We propose a novel framework to analyze how policy-makers can manage risks to the median projection and risks specific to the tail of gross domestic product (GDP) growth. By combining a quantile regression of GDP growth with a vector autoregression, we show that monetary and macroprudential...

This paper predicts phases of the financial cycle by using a continuous financial stress measure in a Markov switching framework. The debt service ratio and property market variables signal a transition to a high financial stress regime, while economic sentiment indicators provide signals for a...

We use narrative evidence along with a novel database of real-time data and forecasts from the Bank of Canada's staff economic projections from 1974 to 2015 to construct a new measure of monetary policy shocks and estimate the effects of monetary policy in Canada. We show that it is crucial to...

We estimate the effects of economic uncertainty on time use and discuss its macroeconomic implications. Using data from the American Time Use Survey, we first infer cyclical variation in home production and leisure time. We then document that higher uncertainty increases housework and reduces...

This paper introduces a new methodology to date systemic financial stress events in a transparent, objective and reproducible way. The financial cycle is captured by a monthly country-specific financial stress index. Based on a Markov-switching model, high financial stress regimes are...

We incorporate quantile regressions into a structural vector autoregression model to empirically assess how monetary and fiscal policy influence risks around future GDP growth. Using a panel of six developed countries, we find that both policy instruments affect the location of the distribution...

This paper utilizes an open-economy New Keynesian overlapping generations model, the Global Integrated Monetary and Fiscal Model (GIMF), to assess the macroeconomic effects of external shocks and the impact of various monetary and fiscal policy responses. The simulations assess the effect of...

We develop a finite-sample procedure to test for mean-variance efficiency and spanning without imposing any parametric assumptions on the distribution of model disturbances. In so doing, we provide an exact distribution-free method to test uniform linear restrictions in multivariate linear...

We develop a finite-sample procedure to test the beta-pricing representation of linear factor pricing models that is applicable even if the number of test assets is greater than the length of the time series. Our distribution-free framework leaves open the possibility of unknown forms of...