tion that explains how much of the variation in each country’s GDP growth rate is a result of the constructed measure.

I include the estimated global GDP factor in a structural factor-augmented VAR (FAVAR) model with data on the real price of oil, U.S. oil consumption, and U.S. and non-U.S. oil production. The FAVAR models the dynamic relationships between these endogenous variables and links them to exogenous shocks, including U.S. energy efficiency and U.S. oil supply shocks. This framework allows me to examine the impact of exogenous changes in, for example, U.S. oil production and U.S. oil consumption on the global business cycle—a difficult task as movements in other endogenous variables tend to confound these effects in the data. The identification of shocks is based on a combination of sign and elasticity restrictions in line with Kilian & Murphy (2012). For example, I impose the restriction that a positive U.S. oil supply shock increases U.S. oil production and decreases real price of oil on impact. The decline in the oil price, in turn, increases U.S. oil consumption and decreases non-U.S. oil production. At the same time, global economic activity—as represented by the global GDP factor—increases because the cost of production falls. Similarly, a positive U.S. energy efficiency shock decreases U.S. oil consumption on impact as firms require less oil to produce a given level of output. This decline in oil consumption leads to a decrease in the real price of oil, and, consequently, increases the global GDP factor and decreases U.S and non-U.S. oil production.

The sign restrictions are sufficiently flexible to capture a wide spectrum of effects. For example, some studies argue that improvements in energy efficiency may not translate to a one-to-one reduction in energy use or may even increase energy consumption as the real price of oil falls—a phenomenon known as the “rebound effect” (see Gillingham et al., 2013; Bruns et al., 2021). Because the maintained sign restrictions do not restrict the magnitude of responses to structural shocks and are only imposed on the impact period, the framework is agnostic about these general equilibrium effects that may result in a sign reversal in later periods.

My main empirical findings can be summarized as follows. First, the results from the dynamic factor model estimation indicate the presence of a world business cycle that has increased in importance in the last two decades. The estimated common factor (henceforth, the global GDP factor) captures key global economic and financial events of the past four decades. The global GDP factor also tracks the changes in world industrial production but it is relatively moderated in amplitude. Moreover, I find that it accounts for an average of 21.6 percent of the variation in GDP growth rates across countries for the period 1980–2019, while its average contribution to output variability has increased to 39.1 percent since early 2000s.

Second, impulse responses from the FAVAR indicate that U.S. energy efficiency shocks have a larger impact on global output and real price of oil than U.S. oil supply shocks. Moreover, I reaffirm the key insight from Kilian (2009) that it is important to disentangle the underlying drivers of oil price fluctuations. In particular, the impulse responses show that both positive U.S. energy efficiency and U.S. oil supply shocks decrease the real price of oil and increase global GDP, while their effects on total oil production and consumption have opposite implications for global oil use.

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