Non-Self-Averaging Phenomena in Macroeconomics: Neglected Sources of Uncertainty and Policy Ineffectiveness

The main analytical exercise by mainstream macroeconomists such as Romer (1986), Lucas (1988), Grossman and Helpman (1991), and Aghion and Howitt (1992) is to explicitly consider the optimization by representative agents using quadratic criterion functions in such activities as education, on-the-job training, basic scientific research, and process and product innovations. This approach is found not only in the study of economic growth but also in research on business cycles. In this chapter we argue that this research program, which dominates modern macroeconomics, is misguided because it does not recognize the distinction between self-averaging and non-self-averaging aspects of their optimization problems. Whether in growth or business cycle models, the fundamental motivation for often complex optimization exercises is that they are expected to lead us to a better understanding of dynamics of the mean or aggregate variables. The standard procedure is to begin with an analysis of optimization for the representative agent and then to translate it into an analysis of the economy as a whole. These exercises presume that different microeconomic shocks and differences among agents will cancel out in the means, and the results can be well captured by the analysis of the representative agents.