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Regulatory capture in the US petroleum refining industry

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Abstract

The capture theory of regulation concludes that regulatory agencies tend to be captured by the firms they are regulating. This paper tests the capture theory in the recent environment of nuanced agency regulation by the administrative state, focusing on the US oil refining industry. Regulation has tended to narrow refiners’ margins, which harms nonintegrated oil refiners more than vertically integrated. Providing evidence of regulatory capture, complementary analysis of stock returns shows that regulations have benefited the stocks of vertically integrated firms. The narrowing of the margins is primarily due to rising input costs.

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Notes

  1. Beattie, Andrew. “World’s Top 10 Oil Companies” Forbes. 7 October 2018, <https://www.investopedia.com/articles/personal-finance/010715/worlds-top-10-oil-companies.asp>. Accessed 5 Aug 2019.

  2. Provided by the US Census Bureau at <https://www.census.gov/eos/www/naics/>, accessed 7 August 2019.

  3. US Energy Information Administration “An introduction to crack spreads” 2 June 2011 <https://www.eia.gov/todayinenergy/detail.php?id=1630>. Accessed 5 Aug 2019. CME Group “Introduction to Crack Spreads” 9 May 2017,<https://www.cmegroup.com/education/articles-and-reports/introduction-to-crack-spreads.html>. Accessed 5 Aug 2019

  4. Tesoro and Western Refining merged in 2017 to become Andeavor after the end of these time series.

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  1. Kennesaw State University, 1000 Chastain Rd, Kennesaw, GA, 30144, USA

    Robert Gmeiner

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Appendix

Appendix

See Figs. 8, 9 and Table 9.

$$\begin{aligned} \Delta _{12} CS_t&= \beta _0 + \beta _1 \Delta _{12} \text {Downstream Regulation}_{t-12} + \beta _2 \Delta _{12} \text {Upstream Regulation}_{t-12} \nonumber \\&\quad + \beta _3 \Delta _{12} \text {Rel. Imp.} + \beta _4 \Delta _{12} \text {WTI} + \beta _5 \Delta _{12} \text {Cap. Util.} + \beta _6 \Delta _{12} \text {CS}_{t-12} + \varepsilon _t \end{aligned}$$
(A1)

In (A1), \(\Delta _{12}\) denotes a twelve-month seasonal difference. This is analogous to (8) using monthly data. Results are presented in Table 8 and are robust to using the end use or resale crack spread. Refinery capacity utilization has been seasonally adjusted using the X-12 ARIMA technique, but results are robust to not adjusting it. Other variables do not display seasonal fluctuations.

The number of observations, indicated in the table reflects the interpolation technique. The series run from January 1985 through December 2014. Annual step interpolation allows for interpolating the January 2014 variable through the end of December, but linear and cubic spline interpolation end at the last observation.

Table 8 Monthly crack spread (resale), Eq. (A1)
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Figures 8, 9 and Table 9 show generalized impulse response functions for the effect of downstream regulatory words on the resale crack spread in a monthly VAR model. Regulations are interpolated with annual steps or linearly. Cubic spline interpolation is not used because the smoothness of that technique induces severe autocorrelation and inflates Granger causality statistics. All variables from the annual VAR model are included capacity utilization is seasonally adjusted. The results from these monthly models confirm the annual result presented in Fig. 6.

Fig. 8
figure 8

GIRF downstream reg. words (annual step) \(\Rightarrow\) resale crack spread

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Fig. 9
figure 9

GIRF downstream reg. words (linear) \(\Rightarrow\) resale crack spread

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Table 9 SUR models for companies estimated but not included in Table 3
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Gmeiner, R. Regulatory capture in the US petroleum refining industry. J. Ind. Bus. Econ. 46, 459–498 (2019). https://doi.org/10.1007/s40812-019-00134-w

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