This paper explores the statistical properties of household consumption-expenditurebudget share distributions —defined as the share of household total expenditure spentfor purchasing a specific category of commodities— for a large sample of Italianhouseholds in the period 1989-2004. We find...

This paper explores the statistical properties of house-hold consumption-expenditure budget share distributions —defined as the share of household total expenditure spent for purchasing a specific category of commodities— for a large sample of Italian households in the period 1989-2004. We...

We review, under a historical perspective, the development of the problem of nonfundamentalness of Moving Average (MA) representations of economic models. Nonfundamentalness typically arises when agents’ information space is larger than the econometrician’s one. Therefore it is impossible...

We propose a refinement of the criterion by Bai and Ng [2002] for determining the number of static factors in factor models with large datasets. It consists in multi-plying the penalty function by a constant which tunes the penalizing power of the function itself as in the Hallin and Liška...

We propose a new method for multivariate forecasting which combines Dynamic Factor and multivariate GARCH models. The information contained in large datasets is captured by few dynamic common factors, which we assume being conditionally heteroskedastic. After presenting the model, we propose a...

We test the performance of a host of real and financial variables as early warning indicators for costly aggregate asset price boom/bust cycles, using data for 18 OECD countries between 1970 and 2007. A signalling approach is used to predict asset price booms that have relatively serious real...

This paper documents macroeconomic forecasting during the global financial crisis by two key central banks: the European Central Bank and the Federal Reserve Bank of New York. The paper is the result of a collaborative effort between staff at the two institutions, allowing us to study the...

This paper aims at providing policymakers with a set of early warning indicators helpful in guiding decisions on when to activate macroprudential tools targeting excessive credit growth and leverage. To robustly select the key indicators we apply the “Random Forest” method, which bootstraps...