We add a nominal tax system to a sticky-price monetary business cycle model. When nominal interest income is taxed, the coefficient on inflation in a Taylor-type monetary policy rule must be significantly larger than one in order for the model economy to have a determinate rational expectations equilibrium. When depreciation is treated as a charge against taxable income, an even larger weight on inflation is required in the Taylor rule in order to obtain a determinate and stable equilibrium. These results have obvious implications for assessing the historical conduct of monetary policy.
The durable goods sector is much more interest sensitive than the non-durables sector, and these sectoral differences have important implications for monetary policy. In this paper, we perform VAR analysis of quarterly US data and find that a monetary policy innovation has a peak impact on durable expenditures that is roughly five times as large as its impact on non-durable expenditures. We then proceed to formulate and calibrate a two-sector dynamic general equilibrium model that roughly matches the impulse response functions of the data. We derive the social welfare function and show that the optimal monetary policy rule responds to sector-specific inflation rates and output gaps. We show that some commonlyprescribed policy rules perform poorly in terms of social welfare, especially rules that put a higher weight on inflation stabilization than on output gap stabilization. By contrast, it is interesting that certain rules that react only to aggregate variables, including aggregate output gap targeting and rules that respond to a weighted average of price and wage inflation, may yield a welfare level close to the optimum given a typical distribution of shocks.
We report estimates of the dynamic effects of a technology shock, and then use these to estimate the parameters of a dynamic general equilibrium model with money. We find: (i) a positive technology shock drives up hours worked, consumption, investment and output; (ii) the positive response of hours worked reflects that the Fed has in practice accommodated technology shocks; (iii) model parameter values and functional forms that match the response of macroeconomic variables to monetary policy shocks also work well for technology shocks; (iv) while technology shocks account for a large fraction of the lower frequency component of economic fluctuations, they account for only a small part of the business cycle component of fluctuations.
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 on 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 wedge plays at best a minor role.
In this paper we make the following three claims. (1), in contradiction with the conventional view according to which the French depression was very different to that observed in the US, we argue that there are more similarities than differences between the French and U.S. experiences and therefore a common explanation should be sought. (2), poor growth in technological opportunities appear neither necessary nor sufficient to account for the French depression. (3), changes in institutional and market regulation appear necessary to account for the overall changes observed over the period. Moreover, we show that the size of these institutional changes may by themselves be enough to quantatively explain the French depression. However, at this time, we have no theory to explain the size or the timing of these changes.