http://repub.eur.nl/res/aut/4260/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/38711/ 2013-01-28T00:00:00Z This article revisits the accuracy of inflation forecasting using activity and expectations variables. We apply Bayesian model averaging across different regression specifications selected from a set of potential predictors that includes lagged values of inflation, a host of real activity data, term structure data, (relative) price data, and surveys. In this model average, we can entertain different channels of structural instability, by either incorporating stochastic breaks in the regression parameters of each individual specification within this average, or allowing for breaks in the error variance of the overall model average, or both. Thus, our framework simultaneously addresses structural change and model uncertainty that would unavoidably affect any inflation forecast model. The different versions of our framework are used to model U.S. personal consumption expenditures (PCE) deflator and gross domestic product (GDP) deflator inflation rates for the 1960–2011 period. A real-time inflation forecast evaluation shows that averaging over many predictors in a model that at least allows for structural breaks in the error variance results in very accurate point and density forecasts, especially for the post-1984 period. Our framework is especially useful when forecasting, in real-time, the likelihood of lower-than-usual inflation rates over the medium term. This article has online supplementary materials. http://repub.eur.nl/res/pub/16709/ 2009-09-10T00:00:00Z This paper revisits inflation forecasting using reduced form Phillips curve forecasts, i.e., inflation forecasts using activity and expectations variables. We propose a Phillips curve-type model that results from averaging across different regression specifications selected from a set of potential predictors. The set of predictors includes lagged values of inflation, a host of real activity data, term structure data, nominal data and surveys. In each of the individual specifications we allow for stochastic breaks in regression parameters, where the breaks are described as occasional shocks of random magnitude. As such, our framework simultaneously addresses structural change and model certainty that unavoidably affects Phillips curve forecasts. We use this framework to describe PCE deflator and GDP deflator inflation rates for the United States across the post-WWII period. Over the full 1960-2008 sample the framework indicates several structural breaks across different combinations of activity measures. These breaks often coincide with, amongst others, policy regime changes and oil price shocks. In contrast to many previous studies, we find less evidence for autonomous variance breaks and inflation gap persistence. Through a \\textit{real-time} out-of-sample forecasting exercise we show that our model specification generally provides superior one-quarter and one-year ahead forecasts for quarterly inflation relative to a whole range of forecasting models that are typically used in the literature. http://repub.eur.nl/res/pub/1642/ 2000-03-24T00:00:00Z In this paper a likelihood-based multivariate unit root testing framework is utilized to test whether the real exchange rates of G10 countries are non-stationary. The framework uses a likelihood ratio statistic which combines the information across all involved countries while retaining heterogeneous rates of mean reversion. This likelihood ratio statistic has an asymptotic distribution which can be typified as a summation of squared, univariate Dickey and Fuller (1979) distributions. Our multivariate unit root tests indicate that bilateral G10 real exchange rates are stationary, irrespective of the numeraire country. We also analyze per panel the time necessary to have an adjustment to a shock in the individual real exchange rates. From this analysis it becomes apparent that there are significant cross-country differences in the adjustment of individual real exchange rates within each panel. http://repub.eur.nl/res/pub/7718/ 1999-07-28T00:00:00Z We propose in this paper a likelihood-based framework for cointegration analysis in panels of a fixed number of vector error correction models. Maximum likelihood estimators of the cointegrating vectors are constructed using iterated Generalized Method of Moments estimators. Using these estimators we construct likelihood ratio statistics to test for a common cointegration rank across the individual vector error correction models, both with heterogeneous and homogeneous cointegrating vectors. The corresponding limiting distributions are a summation of the limiting behavior of Johansen (1991) trace statistics. We also incorporate both unrestricted and restricted deterministic components which are either homogeneous or heterogeneous. The proposed framework is applied on a data set of exchange rates and appropriate monetary fundamentals. The test results show strong evidence for the validity of the monetary exchange rate model within a panel of vector error correction models for three major European countries, whereas the results based on individual vector error correction models for each of these countries separately are less supportive. http://repub.eur.nl/res/pub/7750/ 1998-07-15T00:00:00Z Pure time series-based tests fail to find empirical support for monetary exchange rate models. In this paper we apply pooled time series estimation on a forward-looking monetary model, resulting in parameter estimates which are in compliance with the underlying theory. Based on a panel version of the Engle and Granger (1987) two-step procedure we find that the residuals of our pooled estimated model are stationary. This indicates that on a pooled time series level there is cointegration between the exchange rate and the macroeconomic fundamentals of this monetary model.