Research Database

This paper presents a simple counterexample to the belief that policy cooperation among benevolent governments is desirable. It also explains circumstances under which such counterexamples are possible and relates them to the literature on time inconsistency.

The neoclassical growth model studied in Kydland and Prescott [1982] is modified to permit the capital utilization rate to vary. The effect of this modification is to increase the amplitude of the aggregate fluctuations predicted by theory as the equilibrium response to technological shocks. If following Solow [1957], the changes in output not accounted for by changes in the labor and tangible capital inputs are interpreted as being the technology shocks, the statistical properties of the fluctuations in the post-war United States economy are close in magintude and nature to those predicted by theory.

This paper presents a completely worked example applying the frequency domain estimation strategy proposed by Hansen and Sargent [1980, 1981a]. A bivariate, high order continuous time autoregressive moving average model is estimated subject to the restrictions implied by the rational expectations model of the term structure of interest rates. The estimation strategy takes into account the fact that one of the data series are point-in-time observations, while the other are time averaged. Alternative strategies are considered for taking into account nonstationarity in the data. Computing times reported in the paper demonstrate that estimation using the techniques of Hansen and Sargent is inexpensive.

This paper examines the quantitative importance of temporal aggregation bias in distorting parameter estimates and hypothesis tests. Our strategy is to consider two empirical examples in which temporal aggregation bias has the potential to account for results which are widely viewed as being anomalous from the perspective of particular economic models. Our first example investigates the possibility that temporal aggregation bias can lead to spurious Granger causality relationships. The quantitative importance of this possibility is examined in the context of Granger causal relations between the growth rates of money and various measures of aggregate output. Our second example investigates the possibility that temporal aggregation bias can account for the slow speeds of adjustment typically obtained with stock adjustment models. The quantitative importance of this possibility is examined in the context of a particular class of continuous and discrete time equilibrium models of inventories and sales. The different models are compared on the basis of the behavioral implications of the estimated values of the structural parameters which we obtain and their overall statistical performance. The empirical results from both examples provide support for the view that temporal aggregation bias can be quantitatively important in the sense of significantly distorting inference.

We describe a simple environment in which assets of varying qualities may be used for transactions and consumption. The quality of an asset is known to the seller but not the buyer. We show that this feature can generate a negative relationship between the transactions velocities of assets and their rates of return. We also discuss several versions of Gresham's Law which hold in this environment.