TESTING RESTRICTIONS IN NORMAL DATA MODELS USING GIBBS SAMPLING

The problem of testing a set of restrictions R(q)=0 in a complex hierarchical model is considered. We propose a different approach from the standard PO ratio test, which can be viewed as the Bayesian analogous to the classical Wald type test. With respect to the PO ratio, it has the advantage of being easier to implement and, unlike the PO ratio test, it can be computed also when some prior in the hierarchy is diffuse. Several Monte Carlo simulations show that the procedure scores very well both in terms of power and unbiasedness, generally doing as well as the standard PO ratio approach, or even better in cases where the degree of coefficient heterogeneity is not high.Linear restrictions, Gibbs sampling, Monte Carlo

Monetary Policy Analysis in Real-Time. Vintage combination from a real-time dataset

This paper provides a general strategy for analyzing monetary policy in real time which accounts for data uncertainty without explicitly modelling the revision process. The strategy makes use of all the data available from a real-time data matrix and averages model estimates across all data releases. Using standard forecasting and policy models to analyze monetary authorities’ reaction functions, we show that this simple method can improve forecasting performance and provide reliable estimates of the policy model coe¢cients associated with small central bank losses, in particular during periods of high macroeconomic uncertainty.Monetary policy, Taylor rule, Real-time data, Great Moderation, Forecasting.

Estimating multi-country VAR models

This paper describes a methodology to estimate the coefficients, to test specification hypotheses and to conduct policy exercises in multi-country VAR models with cross unit interdependencies, unit specific dynamics and time variations in the coefficients. The framework of analysis is Bayesian: a prior flexibly reduces the dimensionality of the model and puts structure on the time variations; MCMC methods are used to obtain posterior distributions; and marginal likelihoods to check the fit of various specifications. Impulse responses and conditional forecasts are obtained with the output of MCMC routine. The transmission of certain shocks across G7 countries is analyzed. JEL Classification: C3, C5, E5Flexible priors, International transmission, Markov Chain Monte Carlo methods, Multi country VAR

Global inflation

This paper shows that inflation in industrialized countries is largely a global phenomenon. First, the inflation rates of 22 OECD countries have a common factor that alone accounts for nearly 70 percent of their variance. This large variance share that is associated with Global Inflation is not only due to the trend components of inflation (up from 1960 to 1980 and down thereafter) but also to fluctuations at business cycle frequencies. Second, we show that, in conformity to the prediction of New Keynesian open economy models, there is little spillover of inflationary shocks across countries. The comovement of inflation comes largely from common shocks. Global Inflation is a function of real developments at short horizons and monetary developments at longer horizons. Third, there is a robust "error correction mechanism" that brings national inflation rates back to Global Inflation. A simple model that accounts for this feature consistently beats the previous benchmarks used to forecast inflation 4 to 8 quarters ahead across samples and countries.Inflation (Finance)

The Effects of Monetary Policy on Unemployment Dynamics Under Model Uncertainty. Evidence from the US and the Euro Area

This paper explores the role that the imperfect knowledge of the structure of the economy plays in the uncertainty surrounding the effects of rule-based monetary policy on unemployment dynamics in the euro area and the US. We employ a Bayesian model averaging procedure on a wide range of models which differ in several dimensions to account for the uncertainty that the policymaker faces when setting the monetary policy and evaluating its effect on real economy. We find evidence of a high degree of dispersion across models in both policy rule parameters and impulse response functions. Moreover, monetary policy shocks have very similar recessionary effects on the two economies with a different role played by the participation rate in the transmission mechanism. Finally, we show that a policy maker who does not take model uncertainty into account and selects the results on the basis of a single model may come to misleading conclusions not only about the transmission mechanism, but also about the differences between the euro area and the US, which are on average essentially small.Monetary policy, Model uncertainty, Bayesian model averaging, Unemployment gap, Taylor rule

Inflation Forecasts, monetary policy and unemployment dynamics: evidence from the US and the euro area

This paper explores the role that inflation forecasts play in the uncertainty surrounding the estimated effects of alternative monetary rules on unemployment dynamics in the euro area and the US. We use the inflation forecasts of 8 competing models in a standard Bayesian VAR to analyse the size and the timing of these effects, as well as to quantify the uncertainty relative to the different inflation models under two rules. The results suggest that model uncertainty can be a serious issue and strengthen the case for a policy strategy that takes into account several sources of information. We find that combining inflation forecasts from many models not only yields more accurate forecasts than those of any specific model, but also reduces the uncertainty associated with the real effects of policy decisions. These results are in line with the model-combination approach that central banks already follow when conceiving their strategy. JEL Classification: C53, E24, E37E24, E37, Inflation forecasts, JEL Classification: C53, Model uncertainty, Unemployment

ClubMed? Cyclical fluctuations in the Mediterranean basin

We investigate macroeconomic fluctuations in the Mediterranean basin, their similarities and convergence. A model with four indicators, roughly covering the West, the East and the Middle East and the North Africa portions of the Mediterranean, characterizes well the historical experience since the early 1980. Idiosyncratic causes still dominate domestic cyclical fluctuations in many countries. Convergence and divergence coexist are local and transitory. The cyclical outlook for the next few years is rosier for the East than for the West.Bayesian Methods; Business cycles; Mediterranean basin; Developing and developed countries.

The effects of monetary policy on unemployment dynamics under model uncertainty: evidence from the US and the euro area

This paper explores the role that the imperfect knowledge of the structure of the economy plays in the uncertainty surrounding the effects of rule-based monetary policy on unemployment dynamics in the euro area and the US. We employ a Bayesian model averaging procedure on a wide range of models which differ in several dimensions to account for the uncertainty that the policymaker faces when setting the monetary policy and evaluating its effect on real economy. We find evidence of a high degree of dispersion across models in both policy rule parameters and impulse response functions. Moreover, monetary policy shocks have very similar recessionary effects on the two economies with a different role played by the participation rate in the transmission mechanism. Finally, we show that a policy maker who does not take model uncertainty into account and selects the results on the basis of a single model may come to misleading conclusions not only about the transmission mechanism, but also about the differences between the euro area and the US, which are on average essentially small. JEL Classification: C11, E24, E52, E58Bayesian model averaging, Model uncertainty, monetary policy, Taylor rule, Unemployment gap

Measuring contagion with a Bayesian, time-varying coefficient model

JEL Classification: C11, C15, F41, F42, G15Contagion, Gibbs sampling, Heteroskedasticity, Omitted variable bias, Time-varying coefficient models

Information combination and forecast (st)ability evidence from vintages of time-series data

This paper explores the role of model and vintage combination in forecasting, with a novel approach that exploits the information contained in the revision history of a given variable. We analyse the forecast performance of eleven widely used models to predict inflation and GDP growth, in the three dimensions of accuracy, uncertainty and stability by using the real-time data set for macroeconomists developed at the Federal Reserve Bank of Philadelphia. Instead of following the common practice of investigating only therelationship between first available and fully revised data, we analyse the entire revision history for each variable and extract a signal from the entire distribution of vintages of a given variable to improve forecast accuracy and precision. The novelty of our study relies on the interpretation of the vintages of a real time data base as related realizations or units of a panel data set. The results suggest that imposing appropriate weights on competing models of inflation forecasts and output growth — reflecting the relative ability each model has over different sub-sample periods — substantially increases the forecast performance. More interestingly, our results indicate that augmenting the information set with a signal extracted from all available vintages of time-series consistently leads to a substantial improvement in forecast accuracy, precision and stability. JEL Classification: C32, C33, C53data and model uncertainty, forecast combination, real-time data