Refine
Year of publication
- 2014 (4) (remove)
Document Type
- Working Paper (4)
Language
- English (4)
Has Fulltext
- yes (4)
Is part of the Bibliography
- no (4)
Keywords
- Asymmetry (1)
- Conditional response (1)
- DSGE (1)
- Nonlinearity (1)
- Prediction (1)
- Real GDP (1)
- Time variation (1)
- U.S. oil independence (1)
- VAR (1)
- bootstrap (1)
Institute
One of the leading methods of estimating the structural parameters of DSGE models is the VAR-based impulse response matching estimator. The existing asympotic theory for this estimator does not cover situations in which the number of impulse response parameters exceeds the number of VAR model parameters. Situations in which this order condition is violated arise routinely in applied work. We establish the consistency of the impulse response matching estimator in this situation, we derive its asymptotic distribution, and we show how this distribution can be approximated by bootstrap methods. Our methods of inference remain asymptotically valid when the order condition is satisfied, regardless of whether the usual rank condition for the application of the delta method holds. Our analysis sheds new light on the choice of the weighting matrix and covers both weakly and strongly identified DSGE model parameters. We also show that under our assumptions special care is needed to ensure the asymptotic validity of Bayesian methods of inference. A simulation study suggests that the frequentist and Bayesian point and interval estimators we propose are reasonably accurate in finite samples. We also show that using these methods may affect the substantive conclusions in empirical work.
Although oil price shocks have long been viewed as one of the leading candidates for explaining U.S. recessions, surprisingly little is known about the extent to which oil price shocks explain recessions. We provide the first formal analysis of this question with special attention to the possible role of net oil price increases in amplifying the transmission of oil price shocks. We quantify the conditional recessionary effect of oil price shocks in the net oil price increase model for all episodes of net oil price increases since the mid-1970s. Compared to the linear model, the cumulative effect of oil price shocks over course of the next two years is much larger in the net oil price increase model. For example, oil price shocks explain a 3% cumulative reduction in U.S. real GDP in the late 1970s and early 1980s and a 5% cumulative reduction during the financial crisis. An obvious concern is that some of these estimates are an artifact of net oil price increases being correlated with other variables that explain recessions. We show that the explanatory power of oil price shocks largely persists even after augmenting the nonlinear model with a measure of credit supply conditions, of the monetary policy stance and of consumer confidence. There is evidence, however, that the conditional fit of the net oil price increase model is worse on average than the fit of the corresponding linear model, suggesting much smaller cumulative effects of oil price shocks for these episodes of at most 1%.
This article examines how the shale oil revolution has shaped the evolution of U.S. crude oil and gasoline prices. It puts the evolution of shale oil production into historical perspective, highlights uncertainties about future shale oil production, and cautions against the view that the U.S. may become the next Saudi Arabia. It then reviews the role of the ban on U.S. crude oil exports, of capacity constraints in refining and transporting crude oil, of differences in the quality of conventional and unconventional crude oil, and of the recent regional fragmentation of the global market for crude oil for the determination of U.S. oil and gasoline prices. It discusses the reasons for the persistent wedge between U.S. crude oil prices and global crude oil prices in recent years and for the fact that domestic oil prices below global levels need not translate to lower U.S. gasoline prices. It explains why the shale oil revolution unlike the shale gas revolution is unlikely to stimulate a boom in oil-intensive manufacturing industries. It also explores the implications of shale oil production for the transmission of oil price shocks to the U.S. economy.
Futures markets are a potentially valuable source of information about market expectations. Exploiting this information has proved difficult in practice, because the presence of a time-varying risk premium often renders the futures price a poor measure of the market expectation of the price of the underlying asset. Even though the expectation in principle may be recovered by adjusting the futures price by the estimated risk premium, a common problem in applied work is that there are as many measures of market expectations as there are estimates of the risk premium. We propose a general solution to this problem that allows us to uniquely pin down the best possible estimate of the market expectation for any set of risk premium estimates. We illustrate this approach by solving the long-standing problem of how to recover the market expectation of the price of crude oil. We provide a new measure of oil price expectations that is considerably more accurate than the alternatives and more economically plausible. We discuss implications of our analysis for the estimation of economic models of energy-intensive durables, for the debate on speculation in oil markets, and for oil price forecasting.