Three papers in Bayesian empirical macroeconomics

These three related papers use a variety of Bayesian methods to examine the specification of "New Keynesian" dynamic stochastic general equilibrium (DSGE) models and their uses in forecasting and business cycle analysis.; In the first paper, "Forecasting output and inflation with a Bayesian VAR using a New Keynesian prior," I evaluate the forecasting performance of a simple New Keynesian DSGE model. I do this by using the model to calculate a prior mean and covariance matrix for the coefficients of a VAR forecasting model for output, inflation and interest rates, using Ingram and Whiteman's (1994) technique for using DSGE models to calculate priors for Bayesian vector autoregression (BVAR) forecasting models. The resulting BVAR generates forecasts of inflation competitive with those from a BVAR with a atheoretical prior. However, the New Keynesian BVAR results in very poor output forecasts, particularly in the short run, suggesting some source of misspecification in the New Keynesian DSGE model.; In the second paper, "Loss-based evaluation of a New Keynesian DSGE model," I evaluate and compare the in-sample specification of a simple New Keynesian DSGE model to a cash-credit model with flexible prices and to an identified Bayesian VAR, in a manner similar to Schorfheide's (2000) study of the portfolio adjustment cost model. I calculate Bayes factors for each model so as to calculate posterior probabilities for all three models, and construct a benchmark distribution for correlations and impulse response functions to which I can compare the correlations and impulse responses of the New Keynesian model, according to a variety of loss functions. I find that with a realistic monetary rule, both the flexible and New Keynesian DSGEs are competitive on a posterior odds basis with each other, as well as with the identified VAR. Very different levels of price stickiness, with very different policy implications, are compatible with the same data, making use of outside prior information crucial in assessing the role of the Phillips curve and of "supply-side" and "demand-side" shocks in business cycles.; This point is further underlined in the third paper, "Technology shocks versus monetary shocks: Identifying sources of business cycle fluctuations with a New Keynesian DSGE Model." Following recent papers such as that of Smets and Wouters (2002), I estimate by Bayesian methods similar to that in the previous paper a three-variable New Keynesian DSGE model of output, inflation and interest rates, including habit formation in preferences to improve the model's dynamics as well as stochastic price rigidity. I calculate Bayes factors for the model along with several Bayesian VAR models, and find it competitive with a four-lag BVAR. I use the DSGE model to estimate series for monetary shocks, technology/supply shocks, and autonomous demand shocks for the United States since 1965. I find that monetary policy shocks have probably been of only secondary importance, as compared to that of supply shocks, in movements in US inflation, as well as output, business cycles since 1965. My results conflict with those of Smets and Wouters for Europe, who found a larger role for monetary shocks; I argue that our differing prior assumptions regarding price stickiness are more likely to account for our different results than institutional differences between the US and Europe.