This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range...

This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range...

This paper describes an algorithm to compute the distribution of conditional forecasts, i.e. projections of a set of variables of interest on future paths of some other variables, in dynamic systems. The algorithm is based on Kalman filtering methods and is computationally viable for large...

This paper shows that Vector Autoregression with Bayesian shrinkage is an appropriate tool for large dynamic models. We build on the results by De Mol, Giannone, and Reichlin (2008) and show that, when the degree of shrinkage is set in relation to the cross-sectional dimension, the forecasting...

In semiparametric models it is a common approach to under-smooth the nonparametric functions in order that estimators of the finite dimensional parameters can achieve root-n consistency. The requirement of under-smoothing may result as we show from inefficient estimation methods or technical...

This paper develops methodology for nonparametric estimation of a polarization measure due to Anderson (2004) and Anderson, Ge, and Leo (2006) based on kernel estimation techniques. We give the asymptotic distribution theory of our estimator, which in some cases is nonstandard due to a boundary...

This paper explores the price-setting behavior of Austrian firms based on survey evidence. Our main result is that customer relationships are a major source of price stickiness in the Austrian economy. We also find that the majority of firms in our sample follows a timedependent pricing...

We estimate the effects of stock market volatility on the growth rates of durable consumption, non-durable consumption and invest- ment using post-war US data. Our results indicate that high levels of stock market volatility exert large adverse effects on the growth rates of investment and...

We study the development of bank lending in the U.S. after four large jumps in uncertainty using an event study approach. We find that more liquid banks reduce lending less than banks with smaller liquidity ratios after a surge in uncertainty. Lending by smaller banks is also less responsive to...

We develop a simple experimental setting to evaluate the role of the Taylor principle, which holds that the nominal interest rate has to respond more than one-for-one to fluctuations in the inflation rate. In our setting, the average inflation rate fluctuates around the inflation target if the...