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A common practice in empirical macroeconomics is to examine alternative recursive orderings of the variables in structural vector autogressive (VAR) models. When the implied impulse responses look similar, the estimates are considered trustworthy. When they do not, the estimates are used to bound the true response without directly addressing the identification challenge. A leading example of this practice is the literature on the effects of uncertainty shocks on economic activity. We prove by counterexample that this practice is invalid in general, whether the data generating process is a structural VAR model or a dynamic stochastic general equilibrium model.
We propose a new instrument for estimating the price elasticity of gasoline demand that exploits systematic differences across U.S. states in the pass-through of oil price shocks to retail gasoline prices. These differences, which are primarily driven by variation in the cost of producing and distributing gasoline, create cross-sectional dispersion in gasoline price growth in response to an aggregate oil price shock. We find that the elasticity was stable near -0.3 until the end of 2014, but subsequently rose to about -0.2. Our estimates inform the recent debate about gasoline-tax holidays and policies to reduce carbon emissions.
Consumers purchase energy in many forms. Sometimes energy goods are consumed directly, for instance, in the form of gasoline used to operate a vehicle, electricity to light a home, or natural gas to heat a home. At other times, the cost of energy is embodied in the prices of goods and services that consumers buy, say when purchasing an airline ticket or when buying online garden furniture made from plastic to be delivered by mail. Previous research has focused on quantifying the pass-through of the price of crude oil or the price of motor gasoline to U.S. inflation. Neither approach accounts for the fact that percent changes in refined product prices need not be proportionate to the percent change in the price of oil, that not all energy is derived from oil, and that the correlation of price shocks across energy markets is far from one. This paper develops a vector autoregressive model that quantifies the joint impact of shocks to several energy prices on headline and core CPI inflation. Our analysis confirms that focusing on gasoline price shocks alone will underestimate the inflationary pressures emanating from the energy sector, but not enough to overturn the conclusion that much of the observed increase in headline inflation in 2021 and 2022 reflected non-energy price shocks.