This paper studies asymptotically the bias of the fixed effect (FE) estimator induced by cross-section heterogeneity in the slope parameters of stationary vector autoregressions (VARs). The paper also compares the FE, the mean group estimator (MG), and a simple instrumental variable alternative...

We estimate a latent factor model that decomposes international stock returns into global, country-, and industry-specific shocks and allows for stock-specific exposures to these shocks. We find that across stocks there is substantial dispersion in these exposures, which is partly explained by...

This is the third of a series of papers that are being written as part of a larger project to estimate a small quarterly Global Projection Model (GPM). The GPM project is designed to improve the toolkit for studying both own-country and cross-country linkages. In this paper, we estimate a small...

This paper constructs new business cycle indices for Argentina, Brazil, Chile, and Mexico based on common dynamic factors extracted from a comprehensive set of sectoral output, external data, and fiscal and financial variables spanning over a century. The constructed indices are used to derive a...

If permanent output is uncertain, tax smoothing can be perilous: both debt levels and tax rates are difficult to stabilize and may drift upwards. One practical remedy would be to target the debt. However, our simulations confirm that such a policy would require undesirably volatile fiscal...

This paper presents a multivariate (MV) methodology for obtaining measures of excess demand that can facilitate discussion of monetary policy issues and improve policy decisions. Using data for the Czech Republic, a growing economy undergoing major structural change, it shows how the use of more...

We study the effects of oil-price shocks on the U.S. economy combining narrative and quantitative approaches. After examining daily oil-related events since 1984, we classify them into various event types. We then develop measures of exogenous shocks that avoid endogeneity and predictability...

This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited Information Bayesian Model Averaging (LIBMA) methodology and then test it using simulated data. Simulation...