This paper considers VAR models incorporating many time series that interact through a few dynamic factors. Several econometric issues are addressed including estimation of the number of dynamic factors and tests for the factor restrictions imposed on the VAR. Structural VAR identification based...

Recent empirical work in several economic fields, particularly environmental and energy economics, has adapted the regression discontinuity (RD) framework to applications where time is the running variable and treatment begins at a particular threshold in time. In this guide for practitioners,...

It is well known that the covariance structure of the data alone is not enough to identify an SVAR, and the conventional approach is to impose restrictions on the parameters of the model based on a priori theoretical considerations. This paper suggests that much can be gained by requiring the...

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...

In this paper, we decompose oil price changes into their component parts following Kilian (2009) and estimate the dynamic effects of each component on industry-level production and prices in the U.S. and Japan using identified VAR models. The way oil price changes affect each industry depends on...

What are the shocks that drive economic fluctuations? I examine technology and money shocks in some detail, and briefly review the evidence on oil price and credit shocks. I conclude that none of these popular candidates accounts for the bulk of economic fluctuations. I then examine whether...

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly...

The purpose of this paper is to characterize the changes in risk premium in the 1980s. A five-variable vector autoregressive model (VAR) is constructed to calculate a risk premium series in the foreign exchange market. The risk premium series is volatile and time-varying. The hypothesis of no...

ARCH models are widely used to estimate conditional variances and covariances in financial time series models. How successfully can ARCH models carry out this estimation when they are misspecified? How can ARCH models be optimally constructed? Nelson and Foster (1994) employed continuous record...

We propose a Bayesian procedure for exploiting small, possibly long-lag linear predictability in the innovations of a finite order autoregression. We model the innovations as having a log-spectral density that is a continuous mean-zero Gaussian process of order 1/√T. This local embedding makes...