The (Un-) Stable Relationship between The Exchange rate and its Fundamentals

This study investigates the relationship between the euro-dollar exchange rate and its underlying fundamentals by adopting non-linear time series modelling. We found that this relationship is episodically unstable. We also found that an equilibrium-distorting shock is likely to have a greater effect on the exchange rate during periods when the deviation between exchange rate and fundamentals is large; as a consequence, when the exchange rate is close to its equilibrium value it tends to be less sensitive to any shocks in the fundamentals.Non-linearity, Markov-switching Model, Fundamentals

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

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 coefficients associated with small central bank losses, in particular during periods of high macroeconomic uncertainty.monetary policy, Taylor rule, real-time data, great moderation, forecasting

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

Inflation models, optimal monetary policy and uncertain unemployment dynamics: Evidence from the US and the euro area

This paper explores the role that model uncertainty plays in determining the effect of monetary policy shocks on unemployment dynamics in the euro area and the US. We specify a range of BVARs that differ in terms of variables, lag structure, and the way the inflation process is modelled. For each model the central bank sets the interest rate minimizing a loss function. Given this solution, we quantify the impact of a monetary policy shock on unemployment for each model, and measure the degree of uncertainty as represented by the dispersion of both the policy rule parameters and the impulse response functions between models. The comparative evidence from the US and the euro area data indicates that model uncertainty is indeed an important feature, and that a model combination strategy might be a valuable advise to policymakers.Inflation models, Unemployment, Model uncertainty, Taylor rule, Impulse response analysis

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.

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

Asymmetric Effects of National-based Active Labour Market Policies

Labour market policies settled at national level imply a “one-size-fits-all” labour market strategy. This strategy might not sufficiently take into account region-specific economic structures. We employ a panel factor-augmented vector autoregression (FAVAR) to evaluate whether active labour market programmes (ALMPs) might asymmetrically affect labour markets at regional level in a data-rich environment. The paper focuses on Italian regions. Our results suggest that while in the South employment is mainly driven by social and economic context variables, in the North the employment dynamics is significantly explained by policy interventions. Finally, we suggest two main policy implications. First, the success of active policies depends on the regional labour market conditions. Second, policymakers should adjust labour policy strategy to the regional economic structureActive Labour Market Policies, FAVAR.

Evaluating the Dynamic Effects of Active Labour Policies in Italy

This paper analyses whether active labour market programmes (ALMP) have differing effects on unemployment and employment dynamics according to the particular region in which they are implemented. To this end, it analyses alternative theoretical and econometric models thought to capture the possible effects of active labour market policies on labour force dynamics. The econometric methodologies implemented are the generalized method of moment (GMM) and the panel vector autoregression (P-VAR). The evidence yielded by the GMM models suggests that the effects of different ALMP on unemployment are dissimilar across the Italian regions. It follows that some active programmes are likely to have a greater effect in the South than in the North. The results of the P-VAR models estimated are synthesised by impulse response analysis and forecast error variance decomposition. The impulse response analysis suggests that an increase in total ALMP gives rise to (i) a decrease in the unemployment rate and (ii) a significant increase in labour force participation. More interestingly, the results obtained from the error variance decomposition analysis show that unemployment movements are not driven by shocks in the ALMP and that, especially in the northern regions, atypical contracts shocks account for a substantial portion of unemployment dynamics.ALMP, GMM, P-VAR