Natural Expectations and Macroeconomic Fluctuations.

In recent decades, research in economics and finance has largely focused on the rational actor model, in which economic agents process all available information perfectly. In contrast to an older perspective represented by Keynes and Pigou, the rational model rules out unjustified optimism or pessimism as an amplifying force for aggregate fluctuations. Consequently, the rational model struggles to explain some of the most prominent facts we observe in macroeconomics, such as large swings in asset prices, in other words “bubbles”, as well as credit cycles, investment cycles, and other mechanisms that contribute to the length and severity of economic contractions. Relaxing the assumption of perfect rationality is a potential way of explaining aggregate volatility. Unfortunately, economists lack a consensus on how to do this. Economists often point out that psychological concepts like Keynesian “animal spirits” (Keynes, 1936) are vague and potentially even untestable (for instance, Fama, 1998). If a sample of macroeconomists were forced to write down a formal model of animal spirits, most wouldn’t know where to start and the rest would produce models that had little in common. In contrast, the rational actor model is conceptually elegant, disciplined, and parsimonious. However, even the assumption of perfect rationality is not sufficient for modeling discipline. Creative assumptions about technology, preferences, information, and market frictions can offset the parsimony purchased with rational beliefs. If the methodological goal is modeling discipline, formal quasi-rational models with a small number of free parameters should also be serious contenders. The methodological litmus tests should be parsimony, portability, and explanatory power (Gabaix and Laibson, 2008 propose a list of seven properties of good models). Rational models are only one potential means to these ends. In this paper, we make the case that quasi-rational models deserve greater attention. We begin by discussing a large body of empirical evidence which suggests that beliefs systematically deviate from perfect rationality. Much of the evidence implies that economic agents tend to form forecasts that are excessively influenced by recent changes – in other words, some form of “extrapolation bias.” We then present a parsimonious quasi-rational model that we call natural expectations, which falls between rational expectations and (naive) intuitive expectations. Intuitive expectations are formed by running growth regressions with a limited number of right-hand-side variables. As we will see, this leads to excessively extrapolative beliefs in certain classes of environments. Next, we show empirically that many U.S. macroeconomic time series have hump-shaped dynamics -- in other words, they exhibit momentum in the short run and (partial) mean reversion in the long run. Natural expectations turn out to be sophisticated enough to capture the short-run momentum but fail to fully reflect the more subtle long-run mean reversion. Hence, when the true dynamics are hump-shaped, natural expectations overstate the long-run persistence of economic shocks. In other words, agents with natural expectations turn out to form beliefs that don’t sufficiently account for the fact that good times (or bad times) won’t last forever. Finally, we embed natural expectations in a simple dynamic macroeconomic model and compare the simulated properties of the model to the available empirical evidence. The model’s predictions match many patterns observed in macroeconomic and financial time series, such as high volatility of asset prices, predictable up-and-down cycles in equity returns, and a negative relationship between current consumption growth and future equity returns. We also discuss the model’s shortcomings, how these can be alleviated, and other potential directions for research in this area.