Panel data framework has often been used to build Early Warning Systems for financial crises. This paper questions the implicit assumption that crises are homogenously caused by identical factors. It suggests a preliminary step aiming at forming optimal country clusters.

The aim of this paper is to study the concept of separability in multiple nonstationary time series displaying both common stochastic trends and common stochastic cycles. When modeling the dynamics of multiple time series for a panel of several entities such as countries, sectors, firms,...

This paper unifies two seemingly separate approaches to test weak exogeneity in dynamic regression models with Lagrange-mulptiplier statistics. The first class of tests focuses on the orthogonality between innovations and conditioning variables, and thus is related to the Durbin-Wu-Hausman...

In spite of the increased use of factor-augmented regressions in recent years, little is known regarding the relative merits of the two main approaches to estimation and inference, namely, the cross-sectional average and principal component estimators. By providing a formal comparison of the...

[spa] Modelos con corrección de error y funciones de importación agregadas, . por Jean-Pierre Urbain.. . Este artículo tiene por objeto presentar la modelización empírica de las importaciones agregadas de dos economías europeas abiertas (Bélgica y Holanda). Este análisis se funda en una...

type="main" xml:lang="en" <title type="main">Abstract</title> <p>In this article, we investigate the validity of the univariate autoregressive sieve bootstrap applied to time series panels characterized by general forms of cross-sectional dependence, including but not restricted to cointegration. Using the final equations...</p>

In an influential paper, Pesaran [Pesaran, M.H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74, 967–1012] proposes a very simple estimator of factor-augmented regressions that has since then become very popular. In this note...