The U.S. petroleum industry consists of firms of varying sizes that operate in one or more of three broad segments—the upstream, which consists of the exploration for and production of crude oil; the midstream, which consists of pipelines and other infrastructure used to transport crude oil and refined products; and the downstream, which consists of the refining and marketing of petroleum products such as gasoline and heating oil. While some firms operate in only one or two of these segments, fully vertically integrated oil companies participate in all of them. Chevron is an example of a fully integrated petroleum company, with operations in all three segments, while Wawa—the convenience store chain—is an example of a firm operating in only one market segment as a downstream independent fuel retailer. Refiners produce gasoline and then arrange its delivery, usually via pipeline, but also via barge, truck, or rail, from their refineries to any of the nearly 400 wholesale terminals located throughout the country. Terminals can be near refineries, pipelines, or water ports, and can involve a wide-ranging number of wholesale gasoline sellers, including refiners or importers. The number of sellers at a wholesale terminal is not necessarily related to the number of refineries near the terminal; in some markets, a single refinery can produce gasoline for a number of sellers if they have supply arrangements with that refinery. At wholesale terminals, the majority of gasoline is purchased by marketers or distributors, for subsequent resale at retail gasoline stations, while the rest is sold directly to retailers (see fig. 1). Market dynamics anywhere along the supply chain can influence consumer prices, beginning with upstream crude oil production, all the way through downstream refining and retailing. Gasoline from a wholesale terminal can also be either branded or unbranded. Branded gasolines are those supplied from major refiners selling under their trademarks, such as BP or Marathon, and often contain special additives, while unbranded gasolines may be supplied by major or independent refiners, but are not sold under a refiner’s trademark. Branded prices include a premium reflecting the recognized brand name, fuel additives, and other costs, such as advertising. Unbranded prices, which tend to be lower than those for branded, are paid by distributors who deliver gasoline to retail locations ranging from large supermarkets to small independent retailers that are not affiliated with a major refiner. FTC’s merger review process is conducted by staff in various bureaus and offices throughout the agency, but mainly by the Bureau of Economics and the Bureau of Competition. In reviewing proposed mergers, FTC follows guidelines that it developed jointly with the Department of Justice (DOJ) for predicting the effects of mergers on competition. The unifying theme in the guidelines is that mergers should not be permitted to enhance a firm’s market power or to make it easier for a firm to exercise market power. In its review, FTC examines whether market conditions, including market concentration, would be conducive for firms to act unilaterally or to coordinate to raise prices. Unilateral effects occur when the merged firm profitably reduces its own supply and raises prices, even though other competitors may respond by increasing their own output. Such behavior can be profitable if the merged firm has a significant share of sales and the response of competitors is limited. Coordinated behavior occurs when each firm remaining in the market reduces its output, increasing prices. In their reviews of petroleum industry mergers, FTC staff seek to avoid the possibility of price increases even as small as 1 cent per gallon because the petroleum industry sells large volumes of fuel at thin margins, and price changes of this magnitude can affect industry decisions regarding production or sales. In addition, in some markets, even 1 cent per gallon price increases can lead to more than $100 million per year in additional costs for consumers, according to FTC analysis. After reviewing a merger, FTC has three options: (1) to not challenge the merger; (2) to challenge the merger in court; or (3) to not challenge the merger as long as certain agreed upon remedial actions are met, such as firms selling off, or divesting, overlapping assets that have the greatest potential to harm competition. FTC also performs other activities to monitor petroleum markets, including monitoring fuel prices and conducting special investigations. For example, FTC’s price-monitoring program tracks retail gasoline and diesel prices in 360 cities across the nation and wholesale prices in 20 major urban areas. In addition, on April 16, 2009, FTC issued a Revised Notice of Proposed Rulemaking seeking public comment on a revised proposed rule that would prohibit market manipulation in the petroleum industry. The revised proposed rule would prohibit fraudulent and deceptive conduct that could harm wholesale petroleum markets, but it is not yet clear how this new rule will affect FTC’s monitoring of petroleum industry markets. However, FTC staff indicated that because FTC is an enforcement agency, they focus on merger and antitrust enforcement, rather than ongoing monitoring of the petroleum industry, as a regulatory agency would likely undertake. According to FTC, during the latter part of 2008, approximately 125 FTC staff members–-attorneys, economists, paralegals, research analysts, and others–-worked to some extent on matters involving antitrust and pricing issues in the oil and natural gas sectors, and about 6 or 7 staff economists from the Bureau of Economics were involved in ongoing monitoring of the petroleum industry, although these economists also devoted a portion of their time to other industries. These staff economists also occasionally perform analysis of past mergers, and FTC has indicated retrospective merger reviews are a valuable part of antitrust decision making. If FTC finds anticompetitive behavior in retrospective reviews, it has the ability to conduct further in-depth investigations into the merger and collect substantial company-specific data in order to pursue corrective action to reintroduce competition into the market such as forced divestitures or conduct-based remedies. However, as we reported in 2008, FTC does not regularly look back at past mergers in the petroleum industry to assess their actual effects on prices– –there had been only three such retrospective reviews, between 2000 and 2007. We recommended that FTC undertake more regular retrospective reviews of past petroleum industry mergers and develop risk-based guidelines to determine when to conduct them. In commenting on this, FTC noted that our recommendation was consistent with a recent self- evaluation initiative and would consider it in that regard. Although these reviews can be resource intensive, experts, industry participants, and FTC agreed that regular retrospective reviews would allow the agency to better inform future merger reviews and better measure its success in maintaining competition. In this regard, the National Bureau of Economic Research published a study in March 2009 entitled Generating Evidence to Guide Merger Enforcement, which noted the importance of conducting retrospective merger reviews. The study found that retrospective merger reviews can help to evaluate the impacts of past merger enforcement decisions and can allow antitrust agencies to develop better techniques to predict the effects of future mergers on competition. The study also suggested that it made sense to focus retrospective reviews on completed mergers with the greatest likelihood of anticompetitive effects, such as mergers in highly concentrated markets. FTC is currently working on a fourth retrospective review of a past petroleum industry merger, which is expected to be released later this year. We studied the effects of seven petroleum industry mergers that occurred since 2000 on wholesale gasoline prices and found three that were associated with small changes in wholesale gasoline prices. Specifically, we developed an econometric model to isolate the effects on wholesale gasoline prices of seven mergers––(1) Chevron Corporation/Texaco, (2) Phillips Petroleum Company/Tosco Corporation, (3) Valero Energy Corporation/Ultramar Diamond Shamrock Corporation (UDS), (4) Royal Dutch Shell Group/Texaco, (5) Phillips Petroleum Company/Conoco, (6) Premcor/Williams Companies, and (7) Valero Energy Corporation/Premcor. These mergers ranged widely in the size of transaction, from the Chevron/Texaco merger, valued at about $45 billion, to the Premcor/Williams merger, valued at $367 million. Five of the seven mergers were focused primarily on the downstream sector, with refining, marketing, or retail operations as the key assets that changed ownership, while the other two mergers were concentrated in the upstream exploration and production sector, with oil reserves as the key asset that changed ownership. The rationale for some of these mergers, according to industry officials, was generally to increase operational efficiencies and reduce costs through economies of scale. Summary information about the mergers is provided in table 1. As shown in table 1, the seven mergers we analyzed ranged widely in the number of cities with wholesale terminals that were affected by the merger. We analyzed the effects of the seven mergers at terminals in 78 cities across the United States. The three mergers affecting terminals in 35 or more cities each—-Chevron/Texaco, Shell/Texaco, and Phillips/Conoco—-reflect a wide geographic area, as each merger affected cities across a number of regions of the country. The Valero/Premcor and Valero/UDS mergers, each of which affected terminals in 20 or more cities, were more concentrated geographically, primarily affecting cities in the eastern and western United States, respectively. The two mergers affecting terminals in fewer than 10 cities each—-Phillips/Tosco and Premcor/Williams—-reflect narrower geographic areas, with the former affecting a few cities in the Southeast and Southwest and the latter affecting 2 cities in the Southeast. See appendix III for more information on the geographic regions affected by each merger. Antitrust enforcement actions taken in response to the mergers varied, depending on the characteristics of the firms, the geographic areas affected, and the specifics of the transaction. As shown in table 1, the FTC challenged three of the mergers, as originally proposed, on the basis of potential threats to competition in one or more sectors of the industry. In response to these potential anticompetitive threats, FTC required the merging firms to divest key assets in the sectors of identified concern. In the case of the Chevron/Texaco merger, FTC identified potential threats to gasoline marketing in 23 states across the western and southern United States, as well as potential threats to refining in California and the Pacific Northwest, among others. As a result, it ordered the divestiture of Texaco’s downstream assets in marketing and refining, as well as in pipelines. In the case of the Valero/UDS merger, FTC identified potential threats to the refining and supply sectors in California and subsequently required the divestiture of a UDS refinery in Avon, California, as well as the divestiture of numerous supply contracts and 70 retail outlets across the West. In the case of the Phillips/Conoco merger, FTC identified a number of potential concerns, including threats to gasoline refining and supply in various western and midwestern states. In response, FTC required divestitures in key areas of concern, including the sale of a Phillips refinery near Salt Lake City and marketing assets in northern Utah, as well as the sale of Conoco’s Denver-area refinery and Phillips’s marketing assets in eastern Colorado. In the case of the remaining four mergers, FTC did not identify competitive concerns and consequently did not require divestitures or other remedial actions. As highlighted in table 1, the results of our analysis suggest that two of the seven mergers were associated with small increases in wholesale gasoline prices, while one was associated with a small decrease in wholesale gasoline prices. In the case of these three mergers, the model results were statistically significant, meaning that we were able to reasonably rule out the effects of chance on the estimated impacts on wholesale gasoline prices. In addition, our model held constant the effects of a number of other key variables, including changes in gasoline inventory, refinery capacity utilization, and the type of gasoline sold, although data were unavailable on additional factors that may have affected prices. According to these results, the 2005 acquisition by Valero of four refineries owned by Premcor was associated with an increase of 1.13 cents per gallon for unbranded gasoline. Similarly, the model suggests that the 2001 acquisition by Valero of seven refineries and approximately 5,000 retail stations owned by UDS was associated with an increase in branded wholesale gasoline prices of approximately 1.06 cents per gallon. By contrast, the model suggests that the 2001 merger of Phillips and Conoco, including oil reserves, as well as refining and marketing, was associated with a decrease in branded wholesale gasoline prices of approximately 1.64 cents per gallon and a decrease of 1.14 cents per gallon for unbranded gasoline. The price effects observed in these three cases reflect an average increase or decrease in wholesale gasoline prices at terminals across the cities affected by the merger for the period of time following the merger through September 2008. In the case of the remaining four mergers—- Chevron/Texaco, Phillips/Tosco, Shell/Texaco, and Premcor/Williams—- the results of our model were not statistically significant. Given the complexities of the petroleum industry’s supply chain, we could not provide an explanation as to why certain mergers were associated with changes in wholesale gasoline prices. Gasoline moves through an often complicated supply network, and the efficiency gains associated with mergers, or likewise the opportunities for market participants at any level of the network to exercise market power, could play out in any number of ways. For example, some marketers we spoke with indicated that mergers sometimes spurred refiners to renegotiate the terms of their supply agreements, making them less favorable and potentially indicating the exercise of market power by an individual refiner. On the other hand, mergers can create operational efficiencies and economies of scale that can allow refiners and marketers to pass on savings, in the form of lower prices, to consumers. At the terminal level, there is limited information on gasoline’s refinery of origin, including whether it was even refined domestically, further adding to the difficultly in pinpointing how and where the impacts from a merger are felt. For example, marketers we spoke with indicated that they could not be sure where gasoline shipped via pipeline came from, since similar products are intermingled in the system. In addition, refiners we spoke with indicated that they were able to exchange gasoline with each other, enabling them to have a marketing presence in a city that was not very close to one of their refineries. These “exchange agreements” add to the efficiency of the supply network, because refiners can trade fuel across locations rather than ship it, although these agreements can also greatly add to its complexity. As such, our model does not provide further explanation as to the underlying forces that contributed to any correlation between the three mergers and changes in wholesale gasoline prices, nor does it provide conclusive evidence of unilateral or coordinated behavior to influence gasoline prices. To do this we would have had to conduct in-depth investigations into each merger and collect substantial company-specific data. Nonetheless, our model provides an indicator of the impact that petroleum industry mergers can have on wholesale gasoline prices. And given the substantial size of the gasoline market, even small increases or decreases in wholesale prices can have a significant impact on consumer spending. We also used our model to analyze market concentration and found that less concentrated wholesale gasoline markets—i.e., wholesale terminals with more sellers—were significantly associated with lower gasoline prices at terminals located in 78 cities across the United States. For example, we estimated that prices were about 8 cents per gallon lower at terminals with, for example, 14 sellers compared with prices at terminals that had only 9 sellers. We also measured the concentration of groups of refineries that supplied gasoline to sellers at wholesale terminals in these cities and similarly found that prices were lower if a terminal was supplied by a less concentrated group of refineries. Measures of market concentration often take into account both the number of firms in a market and the market share of each firm, and one such measure, the Herfindahl-Hirschman Index, or HHI, gives proportionally greater weight to firms with larger market shares. According to FTC and DOJ guidelines, an unconcentrated market has an HHI of less than 1,000; a moderately concentrated market has an HHI between 1,000 and 1,800; and a highly concentrated market, with the greater likelihood that a firm could exercise market power, has an HHI over 1,800. We measured market concentration affecting wholesale terminals in two ways: (1) by counting the number of sellers at each wholesale terminal, and (2) by calculating the HHI of refinery groups that supplied gasoline to sellers at wholesale terminals. groups supplied gasoline to sellers at individual wholesale terminals, allowing us to estimate a refinery HHI for individual wholesale terminals in the 78 cities we studied. Both of our measures indicated that less concentrated markets were significantly associated with lower wholesale gasoline prices, as shown in tables 2 and 3. Although we did not observe large changes in market concentration over time, there was variation in market concentration across the wholesale terminals in our analysis. In order to demonstrate the size of the effect that market concentration had on wholesale gasoline prices, we chose to look at the expected changes in wholesale prices across two ranges of market concentration---one range was between the 25th and 75th percentiles of market concentration values in our analysis, and the other was between the 10th and 90th percentiles. We calculated the expected price differences if a terminal were to have moved from the higher end of either of these concentration ranges to the lower end. We found that the terminals with more sellers and therefore lower levels of concentration would be expected to have lower wholesale gasoline prices (see table 2). We estimated that if a terminal were to have gained 5 wholesale gasoline sellers, we would expect prices to be 8 cents per gallon lower at that terminal. In addition, if a terminal were to have gained 11 sellers, we estimated that prices would be 18 cents per gallon lower. We present the number of sellers at each of the terminals in the 78 cities we examined, which ranged from 3 to 21 in 2008, with a median of 11, in appendix IV. We also found that terminals supplied by the refinery spot markets with the lower HHIs would be expected to have lower wholesale gasoline prices (see table 3). We estimated that if a spot market supplying gasoline to a terminal were to have become less concentrated by moving from an HHI of 930 to 790, we would expect prices to be about 2 cents per gallon lower at that terminal. In addition, if a spot market supplying gasoline to a terminal were to have become less concentrated by moving from an HHI of 1470 to 700, we estimated that prices would be about 13 cents per gallon lower at that terminal. In general, our findings were consistent with the idea that markets with more sellers or more refiners supplying those sellers are likely to be more competitive, resulting in lower prices. We present trends in spot market concentration in appendix IV that ranged from 666 to 3,729. The median HHI across all markets was 906. In estimating these results, we treated market concentration as endogenous—-meaning that changes in wholesale gasoline prices could affect market concentration in addition to changes in concentration affecting prices. For example, this could occur if high prices at one terminal spur new sellers to enter the market, thus decreasing concentration. This assumption was supported by statistical tests that we conducted, although because this assumption was likely to have a noticeable impact on our results, we also analyzed our data without it and found that the impact on prices of our concentration measures was statistically significant but smaller. For example, for unbranded prices, in the case of the refinery spot market HHI, the impact on wholesale prices was about half the size without this assumption. For the number of sellers at the terminal, the impact was about one-sixth of the size without this assumption. As noted above, we did not observe a trend of increasing market concentration nationwide between 2000 and 2008, either in the number of sellers at wholesale terminals or in our HHI numbers calculated for refinery spot market groups. For example, the average number of sellers at terminals across the country remained almost the same since 2000, with terminals averaging 11 sellers by 2008 and most having between 7 and 11 sellers during that year (see fig. 2). However, of the terminals located in the 78 cities we studied, we did find that 8 terminals lost 5 or more sellers and 39 lost between 1 and 4—-the remainder had no change or actually gained sellers since 2000. Most of our refinery spot market HHI numbers remained moderately concentrated or unconcentrated during the span of our analysis, and this was consistent with the findings in our 2008 report, where we indicated that concentration was generally moderate and changed little in spot markets throughout the United States since 2000, except in the case of the New York Harbor spot market, which became more concentrated. However, as we reported, the New York Harbor trend may not be completely reflective of actual market conditions because foreign refineries ship a significant amount of gasoline into the East Coast (around 60 percent of consumption). Because we were unable to account for this fuel, the high measure of concentration probably overstates the actual concentration for the market. However, in this current analysis we also found that refinery market concentration in Alaska was very high because of the isolated nature of that state. Because of the complexity of the U.S. petroleum industry, it can be difficult to predict the impact of mergers before they are completed. Refined products move through a complicated supply network, where it can be difficult to identify the origin of fuel supplied to wholesale markets, making it challenging to anticipate the actual impacts of petroleum industry mergers on gasoline prices before the deals are completed. In light of these difficulties, reviewing the effects of past mergers on fuel prices could allow FTC to determine whether the actual effects of a merger reflect the anticipated effects. Although there are some limitations to the analytical approaches used in isolating the effects of past mergers and market concentration on prices, we believe the approach we used in our analysis provides a starting point for potential further studies of these impacts. Conducting retrospective reviews of past mergers could also allow FTC to better understand the impacts of assumptions it makes during merger reviews and to identify the types of mergers that are potentially problematic, allowing it to improve its approach to future merger reviews. As the authors of the recent study published by the National Bureau of Economic Research noted, it makes sense for an antitrust agency to focus retrospective reviews on completed mergers with the greatest likelihood of having reduced competition, such as mergers in highly concentrated markets, and in doing so the agency can focus its limited resources on the mergers with the greatest risk of having adversely affected prices. Given the significant relationship between wholesale gasoline prices and market concentration that we found, we also conclude that it may be useful to focus retrospective merger reviews on highly concentrated market regions. Such retrospective reviews would provide FTC greater assurance that its efforts result in consumer prices that are determined in a fair and competitive marketplace. This study reinforces the need to review past petroleum industry mergers, and we continue to recommend that FTC conduct such reviews more regularly and develop risk-based guidelines to determine when to conduct them. We provided a copy of our draft report to FTC for its review and comment. FTC’s Chairman provided written comments, which are reproduced in appendix II, along with our responses. In general, the Chairman agreed with our recommendation that FTC conduct more reviews of past petroleum industry mergers and that FTC focus those retrospective efforts on mergers that present the greatest likelihood of anticompetitive effects. The Chairman also noted some of the limitations and an apparent inaccuracy in our presentation of the effects of market concentration on wholesale gasoline prices, which we addressed in appendix II. Nonetheless, the Chairman said that FTC will continue to use risk-based criteria for identifying past mergers for review and will direct its staff to evaluate more fully GAO’s contributions as it moves forward with its merger retrospectives and enforcement programs. As agreed with your offices, unless you publicly announce the contents of this report earlier, we plan no further distribution until 14 days from the report date. At that time, we will send copies to the Chairman, Federal Trade Commission; appropriate congressional committees; and other interested parties. In addition, the report will be available at no charge on the GAO Web site at http://www.gao.gov. If you or your staffs have any questions about this report, please contact us at (202) 512-3841, gaffiganm@gao.gov, or (202) 512-2700, mccoolt@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. GAO staff who made major contributions to this report are listed in appendix V. The objectives of this study were to examine the impacts of selected mergers and market concentration on wholesale gasoline prices between 2000 and 2008. Our model examined how wholesale gasoline city terminal prices were affected by mergers and two measures of market competition. We used data from 78 (and in some cases 82) wholesale city terminals from January 2000 through September 2008. We used monthly average data on wholesale city terminal gasoline prices. We believe that the increased information from higher-frequency data, for example, from using weekly data, would be outweighed by the extra noise generated by such relatively high-frequency data. Further, in general, the control variables are available only at monthly intervals, and some only at quarterly intervals. In developing our model, we consulted with a number of economists in industry and academia who had completed similar studies, as well as with economists at the Federal Trade Commission (FTC). We incorporated their suggestions when possible and where we thought appropriate. In addition, a number of economists also provided us with feedback on our preliminary results. Our dependent variable was the logarithm of the wholesale terminal price of gasoline. We used an Augmented-Dickey-Fuller test designed for panel data to test for stationarity in levels of our dependent variables, in the case of both unbranded and branded prices. Our tests showed that our unbranded and branded dependent variable was stationary in levels. We estimated separate models for unbranded and branded products to test for the consistency of our results. There may be multiple gasoline prices reported for a given city termin a given date; in general, we used the wholesale terminal price of gasoline that is required in that specific locale. We believe that such a focus allows us to address the issue of what is happening in the market for gasoline in that city. Our model specification controls for the effects of changes in the aver price level and changes in the price of crude oil over time. We controlled for this and other time-varying effects in our regressions by including a complete set of time dummy variables—-one for each month’s observation in the data. Our primary interest was to identify the impact of (1) oil company mergers, and (2) market concentration on gasoline prices. We limited our analysis to mergers (1) that occurred between 2000 and2007, (2) that had transaction values of $200 million or greater, and (3) for which we had useful and complete gasoline price data where each merger occurred. There were seven mergers that met these criteria. We used data from IHS Herold and the Oil Price Information Service (OPIS) to id these mergers and then had FTC review the list. In addition to the impact of mergers and market concentratio includes other important variables that may influence the price of gasoline. Volume of inventory of gasoline relative to the volume of sales of gaso This could affect the availability of gasoline at the wholesale level and hence affect prices. All other things equal, gasoline prices should decr when inventories are high relative to sales and conversely when inventories are low relative to sales. Further, inventories may themselve respond to changes in wholesale gasoline prices, so this variable may be endogenous. Refinery capacity utilization rate—-this could affect the wholesale pri gasoline through changes in the availability of gasoline product. One possibility is that when utilization rates are high, supply would be increased, resulting in lower prices, and conversely if utilization rates are low. However, it is possible that as utilization rates approach very high levels, there would be significant increases in the cost of production, which could then result in higher prices. As with the inventory-sales ratio, the capacity utilization rate may itself be affected by gasoline prices; for example, if gasoline prices are high, refineries may operate at higher capacity, so this variable may be endogenous. Lagged dependent variable—-lagged values of the left-hand side variabl e. Gasoline price data are sometimes autocorrelated, and it is reasonable to include the effect of past gasoline prices on current gasoline prices. Time fixed effects (dummy variable for each time period in the analysis)— January 2000 through September 2008 is 105 months of data. City fixed effects (dummy variables for each city in the analysis)—-our analysis uses between 78 and 82 cities’ data (we included a fixed effect for each city). These city fixed effects assist in controlling for unobserved heterogeneity. mmy variables for the different types of gasoline used for price. There analysis, and to control for this variation, we include a dummy variable for each type. are over 30 different gasoline types used in our Selection of cities to include in the model—-the OPIS data contain 393 city wholesale terminals. Some of the cities with wholesale terminals may be close geographically so they may not represent independent markets. A result, we used a subset of either 78 or 82 of these cities that were in the refinery most relevant and important metropolitan areas needed to model product flows and product costs. Most cities only had one terminal and we chose to examine only one terminal in the few cases where there was more than one identifying cities where each firm had posted either branded or unbranded . We determined which cities each merger affected by wholesale prices for 26 of the 52 weeks before the merger’s announced date. We assessed the reliability of these data and found them sufficiently reliable for the purposes of this report. This included conducting tests for missing and out-of-range values and checking for completeness and accuracy of the data. y it is the logarithm of wholesale terminal gasoline price at city i in month t. it is a vector of predetermined variables for city i in month t that are x assumed to be independent of the error term uit. This vector includes a lagged value of our dependent variable. r of possibly endogenous variables, at city i in month t. he fixed effect or dummy variable for city i. f is the fixed eff ect or dummy variable for month t. B is a vector of parameters to be estimated. Stata statistical software package. Our parameter estimates are consistent given the assumptions o error estimates arf our model. Our standard e robust to heteroskedasticity and autocorrelation. We estimated the model using the logarithm of pri variable. Note that because we have time dummies control for crude oil because these variables would be co dummies. I, have been shown to be endogenous, so we tested for en squares when appropriate, using merger events and economic activity as instruments. It is also possibl events themselves were endogenous, but in our wor exogenous or predetermined, primarily because we to provide instruments for the seven separate merge dogeneity and used two-stage least other measures of e that the merger k, we treated them had insufficient da rs. We estimated the model with inventory-sales ratio utilization rate as endogenous. In general, our results for the effect of market concentration and mergers were not substantively aff y whether these were treated as exogenous or endogenous. Some of our results for the inventory positive relationship with respect to price, an outcome that was contrary to our expectations. It is possible that either the inventory-sales ratio is misspecified in our model or there may be a complex dynamic relationshi that describes how inventories affect prices and vice versa, conditions could negate the direction of this relationship. -sales ratio showed a significant We estimated separate models for unbranded prices and branded prices. Our gasoline data were selected so as to ge nerally reflect the type of asoline that would be sold in a city, given the local fuel regulations. In g most cases we were able to assign prices accordingly, but in some cases other types of fuel were used in the data. In our regression models, we control for whatever fuel type we did use. We used monthly data for prices and most of our control variables. State- level personal income data were available only quarterly and were app to the appropriate months for that quarter. The inventory-sales ratio and capacity utilization rate were at the PADD level, so we assigned the data observation according to which PADD the city was located in. Similarly, we used state-level data for personal income growth, employment growth, and the unemployment rate, and we assigned the data observations according to the state in which the city was located. Our analysis was performed at the city level, but some of our data were available only at more aggregated geographic levels. The capacity utilization rate and the inventory-sales ratio were available at the PADD level only. Employment growth, personal income growth rate, and the unemployment rate were available at the state level only. One of our measures of market concentration was at the spot market level. It is possible that in some cases these measures are too highly aggregated and these control variables were less precise than would be ideal. We used merger events as instruments for our market concentration measures, which, in general, were found to be endogenous. It is possibl that the merger events themselves are endogenous, but we have no further data that we could have used to instrument the merger variables. We also estimated our model treating the concentration measures, the inventory-sales ratio, and the capacity utilization rate as exogenous. In these results, we found that the impact on prices of our concentration measures was statistically significant but smaller. For example, in the cas of the spot market HHI, the price effects were about half the size in the case of the unbranded regressions, and for the number of city sellers, about one-sixth of the size in the unbranded regressions. While our tests for exogeneity of the concentration measures generally rejected their being exogenous, we wanted to display a range of possible results. We are aware of the limitations of using a fixed effects model to study events such as mergers and to use dummy variables for mergers in such model. Further, we are aware that our model, or any model, is unlikely t account for all conceivable factors affecting prices. With this in mind, w e o used fixed effects for cities and time dummy variables for every time period. The former accounts for special (possibly unobservable) effects that are constant over time, affecting an individual city, and the latter for effects that are constant across cities but vary over time, such as national supply disruptions. Nevertheless, we are aware that these cannot account for every factor that, say, may affect a group of cities for a given period of time; for example, a localized supply disruption, except insofar as this is reflected in the level of inventories or capacity utilization rate in the PADD. The concentration measures that we used are imperfect. On the one h we used the number of sellers at the city terminal, a measure of concentration at the city level that does not measure market share, only market participation. Our other measure, the spot market HHI, geographically than is ideal, and it is measured at the refinery level. The latter means that we are approximating market shares of the sellers a city with shares of refineries in the spot market region. We used a number of methods to test our model but we recognize esults should be viewed carefully. In particular, we are concerned that a r difference in the effect of mergers may depend on whether we used theannounced or the effective merger dates. In order to address this issue, our model of mergers included dummy variables for the period of time between the announced date and the effective date of the merger, as well as a dummy variable for the time following the effective date of each merger. We understand that our methodology is not a substitute for an event st udy. However, our methods could be used in conjunction with such—-in particular, as a broad means to address issues of whether an industry is overly concentrated, since we recognize that it is resource-intensive to conduct an event study for every merger. We are aware that a difference- in-differences model provides an alternative methodology but that method has its own limitations, in particular, the matching of cities for treatment and controls. Our analysis did not account for all gasoline that is sold at wholesale terminals. Our gasoline wholesale price data captured about 60 percent of gasoline sold in the United States, according to EIA analysis. The remaining gasoline is sold directly to retailers, or through other arrangements, and price data for these sales are not always available. These transactions likely also affect the general wholesale market for a particular city. Our model focused on wholesale gasoline prices, so we are unable to determine the extent to which the price effects that we found would be passed on to the retail level. The following are GAO’s comments on the Federal Trade Commission’s letter dated June 3, 2009. 1. Measures of market concentration are inherently difficult to develop because information on relevant market boundaries and sales volumes by gasoline sellers is not readily available. Although we made no changes to the report based on the Chairman’s comment, we wish to emphasize that to improve the robustness of our concentration analysis, we used two measures of market concentration—first, we used the number of sellers at wholesale terminals, and second, we calculated the market concentration of refineries in seven U.S. spot markets. We acknowledge the limitations of our spot market measure that the Chairman noted, especially in the case of the New York Harbor market, and stated these limitations in the draft report. However, as stated above, we did not rely solely on this one measure of market concentration, and we found a qualitatively similar and statistically significant effect when we estimated the impact of the number of sellers at wholesale gasoline terminals on prices. In addition, for both of these measures, we estimated the price effects under another set of statistical assumptions, and found and reported in the draft these similar, though smaller, price effects. Although our two measures of market concentration may not be appropriate for formulating antitrust policy, as the Chairman noted, our findings indicate that the effects of market concentration on prices may occur at lower levels of concentration than previously anticipated, and FTC’s access to more detailed petroleum industry data might allow them to make a more precise estimate of these potential impacts. 2. Although our draft concentration results were correct, our presentation showed that the median value of market concentration was the midpoint in the range of price effects, when in fact the price effects were not evenly spread around the median. We changed the tables and text in our iscussion of the market concentration results to better reflect these price ffects. Additional information on the specific mergers selected for review in GAO’s analysis, including the rationale for the merger, statements or remedial actions identified by the FTC in addressing potential anticompetitive concerns, and other relevant context surrounding the merger, is outlined below. On October 16, 2000, Chevron Corporation and Texaco announced plans to merge, in a transaction ultimately valued at about $45 billion. Both firms were large, fully integrated firms, with operations in oil exploration, pipeline transportation, and refining and marketing of gasoline products, and were considered among the largest integrated oil firms in the world. Chevron’s stated goal in pursuing the merger was to become the industry leader in total stockholder returns. Following the merger, the newly merged firm was projected to become the world’s fourth largest firm in oil exploration and production. FTC’s review of the merger identified a number of antitrust concerns, including coordinated threats in the refining and marketing sectors in a number of regions across the United States, as well as threats in the refining, pipeline, and marketing sectors, primarily across the West. As a result of these threats, FTC required the divestiture of a number of Texaco’s downstream assets, most notably its share of a joint venture with Royal Dutch Shell Group in the refining sector, as well as its share of two major pipelines. See figure 3 for the cities in our analysis where we identified competitive overlaps between these firms before they merged. ated effects of the measures of market concentration on branded asoline prices are shown below. In addition to the individuals named above, Daniel Haas (Assistant Director), Shea Bader, Divya Bali, Frank Cook, Michael Kendix, Robert Marek, Michelle Munn, Alison O’Neill, Susan Offutt, Frank Rusco, R Sandulli, and Barbara Timmerman made important contributions to this report.

Summary: In 2008, GAO reported that 1,088 oil industry mergers occurred between 2000 and 2007. Given the potential for price effects, GAO recommended that the Federal Trade Commission (FTC), the agency with the authority to maintain petroleum industry competition, undertake more regular retrospective reviews of past petroleum industry mergers, and FTC said it would consider this recommendation. GAO was asked to conduct such a review of its own to determine how mergers and market concentration--a measure of the number and market shares of firms in a market--affected wholesale gasoline prices since 2000. GAO examined the effects of mergers and market concentration using an economic model that ruled out the effects of many other factors. GAO consulted with a number of experts and used both public and private data in developing the model. GAO tested the model under a variety of assumptions to address some of its limitations. GAO also interviewed petroleum market participants. GAO examined seven mergers that occurred since 2000--ranging in value and geography and for which there was available gasoline pricing data-and found three that were associated with statistically significant increases or decreases in wholesale gasoline prices. Specifically, GAO found that the mergers of Valero Energy with Ultramar Diamond Shamrock and Valero Energy with Premcor, which both involved the acquisition of refineries, were associated with estimated average price increases of about 1 cent per gallon each. In addition, GAO found that the merger of Phillips Petroleum with Conoco, which primarily involved the acquisition of oil exploration and production assets, was associated with an estimated average decrease in wholesale gasoline prices across cities affected by the merger of nearly 2 cents per gallon. This analysis provides an indicator of the impact that petroleum industry mergers can have on wholesale gasoline prices. Additional analysis would be needed to explain the price effects that GAO estimated. GAO used two separate measures of market concentration, one which measured the number of sellers at wholesale gasoline terminals and another which measured the market share of refiners supplying gasoline to those sellers, and found that less concentrated markets were statistically significantly associated with lower gasoline prices. For example, for wholesale terminals with more sellers--i.e., terminals that were less concentrated--GAO estimated that prices were about 8 cents per gallon lower at terminals with 14 sellers than at terminals that had only 9 sellers. This result is consistent with the idea that markets with more sellers are likely to be more competitive, resulting in lower prices. Using the second measure of concentration, GAO similarly found a statistically significant association between prices and the level of refinery concentration, with less concentrated groups of refineries associated with lower prices.