How important is the oil market for the global economy? Although oil shocks are often viewed as responsible for the poor performance of many countries in the 1970s, these shocks have played a relatively minor role in leading macroeconomic models. Because oil represents a relatively small share of overall production costs, conventional models imply that oil shocks have a limited impact on aggregate output.
This conclusion has recently been challenged by Gabaix (2011), Acemoglu et al. (2012), and Baqaee and Farhi (2019). These authors argue that shocks to sectors with a small factor share that are highly complementary to other inputs can have a large impact on aggregate output. Baqaee and Farhi (2019) emphasise the perils of using linearisation methods to analyse macroeconomic models with strong complementarities and use the impact of oil shocks in the 1970s as a leading example of these perils.
Motivated by this line of research, in a new paper (Bornstein et al. 2021) we revisit the workings of the oil market by proposing and estimating a model of the oil industry embedded in a general equilibrium model of the global economy. This effort is important not only because oil shocks can be crucial determinants of macroeconomic outcomes, but also because there is ongoing structural change within oil markets that merits further study (Killian 2016). While conventional oil production is characterised by long lags and various forms of adjustment costs, new forms of oil production – such as fracking – are much more nimble.
Our estimation procedure relies heavily on a new, comprehensive micro-dataset, with information of production and costs at the oil field level. The granularity of the data allows us to estimate separately the technological parameters of conventional oil producers and firms that use the fracking technology.
Our paper is part of a new, emerging body of research that uses micro-data to shed new light on key aspects of the oil industry. Examples of this work include Kellogg (2014), Anderson et al. (2017), Bjornland et al. (2017), Asker et al. (2019), and Newell and Prest (2019).
Our model is consistent with key properties of aggregate variables related to the oil industry. Examples of these properties are as follows: oil prices and investment in the oil industry are very volatile; they are correlated with each other; and the production of firms that belong to the Organisation of the Petroleum Exporting Countries (OPEC) is more volatile than the production of non-OPEC firms.
The model we propose is also consistent with two key ‘micro facts’ about the oil industry. First, in conventional oil production there is, on average, a 12-year delay between investment and production. Second, the costs of oil extraction are convex in the rate at which oil is extracted.
In our model, firms that belong to OPEC act as a cartel. The remaining firms are a competitive fringe. There are three key features that make the model consistent with the salient properties of the data. First, according to our estimate the demand for oil is relatively inelastic. This low elasticity is consistent with Baqaee and Farhi’s (2019) argument that oil shocks can be an important driver of the business fluctuations, despite their low expenditure share in production. Second, oil supply is elastic in the long run because firms can invest in the discovery of new oil fields. Third, oil supply is inelastic in the short run. This property results from three elements: a lag between investment and production, convex costs of adjusting extraction rates, and decreasing returns to oil investment.
We use our general equilibrium model of the global economy to study the macroeconomic impact of the ongoing large structural changes in the oil industry associated with the advent of hydraulic fracturing (fracking). This production technique involves pumping a mixture of water, sand, and chemicals at high pressure into shale rock formations. This opens up small fissures that release oil and gas. Combined with the ability to drill horizontally through shale layers over long distances, fracking has transformed the US from a top oil importer to a top oil exporter. The expansion of fracking continues, not just in the US but also in countries such as Argentina, China, Mexico, and Russia.
Using micro-data on oil fields, we show that fracking firms are much more nimble than conventional oil producers. The costs of fracking firms are less convex in the extraction rate than the costs of conventional firms. In addition, the average lag between investment and production is much shorter for fracking firms (one year) than for conventional oil producers (12 years).
We find that fracking affects the global economy in three ways. First, the volatility of oil prices falls because the supply of oil becomes more elastic. Second, the volatility of global output rises because the economy becomes more responsive to aggregate demand shocks. Without fracking, a positive demand shock implies a larger rise in oil prices. This rise dampens the effect of the demand shock on the economy (e.g. Lippi 2008). Third, the average level of oil prices falls because fracking firms add to global oil supply and weaken OPEC’s cartel power.
In sum, our model predicts that as fracking becomes a sizeable fraction of the world oil supply, it will herald a new era of lower, more stable oil prices.
Acemoglu, D, V M Carvalho, A Ozdaglar and A Tahbaz‐Salehi (2012), “The network origins of aggregate fluctuations”, Econometrica 80(5): 1977-2016.
Anderson, S T, R Kellogg and S W Salant (2017), “Hotelling Under Pressure”, Journal of Political Economy 126(3): 984-1026.
Asker, J, A Collard-Wexler and J De Loecker (2019), “(Mis)allocation, market power, and global oil extraction”, American Economic Review 109 (4): 1568–1615.
Bjornland, H C, F M Nordvik and M Rohrer (2017), “Supply Flexibility in the Shale Patch: Evidence from North Dakota”, manuscript, Norges Bank.
Bornstein, G, P Krusell and S Rebelo (2021), “A World Equilibrium Model of the Oil Market”, manuscript, Northwestern University.
Baqaee, D R and E Farhi (2019), “The macroeconomic impact of microeconomic shocks: beyond Hulten’s Theorem”, Econometrica 87(4): 1155-1203.
Gabaix, X (2011), “The granular origins of aggregate fluctuations”, Econometrica 79(3): 733-772.
Kellogg, R (2014), “The effect of uncertainty on investment: evidence from Texas oil drilling”, The American Economic Review 104(6): 1698–1734.