Research Database

In this paper, we review the relationship between inflation rates, nominal interest rates, and rates of growth of monetary aggregates for a large group of OECD countries. We conclude that the low-frequency behavior of these series maintains a close relationship, as predicted by standard quantity theory models. In an estimated model, we show those relationships to be relatively invariant to alternative frictions that can deliver very different high-frequency dynamics. We argue that these relationships are useful for policy design aimed at controlling inflation.

It is commonly asserted that with excess plant capacity, expansive policy stimulates output and lowers unemployment without substantially boosting inflation, while at full capacity most of the impact is on inflation. This assertion is critically examined. First, two common definitions of capacity--engineering and economic—are examined and found to be nebulous. The concepts of supply and demand are older, but better. Full capacity is reinterpreted as points where the supply curve is steep and excess capacity as points where it is fairly flat. Then the "Keynesian" model in which stimulative policy shifts only the demand curve is compared to the "classical" model where stimulative policy shifts both demand and supply curves. For the former model the assertion on capacity utilization is correct, while in the latter it is not. Empirical tests are performed to determine whether measured capacity utilization is useful for predicting inflation. The tests are ambiguous, but certainly do not strongly favor capacity utilization.

This paper presents maximum likelihood estimates of a real business cycle model very similar to one Kydland and Prescott [1982] suggested. The results of the paper conflict with Kydland and Prescott’s. The model leaves unexplained much of the variance of two key investment series, namely, structures and equipment. Also, much of the variation in the differences of per capita hours can be generated assuming that past leisure choices do not affect current utility.

This paper is motivated by observations concerning the size of the banking sector and the growth rate of the economy before and after successful stabilizations of high inflations. The facts suggest that the relative size of the banking sector increases during a period of accelerating inflation and decreases immediately following a successful monetary stabilization. Furthermore, the GDP growth rate is lower during the high inflation period than after stabilization. The goal of this paper is to develop a monetary growth model which is qualitatively consistent with these observations. The model we use is a variant of the Lucas and Stokey (1987) model of cash and credit goods. The main innovation in our model is that while cash goods and credit goods are perfect substitutes in consumption we posit different technologies for their production. We show that the model’s predictions on the impact of a permanent stabilization are consistent with the main real and monetary observations on high inflation countries.

This paper develops a vector autoregression (VAR) for macroeconomic time series which are observed at mixed frequencies – quarterly and monthly. The mixed-frequency VAR is cast in state-space form and estimated with Bayesian methods under a Minnesota-style prior. Using a real-time data set, we generate and evaluate forecasts from the mixed-frequency VAR and compare them to forecasts from a VAR that is estimated based on data time-aggregated to quarterly frequency. We document how information that becomes available within the quarter improves the forecasts in real time.