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This paper examines the advantages and drawbacks of alternative methods of estimating oil supply and oil demand elasticities and of incorporating this information into structural VAR models. I not only summarize the state of the literature, but also draw attention to a number of econometric problems that have been overlooked in this literature. Once these problems are recognized, seemingly conflicting conclusions in the recent literature can be resolved. My analysis reaffirms the conclusion that the one-month oil supply elasticity is close to zero, which implies that oil demand shocks are the dominant driver of the real price of oil. The focus of this paper is not only on correcting some misunderstandings in the recent literature, but on the substantive and methodological insights generated by this exchange, which are of broader interest to applied researchers.
The conventional wisdom that inflation expectations respond to the level of the price of oil (or the price of gasoline) is based on testing the null hypothesis of a zero slope coefficient in a static single-equation regression model fit to aggregate data. Given that the regressor in this model is not stationary, the null distribution of the t-test statistic is nonstandard, invalidating the use of the normal approximation. Once the critical values are adjusted, these regressions provide no support for the conventional wisdom. Using a new structural vector regression model, however, we demonstrate that gasoline price shocks may indeed drive one-year household inflation expectations. The model shows that there have been several such episodes since 1990. In particular, the rise in household inflation expectations between 2009 and 2013 is almost entirely explained by a large increase in gasoline prices. However, on average, gasoline price shocks account for only 39% of the variation in household inflation expectations since 1981.
There has been much interest in the relationship between the price of crude oil, the value of the U.S. dollar, and the U.S. interest rate since the 1980s. For example, the sustained surge in the real price of oil in the 2000s is often attributed to the declining real value of the U.S. dollar as well as low U.S. real interest rates, along with a surge in global real economic activity. Quantifying these effects one at a time is difficult not only because of the close relationship between the interest rate and the exchange rate, but also because demand and supply shocks in the oil market in turn may affect the real value of the dollar and real interest rates. We propose a novel identification strategy for disentangling the causal effects of traditional oil demand and oil supply shocks from the effects of exogenous variation in the U.S. real interest rate and in the real value of the U.S. dollar. Our approach exploits a combination of sign and zero restrictions and narrative restrictions motivated by economic theory and extraneous evidence. We empirically evaluate popular views about the role of exogenous real exchange rate shocks in driving the real price of oil, and we examine the extent to which shocks in the global oil market drive the U.S real exchange rate and U.S. real interest rates. Our evidence for the first time provides direct empirical support for theoretical models of the link between these variables.