Credible Granger-causality analysis appears to require post-sample inference, as it is well-known that in-sample fit can be a poor guide to actual forecasting effectiveness. But post-sample model testing requires an often-consequential a priori partitioning of the data into an 'in-sample' period...

The literature on the relationship between real output growth and the growth rate in the price of oil, including an allowance for asymmetry in the impact of oil prices on output, continues to evolve. Here we show that a new technique, which allows us to control for both this asymmetry and also...

Credible inference requires attention to the possible fragility of the results (p-values for key hypothesis tests) to flaws in the model assumptions, notably including the validity of the instruments used. Past sensitivity analysis has mainly consisted of experimentation with alternative model...

Case, Quigley and Shiller (2013) distinguished and quantified two wealth effects in retail sales at the state level: One from wealth held as corporate stock and one from wealth held in the form of home ownership. Here we investigate how each of these wealth e¤ects varies by frequency that is,...

Credible inference requires attention to the possible fragility of the results (p-values for key hypothesis tests) to flaws in the model assumptions, notably including the validity of any instruments used. Past sensitivity analysis has mainly consisted of experimentation with alternative model...

We estimate a monetary policy rule for the US allowing for possible frequency de- pendence - i.e., allowing the central bank to respond differently to persistent innovations than to transitory innovations, in both the real-time unemployment rate and the real-time inflation rate. The estimation...