The asymptotic efficiency of the indirect estimation methods, such as the efficient method of moments and indirect inference, depends on the choice of the auxiliary model. Up to date, this choice is somehow ad hoc and based on an educated guess of the researcher. In this article we develop three...

We modify the criterion by Bai and Ng (2002) for determining the number of factors in approximate factor models. As in the original criterion, for any given number of factors we estimate the common and idiosyncratic components of the model by applying principal component analysis. We select the...

We adopt a time-varying cointegration test to discriminate among different empirical studies claiming to find a stable Euro Area money demand equation. A time invariant relation explaining real balances is rejected by data, even when accounting for housing, financial and labour markets....

We propose a new method for multivariate forecasting which combines Dynamic Factor and multivariate GARCH models. We call the model Dynamic Factor GARCH, as the information contained in large macroeconomic or financial datasets is captured by a few dynamic common factors, which we assume being...

This paper considers the distribution of consumption expenditures for a large sample of documented and undocumented immigrants in Italy. Using the one-sided and two-sided Kolmogorov-Smirnov tests, we show that the distribution of consumption of immigrants with higher permanence in the host...

We estimate the parameters of an elliptical distribution by means of a multivariate extension of the Method of Simulated Quantiles (MSQ) of Dominicy and Veredas (2010). The multivariate extension entails the challenge of the construction of a function of quantiles that is informative about the...

Realized volatilities, when observed through time, share the following stylized facts: co–movements, clustering, long–memory, dynamic volatility, skewness and heavy–tails. We propose a simple dynamic factor model that captures these stylized facts and that can be applied to vast panels of...

We establish the asymptotic normality of marginal sample quantiles for S–mixing vector stationary processes. S–mixing is a recently introduced and widely applicable notion of dependence. Results of some Monte Carlo simulations are given.