Recent studies have highlighted the importance of news shocks in the literature on business cycles, that is, a-priori information that agents receive about future developments in the economy. To examine whether the news shocks can be a major source of aggregate fluctuations, in the first chapter I quantify the relative importance of the news shocks to total factor productivity (TFP) and surprised technology changes by employing two methods. The first method is the Beaudry and Portier’s identification schemes (2006) and the second method is a two-step approach I develop in this study. Empirical results on the US quarterly data show that the news shocks play an important role in generating the business cycles, while the surprised technology changes is not a potential source of macro-economic fluctuations. In addition, the two-step approach seems to be able to solve the identification problem raised in the high dimensional systems in SVAR analysis. In the second chapter, I extend the empirical study of the news shocks to the European countries to test for the generality of the issues about the news shocks raised in the US literature. The empirical results are supportive for the hypothesis of news driven business cycles.