This paper compares different ways to estimate the current state of the economy using factor models that can handle unbalanced datasets. Due to the different release lags of business cycle indicators, data unbalancedness often emerges at the end of multivariate samples, which is sometimes...

This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MF-VAR) approaches to model speci…cation in the presence of mixed-frequency data, e.g., monthly and quarterly series. MIDAS leads to parsimonious models based on exponential lag polynomials for the coe¢ cients,...

This paper discusses pooling versus model selection for now- and forecasting in the presence of model uncertainty with large, unbalanced datasets. Empirically, unbalanced data is pervasive in economics and typically due to di¤erent sampling frequencies and publication delays. Two model classes...

Our objective is to identify a way of checking empirically the extent to which expectations are de-coupled from inflation, how well they might be anchored in the long run, and at what level. This methodology allows us then to identify a measure for the degree of anchorness, and as anchored...

Our objective is to identify a way of checking empirically the extent to which expectations are de-coupled from inflation, how well they might be anchored in the long run, and at what level. This methodology allows us then to identify a measure for the degree of anchorness, and as anchored...

A theoretical model for growth or inflation should be able to reproduce the empirical features of these variables better than competing alternatives. Therefore, it is common practice in the literature, whenever a new model is suggested, to compare its performance with that of a benchmark model....

This paper analyses two features of concern to policy-makers in the countries of the prospective European Monetary Union: the solvency of their government’s finances; and the accuracy of fiscal forecasts. Extending the existing methodology of solvency tests, the paper finds that, with few...

Time series models are often adopted for forecasting because of their simplicity and good performance. The number of parameters in these models increases quickly with the number of variables modelled, so that usually only univariate or small-scale multivariate models are considered. Yet, data...

We analyse the relative performance of the IMF, OECD and EC in forecasting the government deficit, as a ratio to DGP, for the G7 countries. Interesting differences across countries emerge, sometimes supporting the hypothesis of an asymmetric loss function (i.e., of a preference for...

New-Keynesian models are characterized by the presence of expectations as explanatory variables. To use these models for policy evaluation, the econometrician must estimate the parameters of expectation terms. Standard estimation methods have several drawbacks, including possible lack of...