This paper is a general investigation of temporal aggregation in time series analysis. It encompasses traditional research on time aggregation as a particular case and extends the analysis to irregular intervals of aggregation. The Data Generating Process is allowed to evolve at regular,...

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

In this paper we compare alternative approaches for dating the Euro area business cycle and analyzing its characteristics. First, we extend a commonly used dating procedure to allow for length, size and amplitude restrictions, and to compute the probability of a phase change. Second, we apply...

This paper studies the impact of public infrastructure on economic performance. We employ three different methodologies to estimate the returns to public investment. First, we relate growth in total factor productivity to accumulation of public capital. Second, we assess the role of public...

We show how the use of panel data methods such as those proposed in single equations by Kao (1999) and Pedroni (1999) or in systems by Larsson and Lyhagen (1999) to investigate economic hypotheses such as purchasing power parity or the term structure of interest rates may be affected by the...

In this paper we introduce a non-parametric estimation method for a large Vector Autoregression (VAR) with time-varying parameters. The estimators and their asymptotic distributions are available in closed form. This makes the method computationally efficient and capable of handling information...

Global developments play an important role in domestic inflation rates. Previous literature has found that a substantial amount of the variation in a large set of national inflation rates can be explained by a single global factor. However, inflation volatility has been typically neglected,...

Based on evidence gathered from a newly built large macroeconomic data set for the UK, labeled UK-MD and comparable to similar datasets for the US and Canada, it seems the most promising avenue for forecasting during the pandemic is to allow for general forms of nonlinearity by using machine...

This paper proposes the use of Bayesian model averaging (BMA) as a tool to select the predictors' set for bridge models. BMA is a computationally feasible method that allows us to explore the model space even in the presence of a large set of candidate predictors. We test the performance of BMA...

The debate on the forecasting ability in economics of non-linear models has a long history, and the Great Recession provides us with an opportunity for a re-assessment of the forecasting performance of several classes of non-linear models, widely used in applied macroeconomic research. In this...