A0600
Title: Identification of common factors in group factor models
Authors: Firmin Ayivodji - Universite de Montreal and CIREQ (Canada) [presenting]
Abstract: The comovement is examined among factors extracted from two distinct large panels of variables. It is shown that estimating factors introduces a bias in the estimated correlation between factors, which disappears if the factors are estimated from panel data sets containing many cross-sectional series. It is shown that a modified version of the wild bootstrap algorithm can correct the bias and provide reliable inference on the correlation of interest. Additionally, the modified wild bootstrap method is applied to analyze the influence of institutional factors on economic growth and the degree of synchronization of business cycles in developed and emerging economies.
