Since the publication (1976) of the classic Lucas critique, researchers in empirical macroeconomics have endeavored to specify models that capture the underlying dynamic decision-making behavior of consumers and firms who require forecasts of future events. Recently, a number of researchers have developed simple models that have become the workhorses for monetary policy analysis. The models vary considerably with regard to optimizing foundations and explicit treatment of expectations. However, relatively little effort has been devoted to testing the empirical importance of the Lucas critique for these simple models. Can one find specifications that are policy-invariant? This paper develops and implements a set of tests for several monetary policy models used extensively in the literature. In particular, we attempt to test the robustness of optimizing versus nonoptimizing models to changes in the monetary policy regime. We present evidence that shows that some forward-looking models from the recent literature may be less stable than their better-fitting backward-looking counterparts.

This paper examines the out-of-sample performance of various financial variables as predictors of U.S. recessions. Series such as interest rates and spreads, stock prices, and monetary aggregates are evaluated individually and in comparison with other financial and nonfinancial indicators. The analysis focuses on out-of-sample performance from one to eight quarters ahead. Results show that stock prices are useful with one- to three-quarter horizons, as are some well-known macroeconomic indicators. Beyond one quarter, however, the slope of the yield curve emerges as the clear individual choice and typically performs better by itself out of sample than in conjunction with other variables.

Empirical research over the last decade has uncovered predictive relationships between the slope of the yield curve and subsequent real activity and inflation. Some of these relationships are highly significant, but their theoretical motivations suggest that they may not be stable over time. We use recent econometric techniques for break testing to examine whether the empirical relationships are in fact stable. We consider continuous models, which predict either economic growth or inflation, and binary models, which predict either recessions or inflationary pressure. In each case, we draw on evidence from Germany and the United States. Models that predict real activity are somewhat more stable than those that predict inflation, and binary models are more stable than continuous models. The model that predicts recessions is stable over our full sample period in both Germany and the United States.