Research Database

This paper analyzes the effects of money injections on interest rates and exchange rates in a model in which agents must pay a Baumol-Tobin style fixed cost to exchange bonds and money. Asset markets are endogenously segmented because this fixed cost leads agents to trade bonds and money only infrequently. When the government injects money through an open market operation, only those agents that are currently trading absorb these injections. Through their impact on these agents’ consumption, these money injections affect real interest rates and real exchange rates. We show that the model generates the observed negative relation between expected inflation and real interest rates. With moderate amounts of segmentation, the model also generates other observed features of the data: persistent liquidity effects in interest rates and volatile and persistent exchange rates. A standard model with no fixed costs can produce none of these features.

This paper proposes a simple method for guiding researchers in developing quantitative models of economic fluctuations. We show that a large class of models, including models with various frictions, are equivalent to a prototype growth model with time-varying wedges that, at least at face value, look like time-varying productivity, labor taxes, and capital income taxes. We label the time-varying wedges as efficiency wedges, labor wedges, and investment wedges. We use data to measure these wedges and then feed them back into the prototype growth model. We then assess the fraction of fluctuations accounted for by these wedges during the great depressions of the 1930s in the United States, Germany, and Canada. We find that the efficiency and labor wedges in combination account for essentially all of the declines and subsequent recoveries. Investment wedges play, at best, a minor role.

Constant returns to scale is a central construct of neoclassical theory. Previous studies argued that one must adopt a specification of the production function with substantial unobserved service variation to reconcile constant returns with the data. Some economists have argued that this finding has not resolved the size of returns to scale, since factor service variation is unobserved, and there is no generally accepted theory to guide specification of this alternative framework. In this paper we show that the stochastic version of the neoclassical growth model delivers an orthogonality condition which can be used to estimate returns to scale. Rather than the standard finding of increasing returns, we show that standard theory and conventional measures of output and inputs yield estimates of constant returns to scale at the aggregate level. Our estimates also suggest that factor service variation is not an important determinant of output fluctuations.

Prediction interval tests are applied to the reduced forms of two quarterly models of the U.S. (the "old" FRB-MIT model and the Michigan model). The results illustrate the range of tests one can perform on an estimated simultaneous equation model. In particular, the tests determine whether ex post forecast errors can be attributed to structural deficiencies of the models. The paper examines confidence regions and other aspects of forecast distributions-comparisons between mean forecasts and nonstochastic forecasts, comparisons between, forecast variances from multiperiod endogenous simulations and those from one period simulations, and comparisons between forecast variances and residual variances.