WORKING 

 PAPERS

Petroleum Mergers and Competition 

in the Northeast United States

Louis Silvia

Christopher T. Taylor 

WORKING PAPER NO. 300

April 2010

___________________________________________________________________________

FTC Bureau of Economics working papers are preliminary materials circulated to stimulate discussion

and critical comment. The analyses and conclusions set forth are those of the authors and do not

necessarily reflect the views of other members of the Bureau of Economics, other Commission staff, or

the Commission itself. Upon request, single copies of the paper will be provided. References in

publications to FTC Bureau of Economics working papers by FTC economists (other than

acknowledgment by a writer that he has access to such unpublished materials) should be cleared with the

author to protect the tentative character of these papers.

______________________________________________________________________________

BUREAU OF ECONOMICS

FEDERAL TRADE COMMISSION

WASHINGTON, DC 20580
1

 

 

Petroleum Mergers and Competition in the Northeast United States

Louis Silvia1

Federal Trade Commission 

Christopher T. Taylor1

Federal Trade Commission 

Last Revised: April 13, 2010 

Abstract: 

 Sunoco’s 2004 acquisition of El Paso’s, New Jersey refinery and Valero’s 2005 

acquisition of Premcor’s Delaware refinery significantly consolidated refinery control in the U.S. 

Northeast. The Federal Trade Commission investigated both transactions but challenged neither. 

We examine the FTC’s enforcement rationale and test whether these mergers were associated 

with post-merger price increases in either gasoline or diesel at retail and wholesale levels. Our 

findings indicate that the transactions were largely competitively neutral. There was some 

indication that some unbranded rack prices may have increased after the mergers, but this result 

was not robust across controls or assumptions. In some other instances, prices in merger affected 

areas may have fallen relative to prices elsewhere after the transactions. 

JEL Classification: L1, L41, L71 

Keywords: Merger retrospectives, Petroleum industry, Horizontal market structure 

 

1

 The authors are economists in the Bureau of Economics of the U.S. Federal Trade Commission. 

The views expressed are those of the authors and do not necessarily reflect those of the Federal 

Trade Commission. 
2

I. Introduction

 The empirical literature on the competitive effects of consummated petroleum 

mergers is limited and its conclusions are mixed.1 The appropriate quantitative 

methodology to identify competitive effects is also debated among analysts.2

 

More retrospective of petroleum mergers are clearly warranted in view of continued 

widespread interest in the competitiveness of the industry. The federal agency in charge 

of antitrust merger enforcement involving petroleum, the Federal Trade Commission 

(“FTC”) also recognizes that merger retrospectives serve to inform its own antitrust 

enforcement decisions (US FTC (2004)). The U.S. Government Accountability Office 

(“GAO”) has similarly concluded that more retrospectives could enhance the FTC’s 

mission to maintain competition in the petroleum (GAO (2008)). Retrospective studies 

may be especially informative on the appropriateness of key presumptions and 

conclusions of earlier, prospective antitrust analyses of the same transactions (Carlton 

(2009)). 

This paper examines Sunoco’s 2004 acquisition of El Paso’s Eagle Point, New 

Jersey refinery, and Valero’s 2005 acquisition of Premcor’s refinery in Wilmington, 

Delaware. We examine the FTC’s enforcement rationale in these mergers and test for 

post-merger price changes. Unlike previous petroleum merger retrospectives, which were 

restricted to gasoline, we test also for competitive effects in diesel fuel. 

 

1

 See U.S. Government Accounting Office (2004), Hastings (2004), Taylor and Hosken (2007), Simpson 

and Taylor (2008), and Taylor, Kreisle, and Zimmerman (forthcoming). 2

 See U.S. Federal Trade Commission, Papers and Proceedings of Federal Trade Commission Conference, 

“Estimating The Price Effects and Concentration in the Petroleum Industry: Evaluation of Recent 

Learning, available at http://www.ftc.gov/ftc/workshops/oilmergers/index.shtm. For a more general 

overview of merger retrospectives, including those involving other industries, see Hunter, Leonard, and 

Olley (2008). 
3

Section II provides background on the transactions and on Northeast bulk supply 

conditions in gasoline and diesel. Section III identifies the key competitive issues raised 

by the transactions. Section IV describes our methodology and data, while Section V 

presents our empirical findings. Section VI summarizes. 

II. Background.

A. The Transactions 

1. Sunoco/El Paso. Sunoco, Inc. (“Sunoco”) bought El Paso’s Eagle Point, New 

Jersey refinery on January 13, 2004 for about $250 million.3 At the time, Sunoco 

operated refineries in Marcus Hook, PA, Philadelphia, PA, Toledo, OH and Tulsa, OK. 

The firm’s logistical unit, Sunoco Logistical Partners, L.P. operated refined product and 

crude oil pipelines and terminals, primarily in the Northeast, Midwest and South Central 

parts of the U.S. A major branded retail marketer of gasoline and diesel fuel, Sunoco had 

4,528 retail outlets in 25 states at the end of 2003. These retail outlets were concentrated 

in Connecticut, Massachusetts, New, York, New Jersey, Pennsylvania, Ohio, Michigan, 

and Florida. Sunoco refineries produced more than its branded retail operations sold. 

For example, in 2003 Sunoco’s four refineries produced an average of 376 thousand 

barrels per day (“MBD”) of gasoline and had sales to unaffiliated customers of 153 

MBD.4

 Primarily concerned with natural gas and electricity, El Paso entered petroleum 

refining in 2001 by acquiring the Coastal Corporation. Coastal owned four petroleum 

 

3

 The transaction included the purchase of inventory and related assets. Related assets included ship and 

barge docks, product truck racks, and a 4.5 mile product pipeline from the Eagle Point refinery to the 

Harbor pipeline, which runs north to Linden, New Jersey. Sunoco, Inc. sold these related assets to Sunoco 

Logistics Partners L.P for $20 million in March 2004. Sunoco Logistics was a Master Limited Partnership 

formed by Sunoco, Inc. to own and operate petroleum pipelines, terminals and storage facilities. Sunoco 

Logistics acquired El Paso’s 33.3 percent share in the Harbor Pipeline for $7.3 million in June 2004. See 

Sunoco Logistics News Releases, March 30, 2004 and June 29, 2004. 

4

 Sunoco, Inc. 2003 10-K, March 5, 2004 at 2-7. 
4

refineries and related marketing assets, as well as assets in the natural gas and chemical 

industries. Not long after buying Coastal, El Paso began to sell Coastal assets, and in 

2003 the firm announced its intention to exit from the petroleum industry.5 The Eagle 

Point sale reflected that decision. At the time of the sale to Sunoco, Eagle Point was 

purely a “merchant” refiner, selling all its output to unaffiliated customers. The Eagle 

Point refinery was about 15 miles away from Sunoco’s two refineries in Philadelphia. 

2. Valero/Premcor. Valero Energy Corporation (“Valero”) acquired Premcor on 

September 1, 2005 for approximately $6.9 billion.6 Valero had 17 refineries at the time 

of the Premcor transaction, including a refinery and an associated product terminal in 

Paulsboro, New Jersey. Valero also transported and stored petroleum products in many 

parts of the U.S. Its refineries supplied both unaffiliated customers and Valero branded 

distributors and retail dealers. At the time of the merger, Valero controlled about 3,000 

retail sites nationwide. Valero also sold gasoline and diesel through company owned and 

operated branded retail outlets nationwide. There were approximately 1000 Valerobranded outlets at the time of the Premcor merger.7

Premcor had four refineries and was a leading seller of unbranded refined 

petroleum products. Its refineries were located in Port Arthur, Texas, Memphis, 

Tennessee, Lima, Ohio, and Wilmington, Delaware. Premcor had no branded wholesale 

or retail operations when it was bought by Valero. Premcor acquired the Wilmington 

 

5

 El Paso sold Coastal’s refineries in Aruba and Corpus Christi, Texas to Valero in 2002 and 2004 

respectively. El Paso sold Coastal’s Mobile, Alabama refinery to Trigeant in 2003. See El Paso 

Corporation 10-K Filings, March 31, 2003 and September 30, 2004. 

6

 Valero Energy Corporation, 2005 10-K, March 1, 2006 at 2. 

7

 Valero Energy Corporation, 2005 10-K, March 1, 2006 at 3-11. 
5

refinery from Motiva on May 1, 2004.8

 Premcor’s Wilmington refinery was a merchant 

refinery, selling all of its output to unaffiliated customers, and was located approximately 

35 miles downstream on the Delaware River from Valero’s Paulsboro refinery. 

 Nearly coincident with Valero/Premcor, Valero proposed to buy Kaneb Pipeline 

Partners, L.P., and a related entity, Kaneb Services LLC (hereafter collectively referred to 

as “Kaneb”) in November 2004.9 Having operations in many parts of the U.S., Kaneb 

was engaged in transporting and terminalling crude oil, intermediate and finished refinery 

products. Kaneb sold no gasoline or other refined products in the Northeast and derived 

revenue exclusively from transportation and terminalling services sold to refiners and 

other marketers of refined products.10 The combination of Kaneb’s three Philadelphia 

area product terminals and Valero’s nearby refinery and product terminal was challenged 

by the FTC.11 The FTC alleged the proposed merger would result in anticompetitive 

effects in both the sale of gasoline and in terminalling services in the greater Philadelphia 

 

8

 Motiva was a joint venture between Royal Dutch Shell and Saudi Aramco. Premcor did not acquire any 

marketing assets from Motiva—which included the venture’s Shell brand wholesale and retail operations--

as part of the Wilmington transaction. See Premcor Inc., 2004 10-K at 12. 9

 The actual transaction was proposed by Valero Limited Partners (“Valero L.P.”), a master limited 

partnership formed by Valero Energy Corporation. Valero L.P was engaged in the transportation and 

storage of crude oil and refined petroleum products, and at the time derived about 98% of its total revenues 

from Valero Energy, which owned 46% of Valero L.P.’s common units. When analyzing the transaction, 

the FTC treated these Valero entities as one. Under the agreement, Valero L.P. would pay $525 million in 

cash and exchange $1.7 billion in Valero L.P. Partnership units for the Kaneb Pipeline Partners partnership 

units. Kaneb Pipeline Partners was a publicly traded limited partnership that owned Kaneb’s product 

pipeline and petroleum product and specialty liquids storage and terminal facilities, including its wholly 

owned subsidiary, Kaneb Pipeline Company which operated these assets. Kaneb Services LLC owned the 

general partnership in Kaneb Pipeline Partners, as well as 5 million shares of Kaneb Pipeline Partner’s 

limited partnership units. For purposes of its competitive analysis the FTC treated these related Kaneb 

entities as one. See Analysis of Proposed Consent Order to Aid Public Comment, available at: 

http://www.ftc.gov/os/caselist/0510022/050615anal0510022.pdf. 10 See Complaint in the Matter of Valero L.P et al., Docket No. C-4141 (June 14, 2005) (hereafter referred 

to as the FTC Valero/Kaneb complaint) at paragraph 31, available at, 

http://www.ftc.gov/os/caselist/0510022/050615comp0510022.pdf. 

Terminalling services involve the storage and throughput of petroleum products, including the dispensing 

of product to tank trucks for delivery to retail outlets. 

11 The FTC also challenged Valero’s acquisition of Kaneb assets in the Colorado Front Range and in 

Northern California. See FTC Press Release, June 15, 2005, available at: 

http://www.ftc.gov/opa/2005/06/valerokaneb.shtm. 
6

area.12 The FTC entered into a consent agreement with Valero that required divestiture 

of Kaneb’s North and South Philadelphia terminals and Kaneb’s Paulsboro, New Jersey 

terminal. Pacific Energy Partners bought these assets on September 30, 2005. Though 

this divestiture maintained the pre-merger status quo in terminals and therefore 

anticompetitive price effects might not be expected, the FTC’s challenge of the 

Valero/Kaneb merger provides additional insight on the agency’s enforcement rationale 

in Sunoco/El Paso and Valero/Premcor, as we discuss below. 

B. Bulk Supply in the U.S. Northeast. 

 The mergers’ possible competitive implications can be better appreciated with an 

overview of bulk supply conditions in the U.S. Northeast at the time of the transactions. 

Bulk supply refers to refinery production and the transport of refined products to 

terminals by pipelines, tankers or barges. Here we focus on the two largest volume 

categories of refined products--gasoline and No. 2 distillates.13 

The Northeast accounted for approximately 16 and 21 percent of total U.S. 

demand for gasoline and distillates respectively in 2003, the year before Sunoco/El Paso. 

Northeast gasoline demand in 2003 averaged about 1,450 MBD, while distillate demand 

averaged 829 MBD. 14 

 

12 FTC Valero/Kaneb complaint, at Paragraph 40. 

13 No. 2 distillates include No. 2 diesel fuel (used for automobiles, trucks and locomotives) and No. 2 fuel 

oil (used in residential and commercial heating). No.2 diesel fuel and No. 2 fuel oil are close production 

substitutes at the refinery level. Other, smaller volume refinery products include jet fuel, general aviation 

gasoline, kerosene, No. 1 and No. 4 distillates, and residual fuel oil. In our empirical analyses, we limit 

consideration to No.2 diesel fuel, the largest volume category in No. 2 distillates. 14 The “Northeast” is defined as the six New England states, New York, Pennsylvania, New Jersey and 

Delaware. Gasoline and distillates consumption for this region are derived from U.S. Energy Information 

Administration (“EIA”) data, available at: 

http://tonto.eia.doe.gov/dnav/pet/pet_pnp_unc_dcu_nus_m.htm

http://tonto.eia.doe.gov/dnav/pet/pet_pnp_pct_dc_nus_pct_m.htm

http://www.eia.doe.gov/pub/oil_gas/petroleum/data_publications/petroleum_supply_annual/psa_volume1/h

istorical/2003/pdf/table_36.pdf

http://www.eia.doe.gov/emeu/states/sep_use/notes/use_print2006.pdf
7

Seven refiners operated in the Northeast in 2003. Aside from the relatively small 

United Refining refinery in western Pennsylvania, all Northeast refineries were located 

on Atlantic Coast. (See Figure One.) Amerada Hess and ConocoPhillips each operated a 

refinery on the New Jersey side of the New York Harbor area. Six other refineries, 

accounting for 80 percent of regional capacity, were located on the lower Delaware River 

in the greater Philadelphia area. These refineries were controlled by five firms in 2003--

Valero, ConocoPhillips, El Paso, Motiva, and Sunoco (with two refineries). Sunoco was 

the Northeast’s leading refiner in 2003, with nearly 33 percent of the Northeast. (See 

Table One.) We estimate that Northeast refinery production accounted for roughly 70 

percent of regional gasoline consumption and roughly 50 percent of distillates 

consumption in 2003.15 

Imports from foreign refineries in 2003 accounted for approximately 22 and 30 

percent of total Northeast consumption of gasoline and distillates respectively.16 Most 

imports were landed in New England and in the New York Harbor area, along with a 

smaller quantity in the Philadelphia area. At least 25 firms imported significant 

quantities of gasoline and distillates into region in 2003, though about 70 percent of both 

gasoline and distillates imports in that year were accounted for by 5 firms. The top five 

gasoline importers in 2003 were Amerada Hess, BP, Citgo, Irving Oil, and Vitol. 

 http://www.eia.doe.gov/emeu/states/_seds.html

http://www.eia.doe.gov/oil_gas/petroleum/data_publications/company_level_imports/cli.html

http://tonto.eia.doe.gov/dnav/pet/pet_move_ptb_dc_R20-R10_mbbl_m.htm

15 Individual refinery production data are not publically available. The Northeast production for gasoline 

and distillates were estimated using EIA data on 2003 Northeast refinery capacity, capacity utilization 

rates, and product percentage yields. 

16 Estimates are based on import data obtained from EIA. 
8

Amerada Hess, Citgo, Global, Irving Oil, and Morgan Stanley were the top five distillates 

importers.17

Gasoline and distillate shipments from the Gulf, approximately 8 and 20 percent 

of Northeast consumption, completed Northeast supply.18 Gulf product arrived in the 

Northeast largely on the Colonial Pipeline, with smaller quantities coming by tanker and 

barge.19 The nation’s largest refined products pipeline, Colonial connected refineries in 

Texas, Louisiana, Mississippi, and Alabama with terminals in the Southeast and MidAtlantic states before terminating in Linden, New Jersey. While quantity data on 

individual shippers into the Northeast from the Gulf are not publically available, many 

firms, including firms without Northeast refinery assets, sent or could have sent Gulfrefined gasoline and distillates into the Northeast.20

Within the Northeast, gasoline and distillates were distributed by pipeline, water, 

and (less frequently) by rail to about 180 product terminals (See Figure One.) Tank 

wagon trucks drew from terminal “racks” to supply retail service stations within a radius 

such as 50 to 75 miles.21 The Laurel, Sun, and Mobil pipelines shipped Delaware River 

refinery product to terminals in western and south central Pennsylvania. Other segments 

of the Sun and Mobil pipeline systems moved products from the Delaware River to north 

central and north eastern Pennsylvania and to central and western New York. Another 

 

17 Company level imports are based on data from EIA. 

18 EIA does not directly report shipments of domestically refined product into the Northeast. Our estimates 

of domestically refined products shipped into the Northeast are based on EIA data on inter-PADD 

shipments, adjusting for apparent consumption of these shipments outside of the Northeast. 

19 Small quantities of gasoline and diesel may also have been barged into the Northeast from the Giant 

refinery in Yorktown, Virginia. Relatively small quantities of refined product may also have been barged 

on the Ohio River into the Pittsburgh area. 

20 Gulf refiners connected to Colonial, but having no Northeast refineries in 2003, included BP, 

ExxonMobil, and Chevron. Colonial reported over 80 shippers on its system in 2008, including Gulf area 

refiners, branded marketers not integrated into refining, and product traders. See Colonial Pipeline website 

at www.colpipe.com/ab_oc.asp. 21 This distance depends on traffic congestion, fuel costs, demand density, and relative prices at other 

terminals. 
9

segment of the Sun pipeline system and the Harbor Pipeline transported Delaware River 

refined product to the New York Harbor. Colonial could also pick up product from some 

Delaware River refiners for shipment north to the New York Harbor. Some Delaware 

River refineries also barged some product to the New York Harbor. 

The Buckeye pipeline system was an important regional pipeline. From origins in 

the New York Harbor area, gasoline and distillates traveled west on Buckeye to north 

central New Jersey and into Pennsylvania. In Macungie, Pennsylvania, the Buckeye 

system branched north to supply terminals in northeast Pennsylvania and upstate New 

York. The southern branch served terminals in southern Pennsylvania and connected with 

the Laurel pipeline in Sinking Spring, Pennsylvania, approximately 65 miles northwest of 

Philadelphia. The Colonial pipeline connected with the Laurel pipeline at Booth, 

Pennsylvania. The Laurel pipeline was thus capable of shipping product originating from 

three sources: the Gulf, Delaware River refineries, and from the New York Harbor. 

Some volumes of gasoline and distillates were redistributed from the New York 

Harbor area by barge or tanker to smaller ports such as Albany and New Haven. Though 

water redistribution from New York Harbor was generally to the north, shipments to 

terminals to the south, such as those on the Delaware River, may have sometimes 

occurred. 

Domestically refined petroleum products arrived in New England primarily by 

tanker or barge, though limited quantities may have come from Canada and New York 

State by truck or rail. No pipeline connected New England to sources in the south, though 

several small pipelines linked New England ports to terminals in the interior. A Buckeye 

pipeline moved product from New Haven through Hartford to terminals near Springfield, 
10

Massachusetts. An ExxonMobil pipeline carried refined product into central 

Massachusetts from East Providence, Rhode Island. Another ExxonMobil pipeline 

originated Portland, Maine and carried product north to Bangor. 

New England relied more heavily on imports than the rest of the Northeast. In 

2003, for example, foreign imports delivered to New England ports were about 57 and 60 

percent of New England consumption of gasoline and distillates, respectively.22

 To sum up, Northeast refinery capacity at the time of the mergers was primarily 

located on the Atlantic Coast, with most capacity concentrated on the lower Delaware 

River. Though accounting for most of regional supply, regional refiners had insufficient 

capacity to meet regional demand. Shipments from the Gulf on Colonial and foreign 

imports, which were primarily landed in New England and the New York Harbor area, 

rounded out Northeast supply. Pipelines, tankers and barges, and to a lesser extent rail, 

were used to move bulk quantities of refined product within the Northeast, though the 

logistics in supplying particular terminals with the region varied. 

III. The FTC’s Antitrust Concerns.

 The FTC’s closing statement on the Sunoco/El Paso investigation identified the 

two “most plausible concerns of anticompetitive harm”: 1) an increase gasoline prices in 

the Philadelphia area, and 2) an increase in gasoline prices along locations served by the 

Laurel pipeline, an area in central Pennsylvania which the FTC referred to as the “Laurel 

Corridor.” 23 The FTC concluded that an anticompetitive, Philadelphia-area price 

increase by local refiners would be defeated by diversion of Colonial shipments from 

 

22 Based on EIA import and consumption data. See footnote 15. 

23 Statement of the Commission in the Matter of Sunoco Inc./Coastal Eagle Point Company, File No. 

0310139, December 29, 2003, (hereafter referred to as the FTC statement on Sunoco/El Paso) available at: 

http://www.ftc.gov/os/caselist/0310139/031229stmt0310139.pdf. The FTC does not usually issue 

statements when investigations are closed. No statement was issued in Valero/Premcor. 
11

delivery in the New York Harbor area to Philadelphia area terminals. The FTC concluded 

that, because the New York area had ample supply from alternative sources, a diversion 

of Colonial supply into Philadelphia would not cause price increases in the New York 

area. Increased waterborne shipments into the Philadelphia area, particularly from the 

U.S. Virgin Islands, would also keep prices at a competitive level, according to the FTC 

statement.24 As for the Laurel Corridor, the FTC analyzed “expressions of concern” that 

Delaware River refiners could increase post-merger prices in the Corridor because other 

potential sources, Buckeye and Colonial, were full during the summer, were not 

“economically viable” relative to Delaware River refiners, or were otherwise 

“constrained by certain logistical impediments.” Upon further investigation the FTC 

concluded that any post merger attempt by Delaware River refiners to raise Corridor 

gasoline prices anti-competitively would not succeed because of increased shipments into 

the Corridor via the Colonial Pipeline. 

 The FTC’s complaint in Valero/Kaneb provides information about the agency’s 

competitive concerns in this region and therefore provides additional insight regarding 

Sunoco/El Paso and Valero/Premcor. Kaneb operated three terminals, two in 

Philadelphia and one in nearby Paulsboro, New Jersey. Among other things, the FTC 

alleged that the Valero/Kaneb merger would have adverse competitive consequences at 

the bulk supply level.25 The Kaneb terminals were connected to Colonial. One of 

 

24 The Hovensa refinery, located in the U.S. Virgin Islands, had an operable capacity in 2003 of 470 MBD, 

making it one of the largest refineries in the world. Hovensa was a joint venture of Amerada Hess and 

Petroleos de Venezuela, S.A. Amerada Hess operated a product terminal in the Philadelphia area capable 

of receiving deep water cargoes. 

25 The FTC also alleged that Valero and Kaneb were direct horizontal competitors in providing terminalling 

services for refined products in the greater Philadelphia area. Valero operated a product terminal in 

Paulsboro, NJ, which was supplied by its adjacent refinery. This competitive concern was independent of 

the transaction’s competitive implications at the bulk supply level to the extent that terminals in the area 

only provided terminalling services for locally refined product. 
12

Kaneb’s Philadelphia terminals also could receive product by barge, and the Paulsboro 

terminal was capable of receiving bulk shipments by deepwater tankers. The FTC 

alleged that shippers using the Kaneb terminals imposed a competitive constraint upon 

Philadelphia area prices such that area prices would be generally limited by “either Gulf 

prices plus pipeline tariff or New York Harbor prices adjusted by water-borne 

transportation costs...”26 Absent this constraint, the FTC alleged that a combined 

Valero/Kaneb could effectively coordinate with other Delaware River refiners or terminal 

operators (presumably including Amerada Hess, which also operated an terminal in the 

area) to raise Philadelphia area prices. As earlier discussed, the FTC entered into a 

consent agreement under which Kaneb’s Philadelphia area terminals would be divested. 

The FTC’s analysis in Valero/Kaneb presumed that Valero/Premcor had been 

consummated, indicating that the agency believed that the constraint imposed by Colonial 

and water shipments into the Philadelphia area were sufficient to maintain the level of 

pre-merger competition among the three remaining local refiners.27 

As stated in the FTC complaint in Valero/Kaneb, the leading competitive concern 

was collusion among Delaware River refiners to raise gasoline prices in selected 

locations in the Northeast. The agency apparently concluded that price increases in other 

parts of the Northeast (or for the Northeast overall), or for refined products other than 

gasoline, were less plausible.28 Implicit in the FTC’s enforcement rationale is the 

assumption that successful collusion among a broader group of firms that also included 

 

26 FTC Complaint in Valero/Kaneb, at Paragraph 38. 

27 Ibid., at Paragraph 36. 28 The FTC statement on Sunoco/El Paso noted that it did not discuss all the potential markets for which the 

FTC conducted an investigation, only those that raised the most plausible anticompetitive concerns. 
13

Colonial shippers and importers was unlikely, and absent any significant constraints on 

these alternatives, the mergers would not likely result in anticompetitive price increases. 

 We test the FTC’s enforcement rationale in these mergers by evaluating the 

following questions: 

 1) Did gasoline or diesel prices in the greater Philadelphia area rise after the 

Sunoco/El Paso and Valero/Premcor mergers compared to other prices elsewhere in the 

Northeast29? 

 2) Did gasoline or diesel prices along the Laurel Corridor go up after the mergers 

compared to prices at other Northeast locations? 

 3) Did gasoline or diesel prices in the Northeast increase post-merger relative to 

prices outside the Northeast? 

IV. Methodology and Data. 

The most common empirical strategy to identify merger price effects is some 

form of a difference-in-difference (“DID”) estimator.30 Prices in areas potentially 

affected by a merger (“treatment” areas) are compared to prices in unaffected areas 

(“control” areas) that have similar demand and cost changes as those in treatment areas. 

Differences in the pre- and post-merger price difference between treatments and controls 

ideally identify merger effects because common cost and demand shocks are netted out. 

A. Baseline Model 

 

29 We do not separately test for effects from Valero/Kaneb. First, Valero/Premcor and Valero/Kaneb were 

consummated nearly at the same time, thus making it difficult to segregate any effects from the two 

mergers. Second, because the FTC entered into a consent requiring divestiture of Philadelphia area 

terminals in Valero/Kaneb, anticompetitive effects might not be expected. However, if for some reason the 

divestiture did not maintain the competitive status quo, any price effects from Valero/Kaneb would be 

limited to the Philadelphia area, and in our analyses these would be attributed to Valero/Premcor. 30 For examples of this approach involving non-petroleum industry mergers, see Barton and Sherman 

(1984), Kim and Singal (1993), and Vita and Sacher (2001). See Hastings (2004), Hastings and Gilbert 

(2005), Taylor and Hosken (2007) and Simpson and Taylor (2008) for examples involving petroleum 

industry mergers. 
14

 We assume that the price of gasoline (or diesel fuel) in an affected area (pAt) can 

be explained by changes induced by Sunoco/El Paso and Valero/Premcor, seasonal 

effects (proxied by month dummies, Dmt), and time-specific supply and demand shocks 

(t) as described by equation (1) below. We make the usual assumption that the 

transactions are exogenous. 

11

At 0 1 2

1

(1) p Sunoco(1) Valero(2) t t m mt t At

m

     D      

The prices in the control areas (pCt) are explained by a similar relationship described by 

equation (2) below: 

11

Ct 0

1

(2) p m mt t Ct

m

   D    

To estimate the price effects of the transactions, we take the difference of equations (1) 

and (2) and estimate equation (3) below, which eliminates common, time-specific shocks 

(t). 

11

At Ct 0 0 1 2

1

(3) p -p ( ) (1) (2) ( ) ( ) t t m m mt At Ct

m

       Sunoco Valero D        

We allow for differing price levels in affected and control areas 0 0 ( )    and for 

systematic differences in seasonal pricing( )  m m   .

31 Because the error term of 

equation (3) is autoregressive, we employ an AR(1) correction.32 Estimates of α1 and α2

may be either positive or negative depending on whether the merger was anticompetitive 

or, on the other hand, led to lower prices due to merger-related efficiencies. 

 B. Control Areas

 

31 For example, there are regional differences in seasonal changes in gasoline prices, driven by such factors 

as pipeline constraints and summer/winter differences in formulations. 

32 We use the Prais-Winsten correction for autocorrelation. 
15

 Identification of merger price effects requires common, time-specific supply and 

demand shocks (t) in treatment and control areas. If treatment and control areas instead 

experience persistently different demand or cost shocks, disentangling any merger price 

effects from any demand or cost changes is impossible.33 Most of the variability in 

gasoline and diesel prices is attributable to changes in crude oil prices. Because refined 

product prices everywhere are similarly sensitive to crude oil price changes, choice of 

control area is not very critical to account for shocks related to crude. The bigger 

challenge is designating control areas that share other important cost and demand shocks 

affecting refining and bulk transport, including outages, capacity constraints, and changes 

in transportation charges or in the refiners’ and marketers’ opportunity costs in 

geographically allocating product. Areas close to a treatment area would more likely 

share these demand and costs shocks, but relatively close areas may be less than ideal 

controls because their prices might be impacted by a merger-related price change in a 

treatment area due to geographic arbitrage. 

Acknowledging these tradeoffs, we use multiple, alternative control areas of 

varying proximity for each affected area to assess the robustness of our results. We have 

generally designated controls far away enough from affected areas such that price 

differences are unlikely to be arbitraged by consumers at the retail level or by distributors 

at wholesale who might divert tank trucks from terminals in a treatment area to terminals 

in a control area. 

 

33 Not only should the areas experience the same shocks, but the pass through of the shocks from one price 

level to the next needs to be the same. See Simpson and Schmidt (2008). 
16

We also pair treatment and control areas with the same gasoline specification 

because time-specific shocks across different gasoline specifications may vary.34 At the 

time of the mergers, federal environmental regulations required that the entire states of 

Delaware, New Jersey, Connecticut, Rhode Island, and Massachusetts and parts of New 

York, Pennsylvania and New Hampshire use “reformulated” gasoline (“RFG”), a more 

expensive, but less polluting specification than conventional gasoline. Conventional 

gasoline was sold in all other parts of the Northeast at the time of the mergers, though the 

greater Pittsburgh area and southeast Maine required a variant of conventional gasoline 

(low Reid Vapor Pressure gasoline, sometimes referred to as “7.8 grade”) for summer 

time use. 

Arbitrage between our designated control and treatment areas at the bulk supply 

level might still occur. For example, in response to a merger-related price in the 

Northeast, Gulf refiners and other marketers might divert pipeline shipments to the 

Northeast from control areas that we have designated in the Southeast and Midwest. 

However, we assume, that for any plausible merger-related output reduction in any 

affected Northeast location, any resulting arbitrage at the bulk supply level would be 

spread over such a broad area that any price effect in specific control areas is de minimus. 

 1. Northeast Controls for Philadelphia. We select Boston and Newark as 

controls to test whether Philadelphia post-merger prices changed relative to other 

Northeast locations. These three areas consistently used the same gasoline specification 

 

34 For example, refiners might differ, at least in the short run, in their capabilities to produce different 

gasoline fuel specifications, raising the possibility of different supply shocks across gasoline specifications 

should there be refinery outages. 
17

during the period--RFG North. 35 We also used Boston and Newark as controls in our 

diesel analysis, although diesel regulatory requirements were not similarly geographically 

differentiated. Though close enough to Philadelphia to raise some questions about its 

independence as a control due to tank truck arbitrage, Newark is of interest due to the 

FTC’s conclusion that New York Harbor area prices would not increase after the Sun/El 

Paso merger because of competition from imports and the two New York Harbor refiners. 

2. Northeast Controls for the Laurel Corridor. We measure prices in the 

affected Laurel Corridor at two points—Harrisburg and Pittsburgh. Harrisburg and most 

of the rest of Pennsylvania used standard conventional gasoline. Albany, NY and Bangor, 

Maine used the same fuel specification as Harrisburg, and we utilize those areas as 

Northeast controls for Harrisburg. Pittsburgh also used conventional gasoline, but with a 

special 7.8 RVP mandate during the summer. Having the same RVP restrictions during 

the period, Portland, Maine was our only Northeast control choice for Pittsburgh. We use 

the same control areas for Harrisburg and Pittsburgh in our diesel analysis. Interest in 7.8 

RVP is motivated by the possibility that market power might be more easily exercised in 

relatively low volume, “boutique fuels.” 

 3. Outside of Northeast Controls for Northeast Prices. To test whether 

Northeast prices rose relative to prices outside the Northeast, we again group treatments 

and controls by gasoline specification. We compare gasoline prices in Philadelphia, 

Newark, and Boston to RFG prices in other parts of the U.S. However, aside from 

Louisville, KY which also requires RFG North and which we use as a control, other parts 

 

35 We ruled out controls in New York and Connecticut because, although these areas also used RFG North, 

they switched to ethanol from MTBE as a gasoline oxygenate by December 31, 2003, a date nearly 

coincident with Sunoco/El Paso transaction. Other parts of the Northeast using RFG North did not switch to 

ethanol as an oxygenate until summer of 2006. 
18

of the U.S. requiring RFG used the slightly different RFG South formulation.36 Because 

RFG South and RFG North appeared to be close substitutes in production (closer than 

conventional gasoline or diesel), we use the RFG South locations of Fairfax, Virginia 

and Houston, Texas as controls for Northeast RFG prices, though we recognize that RFG 

North/South differences somewhat weaken these controls. In conventional gasoline we 

pair the treatment area, Harrisburg, with the controls areas of Charlottesville, Virginia, 

Roanoke, Virginia, and Lexington, Kentucky. Outside-of-Northeast controls for 

Pittsburgh and its 7.8 RVP gasoline are Detroit, Michigan and New Orleans, Louisiana. 

The same out-of-Northeast controls are used in the diesel analysis. 

C. Merger Windows

 Our analysis requires a pre-merger period sufficiently long to estimate pre-merger 

price relationships between treatment and control areas, and a post-merger period 

sufficiently long to allow firms to take advantage of any merger-related market power or 

efficiencies. The post-merger period cannot be so long, however, as to pick up nonmerger related changes in market conditions that might affect relative prices in treatment 

and control areas. In our baseline estimates we use a two year window prior to January 

13, 2004, the day Sunoco/El Paso was consummated. 

We assume that merger price effects may occur immediately upon consummation. 

The Sunoco/El Paso post-merger window in our baseline estimates is twenty months, 

ending on September 1, 2005, the consummation day for Valero/Premcor. The possible 

merger effect for Valero/Premcor is measured from September 1, 2005 until the end of 

 

36 Northern and Southern RFG have different volatile organic compound (“VOC”) emission standards 

during the summertime. See U.S. Environmental Protection Agency, “Study of Unique Fuel Blends 

(“Boutique Fuels”), Effects on Fuel Supply and Distribution and Potential Improvements,” October 2001, 

available at http://www.epa.gov/otaq/regs/fuels/p01004.pdf at 85-86. 
19

the data in December 2007. Note that if there were a Sunoco/El Paso effect that did not 

show up until after consummation of Valero/Premcor, that effect would be reflected in 

the Valero/Premcor merger estimate. Recognizing that merger effects might not occur 

immediately, we also test for effects with windows opening three and six months after 

consummation as a robustness check.37 

 D. Measurement of Price

 The mergers did not increase control of competing retail outlets and directly 

implicated competition only at the bulk supply level. As such, the transactions’ primary 

effect should be upon wholesale prices. However, suitably disaggregated available data 

on wholesale gasoline and diesel prices are limited to wholesale rack prices: those prices 

paid by distributors at product terminals. Other wholesale prices, for which public data 

are more limited or totally unavailable, include bulk spot prices (arm’s length, individual 

sales of large quantities of gasoline or diesel), refinery gate price (FOB prices for 

specified volumes or range of volumes set under negotiated contracts of various 

durations), dealer tank wagon prices (prices set by refiners and other marketers for 

delivery of gasoline and diesel to individual service stations), and internal transfer prices 

(for refiners and marketers who own and operate their own service stations). If merger-

 

37 Some analysts have used a post-merger window beginning at a transaction’s announcement date (GAO 

(2009)). We think a post-merger window beginning at the announcement date is unrealistic because of the 

uncertainty that the transaction will be completed due to either antitrust challenge or purely business related 

reasons and because of significant penalties should antitrust enforcers uncover any attempts to jointly 

control the merging firms prior to consummation. Such “gun jumping” may be detected during prospective 

review by antitrust authorities, and merging firms may be liable for penalties even if the merger itself goes 

unchallenged. 

Effects beginning sometime after consummation might be expected for several reasons. Refinery 

output slates are largely determined up to several months in advance as refiners seek to lock in crude oil 

and other input purchases. Pipeline nominations are also made on an advance basis, and some contracts 

with bulk purchasers may limit refiners’ ability to adjust output immediately. Moreover, if post-merger 

collusion were a competitive concern, some time might pass before coordinating rivals reached a consensus 

on prices. Finally, even a longer period of time might be required for firms to capture any merger-related 

efficiency gains. 
20

related price effects vary across these different wholesale prices, basing the analysis just 

on rack prices may yield misleading results. The net effect of any changes across all 

wholesale prices should be reflected in retail prices, however. Consequently, we test for 

both retail and wholesale rack price effects. 

Our price data comes from the Oil Price Information Service (“OPIS”). OPIS 

collects data on retail and wholesale rack prices for numerous areas. Rack prices consist 

of the daily average price for branded and unbranded gasoline and diesel at terminal 

locations based on OPIS’ survey of terminal operators. OPIS’ retail data is derived from 

service stations that accept corporate fleet cards. We use the OPIS constructed average 

retail price for specific OPIS-designated areas. OPIS calculates this price as the average 

price over all retail outlets in an area that report on a give day, e.g., all stations in the 

Pennsylvania portion of the Philadelphia area. While OPIS retail price data are among the 

best available, they do not represent a random sample of retail outlets, and not every 

outlet may report on every day. 

OPIS’ retail price includes taxes, but we remove all federal, state and local taxes. 

We aggregate the daily data to the weekly level, in part to mitigate any changes in sample 

composition that might arise from day to day changes in the number and identity of 

reporting retail outlets. For comparability, we also aggregate daily wholesale prices to 

the weekly level by taking the weekly average of the daily average branded and 

(separately) the unbranded low wholesale OPIS prices. 
21

Most gasoline sold in the U.S.--approximately 80 percent in 2002--is regular 

octane gasoline, and thus we focus on the regular gasoline in this study. There is only one 

grade of diesel fuel, although its specification has changed over time.38 

E. The 2005 Hurricanes 

 The supply disruptions from two major Gulf area hurricanes of 2005 would likely 

confound our merger effect estimates. Hurricane Katrina came ashore on August 29, 

2005 and Hurricane Rita struck on September 24, 2005. These storms devastated Gulf 

Coast refinery and pipeline infrastructure and resulted in large price spikes for refined 

products throughout the U.S, as well as temporarily widening price differences among 

geographic areas. To control for these hurricane effects, we include a week-specific 

dummy, and in our baseline estimates we designate the weeks from September 1 through 

the end of November 2005 as hurricane-affected. While we report results without the 

hurricane control below, we believe that estimates controlling for the hurricanes to be 

more probative.39 We also later report on robustness checks in varying the duration of 

the hurricane affected period. 

V. Results 

 A. Descriptive Statistics

 Table Two presents descriptive statistics on gasoline and diesel prices grouped by 

treatment area and measure of price. Reading right to left, the first row of each grouping 

shows the number of weekly observations, the treatment area’s mean price, standard 

 

38 A formulation change from low-sulfur to ultra-low sulfur diesel was mandated by the U.S. 

Environmental Protection Agency (“EPA”) in 2006 for on-highway diesel, and in 2007 for off-road diesel. 

Most states completed this change by the end of summer 2006. See EPA’s Direct Final Rule, available at, 

http://www.epa.gov/otaq/regs/fuels/diesel/420f06033.htm. 39 See U.S. Federal Trade Commission, Investigation of Gasoline Price Manipulation and Post-Katrina 

Gasoline Price Increases, (Spring 2006) (hereafter referred to as “FTC Katrina Report”), available at 

http://www.ftc.gov/reports/060518PublicGasolinePricesInvestigationReportFinal.pdf. 
22

deviation, and its minimum and maximum prices. Rows below in each grouping report 

the mean price difference between the treatment and control areas, this difference’s 

standard deviation, and the minimum and maximum differences. For example, 

Philadelphia’s mean (less tax) retail gasoline price was $1.62 per gallon over the period, 

ranging from a low of 60 cents per gallon to a high of $2.84. The mean difference in 

gasoline between Philadelphia and the control areas was no more than about 5 cpg, 

although there was considerable variation in the minimum and maximum differences 

across controls. Standard deviation of treatment/control price differences, as well as 

minimum and maximum treatment/control differences varied across pairings. For 

example, the standard deviations of Philadelphia-Boston and Philadelphia-Newark price 

differences (3.1 and 3.5 respectively) were smaller than those for the other Philadelphia 

controls of Fairfax (5.1), Louisville (11.2) and Houston (7.4). 

 Table Two also shows that both branded and unbranded rack prices have smaller 

average treatment/control differences as compared to retail. Standard deviations of the 

differences in rack prices are also generally lower than those at retail, which is not 

surprising because the rack prices do not include variation in the retail markup. 

Unbranded pricing differences are more volatile than the branded pricing differences as 

expected because unbranded prices typically react more to supply disruptions or 

shortages than branded prices.40 The average price for the different gasoline 

specifications are in the order expected based on differences in refinery costs: the 

average branded conventional price (in Harrisburg) is about two cents per gallon less than 

boutique, low RVP conventional (Pittsburgh) and about five cents less than the average 

 

40 See Bulow et al. (2003) for a discussion of relationship between branded and unbranded prices and their 

reactions to supply disruptions. 
23

price of RFG (Philadelphia).41 Diesel price relationships and standard deviations among 

treatment/control pairs are generally similar to those for gasoline, adjusting for the higher 

average price of diesel compared to gasoline. 

 B. Baseline Results. 

 Table Three presents estimated price effects for the Sunoco/El Paso and 

Valero/Premcor based on control areas within the Northeast. Table Four shows estimated 

effects in treatment areas based on controls outside the Northeast. Rows 2, 4, and 6 of 

the tables show estimated effects on retail, branded rack, and unbranded rack prices, 

taking into account the hurricane period, while estimates in rows 1, 3, and 5 are without 

the hurricane control. It is obvious that the estimates can be very sensitive to controlling 

for the hurricane period. As noted above, we believe the estimates controlling for the 

hurricanes are more probative of the mergers’ possible effects, and we restrict our 

discussion to those results. 

 Turning first to Sunoco/El Paso, we find no statistically significant, positive 

estimate for retail prices for any treatment area, although statistically significant negative 

estimates are found in two instances (Pittsburgh/Portland in diesel, and 

Harrisburg/Roanoke in gasoline). Sunoco/El Paso was not associated with any 

significant price effect in branded rack prices in any treatment/control pairing. Estimates 

for unbranded rack were not generally significant, but there were several exceptions: 

significant positive estimates in gasoline for the Philadelphia/Newark pairing and in 

diesel for Harrisburg/Bangor, Pittsburgh/Portland and Harrisburg/Charlottesville; a small 

but statistically significant effect was found in diesel for Harrisburg/Albany. On net, 

 

41 Lidderdale and Bohn (1999) estimate that phase II RFG would cost four to five cents more per gallon 

than conventional gasoline. 
24

these baseline results indicate that Sunoco/El Paso had little or no important 

anticompetitive effect. They suggest no positive impact on either retail or branded rack 

prices, a finding that was robust across all control areas. Estimates for unbranded prices 

were more mixed, but even here most controls suggested no significant effect. 

 Results for Valero/Premcor are somewhat more complex.42 The results suggested 

no positive price impact upon Laurel Corridor prices, and, as Table Four shows, in a 

number of instances Harrisburg and Pittsburgh prices appear to have significantly fallen 

relative to control areas outside of the Northeast--nearly all relative price declines were in 

diesel. Any anticompetitive effects of Valero/Premcor appear limited to Philadelphia 

prices, although the evidence for a Philadelphia effect is mixed. Table Three shows 

merger-related, retail price increases of about 3 cents per gallon in Philadelphia relative 

to Boston in both gasoline and diesel; a similar increase in Philadelphia diesel (but not in 

gasoline) relative to Newark was also found. Retail estimates using the outside of 

Northeast controls of Fairfax, Louisville and Houston were not significant, however. At 

rack, the Valero/Premcor transaction was estimated to have a significant positive effect 

upon Philadelphia branded diesel prices relative to Newark, while the estimated effect on 

Philadelphia unbranded diesel prices relative to Newark was significantly negative (and 

surprisingly large). Unbranded Philadelphia rack gasoline prices appeared to have risen 

relative to Newark post merger. Estimated Valero/Premcor rack price effects for all other 

treatment/control pairs were either insignificant or significant and negative. 

 C. Discussion and Robustness Checks

 

42 As noted previously, these estimates may also reflect any effects from Sunoco/El Paso that occurred after 

consummation of Valero/Premcor. 
25

 Identification of merger effects depends critically on choice of control areas. 

Because no control is ideal, evaluating post merger effects using multiple alternatives is 

an important robustness check. Our baseline results provided 168 merger effects 

estimates. The vast majority (138 out of 168) was statistically insignificant, while 21 

estimates were significant but negative. Only 9 estimates suggested a significant positive 

price increase, and just 3 of these were at retail. Thus the preponderance of evidence, 

based on a count of significant estimates among treatment/control pairings, suggest that 

the mergers were, at worst, competitively neutral. 

 Differences in the price relationship of the treatment and control areas caution 

against drawing inferences only from a count of significant results across control 

alternatives. Prices in treatment areas are more closely related to those in controls within 

the Northeast compared to outside controls. This pattern is consistent for the three price 

levels for both gasoline and diesel. As Table Two indicates, for example, the standard 

deviation of Philadelphia/Boston RFG price difference (3.1 at retail) is noticeably smaller 

than the standard deviation in the Philadelphia/Fairfax price difference (5.1), despite 

Fairfax and Philadelphia being closer geographically. Similarly, in conventional gasoline, 

Harrisburg retail prices are more closely related to those in Bangor, Maine than in 

Roanoke, Virginia (standard deviation in the difference from Bangor of 2.8, compared to 

5.1 for the difference from Roanoke). We interpret these differences in the tightness of 

price relationships as indicating that, although both Gulf and foreign imports are shipped 

into the regions, imports are generally the more important of the two in determining 

Northeast prices. This finding is contrary to the FTC’s assumption in evaluating these 
26

transactions, which as noted above, viewed Gulf product as the chief potential constraint 

of any anticompetitive behavior by Northeast refiners. 

 These considerations also imply that results with Northeast controls should be 

given greater weight in assessing the mergers’ competitive effects. While the Northeast 

controls may not be ideal because their prices may be more likely affected by the 

transactions compared to out of the Northeast control area, the impact of any such effect 

should be to bias against finding significant, merger related effects. But Table Three 

reports a number of significant effects, including several positive estimates of between 

one and three cents per gallon for Philadelphia area prices. Because the results with 

Northeast controls may be more telling about the mergers’ competitive effects, we focus 

our robustness checks on the regressions in Table Three. 

 1. Robustness and Timing Assumptions. We first apply robustness checks that 

vary our baseline timing assumptions on 1) the length of the pre-merger period, 2) the 

time when the mergers were assumed to affect prices, and 3) the duration of the 

hurricane-affected period. That the baseline merger estimates might be sensitive to timing 

assumptions is illustrated by Figure Two. Figure Two depicts the timing assumptions in 

the baseline model along with, as an example, retail price differences between 

Philadelphia and three control areas-Newark, Boston and Fairfax. While there is volatility 

in all price difference series, the tighter price relationships between Philadelphia and 

Newark and Philadelphia and Boston compared to Philadelphia versus Fairfax is evident. 

The extreme volatility in price differences during the hurricane period is particularly 

notable. Differences in other treatment and control prices exhibit similar volatility over 

the period of the data. 
27

 Table Five reports the results of varying our timing assumptions for Sunoco/El 

Paso, while Table Six reports comparable findings for Valero/Premcor. Column Two 

identifies significant merger effect estimates in the baseline model for all 

treatment/control/price combinations, while columns to the right indicate whether 

significant merger effect results were obtained by altering timing assumptions. The “premerger period” column reports results when the baseline model is re-estimated by 

dropping 2002, thus using a pre-merger period of just 2003. Columns 4 and 5 report 

results when the baseline model is re-estimated by delaying the effective date for possible 

price effects by three and six months respectively after the mergers’ actual 

consummation. Columns 6 and 7 show results in changing assumptions about the 

duration of the hurricane-affected period. The re-estimation in Column 6 assumes the a 

hurricane period beginning two weeks earlier than in the baseline to capture any 

anticipatory price changes; the estimates in Column 7 assumed that the hurricane period 

lasted an additional three months beyond the baseline assumption so as to capture any 

lingering effects of the storms. 

Tables Five and Six show that the results are largely robust to these changes in 

timing assumptions. Results that were statistically insignificant under the baseline 

generally remained insignificant under the timing assumption alternatives. There were 

several exceptions to this (e.g. Philadelphia/Newark gasoline and diesel retail in 

Sunoco/El Paso) but none of these results were robust across the timing alternatives. With 

some exceptions (e.g. Philadelphia/Newark diesel retail in Valero/Premcor), estimates 

that were significant in the baseline generally remained significant (and with the same 

sign) under the timing assumption alternatives. 
28

 One robust significantly positive result in both transactions is the positive effect in 

unbranded RFG gasoline in the Philadelphia/Newark comparison. While this positive 

result was not observed in the other RFG comparison (Philadelphia/Boston), we note that 

the only other study to examine any of these transactions, GAO (2009), found that the 

Valero/Premcor merger was also associated with a statistically significant price increase 

in unbranded rack gasoline of 1.1 cents per gallon, but –similar to our results--no 

statistically significant effect for branded rack.43 

 Significantly positive retail price effects in the Philadelphia/Boston comparison 

in Valero/Premcor were also relatively robust. We found this result surprising in the 

absence of positive rack price effects, although, as discussed above, such an outcome 

might occur because not all wholesale prices are observed. As can be seen in Figure Two, 

the retail price of gasoline was increasing in Philadelphia relative to Boston in the premerger period. This trend is even more pronounced in the retail diesel data, but the causes 

for these trends are unclear. To further examine whether retail prices changed in 

Philadelphia, we re-ran the regressions with three other New England areas--Barnstable, 

Massachusetts, Portsmouth, New Hampshire and Providence, Rhode Island--as controls. 

We did not detect any significant increase retail price of gasoline or diesel in Philadelphia 

after Valero/ Premcor relative to any of these three alternative control areas.44 

 2. Year Effects 

We also checked the robustness of the baseline results by comparing one full year 

before the transactions, 2003, to one year after each transaction, 2004 for Sunoco/El Paso 

 

43 GAO (2009) took into account rack prices at more locations than in our study, but did not control for 

supply disruptions from the 2005 hurricanes. As Tables Three and Four show, the hurricanes mattered, 

especially for the unbranded rack estimates. 

44 We do not have rack prices for these three additional New England areas. 
29

and 2006 for Valero/Premcor. This regression had the same dependent variable as 

equation (3) and has year dummy variables instead of merger specific dummy variables. 

11

At Ct 0 0 1 2 3 4

1

(4) p -p ( ) 2004 2005 2006 2007 ( ) ( ) tttt m m mt At Ct

m

         D          

The regression was estimated using data from 2003-2007. Sunoco/El Paso was 

consummated in the first weeks of 2004. Valero/Premcor was consummated right after 

Hurricane Katrina in 2005. The coefficient α1 shows the year effect for 2004 relative to 

2003, one year before and after Sunoco/El Paso. The coefficient α3 shows the year effect 

for 2006 relative to 2003, one year before either transaction, relative to the first full 

calendar year after Valero/Premcor. While this estimation uses a different amount of data 

in both the pre and post period than in the baseline results, it uses symmetric amounts of 

data in the pre and post periods for complete calendar years. 

The results of this estimation for the Northeast are given in Table Seven. With 

respect to retail prices, the only year coefficient estimate for either 2004 or 2006 for the 

Northeast treatment/ control pairs that is statistically significant is a decrease in the price 

of diesel in Harrisburg relative to Bangor. The estimated relationship for retail diesel fuel 

in Philadelphia relative to Boston for 2006, Valero/Premcor, is not significantly different 

from zero but it is positive and significant for 2005 and 2007. 

Almost all of the estimated rack relationships in the baseline results are 

qualitatively unchanged from this robustness check with the exception of the positive and 

significant effect estimated for the unbranded rack in Harrisburg relative to Bangor for 

Sunoco/El Paso, which is no longer significantly different from zero. 

3. Summary of Merger Effect Point Estimates 
30

Tables Eight and Nine summarize our price change point estimates across both 

mergers. Table Eight separately summarizes the baseline model results for the retail, 

branded rack and unbranded regressions across all treatment/control pairs and across both 

gasoline and diesel. The table’s last two columns reflect baseline model point estimates 

across all three price levels and across both fuels for inside and outside Northeast control 

regressions separately. As Table Eight shows, a minority of point estimates for the 

baseline model was positive in all instances. In all instances very few of these positive 

point estimates were strongly statistically significant. To the extent there were 

significantly positive estimates, these occurred only in regressions using inside Northeast 

controls and were most frequent in the unbranded regressions. As for the frequency 

distribution of point estimates, estimates between -1 and +1 cpg were most common 

followed by estimates ranging between -1 and -5 cpg. Big estimates—more than plus or 

minus 5 cpg, were very few in number. 

Table Nine compares summaries of price change point estimates for our six 

robustness checks across all three price levels and across both fuels. (As may be recalled, 

our robustness check regressions are limited to inside Northeast controls.) Percentages of 

positive results, and percentages of strongly significant positive results, varied modestly 

across robustness checks. As with the baseline model, point estimates under all 

robustness checks were most frequently in the -1 to +1 cpg range, with the -1 to -5 cpg 

range having the next highest number of estimates. Large positive or negative estimates 
31

were relatively infrequent and were mostly limited to large negatives associated with the 

year effects regressions.45 

 D. Gulf and Northeast Spot Price Comparisons.

We found little evidence that Northeast prices increased relative to prices outside 

the Northeast after the mergers controlling for the Hurricanes. If anything, relative prices 

in the Northeast, particularly for diesel, went down.46 As an additional check on whether 

the post-merger prices in the Northeast changed relative to prices outside the Northeast, 

we examined New York Harbor and Gulf spot prices for both gasoline and diesel. Spot 

prices involve individual transactions on the order of thousands of barrels and occur at 

transfer points such as refineries, ports, and pipeline junctures. Spot prices are important 

determinants of wholesale rack prices, and rack prices are highly responsive to changes in 

spot prices.47 

Table Ten presents DID merger price effect estimates for New York Harbor spot 

prices (treatment) relative to Gulf spots (control) for conventional and RFG/RBOB 

gasoline and for diesel. Estimates without and the baseline hurricane control period are 

shown, along with estimates generated if a number of additional price spikes are excluded 

in addition to the hurricane period48 As the Table shows, neither merger was associated 

 

45 Considering the estimates for the two mergers separately yield broadly similar conclusions. One notable 

exception, however, is that the modal price change estimates in Sunoco/El Paso regressions were between -

1 and +1 cpg, while the modal range in Valero/Premcor was between -1 and -5 cpg. 

46 One exception was a marginally significant 1.4 cpg increase in Harrisburg’s unbranded diesel rack prices 

relative to Charlottesville in Sunoco/El Paso. 

47 FTC Katrina Report at 99. 

48We identified seven periods during the six years of data of positive and negative price spikes, each lasting 

between 2 and 5 weeks. The regressions reported in the bottom box of Table Ten remove these seven 

periods. There were two time periods before the first transaction, late February through early March 2003 

and the middle of August thorough the middle of September 2003 -- where the price differences between 

New York Harbor and the Gulf were large by historical standards, more than 10 cents per gallon. 

Removing just these two periods (eight observations) from the pre-transaction period changes the 

significance of the reformulated gasoline estimated price change but does not appreciably change the 

estimated effect and significance of the diesel price change. 
32

with a significant change in New York Harbor spot conventional gasoline prices relative 

to Gulf spot, and all point estimates were close to zero. Sunoco/El Paso estimates for 

New York Harbor RFG/RBOB also are all insignificant with point estimates close to 

zero. RFG/RBOB and diesel prices may have declined relative to the Gulf after 

Valero/Premcor. The Valero/Premcor RFG/RBOB estimates, however, are not robust to 

removing a small number of pre-and post-transaction observations. The estimated change 

in the relative spot price of diesel fuel associated with Valero/Premcor--approximately 

negative two to three cpg--is not appreciably sensitive to controlling for the hurricanes or 

for other pre-and post-merger spikes. 

VI. Conclusions 

Sunoco’s 2004 acquisition of El Paso’s New Jersey refinery and Valero’s 2005 

acquisition of Premcor’s Delaware refinery significantly consolidated refinery control in 

the U.S. Northeast. The FTC investigated these transactions but challenged neither, in 

large part because the agency perceived that shipments from the Gulf of Mexico would 

constrain any anticompetitive behavior by Northeast refiners. 

Examining prices for gasoline and diesel at both the retail and wholesale levels, 

our findings across multiple treatment and control areas generally suggest that the 

transactions were at worst competitively neutral. A few results indicated that some 

unbranded rack prices may have increased relative to other Northeast prices after the 

mergers. However, this outcome was not robust across controls or assumptions, and these 

unbranded price increases were not accompanied by branded rack or retail price 

increases. Northeast prices did not generally increase relative to prices outside the 

Northeast after the transactions. Differences in the closeness of the price relationships 
33

between various treatment and control areas suggest that, contrary to the FTC’s view at 

the time of the transactions, imports were generally more important in determining 

Northeast prices—and in constraining any anticompetitive behavior by regional 

refiners—than shipments from the Gulf. Additional analysis of the relative importance of 

Gulf and import supply may be warranted, however. 

Many factors affect gasoline and diesel prices. We suspect that the impact from 

petroleum mergers upon prices is likely to be small relative to many of these other 

factors. The success of the DID approach in disentangling merger impacts from other 

factors affecting prices depends critically upon selection of control areas. No single 

control is likely to be ideal. Identifying good controls with time-specific cost and supply 

shocks common to treatment areas may be particularly challenging for refinery mergers 

because such mergers may affect prices over a broad geographic area in which supply 

and demand conditions may vary. Evaluating possible merger effects with multiple, 

reasonably plausible, controls is clearly warranted under these circumstances. Our 

analysis also points out the necessity of controlling for supply shocks, such as hurricanes, 

which can differentially affect treatment and control areas. 
34

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Kim, E, and Singal, V., 1993, “Mergers and Market Power: Evidence from the Airline 

Industry”, American Economic Review, 83(3), 549 

Lidderdale, T., and Bohn, A., 1999, "Demand and Price Outlook for Phase 2 Reformulated 

Gasoline, 2000", U.S. Energy Information Administration, available at 

http://www.eia.doe.gov/emeu/steo/pub/special/rfg4.html

Simpson, J., and Schmidt, D., 2008, “Difference-in-Differences Analysis in Antitrust: A 

Cautionary Note”, Antitrust Law Journal, 75(2) 623 

Simpson, J., and Taylor, C., 2008, “Do Gasoline Mergers Affect Consumer Prices? The 

Marathon Ashland and Ultramar Diamond Shamrock Transaction”, Journal of Law and 

Economics, 51(1), 135 

Taylor C., and Hosken, D., 2007, “The Economic Effects of the Marathon-Ashland Joint 

Venture: The Importance of Industry Supply Shocks and Vertical Market Structure”, 

Journal of Industrial Economics, 55(3), 419 

Taylor, C., Kreisle, N., and Zimmerman, P. “Vertical Relationships and Competition in 

Retail Gasoline Markets: Comment”, American Economic Review, forthcoming 

U.S. Federal Trade Commission, 2004, Fulfilling the Original Vision: The FTC at 90. 
35

U.S. Federal Trade Commission, 2006, Investigation of Gasoline Price Manipulation and 

Post-Katrina Gasoline Price Increases

U.S. Government Accountability Office, 2004, Energy Markets: Effects of Mergers and 

Market Concentration in the U.S. Petroleum Industry 

U.S. Government Accountability Office, 2008, Energy Markets: Analysis of More Past 

Mergers Could Enhance Federal Trade Commission’s Efforts to Maintain Competition in 

the Petroleum Industry 

U.S. Government Accountability Office, 2009, Energy Markets: Estimates of the Effects 

of Mergers and Market Concentration on Wholesale Gasoline Prices 

Vita, M. and Sacher, S., 2001, “The Competitive Effects of Not-for-Profit Hospital 

Mergers: A Case Study”, Journal of Industrial Economics, 49(1), 63 
4

4

4

4

4

4 4

4

4

(

(

( (

(

(

(

(

(

( ( (

(

(

(

(

(

( (

( (

( ( ( ( (

( (

(")

")

")

")")

")

")

")

Bangor

Portland

New York

Buffalo

Rochester Albany

New Haven

Providence

Boston

Pittsburgh

Harrisburg Philadelphia

Newark

Ohi o

Hudson

Susquehanna

Source: OPIS Terminal Encyclopedia 2004 and pipeline operators' system maps. Pipeline locations and shape

are approximate. Some terminal locations may not be shown.

0 40 80 160 4 Miles

Figure One

Northeast Supply Infrastructure

Terminals

1

2

3-4

5-6

>6

Pipelines

( Buckeye

4 Colonial

Laurel

Mobil

Sun

Legend

") Refinery
Figure Two 

The Retail Price of Gasoline in Philadelphia Relative to Boston, Newark and Fairfax (No 

-25-20-15-10

-5

05

1015

5-Jan-02

5-Mar-02

5-May-02

5-Jul-02

5-Sep-02

5-Nov-02

5-Jan-03

5-Mar-03

5-May-03

5-Jul-03

5-Sep-03

5-Nov-03

5-Jan-04

5-Mar-04

5-May-04

5-Jul-04

5-Sep-04

5-Nov-04

5-Jan-05

5-Mar-05

5-May-05

5-Jul-05

5-Sep-05

5-Nov-05

5-Jan-06

5-Mar-06

5-May-06

5-Jul-06

5-Sep-06

5-Nov-06

Cents Per Gallon

Philadelphia - Boston Philadelphia - Newark Philadelphia - Fa

K

Valero/Prem

Sunoco/ El Paso
Table One 

U.S. Northeast Refineries - 2003 

 

Firm Refinery Location 

Refinery Capacity1

(MBD) 

Firm Share of 

Northeast Capacity 

(%) 

Sunoco Marcus Hook, PA 175 

 Philadelphia, PA 330 

 33 

Conoco-Phillips Linden, NJ 255 

 Trainer, PA 180 

 28 

Motiva Wilmington, DE 175 11 

Valero Paulsboro, NJ 160 10 

El Paso Eagle Point, NJ 150 10 

United Refining Warren, PA 65 4 

Amerada Hess Port Reading, NJ 59 4 

 

Source: Energy Information Administration 

1

Capacity based on refinery operable crude oil distillation capacity, excepting Amerada 

Hess. Amerada Hess capacity based on refinery catalytic cracking capacity. 
Variable Name Type

# 

Weeks Mean Std Dev Min Max Type

# 

Weeks Mean Std Dev Min Max

Philadelphia Retail Price (ex tax) RFG 312 161.8 56.1 59.5 283.7 LS-ULSD 312 170.4 61.7 69.9 302.9

Boston Difference from Philadelphia RFG 312 -3.5 3.1 -12.5 4.2 LS-ULSD 312 -5.4 2.6 -14.7 -0.7

Newark Difference from Philadelphia RFG 312 -5.3 3.5 -19.7 6.3 LS-ULSD 312 2.0 2.6 -3.9 9.9

Fairfax Difference from Philadelphia RFG 312 -1.0 5.1 -20.4 12.1 LS-ULSD 312 -6.0 4.6 -32.4 4.4

Louisville Difference from Philadelphia RFG 312 -3.7 11.2 -40.9 29.8 LS-ULSD 312 1.0 6.7 -39.6 14.4

Houston Difference from Philadelphia RFG 312 4.4 7.4 -17.3 28.3 LS-ULSD 312 9.8 7.2 -31.8 27.2

Harrisburg Retail Price (ex tax) Conv. 312 153.3 54.5 65.3 262.0 LS-ULSD 312 160.0 59.7 69.5 294.1

Albany Difference from Harrisburg Conv. 312 -5.5 5.0 -24.3 4.7 LS-ULSD 312 -6.1 4.7 -27.2 3.7

Cleveland Difference from Harrisburg Conv. 312 -5.3 7.6 -33.2 18.7 LS-ULSD 312 -9.5 6.1 -49.3 1.8

Roanoke Difference from Harrisburg Conv. 312 -0.6 5.1 -29.5 10.6 LS-ULSD 312 -5.9 7.3 -41.0 10.2

Bangor Difference from Harrisburg Conv. 312 -9.8 2.8 -17.1 -0.6 LS-ULSD 301 -9.6 3.7 -23.6 -1.8

Lexington Difference from Harrisburg Conv. 312 -9.2 6.9 -27.9 15.2 LS-ULSD 312 -10.3 6.4 -50.7 2.9

Charlottesville Difference from Harrisburg Conv. 312 -8.8 6.8 -41.3 3.5 LS-ULSD 312 -8.6 6.3 -44.2 3.0

Pittsburgh Retail Price (ex tax) Conv. (low rvp) 312 156.2 55.1 66.5 265.0 LS-ULSD 312 165.9 59.7 74.7 299.4

Portland Difference from Pittsburgh Conv. (low rvp) 312 -5.8 3.5 -15.9 3.2 LS-ULSD 312 -4.3 3.0 -14.4 3.8

Detroit Difference from Pittsburgh Conv. (low rvp) 312 -1.2 8.3 -32.1 33.7 LS-ULSD 312 -0.3 5.7 -44.8 10.9

New Orleans Difference from Pittsburgh Conv. (low rvp) 312 -3.2 7.9 -51.9 29.1 LS-ULSD 312 0.4 7.7 -40.1 12.8

Philadelpia Branded Rack Price RFG 312 148.5 56.2 58.1 259.5 LS-ULSD 309 147.4 60.7 54.6 289.6

Boston Difference from Philadelphia RFG 312 -1.1 1.9 -9.2 5.4 LS-ULSD 309 -1.1 2.5 -11.3 5.6

Newark Difference from Philadelphia RFG 312 0.9 1.6 -7.6 5.7 LS-ULSD 309 1.3 1.8 -1.8 7.3

Fairfax Difference from Philadelphia RFG 312 -0.6 4.6 -20.9 16.6 LS-ULSD 309 0.4 5.2 -36.1 15.2

Louisville Difference from Philadelphia RFG 312 -8.7 7.4 -36.7 12.4 LS-ULSD 309 -3.2 7.0 -55.8 13.0

Houston Difference from Philadelphia RFG 312 2.4 5.3 -18.2 25.2 LS-ULSD 309 2.0 6.0 -36.3 24.0

Harrisburg Branded Rack Price Conv. 312 143.7 52.8 56.8 250.0 LS-ULSD 309 147.6 59.8 55.1 283.5

Albany Difference from Harrisburg Conv. 312 -0.4 1.7 -4.0 4.5 LS-ULSD 309 -0.9 1.7 -5.5 6.8

Cleveland Difference from Harrisburg Conv. 312 -3.1 6.8 -37.4 18.3 LS-ULSD 309 -4.0 6.7 -56.8 8.6

Roanoke Difference from Harrisburg Conv. 312 0.8 4.5 -16.7 19.7 LS-ULSD 309 0.9 4.9 -36.4 11.6

Bangor Difference from Harrisburg Conv. 312 -1.2 2.9 -9.3 7.4 LS-ULSD 309 -2.5 2.6 -9.2 7.0

Lexington Difference from Harrisburg Conv. 309 -2.2 5.0 -16.3 20.7 LS-ULSD 309 -3.0 6.8 -54.9 11.0

Charlottesville Difference from Harrisburg Conv. 312 -0.3 4.9 -23.5 18.4 LS-ULSD 309 0.6 4.9 -39.8 10.8

Pittsburgh Branded Rack Price Conv. (low rvp) 312 145.1 53.3 57.8 252.1 LS-ULSD 309 148.8 60.1 55.2 287.1

Portland Difference from Pittsburgh Conv. (low rvp) 312 -0.3 3.2 -9.3 29.8 LS-ULSD 309 -1.3 3.4 -11.1 12.5

Detroit Difference from Pittsburgh Conv. (low rvp) 312 -1.3 7.4 -33.7 34.6 LS-ULSD 309 -0.2 5.7 -43.5 16.4

New Orleans Difference from Pittsburgh Conv. (low rvp) 312 3.1 5.5 -11.0 44.3 LS-ULSD 309 4.8 5.0 -26.8 23.2

Philadelpia Unbranded Rack Price RFG 312 144.1 55.7 54.9 281.4 LS-ULSD 309 143.8 58.6 53.3 280.1

Boston Difference from Philadelphia RFG 312 -0.4 4.2 -15.4 29.0 LS-ULSD 309 -1.5 1.7 -8.4 4.6

Newark Difference from Philadelphia RFG 312 1.7 3.1 -11.8 27.5 LS-ULSD 309 -7.5 10.8 -50.9 8.6

Fairfax Difference from Philadelphia RFG 312 -0.8 5.2 -25.8 29.4 LS-ULSD 309 -0.1 4.8 -44.8 9.9

Louisville Difference from Philadelphia RFG 312 -9.8 9.2 -41.9 27.4 LS-ULSD 309 -4.1 6.4 -46.3 11.9

Houston Difference from Philadelphia RFG 312 1.5 6.0 -13.8 36.4 LS-ULSD 309 0.2 6.3 -30.1 23.8

Harrisburg Unbranded Rack Price Conv. 312 140.8 52.0 54.1 249.3 LS-ULSD 309 144.7 58.5 53.8 278.0

Albany Difference from Harrisburg Conv. 312 0.2 2.5 -7.3 12.6 LS-ULSD 309 0.1 2.0 -5.9 10.0

Cleveland Difference from Harrisburg Conv. 312 -1.9 6.7 -33.9 23.8 LS-ULSD 309 -3.5 6.3 -48.2 7.5

Roanoke Difference from Harrisburg Conv. 312 1.3 5.1 -36.6 21.0 LS-ULSD 309 1.2 4.8 -37.4 17.1

Bangor Difference from Harrisburg Conv. 312 -1.2 3.5 -13.1 10.2 LS-ULSD 309 -2.2 3.9 -25.6 11.6

Lexington Difference from Harrisburg Conv. 312 -1.6 5.1 -19.3 22.3 LS-ULSD 309 -3.2 6.2 -43.2 11.9

Charlottesville Difference from Harrisburg Conv. 312 0.6 5.0 -25.6 26.7 LS-ULSD 309 0.8 4.7 -43.8 11.4

Pittsburgh Unbranded Rack Price Conv. (low rvp) 312 142.5 53.4 54.4 254.2 LS-ULSD 309 145.4 58.9 53.5 279.4

Portland Difference from Pittsburgh Conv. (low rvp) 312 -0.4 3.9 -13.2 11.0 LS-ULSD 309 -1.6 4.1 -25.1 9.4

Detroit Difference from Pittsburgh Conv. (low rvp) 312 -0.5 7.0 -23.6 39.6 LS-ULSD 309 -0.7 6.1 -41.2 19.9

New Orleans Difference from Pittsburgh Conv. (low rvp) 312 4.6 6.1 -9.9 60.9 LS-ULSD 309 4.0 5.1 -27.1 23.0

Diesel

Descriptive Statistics (Cents Per Gallon)

Gasoline

Table Two
Gas Diesel Gas Diesel Gas Diesel Gas Diesel Gas 

Sun/El Paso -0.16 -0.04 0.85 -0.51 -0.09 0.55 0.57 0.96 0.70 

t-stat -0.22 -0.08 1.14 -0.85 -0.10 0.52 0.40 0.79 0.66 

Valero -0.24 1.51 -0.39 -2.02 1.88 -0.51 1.23 1.29 0.34 

t-stat -0.24 2.25 -0.37 -2.34 1.79 -0.38 0.67 0.79 0.27 

Sun/El Paso -0.11 0.11 0.88 -0.35 -0.58 0.34 0.17 0.73 0.78 

t-stat -0.18 0.21 1.38 -0.59 -0.71 0.33 0.13 0.61 0.78 

Valero 3.03 2.85 0.80 2.97 -0.58 -2.98 -2.00 -1.54 1.28 

t-stat 1.83 2.93 0.44 1.92 -0.49 -1.60 -0.81 -0.60 0.78 

Sun/El Paso 0.18 -0.40 0.65 -0.09 -0.01 -0.90 -0.09 -0.63 -0.64 

t-stat 0.31 -0.47 1.22 -0.15 -0.01 -1.12 -0.18 -1.09 -0.92 

Valero 0.41 0.59 0.02 1.36 0.72 -1.41 -0.14 -0.79 -3.72 

t-stat 0.51 0.52 0.03 2.01 0.68 -1.34 -0.21 -1.25 -5.81 

Sun/El Paso 0.33 -0.39 0.47 -0.07 0.08 -0.68 0.16 -0.51 -0.71 

t-stat 0.59 -0.44 0.92 -0.11 0.14 -0.81 0.35 -0.83 -1.09 

Valero -0.39 0.54 0.74 1.36 -4.21 -2.26 -2.08 -0.99 -3.98 

t-stat -0.39 0.35 0.95 1.80 -3.55 -1.66 -2.44 -1.38 -6.44 

Sun/El Paso -0.61 -0.66 1.64 -2.65 -0.10 5.89 -1.15 -0.89 -0.56 

t-stat -0.39 -1.27 2.22 -1.13 -0.07 3.14 -2.22 -1.92 -0.47 

Valero 2.47 -0.67 1.72 -1.33 7.90 5.44 -2.32 -0.85 -3.30 

t-stat 1.58 -1.31 2.53 -0.68 3.68 2.05 -4.81 -1.98 -2.72 

Sun/El Paso 1.25 -0.60 1.97 -2.43 -0.19 5.01 -0.57 -0.85 -0.37 

t-stat 0.93 -1.09 2.93 -1.29 -0.22 2.83 -1.09 -1.79 -0.31 

Valero 0.24 -0.72 1.25 -14.77 -5.07 -0.61 -2.52 -0.95 -3.66 

t-stat 0.17 -1.29 1.97 -2.18 -5.32 -0.20 -4.93 -2.12 -2.93 

T-Statistics in shaded bold are significant at the 5 percent levelT-Statistics in bold with no shading are significant at the 10 percent level

Table Three

Unbranded Rack: Coefficients and T-Statistics

Unbranded Rack: Coefficients and T-Statistics (With Hurricane Controls)

Philadelphia - Boston Philadelphia - Newark

Baseline Merger Effects Estimates, Northeast Controls (Cents Per Gallon)

Retail Coefficients and T-Statistics (With Hurricane Controls)

Branded Rack: Coefficients and T-Statistics

Branded Rack: Coefficients and T-Statistics (With Hurricane Controls)

Harrisburg - Bangor Harrisburg - Albany Pittsburgh 

Retail Coefficients and T-Statistics
Gas Diesel Gas Diesel Gas Diesel Gas Diesel Gas Diesel Gas Diesel Gas Diesel Gas Diese

Sun/El Paso -0.28 -0.14 -0.09 -1.17 -0.92 -0.91 0.87 1.04 -4.02 -1.04 -2.45 0.00 -0.47 0.11 0.70 -0.71 

t-stat -0.19 -0.12 -0.03 -0.67 -0.50 -0.56 0.40 0.71 -2.85 -0.71 -1.29 0.00 -0.31 0.07 0.29 -0.48 

Valero 2.89 -0.65 -1.37 3.25 5.31 -1.46 2.88 0.98 -3.05 -4.95 -0.47 0.27 -0.94 -7.60 1.83 -2.92 

t-stat 1.57 -0.41 -0.36 1.42 2.05 -0.64 1.29 0.48 -1.95 -2.41 -0.25 0.12 -0.45 -3.67 0.71 -1.60 

Sun/El Paso -0.92 -0.36 -0.53 -0.94 -1.27 -1.29 0.78 0.61 -3.70 -1.28 -2.64 0.01 -0.85 0.50 0.89 -0.83 

t-stat -0.81 -0.47 -0.15 -0.75 -0.86 -1.46 0.34 0.59 -3.18 -1.07 -1.36 0.01 -0.65 0.40 0.38 -0.81 

Valero 1.17 0.30 -3.19 1.87 -0.67 5.54 2.52 -6.20 -1.37 -8.63 -0.81 -3.66 -2.82 -3.72 2.88 -3.90 

t-stat 0.42 0.12 -0.71 0.89 -0.16 1.37 1.00 -3.52 -0.88 -2.86 -0.40 -2.06 -1.15 -1.75 0.94 -2.41 

Sun/El Paso -0.03 1.01 -0.34 0.64 0.00 -0.58 1.12 -0.12 -0.94 0.37 -1.63 0.13 -1.99 0.85 1.50 1.04 

t-stat -0.02 0.54 -0.13 0.27 0.00 -0.28 0.54 -0.06 -0.66 0.22 -1.08 0.06 -1.18 0.50 0.64 0.64 

Valero -2.48 1.02 -0.09 0.50 1.47 -2.75 -1.28 -3.59 -1.67 -1.18 -2.13 -1.25 -1.79 -0.29 -0.18 -2.50 

t-stat -1.71 0.49 -0.03 0.17 0.71 -1.17 -0.62 -1.87 -1.15 -0.68 -1.40 -0.48 -0.96 -0.16 -0.07 -1.54 

Sun/El Paso 0.12 1.12 0.16 1.42 0.74 0.23 1.00 0.07 -0.92 0.73 -1.10 0.96 -1.12 1.22 0.82 1.12 

t-stat 0.09 0.85 0.07 0.77 0.44 0.14 0.48 0.05 -0.68 0.75 -0.77 0.59 -0.76 1.26 0.34 0.92 

Valero -2.44 1.99 -1.92 -0.43 -0.13 -2.87 -1.91 -3.04 -1.39 -0.50 -2.44 -2.12 -2.75 0.50 0.09 -1.82 

t-stat -1.72 1.35 -0.47 -0.17 -0.06 -1.29 -0.87 -2.26 -0.90 -0.50 -1.53 -1.10 -1.41 0.51 0.03 -1.49 

Sun/El Paso -2.00 1.12 -2.09 -0.34 -2.31 -0.53 -0.29 0.59 -1.83 0.15 -0.05 -0.58 -1.04 1.04 1.39 1.51 

t-stat -1.11 0.74 -0.55 -0.16 -0.64 -0.32 -0.14 0.36 -1.08 0.10 -0.02 -0.30 -0.36 0.75 0.72 0.92 

Valero 0.85 -1.33 23.02 -2.00 22.74 -6.97 1.65 -2.92 -1.64 -2.33 24.46 -2.34 23.65 -1.35 2.06 -1.84 

t-stat 0.48 -0.88 4.26 -0.87 4.48 -4.08 0.77 -1.81 -0.97 -1.60 5.64 -1.13 5.62 -0.98 1.10 -1.13 

Sun/El Paso 0.16 1.39 -0.60 0.78 1.75 0.54 1.50 1.17 -0.80 0.60 -0.60 0.60 -1.43 1.42 1.04 1.77 

t-stat 0.12 1.57 -0.19 0.49 1.05 0.36 0.76 0.94 -0.57 0.59 -0.41 0.41 -0.96 1.77 0.53 1.47 

Valero -0.87 -0.45 -0.67 -2.79 0.74 -7.76 -0.49 -2.67 -1.80 -2.00 -1.16 -3.00 -1.74 -0.65 1.19 -0.97 

t-stat -0.68 -0.52 -0.13 -1.51 0.44 -4.44 -0.24 -2.14 -1.22 -1.95 -0.75 -1.92 -1.05 -0.83 0.58 -0.81 

T-Statistics in shaded bold are significant at the 5 percent levelT-Statistics in bold with no shading are significant at the 10 percent level

Unbranded Rack: Coefficients and T-Statistics (With Hurricane Controls)

Baseline Merger Effects Estimates, Outside of Northeast Controls (Cents Per Gallon)

Table Four

Retail Coefficients and T-Statistics (With Hurricane Controls)

Branded Rack: Coefficients and T-Statistics

Branded Rack: Coefficients and T-Statistics (With Hurricane Controls)

Unbranded Rack: Coefficients and T-Statistics

Harrisburg - 

Charlottesville

Pittsburgh - 

Detroit

Retail Coefficients and T-Statistics

Philadelphia - 

Fairfax

Philadelphia - 

Louisville

Philadelphia - 

Houston

Harrisburg - 

Cleveland

Harrisburg - 

Roanoke

Harrisburg - 

Lexington
Product Baseline

Change 

Pre Merger 

Period

Change 

Effective 

Date 3 mos

Change 

Effective 

Date 6 mos

Change 

Hurricane 2 

weeks

Change 

Hurricane 3 

mos

Gasoline Retail

Diesel Retail ++

Gasoline Branded Rack

Diesel Branded Rack

Gasoline Unbranded Rack

Diesel Unbranded Rack

Gasoline Retail + +

Diesel Retail - -

Gasoline Branded Rack

Diesel Branded Rack

Gasoline Unbranded Rack ++ ++ ++ ++ ++ ++

Diesel Unbranded Rack

Gasoline Retail

Diesel Retail

Gasoline Branded Rack

Diesel Branded Rack

Gasoline Unbranded Rack

Diesel Unbranded Rack ++ ++ ++ ++

Gasoline Retail

Diesel Retail

Gasoline Branded Rack +

Diesel Branded Rack

Gasoline Unbranded Rack --

Diesel Unbranded Rack - -- -- - -

Gasoline Retail +

Diesel Retail - -- --

Gasoline Branded Rack

Diesel Branded Rack

Gasoline Unbranded Rack

Diesel Unbranded Rack + + -- + +

++ indicates postive coefficient significant at 5 percent level

+ indicates positve coefficient significant at 10 percent level

-- indicates negative coefficient significant at 5 percent level

- indicates negative coefficient significant at 10 percent level

Pittsburgh - Portland

Sunoco-El Paso Effects Robustness Checks

Table Five

Philadelphia - Boston

Philadelphia - Newark

Harrisburg - Bangor

Harrisburg - Albany
Product Baseline

Change 

Pre Merger 

Period

Change 

Effective 

Date 3 mos

Change 

Effective 

Date 6 mos

Change 

Hurricane 

2 weeks

Change 

Hurricane 3 

mos

Gasoline Retail + ++ ++ +

Diesel Retail ++ ++ ++ ++

Gasoline Branded Rack

Diesel Branded Rack

Gasoline Unbranded Rack

Diesel Unbranded Rack

Gasoline Retail +

Diesel Retail +

Gasoline Branded Rack

Diesel Branded Rack + ++ + ++

Gasoline Unbranded Rack + ++ + + ++

Diesel Unbranded Rack -- - -

Gasoline Retail

Diesel Retail -- - -

Gasoline Branded Rack -- -- -- -- --

Diesel Branded Rack -

Gasoline Unbranded Rack -- -- -- -- -- --

Diesel Unbranded Rack --

Gasoline Retail

Diesel Retail

Gasoline Branded Rack -- -- -- - -- -

Diesel Branded Rack

Gasoline Unbranded Rack -- -- -- -- -- --

Diesel Unbranded Rack -- -- - -- -- -

Gasoline Retail

Diesel Retail -

Gasoline Branded Rack -- -- -- -- -- --

Diesel Branded Rack -

Gasoline Unbranded Rack -- -- -- -- -- --

Diesel Unbranded Rack -- --

++ indicates postive coefficient significant at 5 percent level

+ indicates positve coefficient significant at 10 percent level

-- indicates negative coefficient significant at 5 percent level

- indicates negative coefficient significant at 10 percent level

Pittsburgh - Portland

Valero-Premcor Effects Robustness Checks

Table Six

Philadelphia - Boston

Philadelphia - Newark

Harrisburg - Bangor

Harrisburg - Albany
Gas Diesel Gas Diesel Gas Diesel Gas Diesel Gas 

YR 2004 0.04 0.89 -0.04 0.37 -1.71 -0.34 -0.32 0.93 1.82 

t-stat 0.05 1.33 -0.04 0.35 -1.61 -0.22 -0.16 0.49 1.24 

YR 2005 0.80 2.30 -0.28 -0.22 -2.40 -1.05 -0.62 3.66 2.45 

t-stat 0.68 2.71 -0.18 -0.13 -1.91 -0.48 -0.24 1.40 1.30 

YR 2006 0.26 0.92 -0.27 -3.10 -1.81 -7.11 -0.46 0.07 0.02 

t-stat 0.18 0.97 -0.14 -1.32 -1.37 -2.66 -0.15 0.02 0.01 

YR 2007 1.99 2.11 1.73 -2.56 -2.73 -6.38 -0.70 0.33 0.59 

t-stat 1.20 1.92 0.72 -0.85 -1.89 -1.96 -0.20 0.09 0.24 

YR 2004 -0.32 -0.41 -0.12 -0.51 -1.51 -0.46 -0.56 -0.35 -1.08 

t-stat -0.48 -0.43 -0.20 -0.77 -2.26 -0.46 -0.99 -0.49 -1.25 

YR 2005 -0.40 -0.89 0.21 -0.71 -2.87 -1.16 -1.33 -1.51 -1.72 

t-stat -0.43 -0.70 0.27 -0.92 -3.23 -0.85 -1.64 -1.77 -1.60 

YR 2006 -0.75 -0.44 0.06 0.05 -4.42 -1.17 -1.55 -1.00 -3.05 

t-stat -0.65 -0.30 0.07 0.06 -4.22 -0.72 -1.53 -1.14 -2.57 

YR 2007 -0.26 1.71 0.85 1.95 -6.08 -2.49 -2.20 -1.45 -4.52 

t-stat -0.19 1.02 0.81 2.33 -4.86 -1.29 -1.77 -1.54 -3.34 

YR 2004 1.32 -0.50 2.22 -5.11 -0.79 0.11 -0.84 -0.93 -0.19 

t-stat 0.99 -0.95 2.83 -1.72 -0.93 0.07 -1.20 -1.54 -0.16 

YR 2005 0.64 -1.65 1.78 -7.05 -2.86 -1.60 -2.12 -1.87 -1.01 

t-stat 0.41 -2.82 2.01 -1.38 -2.59 -0.83 -2.80 -2.80 -0.77 

YR 2006 1.45 -1.96 2.54 -5.13 -4.13 -0.73 -2.56 -1.06 -3.63 

t-stat 0.58 -3.57 1.95 -0.71 -3.15 -0.37 -3.32 -1.71 -2.41 

YR 2007 -0.29 0.24 0.78 -5.32 -7.36 -7.59 -3.32 -1.80 -3.54 

t-stat -0.18 0.44 0.97 -0.57 -5.71 -3.50 -4.24 -2.90 -1.69 

T-Statistics in shaded bold are significant at the 5 percent levelT-Statistics in bold with no shading are significant at the 10 percent level

Table Seven

Unbranded Rack: Coefficients and T-Statistics (With Hurricane Controls)

Philadelphia - Boston Philadelphia - Newark

Merger Effects Estimates - Year Effects Robustness Check (Cents Per Gallon)

Retail Coefficients and T-Statistics (With Hurricane Controls)

Branded Rack: Coefficients and T-Statistics (With Hurricane Controls)

Harrisburg - Bangor Harrisburg - Albany Pittsburgh - P
Retail1 Branded Rack1 Unbranded Rack1

Outside 

Northeast2

Inside 

Northeast3

Percentage positive price ∆s 39.3% 42.9% 37.5% 39.8% 40.0%

Percentage of positive price ∆s with t > 2 4.5% 0.0% 9.5% 0.0% 12.5%Frequency Distribution of Price Changes

∆p < -5 cpg 4 0 352

 -5 < ∆p < -1 17 19 14 36 14

 -1 < ∆p < 1 26 30 26 48 34

 1 < ∆p < 5 8 7 12 18 9

∆p > 5 cpg 1 0 111

Number of estimated price effects 56 56 56 108 60

1 Retail, branded rack and unbranded rack columns reflect estimates in 56 regressions: 14 control groups, 2 fuels and 2 mergers.2 Outside Northeast columns reflect estimates in 108 regressions: 9 control groups, 3 price levels, 2 fuels and 2 mergers.3 Inside Northeast columns reflect estimates in 60 regressions: 5 control groups, 2 fuels and 2 mergers.

Summary of Estimated Price Effects for Sunoco-El Paso and Valero-Premcor in Baseline Model

Table Eight
Pre-Merger 

Drop 20021

Effective Date 

∆ 3 Month 

Window1 

Effective Date ∆

6 Month 

Window1

Hurricane 

Window ∆ 2 

Weeks1

Hurricane 

Window ∆ 3 

Months1 

Percentage positive price ∆s 38.3% 36.7% 33.3% 38.3% 36.7% 

Percentage of positive price ∆s with t > 2 13.0% 13.6% 15.0% 17.4% 22.7% 

Frequency Distribution of Price Changes

∆p < -5 cpg 2 3 0 2 1 

 -5 < ∆p < -1 17 15 17 17 18 

 -1 < ∆p < 1 32 33 33 29 29 

 1 < ∆p < 5 8 9 10 11 12 

∆p > 5 cpg 10 0 1 0 

Number of estimated price effects 60 60 60 60 60 

1 These columns reflect the robostness checks estimates in 60 regressions: 5 control groups, 3 price levels, 2 fuels and 2 me2 This columns reflects the 120 year effect estimates in 30 year effects regressions: 5 control groups, 3 price levels, 2 fuels an

Summary of Estimated Price Effects of Sunoco-El Paso and Valero-Premcor

Table Nine
Conventional Gas 

(NHY - Gulf)

RFG/RBOB Gas 

(NYH - Gulf)

No. 2 Diesel Fuel 

(NYH - Gulf)

Sun/El Paso -0.68 -0.32 0.15

t-stat -0.46 -0.19 0.09

Valero -0.38 -2.85 -3.25

t-stat -0.27 -1.85 -2.01

Conventional Gas 

(NHY - Gulf)

RFG/RBOB Gas 

(NYH - Gulf)

No. 2 Diesel Fuel 

(NYH - Gulf)

Sun/El Paso -0.27 -0.17 0.41

t-stat -0.30 -0.15 0.48

Valero 0.40 -1.88 -2.34

t-stat 0.45 -1.77 -2.86

Conventional Gas 

(NHY - Gulf)

RFG/RBOB Gas 

(NYH - Gulf)

No. 2 Diesel Fuel 

(NYH - Gulf)

Sun/El Paso -0.05 -0.11 0.29

t-stat -0.06 -0.10 0.39

Valero 0.88 -1.36 -2.05

t-stat 1.01 -1.30 -2.88

Source: Energy Information Administration Spot Price Data, http://tonto.eia.doe.gov/dnav/pet/pet_pri_spT-Statistics in shaded bold are significant at the 5 percent levelT-Statistics in bold only are significant at the 10 percent level

Table Ten

Spot Price Merger Effects Estimates

Differences of New York Harbor - Gulf Coast (Cents Per Gallon)

Coefficients and T-Statistics (With Huricanes)

Coefficients and T-Statistics (Without Hurricanes)

Coefficients and T-Statistics (Without Hurricanes, date adjusted and spikes 

removed)