We develop uncertainty indices for the United States and Australia based on freely accessible, real time Google Trends data. Our Google Trends Uncertainty (GTU) indices are found to be positively correlated to a variety of alternative proxies for uncertainty available for these two countries....

We model U.S. post-WWII monthly data with a Smooth Transition VAR model and study the effects of an unanticipated increase in economic policy uncertainty on unemployment in recessions and expansions. We find the response of unemployment to be statistically and economically larger in recessions....

We estimate a nonlinear VAR to quantify the impact of economic policy uncertainty shocks originating in the US on the Canadian unemployment rate in booms and busts. We find strong evidence in favor of asymmetric spillover effects. Unemployment in Canada is shown to react to uncertainty shocks in...

The IFO Business Climate is the most important indicator for the business cycle in Germany. In 1993 the connection between the two components of the business climate – business situation and business expectations – was graphically portrayed by Ifo in a 4-quadrant scheme: the IFO Business...

This paper adopts a flexible framework to assess both short- and long-run business cycle linkages between six Latin American (LA) countries and the four largest economies in the world (namely the US, the Euro area, Japan and China) over the period 1980:I-2011:IV. The result indicate that within...

Traditional approaches to structural vector autoregressions can be viewed as special cases of Bayesian inference arising from very strong prior beliefs. These methods can be generalized with a less restrictive formulation that incorporates uncertainty about the identifying assumptions...

This paper is concerned with the apparent change in the U.S. oil price-macroeconomy relationship. It is investigated to what extent this change can be accounted for by the large oil price surges witnessed in the 1970s. The innovative approach of rolling impulse responses is applied and both the...

In this paper we use a general procedure to detect structural breaks at unknown points in time which allows for different orders of integration and deterministic components in each subsample (see Gil-Alana, 2006). First, we extend it to the non-linear case, and show by means of Monte Carlo...

Set identification in Bayesian vector autoregression (VARs) is becoming increasingly popular while facing recent criticism about potentially unwanted prior dominance and underrepresented bounds of the identified set. This can lead to biased inference even in large samples. Common estimation...

We propose a new instrument to identify uncertainty shocks in a SVAR model with external instruments. The instrument is constructed by exploiting variations in the price of gold around events that capture periods of changes in uncertainty. The variations in the price of gold around the events...