In the field of empirical macroeconomics factor-augmented vector autoregressive (FAVAR) models have become a popular tool in explaining how economic variables interact over time. FAVAR is based upon a data-reduction step using factor estimation, which are then employed in a vector autoregressive model. This paper aims to study alternative methods regarding factor estimation. More precisely, we compare the generally used principal component method with the uncomplicated common correlated effect estimation. Results show low divergence between the two factor estimation methods employed, indicating interchangeability between the two estimation approaches.

Until very recently, most emerging market economies have achieved higher growth rates for the last decade. It is controversial whether this good economic environment is due to domestic reforms or due to favorable external factors. In this framework, the main aim of this study is to investigate the structure and sources of business cycles in emerging market economies and to determine how these cycles differ than those in developed countries. The role of external and domestic factors on business cycles are analyzed by applying not only the conventional panel data estimations but also common correlated effects panel mean group method which is introduced by Peseran (2006). Besides, the convergence of business cycles in emerging market economies to the business cycles in developed countries is discussed based on factor analysis. The major results indicate the common global factors are the leading source of the business cycles both in emerging market economies and developed countries. However, domestic determinants of fluctuations differ across two groups of countries. In addition, results show that in the last two decades fluctuations in emerging market economies have started to be more dependent on the fluctuations in developed countries.