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This paper presents a behavioral economics model with bounded rationality to describe an individual's food consumption choices that lead to weight gain and dieting. Using a physiological relationship determining calories needed to maintain weight, we simulate the food consumption choices of a representative female over a 30-year period. Results show an individual will periodically choose to diet, but that diet will reduce weight only temporarily. Recurrence of weight gain leads to cyclical dieting, which reduces the trend rate of weight increase. Dieting frequency is shown to depend on decision period length, dieting costs, and habit persistence.

This chapter analyzes the empirical relationship between the pricesetting/consumption behavior and the sources of persistence in inflation and output. First, a small-scale New-Keynesian model (NKM) is examined using the method of moment and maximum likelihood estimators with US data from 1960 to 2007. Then a formal test is used to compare the fit of two competing specifications in the New-Keynesian Phillips Curve (NKPC) and the IS equation, that is, backward- and forward-looking behavior. Accordingly, the inclusion of a lagged term in the NKPC and the IS equation improves the fit of the model while offsetting the influence of inherited and extrinsic persistence; it is shown that intrinsic persistence plays a major role in approximating inflation and output dynamics for the Great Inflation period. However, the null hypothesis cannot be rejected at the 5% level for the Great Moderation period, that is, the NKM with purely forward-looking behavior and its hybrid variant are equivalent. Monte Carlo experiments investigate the validity of chosen moment conditions and the finite sample properties of the chosen estimation methods. Finally, the empirical performance of the formal test is discussed along the lines of the Akaike's and the Bayesian information criterion.

This paper surveys the treatment of expectations in estimated Dynamic Stochastic General Equilibrium (DSGE) macroeconomic models.

A recent notable development in the empirical macroeconomics literature has been the rapid growth of papers that build structural models, which include a number of frictions and shocks, and which are confronted with the data using sophisticated full-information econometric approaches, often using Bayesian methods.

A widespread assumption in these estimated models, as in most of the macroeconomic literature in general, is that economic agents' expectations are formed according to the Rational Expectations Hypothesis (REH). Various alternative ways to model the formation of expectations have, however, emerged: some are simple refinements that maintain the REH, but change the information structure along different dimensions, while others imply more significant departures from rational expectations.

I review here the modeling of the expectation formation process and discuss related econometric issues in current structural macroeconomic models. The discussion includes benchmark models assuming rational expectations, extensions based on allowing for sunspots, news, sticky information, as well as models that abandon the REH to use learning, heuristics, or subjective expectations.

Expectations play a crucial role in finance, macroeconomics, monetary economics, and fiscal policy. In the last decade a rapidly increasing number of laboratory experiments have been performed to study individual expectation formation, the interactions of individual forecasting rules, and the aggregate macro behavior they co-create. The aim of this article is to provide a comprehensive literature survey on laboratory experiments on expectations in macroeconomics and finance. In particular, we discuss the extent to which expectations are rational or may be described by simple forecasting heuristics, at the individual as well as the aggregate level.