This paper proposes a simple explanation for the frequent appearance of a price puzzle in VARs designed for monetary policy analysis. It suggests that the best method of solving the puzzle implies a close connection between theory and empirics rather than the introduction of a commodity price....

We summarize some methods useful in formulating and solving Hansen-Sargent robust control problems, and suggest extensions to discretion and simple rules. Matlab, Octave, and Gauss software is provided. We illustrate these extensions with applications to the term structure of interest rates, the...

Abel (2002) shows that pessimism and doubt in the subjective distribution of the growth rate of consumption reduce the riskfree rate puzzle and the equity premium puzzle. We quantify the amount of pessimism and doubt in survey data on US consumption and income. Individual forecasters are in fact...

Few propositions in macroeconomics are less controversial than long-run money neutrality, yet clear and robust empirical support has not been found in time series studies. Bernanke and Mihov (1998) are comparatively successful in this hunt, but their output response to monetary policy shocks...

New Keynesian models of monetary policy assign no role to monetary aggregates, in the sense that the level of output, prices, and interest rates can be determined without knowledge of the quantity of money. We evaluate the empirical validity of this prediction by studying the effects of shocks...

Most of the literature on monetary policy delegation assumes that the government can credibly commit to the delegation contract, an assumption criticized by McCallum. This paper provides foundations for the assumption that renegotiating a delegation contract can be costly by illustrating how...

Bayesian inference for DSGE models is typically carried out by single block random walk Metropolis, involving very high computing costs. This paper combines two features, adaptive independent Metropolis-Hastings and parallelisation, to achieve large computational gains in DSGE model estimation....

We demonstrate improvements in predictive power when introducing spline functions to take account of highly non-linear relationships between firm failure and earnings, leverage, and liquidity in a logistic bankruptcy model. Our results show that modeling excessive non-linearities yields...

We model a regression density nonparametrically so that at each value of the covariates the density is a mixture of normals with the means, variances and mixture probabilities of the components changing smoothly as a function of the covariates. The model extends existing models in two important...

We introduce a non-Gaussian dynamic mixture model for macroeconomic forecasting. The Locally Adaptive Signal Extraction and Regression (LASER) model is designed to capture relatively persistent AR processes (signal) contaminated by high frequency noise. The distribution of the innovations in...