (Stigler 1986; Hald, 1990; Morgan 1992; Epstein 1987; and Klein 1997) and makes no claim of thoroughness in terms of documenting its full development. Its focus is on a narrow slice of that history relating to probability theories and statistical approaches that had an emphasis on Bayesian methods. One of the difficulties in the research of the history of economic thought is gauging the influence of a set of ideas. As this chapter will describe, a group of early advocates and practitioners of the use of statistics in economics followed the ‘inverse approach’...
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