Do oil companies routinely price gouge the public?
In recent years there has been much discussion on whether or not oil companies arbitrarily increase the price of gasoline at the pump. This has been exacerbated by the profits these companies have shown in recent quarters. Many studies have been undertaken to analyze if indeed price gouging is the driving force leading to these profits. Anderson (2006) asserts that oil company profits do not contribute to higher gas prices. Krantz (2007) states that the relationship between oil and gas prices is cyclical. He concludes that profits are influenced by factors such as world-wide demand and the associated cost of production. Barley (2006) posits that the key influencing factor is the series of mergers and joint ventures that preceded the run up in oil company profits. While Jenks and Clark (2007) state that this is an old issue that dates back to the days of the Standard Oil monopoly. We have too few players today, thus resulting in an oligopoly situation where a few control profits.
These findings indicate that there can be quite a bit of disagreement on what has caused oil company profits to spike and to what extent, if any, the oil companies are seeking unfair profits. One thing that cannot be overlooked is the fact that in the fourth quarter of 2007, the net profits of the top five oil companies amounted to $22.55 billion compared to $1.59 billion in the fourth quarter of 2001. And therein lies the crux of the matter. The investing and consuming public is fixated on net profits or the bottom line. And why not? Net Income is used as a basis to determine return to the stockholder, a key indicator of wealth building. But there is also another profit element that goes virtually unnoticed in the financial report, the "gross profit" figure. Many items, both operating and non-operating in nature, are deducted from gross profit in arriving at net profit. These are important items because, among other things, they aid in assessing the company's ability to manage in a responsible manner. So when we look at the net income for an oil company, or any company, we have difficulty in determining if the profits are due to price gouging or maybe just good management skills. Could there be another way of assessing if price gouging exists?
Gross profit is the result of a company's revenue less the costs of manufacturing the product (i.e., material, labor and overhead). If a company finds itself paying more for the costs of production, they have two options; reduce other expenses (operating or non-operating) or increase prices commensurately, in order to maintain net profit. An easy way of maintaining gross profit goals is to pass any increase in production costs on to the consumers. This causes the gross profit percentage to stay constant. If there is an increase in the gross profit percentage, while costs of production are increasing, one can infer that the price charged to the consumers (resulting in the revenue of the company) has increased more than the increase in costs. Regarding the oil companies, their major cost of manufacturing, i.e., oil, has steadily increased over the past five years. How has the gross profit been affected during this period? No research has yet to answer that question.
This study will extend prior research in attempting to ascertain if oil companies do indeed show indications of price gouging the consumers. In doing so three questions will be answered: 1. Have gross profit percentages for the major oil companies increased over the past five years? 2. Do gross profit percentages vary significantly between the major oil companies? 3. Do gross profit percentages for oil companies vary significantly from those in other industries?
If oil companies have been engaging in price gouging, one would expect to see an increase in gross profit levels over some period(s) in the past five years, indicating that the price charged the consuming public is greater than the cost paid for the elements of production. If, however, the gross profit percentage stays the same, or decreases, it is more difficult to level accusations of price gouging toward these firms. The following null hypothesis is tested:
H1: There is no significant difference in the gross profit percentage among each oil company for the past five year period.
Some oil companies have reported net profits in recent quarters at historic highs and significantly larger than other oil companies. This may be attributed to, what prior researchers theorize as, a "conglomerate" effect. In other words, the larger oil companies can manipulate prices easier since their control is greater. If this is the case, we should have the ability to notice this effect at the gross profit level. If some oil companies reflect gross profit percentages significantly different from other oil companies, this "conglomerate" effect may be in play, along with the ability to manipulate prices favorably. The following null hypothesis is tested:
H2: There is no significant difference in the gross profit percentage between oil companies for the past five year period.
Lastly, many researchers point to the fact that since oil companies operate in an environment with limited competition (oligopoly), that the ability exists to set prices artificially higher than would be the case in an environment with many competitors (pure competition). If so, then we should see a significant difference in the gross profit percentage of the oil industry relative to other industries. The following null hypothesis is tested:
H3: There is no significant difference in the gross profit percentage between the oil industry and other industries for the past five years.
Gross profit percentages were derived from Hoovers for the period 2003-2007. Five oil companies were represented in the sample for the oil industry. These companies consisted of; British Petroleum, Conoco/Phillips, Royal Dutch Shell, Chevron, and Exxon/Mobil. In addition, 112 other companies representing 8 additional industries were selected for comparison and their gross profit percentages analyzed. The breakdown by industry is represented in table 1.
In attempting to assess any differences among gross profit percentages of the individual oil companies and between oil companies and firms in other industries, a statistical tool must be used. Walsh (1990) indicates that the tool most suited for these types of tests is the Analysis of Variance (ANOVA). The ANOVA test is used when the researcher wishes to compare means or percentages of two or more groups of samples.
TEST OF HYPOTHESIS 1
In order to test if there were any significant differences in the gross profit percentages for the years 2003-2007 among the oil companies, data were analyzed with the help of ANOVA. The main effect of assessing any difference in the gross profit percentage over the five year period for each oil company was first analyzed as seen in Table 2. The F-ratios for each firm across the years 2003-2007 is less than the F-critical value of 3.073, thus, we fail to reject the null hypothesis that there is no significant difference among each firm's gross profit percentage for the period.
TEST OF HYPOTHESIS 2
In order to test if there were any significant differences in the gross profit percentages between the oil companies for the years 2003-2007, an ANOVA test was performed to assess interaction effects between the firms. As can be seen in Table 3, the computed F-ratios for each interaction effect again are less than the F-critical value of 3.073. Thus, we fail to reject the null hypothesis that there is no significant difference in gross profit percentages between the oil companies for the period under study.
TEST OF HYPOTHESIS 3
In order to test if there were any significant differences in the gross profit percentages between the oil industry and other industries for the years 2003-2007, an ANOVA test was performed which assessed the effects between the industries. Mean gross profit percentages were calculated for each of the nine represented industries. Interaction effects between gross profit percentages of the oil industry and each sampled industry were computed. As can be seen in Table 4, the computed F-ratios for each interaction effect are less than the F-critical value. No degree of significance is registered for any interaction. Thus, we fail to reject the null hypothesis that there is no significant difference in gross profit percentages between the oil industry and other industries during the period under study.
This study provides empirical research concerning the issue of whether or not companies within the oil industry have sought to set abnormally high prices of gasoline at the pump, i.e., "price-gouge." Because existing research is inconclusive regarding this matter, our research sought to advance the issue beyond net profit, or "bottom line," and instead concentrate on gross profit, where the effects of price setting and material cost could be more readily assessed. Based on a series of ANOVA tests, we conclude that; 1. Gross profit percentages for each oil company are not significantly different for the period 2003-2007. 2. Gross profit percentages between oil companies are not significantly different for the period 2003-2007. 3. Gross profit percentages between the oil industry and eight other selected industries are not significantly different for the period 2003-2007.
Given the results of our study, we cannot conclude that price-gouging by oil companies exists. It is possible that it may occur at a local level or in times of calamity (i.e., natural disasters), however, when the annual financial results of the large oil companies are analyzed, it becomes more difficult to conclude that these firms are taking advantage of the consumer at the pump.
Anderson, W.L. 2006. Profits and High Gas Prices. Ludwig von Mises Institute (Spring).
Barley, E. 2006. Oil Company Consolidations and the Price of Gasoline. Journal of Economic and Public Policy (November).
Jenks, J.W., and Clark, W.E. 2007. The Oil Trust Problem. College of the City of New York (January).
Krantz, M. 2007. Big Oil and Profits. Business Today (May).
Walsh, A. 1990. Statistics and Computer Applications for the Sciences. New York: Harper and Row.
Ronald A. Stunda, Birmingham-Southern College
George I. Voltz, Birmingham-Southern College
Table 1: Industry Representation Sample Industry Number of Firms in Sample Agriculture 19 Mining 12 Oil 5 Construction 18 Food 20 Tobacco 6 Transportation 15 Utilities 10 Personal Services 7 Total Firms in Sample 112 Table 2: Main Effect Difference in Gross Profit Percentage of Each Oil Company 2003-2007 Group SS df Mean F P-value F-critical BP(B) 366.278 4 12.81 1.587 .20885 3.073 Conoco(Co) 257.117 4 13.23 1.476 .39820 Shell(S) 345.286 4 15.21 1.871 .29751 Chevron(Ch) 277.981 4 13.19 1.382 .40019 Exxon(E) 324.423 4 15.40 1.592 .27223 Table 3: Interaction Effects Difference in Gross Profit Percentage Between Oil Companies Group SS df Mean F p-value F-critical BCo 1286.365 9 13.04 1.679 .25873 3.073 BS 1487.219 9 14.28 1.489 .30276 BCh 1629.457 9 14.42 1.596 .29861 BE 1539.002 9 13.39 1.826 .25091 CoS 1398.012 9 12.92 1.765 .38229 CoCh 1458.091 9 14.12 1.659 .27413 CoE 1680.279 9 13.87 1.801 .23023 SCh 1489.255 9 14.45 1.409 .27892 SE 1560.209 9 14.87 1.567 .24891 ChE 1398.463 9 13.67 1.667 .31219 Table 4: Interaction Effects Difference in Gross Profit Percentage Between Oil Industry and Other Industries Group SS df Mean F p-value F-critical OA 1682.465 9 13.92 2.081 .16253 3.073 OM 1489.762 9 14.09 2.330 .18709 OC 1426.578 9 12.69 2.129 .17491 OF 1539.920 9 15.08 2.228 .18002 OT 1499.229 9 14.48 2.389 .15715 OTr 1509.997 9 13.69 2.019 .16729 OU 1602.423 9 14.48 2.439 .16821 OP 1500.303 9 13.56 2.231 .15762 Symbols Code: O = Oil, A = Agriculture, M = Mining, C = Construction, F = Food, T = Tobacco, Tr = Transportation, U = Utilities, P = Personal Services
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|Author:||Stunda, Ronald A.; Voltz, George I.|
|Publication:||Academy of Accounting and Financial Studies Journal|
|Date:||Jan 1, 2010|
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