This paper aims at providing a primer on the use of big data in macroeconomic nowcasting and early estimation. We discuss: (i) a typology of big data characteristics relevant for macroeconomic nowcasting and early estimates, (ii) methods for features extraction from unstructured big data to...

Different definitions of sustainability and of the empirical counterparts of the variables involved are reviewed in the paper by Michael Artis and Massimiliano Marcellino. They apply retrospective tests for fiscal sustainability along the lines of the paper by Fernandez and de Cos to EU...

This paper analyses the forecasting ability of economic summary indicators in EU economies. We employ the use of Partial Least Squares and Bayesian Shrinkage Regression methods and we predict the growth rates of quarterly GDP and Consumption and monthly Industrial Production. We find evidence...

This paper is concerned with the forecasting performance of variable reduction and variable selection methods using medium and large datasets. The variable reduction methods include Principal Components, Partial Least Squares and Bayesian Shrinkage Regression. The variable selection methods...

We consider forecasting key macroeconomic variables using many predictors extracted from the Eurostat PEEIs dataset. To avoid the curse of dimensionality, we rely on model selection and model reduction. For model selection we use heuristic optimisation of information criteria, including...

This paper investigates the performance of Financial Condition Indexes (FCIs) in forecasting four key macroeconomic variables of EU economies. A wide range of carefully selected financial indicators include Rates and Spreads, Stock Market Indicators and Macroeconomic Quantities. The results...

This paper investigates the estimation of turning points in the business cycles of six major EU economies and the EA. The core dating algorithm as implemented by King and Plosser (1994) is used here and it sheds some more light in the recent financial crisis. We are particularly concerned with...

A mismatch between the time scale of a structural VAR (SVAR) model and that of the time series data used for its estimation can have serious consequences for identification, estimation and interpretation of the impulse response functions. However, the use of mixed frequency data, combined with a...

With reference to S&P 500 daily returns, we report evidence of an in-sample predictive accuracy breakdown for realized variance by GARCH models in correspondence to the March 2020 Covid-19 outbreak. However, a variety of macroeconomic risk, political and social media sentiment uncertainty...

It is investigated whether Euro-area variables can be forecast better based on synthetic time series for the pre-Euro period or by using just data from Germany for the pre-Euro period. Our forecast comparison is based on quarterly data for the period 1970Q1 - 2003Q4 for ten macroeconomic...