WORKING 

 PAPERS

MICHIGAN GASOLINE PRICING AND THE MARATHON-ASHLAND 

AND ULTRAMAR DIAMOND SHAMROCK TRANSACTION

John Simpson

and

Christopher T. Taylor

WORKING PAPER NO. 278

July 2005

___________________________________________________________________________

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acknowledgment by a writer that he has access to such unpublished materials) should be cleared with the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 The authors are economists at the Federal Trade Commission. Views and

opinions expressed in this paper are solely those of the authors and should not be interpreted as

reflecting the views of the Federal Trade Commission, any of its individual Commissioners, or

other members of the staff. Comments by Daniel Hosken, Jeffrey Fischer, Robert McMillan and

Louis Silvia and excellent research assistance by Anthony Alcorn are appreciated.

Michigan Gasoline Pricing and the Marathon - Ashland and Ultramar Diamond Shamrock

Transaction

John Simpson

Federal Trade Commission

Christopher T. Taylor1

Federal Trade Commission

Last Revised: July 27, 2005

Abstract: Marathon Ashland Petroleum’s (MAP) 1999 acquisition of the Michigan assets of

Ultramar Diamond Shamrock (UDS) increased MAP’s share of terminal storage in Michigan

from about 16 percent to about 25 percent and increased the share of gasoline stations bearing a

MAP brand from about 16 percent to about 24 percent. In this paper, we examine whether this

acquisition affected the retail price of gasoline. We use a difference-in-differences model to

compare price movements in six Michigan cities affected by the acquisition with price

movements in two nearby cities unaffected by the acquisition. Using this model, we find no

evidence that this acquisition led to higher prices for consumers. 

JEL Classification: L1, L41, L71

Keywords: Merger retrospectives, Petroleum industry
1 See ExxonMobil Corporation, Investor and Media Meeting, New York, August 1,

2000, pp. 36-37; Remarks by David J. O’Reilly, Chairman and CEO Chevron Texaco

Corporation at the 2003 Annual Meeting of Stockholders Midland, Texas May 22, 2003 

(www.chevrontexaco.com/news/speeches/2003/22may2003.oreilly.asp); Conoco Phillips 2003

Annual Report.

2 See http://www.ftc.gov/opa/1999/11/exxonmobil.htm

3 The working paper version of this paper, Chouinard and Perloff (2003), includes a

more detailed discussion of how mergers and divestitures were modeled. 

1

I. Introduction and Literature Review

Since the late 1990s, many large oil companies have combined with other large oil

companies through a series of mergers and acquisitions. While these firms claim that these

transactions have benefitted society by generating billions of dollars in cost savings,1 others

claim that these mergers and acquisitions have harmed society by enabling the firms to raise

gasoline and diesel prices. This paper seeks to help differentiate between these two claims by

examining the effect on retail gasoline prices of one particular acquisition, Marathon Ashland

Petroleum’s (MAP) 1999 acquisition of the Michigan assets of Ultramar Diamond Shamrock

(UDS). 

MAP’s acquisition of UDS’s Michigan assets, which was not challenged by the

government, is a good candidate for study because it had a much larger effect on wholesale and

retail concentration than more prominent petroleum mergers such as Exxon’s merger with Mobil. 

The acquisition increased MAP’s share of terminal storage in Michigan from about 16 percent to

about 25 percent and increased the share of gasoline stations bearing a MAP brand from about

16 percent to about 24 percent. In contrast, the Federal Trade Commission required Exxon and

Mobil to divest sufficient distribution and retailing assets to ensure that concentration stayed the

same in most of the companies’ overlapping businesses.2

Previous studies of the price effects of oil mergers can be divided into two categories. 

The first set of papers (United States Government Accountability Office (GAO) (2004),

Chouinard and Perloff (2004)3

), examines the effect of multiple mergers on a broad cross section

of markets over time and concludes that some oil mergers led to higher prices. In our view this

approach is poorly suited to examining the price effects of oil mergers. Various localities have
2

adopted different fuel specifications to comply with environmental regulations. For example, a

seven-county area centered on Detroit uses a different type of gasoline (low Reid Vapor Pressure

conventional) than all of Ohio, most of northern Indiana, and the rest of Michigan. This

balkanized nature of gasoline demand, along with constraints on the refining capacity and

pipeline capacity that can supply an area, means that local supply and demand conditions often

play an important role in determining price. For instance, a pipeline rupture might drive up

prices in one city while leaving prices in a city 200 miles distant unchanged. Identifying and

controlling for all of the local supply and demand shocks is very time-consuming where a single

merger affects a small group of markets. Where many mergers affect many markets, we suspect

that this task is unmanageable. For this reason, we believe that those papers that examine the

effect of many oil mergers in many markets run a serious risk of wrongly attributing to a merger

a price increase or decrease that was caused by a local demand or supply shock.

A second set of papers (Hastings (2004), Hastings and Gilbert (2002), Taylor and Hosken

(2004)) examines the price effects of specific mergers. By focusing on the effect of a specific

merger in a small number of markets, these papers are better able to identify and account for

local supply and demand shocks. Hastings (2004) examines ARCO’s 1997 long-term lease of

260 gasoline stations in Southern California from Thrifty. She finds that competing stations

increased their price by 5 cents per gallon when ARCO converted the Thrifty stations to the

ARCO brand. Based on this, she argues that independent retailers, such as Thrifty, play a

disproportionately large role in ensuring competition. Hastings and Gilbert (2002) examine

Tosco’s 1997 purchase of three refineries, 1,100 gasoline stations, and related terminal and

transportation assets from Unocal. Prior to this transaction, Tosco operated two refineries on the

West Coast but had few retailing assets. Focusing on the vertical aspect of this acquisition,

Hastings and Gilbert find some evidence that Tosco set higher wholesale prices in those markets

where its newly-acquired retail assets competed most intensely with independent retailers. 

Hastings and Gilbert, however, do not examine the overall effect of this acquisition on wholesale

or retail gasoline prices. Taylor and Hosken (2004) examine the effect of the 1998 joint venture

between Marathon Oil Corporation and Ashland Inc. on retail gasoline price in Louisville,
4 According to Taylor and Hosken, this transaction increased the HerfindahlHirschman Index (HHI) in the state of Kentucky by about 880 points to 2263 for gasoline

wholesaling and by about 250 points to about 1550 for gasoline retailing. 

5 MAP’s acquisition of UDS’s Michigan assets apparently had little direct effect on

the supply of refined products into Michigan. In October 1999, UDS closed its 50,000 barrel-aday refinery in Alma, Michigan after unsuccessfully trying to sell it for a year (Ultramar

Diamond Shamrock 2000 10K; Kronenwetter, Eric, “Ventech Gets Ready for Refinery

Cannibals,” The Oil Daily, June 15, 1999, No. 113, Vol 49). As part of its acquisition of UDS’s

Michigan assets, MAP acquired a pipeline system that served this refinery. MAP immediately

sold this system to the Wolverine Pipeline Company (Wolverine), which then connected the

UDS pipeline system to its main pipeline. (See Figure 1) 

3

Kentucky. Although this joint venture significantly increased concentration in Kentucky,4

Taylor and Hosken find it had no significant effect on retail gasoline prices in Louisville. While

Taylor and Hosken find some evidence of higher wholesale prices following the joint venture,

they conclude these higher wholesale prices were unrelated to the joint venture. 

This paper complements this second set of papers in two respects. First, by examining

another merger, this paper provides an additional case study with which to judge the price effects

of mergers. Second, by providing detailed information about the pre-merger competitive

environment, this paper enables the reader to relate these price effects to the acquisition’s effect

on market structure. This paper is structured as follows. Section II describes the effect that this

acquisition had on market structure in the supply of refined products into Michigan, the

distribution of wholesale gasoline in Michigan, and the sale of gasoline in several metropolitan

statistical areas in Michigan. Section II also discusses possible ways in which these changes in

market structure might lessen competition. Section III discusses the data and the methodology

used to examine this acquisition’s effect on retail gasoline prices. We present our results in

section IV and offer several concluding comments in section V.

II. MAP’s acquisition of UDS

MAP’s acquisition of UDS’s Michigan assets substantially increased MAP’s share of

terminal capacity in Michigan and substantially increased the number of gasoline stations in

Michigan carrying a MAP brand.5

 The following paragraphs describe several ways in which this

could lead to higher gasoline prices. 
6 Pinske, Slade and Brett (2002) found that the competition among gasoline

terminals was localized. Shapiro (1996) and Willig (1991) provide a theoretical discussion of

how mergers can reduce localized competition.

7 Testimony of Michigan Attorney General Granholm before U.S. Senate;

testimony of Michael D. Swan before Federal Energy Regulatory Commission, Docket No.

OR99-15 (Wolverine Pipe Line Company). 

4

A refined products terminal (terminal) is basically a set of large tanks where refined

products are stored, combined with any desired additives, and dispersed into trucks that supply

gasoline stations and other commercial customers. Prior to MAP’s acquisition of UDS, thirtyfour terminals served Michigan. MAP operated six of these terminals accounting for about 16

percent of the terminal storage capacity in Michigan, and UDS operated three of these terminals

accounting for about 9 percent of the terminal storage capacity in Michigan. Figure 2 shows the

location and ownership of the terminals in Michigan, and Table 1 lists the capacities, market

shares, and supply sources of these terminals. 

Terminals typically supply gasoline stations within a 50-75 mile radius. Thus, two

terminals located 100 to 125 miles apart might compete to supply the gasoline stations that are

located between them (FTC 2004, p. 219). Given this and the terminal locations shown in Figure

2, MAP’s acquisition of UDS could have reduced localized competition among terminals in the

area surrounding Grand Rapids and the area surrounding Lansing, Flint, and Bay City.6

 In the

Grand Rapids area, the MAP terminal in North Muskegon may have competed with the UDS

terminals in Lansing and Traverse City. In the area comprising the cities of Lansing, Flint,

Saginaw, Bay City, and Midland, the MAP terminal in Flint may have competed with the UDS

terminals in Lansing and Bay City. This localized competition would be more significant than

figure 2 implies if, as some evidence suggests, the MAP and UDS terminals were more willing

than other terminals to serve independent dealers.7 MAP’s acquisition of UDS’s Michigan assets

might have also facilitated coordinated behavior among the terminals in the two regions by

reducing the number of firms that would need to coordinate their behavior. 

Approximately 5300 gasoline stations served Michigan at the time of the acquisition

(FTC 2004, p.239). About 24 percent of these stations operated under either a MAP or UDS

brand: UDS owned 179 stations and had contracts to supply another 240 stations that operated
8 http://www.marathon.com/News_Center/Press_Releases/1999_News_Releases/?r

eleaseid=245674

9 Branded Retail Outlets in the United States, 1998, National Petroleum News,

Mid-Jul99, Vol. 91 Issue 8, p.42.

5

under the UDS brand;8

 MAP owned and operated 214 Speedway SuperAmerica stations and had

contracts to supply another 619 stations that operated under the Marathon Ashland brand.9 

Geographic markets for gasoline retailing are almost certainly no larger than a

metropolitan area since few people commute outside of a metropolitan area on a regular basis. 

Consistent with this, previous studies of gasoline retailing have defined geographic markets as

metropolitan areas or smaller (e.g., Slade (1992), Hastings (2004), Borenstein & Shepard

(2001)). Table 2, which is compiled from phone book listings from 1999, records the number of

stations by brand affiliation for several Michigan metropolitan statistical areas (MSAs). 

According to Table 2, MAP’s post-acquisition market share (measured as the number of stations

bearing a MAP affiliated brand) was about 30 percent in the Lansing and Flint MSAs, was

almost 20 percent in the Bay City and Kalamazoo MSAs, and was 12 and 13 percent respectively

in the Grand Rapids and Jackson MSAs. While there were a sizeable number of stations not

listing a brand affiliation, we believe that the figures for MAP and UDS are accurate since they

are consistent with statewide figures.

Given the environment described above, MAP’s acquisition of UDS’s Michigan gasoline

stations could lead to higher prices in several ways: The acquisition could eliminate localized

competition between gasoline stations supplied by MAP and gasoline stations supplied by UDS;

the acquisition could also facilitate coordinated interaction by reducing the number of

competitors; and the acquisition could lead to higher prices by prompting the combined firm to

restrict access to its terminals thereby raising the costs of its independent rivals. 

III. Methodology and Data

Methodology

To examine whether the changes in market structure described above led to higher retail

gasoline prices, we need to isolate the effect of this acquisition from the effect of changes in the
6

demand or supply of gasoline and the effect of other changes in market structure. Previous

studies of consummated mergers have employed two basic methods to control for other factors

that affect price. The first method identifies those cost and demand factors that affect price and

then regresses price on these factors and a dummy variable accounting for the merger (e.g.,

Schumann et al. 1997; Schumann et al. 1992). This method is not feasible in this case because

data on the various supply and demand factors affecting price are largely unavailable on a

weekly or monthly basis at a city level. The second method uses a difference-in-differences

(DID) approach to compare price changes in a market where a merger occurred (treatment

market) with price changes in a market with similar demand and cost conditions where no

merger occurred (control market) (e.g., Kim and Singal (1993), Barton and Sherman (1984)). 

We use this approach in this paper.

As described by the equation below, we assume that prices in the treatment city are

explained by the acquisition, supply and demand shocks shared with the control cities, and

supply and demand shocks unique to the treatment cities. The specific supply shock dummy

variables are described in detail below. Because the error term of the equation is autoregressive,

we estimate it using an AR(1) correction.10

PT - PC = " + $1MERGER + $2RUPTURE + $3LEMONT + $4MIDWEST + ,

where: PT - price in the treatment city

PC - price in the control city

" - constant

MERGER - a dummy for the post-acquisition period (12/13/1999-12/31/2002)

RUPTURE - a dummy for the Wolverine Pipeline disruption (6/7/00 to 8/31/00) 

LEMONT - a dummy for the Citgo Lemont refinery disruption (8/13/01-10/8/01)

MIDWEST - a dummy for the Midwest gas price spike (5/20/00-6/7/00)

, - error term

MAP’s acquisition of UDS’s Michigan assets changed market structure in the Flint,

Lansing, Saginaw-Bay City, Grand Rapids-Muskegon, Jackson, and Kalamazoo-Battle Creek
10 The results when using Detroit as a control city were very similar to the results

from using the other control cities. MAP and UDS also posted prices in Detroit along with 10

other firms. Using Detroit as a treatment city and comparing it to the control cities showed no

change in pricing.

7

MSAs. These six MSAs are our treatment cities. For the DID approach to isolate the

acquisition’s effect on gasoline prices in these cities, three conditions must hold. The treatment

and control cities must experience the same supply and demand shocks. The transmission of

supply and demand shocks must be the same in the treatment and control cities. And, the

treatment and control cities must be free of any other significant changes in market structure. 

The next subsection notes that we can largely meet these three conditions through our choice of

control cities. The subsection after that describes the several remaining confounding factors. 

Choice of Control Cities

Two cities, South Bend and Elkhart-Goshen, appear to largely meet the requirement of

experiencing the same supply and demand shocks as the treatment cities. Grand RapidsMuskegon, Jackson, and Kalamazoo-Battle Creek all obtain refined products through pipelines

originating in the areas around Chicago, Illinois. Lansing and Saginaw-Bay City also obtained

refined products through these pipelines after the closure of the Alma Refinery. These pipelines

serve the South Bend and Elkhart-Goshen MSAs in Indiana before they reach metropolitan areas

in Michigan. Like all of the treatment cities, South Bend and Elkhart-Goshen use conventional

gasoline. Thus, these two control cities should experience most of the same supply shocks as the

treatment cities. These cities should also experience the same demand shocks as the treatment

cities since they are geographically close and thus will experience the same regional economic

effects. 

Detroit and Toledo, while geographically close, do not appear to meet the requirement of

experiencing the same supply shocks as the treatment cities. Detroit uses a different formulation

of gasoline than the treatment cities. (Moreover, it also may have been affected by the merger).10

The Buckeye Pipeline, the major pipeline transporting refined products from Toledo to Flint and
11 See infra. Also, the relationships between the retail price in Toledo and the retail

prices in Detroit, Flint, and Bay City were not stable either before or after the acquisition. This

provides further support for the view that Toledo was not the marginal source of supply to these

areas. 

8

Bay City, is apparently at capacity.11 Since the Buckeye Pipeline is likely not the marginal

source of supply to any of the treatment cities, the treatment cities likely would experience

different supply shocks than Toledo. 

To address the requirement that the transmission of supply and demand shocks be largely

the same in the treatment cities and control cities, we do two things. First, we ensure that there

are no huge obvious differences between the treatment cities and the control cities in the

intensity of rivalry among producers: All of the treatment and control cities are within 75 miles

of at least three terminals. Second, we compare each of our six treatment cities with two control

cities. To the extent that the transmission of supply and demand shocks differ for the treatment

and control cities, we would expect that the transmission would be greater for treatment cities in

some cases and greater for control cities in other cases. In other words, while differences in the

transmission of supply and demand shocks between a treatment city and a control city might bias

the DID results for a single pairing, this bias should not be systematic. Thus, if we observe that

the prices in the treatment cities did not increase relative to the price in the control city in any of

the twelve combinations, then we can conclude that the merger did not have a broad

anticompetitive effect. However, if we observe that the price in the treatment city increased

relative to the price in the control city in nearly all of the twelve combinations, then the merger

would seem to have decreased competition in at least some cities. 

To address the requirement that the control city be free of any treatment, and the related

requirement that the treatment city be free of any treatment other than the acquisition, we

examined whether any other changes in market structure occurred in the control cities and

treatment cities during the period we study. Other than MAP’s acquisition of UDS’s Michigan

assets, we are unaware of any major change in market structure in any control or treatment city. 

Several minor changes in market structure are briefly discussed in the next subsection.
12 UDS’s closure of its Alma refinery appears to be unrelated to this acquisition. In

mid-1999, UDS decided to close its Alma refinery after unsuccessfully trying to sell it for a year. 

(See footnote 5) UDS’s closure of its Alma refinery is consistent with a nationwide trend toward

consolidating refining capacity at fewer but larger refineries. Smaller refineries operate at a cost

disadvantage because of their lower scale of operation. In some cases where a small refinery is

near both crude oil supplies and areas that consume refined product, this cost disadvantage may

be offset by lower transportation costs (FTC 2004, pp.179-180). In the case of the Alma

refinery, crude oil was produced nearby, but the production of this crude oil was falling sharply: 

Michigan crude oil production decreased from over 38 million barrels in 1979 to under 7.5

million barrels in 1999 (Energy Information Administration, U.S. Department of Energy,

Petroleum Supply Annual, various issues).

13 In the matter of the application of Wolverine Pipe Line Company to construct,

operate, and maintain a combination 12-inch and 16-inch outer diameter liquid petroleum

products pipeline system in Jackson, Ingham, and Clinton Counties, Case No. U-12334, March

7, 2001 Michigan Public Service Commission, see pages 5, 15.

14 See http://www.wolverinepipeline.net/wol122404.pdf.

9

Treatment of Confounding Factors

While we can select control cities that will experience most of the demand and supply

shocks experienced by the treatment cities, a few factors affecting supply that are specific to the

treatment cities remain. First, the source of supply for two terminals changed at about the same

time as the acquisition. Prior to late 1999, UDS’s Alma refinery supplied the UDS terminals in

Lansing and Bay City. After early 2000, Wolverine supplied these two refineries through a

pipeline that it purchased from UDS and connected to its main pipeline. In an application to

expand the capacity of the former UDS pipeline, Wolverine claimed that UDS’s closure of its

Alma refinery created a shortage of refined products in southeastern and central Michigan which

the former UDS pipeline lacked the capacity to offset.12 Wolverine further claimed that the

Buckeye Pipeline, which also serves Bay City, operates near its capacity and thus the marginal

demand in southeastern and central Michigan must be met by either truck transport or barge

transport, both of which have a higher marginal cost than pipeline transport.13 As of November

2004, Wolverine had not secured the necessary regulatory approvals to add this capacity.14

It is difficult to judge the validity of Wolverine’s claim that the closure of the Alma

refinery reduced the supply of refined products into central Michigan since firms keep data on

transport through pipelines and terminals private. However, Wolverine’s website currently lists
15 See http://www.wolverinepipeline.net/

16 For accounts of the Wolverine Pipeline Rupture see “Ruptured gas line should be

fixed by Thursday” Associated Press, June 14, 2000; “Gasoline pipeline is shut down again for

repairs” Associated Press, August 16, 2000; “Pain at the pump: Gas crisis that put drivers over a

barrel shows weaknesses in U.S. fuel lifeline.” Alejandro Bodipo-Memba, Free Press Business

Writer, October 16, 2000; and Bulow, Jeremy, Jeffrey Fischer, Jay Creswell, and Christopher

Taylor, “U.S. Midwest Gasoline Pricing and the Spring 2000 Price Spike,” The Energy Journal,

2003, 24(3) pp. 121-149.

17 A search of the Department of Transportation’s Office of Pipeline Safety website

found only one other pipeline incident that might have differentially affected our treatment cities

and control cities. We searched trade press sources and examined the pricing data and found no

10

the capacity of the former UDS pipeline into central Michigan as 50,000 barrels, which equals

the capacity of the Alma refinery.15 (And, our results suggest that gasoline prices in Lansing fell

after the acquisition.) It is also difficult to isolate the possible effect of UDS’s closure of its

Alma refinery. Because the closure of the Alma refinery shortly preceded MAP’s acquisition of

UDS’s other Michigan assets, there is not a significant time period during which we can observe

one effect but not the other. In addition, the effect of reduced supply at Lansing and Bay City

could spill over into cities such as Flint and Grand Rapids. Thus, the same cities that are

affected by the change in market structure in terminal services might also be affected by the

closure of the Alma Refinery. If the closure of the Alma Refinery reduced the supply of refined

products into central Michigan, failing to control for it would tend to bias our results toward

finding a price increase from this acquisition.

Several other supply shocks are easier to isolate. On June 7, 2000, the Wolverine

Pipeline ruptured outside of Jackson, Michigan. As a consequence, no refined products were

shipped on the Wolverine Pipeline between Jackson and Detroit from June 7 to June 16. After

June 16, the Wolverine Pipeline operated at a reduced capacity until the end of August. The

rupture of the Wolverine Pipeline caused a shortage of gasoline in eastern Michigan, which

caused gasoline prices to rise to over $2 per gallon. The effects of this shortage spilled over into

neighboring areas as purchasers of refined products sought to secure supplies. By the end of

August, the effects of the Wolverine Pipeline rupture had largely passed. To control for this

supply shock, we use a dummy variable for the period from June 7th until the end of August.16,17
indication that this disruption had any significant effect. 

11

Between early May and late July of 2000, the price of gasoline in the Chicago and

Milwaukee areas increased relative to the rest of the country. This price increase (hereafter, the

Midwest gas price spike) was primarily caused by supply disruptions relating to the introduction

of a new formulation of reformulated gasoline in Chicago and Milwaukee (see Bulow et al.

2003). While the price increase was greatest for reformulated gasoline sold in Chicago and

Milwaukee, the price of conventional gasoline also increased. We include a dummy variable to

control for any differential effects that this Midwest gas price spike had on prices in the cities we

examine. To allow the effects of the Midwest gas spike and the Wolverine outage to be

different, this dummy variable goes to zero when the Wolverine outage begins.

In August of 2001, Citgo’s Lemont (Chicago) refinery experienced a fire which reduced

its output for six months. However, increased shipments from the Gulf returned the price

differential between the upper Midwest and the Gulf to normal after approximately two months. 

To control for any differential effects that this refinery outage had on prices in the cities we

examine, we include a dummy variable for the two-month period when this refinery outage

appeared to affect prices.

Several terminals closed or changed ownership within several years of the acquisition. 

These changes in terminal ownership probably had little effect on competition in the cities that

we study with two possible exceptions. Depending on the geographic scope of the relevant

terminal markets, Uno-Ven’s shutdown of its terminal in Bay City between 1997 and 1999 and

Equilon’s purchase of the Clark Oil terminal in Marshall sometime between 1999 and 2001 may

have affected price. We cannot control for these changes, however, because we are unable to get

approximate dates for when they occurred. Failing to control for these changes would tend to

bias our results toward finding a price increase from this acquisition. 

We initially included several dummy variables in our regression to account for other

possible supply and demand shocks. We later deleted these dummy variables since their

coefficients were small and rarely statistically significant and their exclusion did not affect our

other results. These dummy variables included monthly dummy variables to allow for

systematic differences in seasonal prices between our treatment cities and control cities, a
18 A fleet card is basically a credit card that a company issues to some of its

employees (salesmen, insurance claims adjusters) to pay for gasoline and possibly repairs.

12

dummy variable to account for a 2001 fire at Tosco’s refinery in Wood River, IL, a dummy

variable accounting for the Federal Energy Regulatory Commission’s (FERC) September 2001

decision to allow Wolverine to set market-based rates for pipeline transport to Chicago, Elkhart,

and Toledo, and a dummy variable accounting for FERC’s July 2001 decision to allow

Wolverine to set market-based rates for pipeline transport to Detroit and Wolverine’s

concomitant agreement to facilitate third-party refined products shipments to Grand Rapids (see

FERC Docket No. OR99-15). 

Data

To study gasoline prices in the six treatment and two control cities, we use a dataset

drawn from data on retail gasoline prices compiled by the Oil Price Information Service (OPIS). 

The OPIS data is based on transactions in which someone uses a fleet card to purchase gasoline

from a gasoline station.18 While this data is among the best available, we only observe the price

for a specific station if someone used a fleet card to purchase gasoline at that station. Hence

gasoline stations that do not accept fleet cards are not sampled. Because the stations that do not

accept fleet cards tend to sell unbranded gasoline and unbranded retailers generally charge lower

prices than branded retailers, the OPIS data will tend to overestimate the actual retail gasoline

prices in an area. We do not believe that this affects the results in this paper, however, since any

changes over time in this overestimate will likely affect our treatment and control cities equally. 

 The fact that OPIS records a price only if someone uses a fleet card to purchase gasoline

also means that the set of stations reporting price data to OPIS varies from day to day. As a

consequence, the prices reported by OPIS are more volatile than the actual underlying prices. To

reduce this volatility, we define an observation as the average of the daily prices reported over

the course of a week. We focus on the pricing of regular gasoline in this study because

approximately 80 percent of the gasoline sold in the U.S. is regular octane gasoline. 

Following similar studies that use the event study methodology, we focus on a time period long

enough to allow the acquirer to take advantage of any increased market power or efficiencies
19 Using a dummy variable to control for the period between the acquisition’s

announcement and consummation has little effect on our results. Using the acquisition’s

announcement date as the starting point for the post-acquisition period has little effect on our

results. Examining a time period beginning two years before and ending two years after the

transaction did not affect the results. 

20 Because it moderates the volatility of short-term price swings, the 12-week

moving average provides a cleaner comparison of pre- and post- acquisition prices than does the

raw price data.

21 The standard errors in a conventional difference-in-differences estimation may be

biased downward (Bertrand et al (2004)). Since in this case most of the point estimates are not

statistically different from zero, it is less of a concern. 

13

resulting from the acquisition but short enough that changes in market conditions unrelated to the

acquisition do not swamp the effects of the acquisition. For this reason, we analyze a window

beginning three years prior to the acquisition and ending three years after the acquisition.19

IV. Results

To obtain a rough estimate of the effect of this acquisition, we plot the price of gasoline

in the treatment cities relative to the control cities. Figure 3 shows the 12-week moving average

of the price of gasoline in Lansing and in Flint relative to South Bend.20 The graph suggests that,

apart from the price spike resulting from the rupture of the Wolverine Pipeline in the summer of

2000, the relative price in Flint did not change and the relative price in Lansing decreased. The

graphs for pairings of other treatment cities with the two control cities look similar to the results

for Flint. 

We next estimate the relationships between the treatment cities and the control cities

using the simple difference-in-differences estimator discussed in the methodology section. For

the twelve pairings of treatment city and control city, Table 3 presents the estimated coefficients

and the standard errors for the merger dummy variable.21 The estimated coefficient is less than

1.2 cents per gallon in all of the pairings and is negative in four of the pairings. In no pairing is

the estimated coefficient positive and statistically significant from zero at the five percent level. 

The estimated coefficient is negative and statistically significant in both pairings where Lansing

is the treatment city. This result suggests that Lansing area consumers may have benefitted from
22 This period includes an unanticipated 10-day period and an anticipated 7-day

period when no shipments were made on Wolverine. During the rest of this period, Wolverine

operated at about 80 percent of capacity. (See “Gasoline pipeline is shut down again for repairs,

Associated Press, August 16, 2000 at www.detnews.com/2000.metro/0008/16/-106455.htm)

14

Wolverine’s integration of the former UDS pipeline into its existing pipeline system.

Table 4 shows the full regression results for the six treatment cities relative to South

Bend. (The results using Elkhart-Goshen as a control are similar to the results using South Bend

as a control.) The June 2000 rupture of the Wolverine Pipeline meant that refined products

from the Chicago area could not reach terminals located in Detroit, Lansing, and Bay City

through the Wolverine Pipeline. Obviously, we would expect that gasoline prices in these cities

would rise relative to the control cities. Gasoline jobbers responded to higher prices in these

cities by using the nearest terminals that still could receive refined products. Thus, we would

also expect that gasoline prices in cities such as Jackson and Grand Rapids would increase. Our

results show this. The dummy variable for the Wolverine Pipeline rupture accounts for the

average increase in price in the treatment cities relative to the control cities from June 7 to

August 31, which captures the period when Wolverine Pipeline shipments were disrupted.22 The

estimated coefficient for this dummy variable ranges from roughly zero to roughly five and onehalf cents. The estimated coefficient is statistically significant at the 5 percent level in most of

the pairs of treatment cities and control cities. 

The coefficient for the dummy variable for the supply disruption relating to the

introduction of phase II reformulated gasoline in Chicago and Milwaukee is positive but not

statistically significant. The coefficient for the Citgo Lemont refinery outage is negative in four

of the pairings. In one pairing it is negative and statistically different from zero. 

 Table 5 shows the estimated merger effects for the twelve pairings of treatment city and

control city when we do not control for supply shocks. In some cases the results differ

significantly: The estimated price decreases in Lansing relative to Elkhart-Goshen and South

Bend decline in magnitude and statistical significance; estimated price increases in Jackson

relative to Elkhart-Goshen and in Kalamazoo relative to Elkhart-Goshen increase in magnitude

and become statistically significant at the 5 percent level. This suggests that failing to account

for supply shocks affects the results. 
23 Taylor and Hosken(2004) examine a case where an increase in rack prices was

not fully passed through to retail prices. 

15

In a previous study, the GAO (2004) found that MAP’s acquisition of UDS’s Michigan

assets led to a statistically-significant price increase of 1.4 to 2.6 cents per gallon. There are

several possible explanations for the difference between our results and the GAO’s results. Our

study explicitly accounts for three supply shocks that differentially affected prices in the

treatment cities and the control cities whereas the GAO study only accounts for the Midwest gas

price spike. Our study also examines prices for three years after the merger while the GAO

study only examines prices for one year after the merger. Finally, in our study we examined

retail prices while the GAO examined wholesale rack prices. Because wholesale rack prices

measure the wholesale price paid by only a fraction of gasoline retailers, observing an increase in

wholesale rack prices is not sufficient to infer an increase in retail prices.23

IV. Conclusion

The above results suggest that MAP’s acquisition of UDS’s Michigan wholesale and

retail assets had very little effect, positive or negative, on retail gasoline prices in Michigan. 

This result is robust to changes in the length of time studied and changes in the starting date of

the post-merger period. Since we would be unlikely to see these results if MAP’s acquisition of

UDS substantially lessened competition, we believe that these results provide some support for

the view that gasoline mergers with pre-merger and post-merger wholesale and retail

concentration levels similar to those in this case study do not substantially harm competition. 

MAP’s acquisition of UDS’s Michigan assets had little direct effect on the refining and

pipeline sectors of the oil industry. Thus, this study is silent about what types of refinery or

pipeline mergers might harm consumers with one exception: The observation that gasoline

prices in Lansing fell relative to gasoline prices in the control cities suggests that consumers may

have benefitted from Wolverine’s integration of the former UDS pipeline into its existing

pipeline system.
16

References

Barton, David, and Roger Sherman. 1984. The price and profit effects of horizontal merger: A 

case study. Journal of Industrial Economics. 33: 165-77.

Bertrand, M., E. Duflo, S. Mullainathan, M. Page 2004. How Much Should We Trust 

Difference-in- Difference Estimates? Quarterly Journal of Economics, 119: 249-275.

Borenstein, Severin, and Andrea Shepard. 1996. Dynamic pricing in retail gasoline markets. 

The RAND Journal of Economics, 27: 429-451.

Bulow, Jeremy, Jeffrey Fischer, Jay Creswell, and Christopher Taylor. 2003. U.S. Midwest 

Gasoline Pricing and the Spring 2000 Price Spike. The Energy Journal, 24: 121.-149.

Chouinard, Hayley, and Jeffrey Perloff. 2003. Gasoline price differences: Taxes, pollution 

regulations, mergers, market power, and market conditions, mimeo 

Chouinard, Hayley, and Jeffrey Perloff. 2004. “Incidence of Federal and State Gasoline Taxes,” 

Economic Letters 83: 55-60. 

Hastings, Justine. 2004. Vertical relationships and competition in retail gasoline markets: 

Empirical evidence from contract changes in Southern California. American Economic 

Review 94: 317-328.

Hastings, Justine, and Richard Gilbert. 2002. Market power, vertical integration and the 

wholesale price of gasoline. mimeo.

Kim,E.H, and V. Singal. 1993. Mergers and market power: Evidence from the airline industry. 

American Economic Review, 83: 549-69. 

Pinske, J., M. Slade and C. Brett, 2002, “Spatial Competition: A Semiparametric Approach,” 

Econometrica, 70: 1111-1153.

Shapiro, Carl. 1996. “Mergers with differentiated products.” Antitrust. 23-30.

Schumann, L., J. Reitzes, and R. Rogers. 1997. In the matter of Weyerhaeuser company: The

use of a hold-separate order in a merger with horizontal and vertical effects. Journal of 

Regulatory Economics, 11: 271-89.

Schumann, L., R. Rogers, and J. Reitzes, 1992. Case Studies of The Price Effects of Horizontal 

Mergers, Federal Trade Commission: Washington DC.. 

Slade, Margaret, 1992. Vancouver’s gasoline price wars: An empirical exercise in uncovering 

supergame strategies. Review of Economic Studies. 59:257-76.
17

Taylor, Christopher and D. Hosken,. 2004. The Economic Effects of the Marathon - Ashland 

Joint Venture: The Importance of Industry Supply Shocks and Vertical Market Structure. 

mimeo

United States Federal Trade Commission, 2004. Petroleum industry : Mergers, structural 

change and antitrust enforcement. Washington, DC.

United States Government Accountability Office. 2004. Effects of mergers and market

concentration in the U.S. petroleum industry. rev. ed. Washington, DC.

Willig, Robert. 1991. Merger analysis, industrial organization theory, and merger guidelines. 

Brookings Papers on Economic Activity. 281-312. 
18

Term inal C ity S upply S ourc e C apac ity S hare F irm S hare 

A m oc o O il C om pany C heboy gan barge, tank er 150,000 1.5%

A m oc o O il C om pany N apoleon P ipeline, Truc k 250,000 2.5%

A m o c o O il C o m p a n y R ive r R o u g e B u c k e y e , A m o c o 8 0 3 ,0 0 0 7 .9 %

A m o c o O il C o m p a n y Ta y lo r W o lve rin e , A m o c o 2 4 8 ,0 0 0 2 .4 % 1 4 .3 %

C itg o P e tro le u m F e rry s b u rg W o lve rin e P ip e lin e 1 8 0 ,7 2 2 1 .8 %

C itg o P e tro le u m Ja c k s o n W o lve rin e P ip e lin e 2 2 2 ,7 0 0 2 .2 %

C itg o P e tro le u m N ile s W o lve rin e P ip e lin e 2 7 0 ,6 8 8 2 .7 %

C itg o P e tro le u m R o m u lu s W o lve rin e , S u n 1 7 5 ,0 0 0 1 .7 % 8 .4 %

C la rk R e fin in g & M a rk e tin g M a rs h a ll W o lve rin e P ip e lin e 2 8 1 ,0 0 0 2 .8 %

C la rk R e fin in g & M a rk e tin g Ta y lo r B u c k e y e , W o lve rin e 3 1 1 ,0 0 0 3 .1 % 5 .8 %

E q u ilo n E n te rp ris e s L L C D e tro it B u c k e y e , W o lve rin e 6 0 8 ,0 0 0 6 .0 %

E q u ilo n E n te rp ris e s L L C F e rry s b u rg W o lve rin e P ip e lin e 3 0 6 ,0 0 0 3 .0 %

E q u ilo n E n te rp ris e s L L C Ja c k s o n W o lve rin e P ip e lin e 8 1 ,1 0 0 0 .8 %

E q u ilo n E n te rp ris e s L L C N ile s W o lve rin e P ip e lin e 4 1 6 ,9 0 0 4 .1 %

E q u ilo n E n te rp ris e s L L C R o m u lu s W o lve rin e , B u c k e y e , E q u ilo n 3 5 3 ,0 0 0 3 .5 % 1 7 .4 %

M arathon A s hland P etroleum D etroit truc k 100,000 1.0%

M a ra th o n A s h la n d P e tro le u m Ja c k s o n W o lve rin e P ip e lin e 2 8 0 ,0 0 0 2 .8 %

M arathon A s hland P etroleum M ount M orris B uc k ey e 237,000 2.3%

M a ra th o n A s h la n d P e tro le u m N ile s W o lve rin e P ip e lin e 3 3 2 ,0 0 0 3 .3 %

M arathon A s hland P etroleum N . M us k egon M A P 455,000 4.5%

M a ra th o n A s h la n d P e tro le u m Ta y lo r B u c k e y e , S u n , W o lve rin e 2 2 9 ,0 0 0 2 .3 % 1 6 .1 %

M obil O il C orporation F lint B uc k ey e 191,000 1.9%

M o b il O il C o rp o ra tio n N ile s W o lve rin e P ip e lin e 1 1 7 ,3 0 0 1 .2 %

M o b il O il C o rp o ra tio n W o o d h a ve n W o lve rin e , B u c k e y e 1 ,1 9 8 ,3 0 0 1 1 .8 % 1 4 .9 %

S u n R e fin in g C o m p a n y D e tro it S u n P ip e lin e 1 7 6 ,0 0 0 1 .7 %

S u n R e fin in g C o m p a n y O w o s s o B u c k e y e 2 3 0 ,0 0 0 2 .3 % 4 .0 %

U D S B ay C ity U D S P ipeline 400,000 4.0%

U D S Lans ing U D S P ipeline 400,000 4.0%

U D S Tra ve rs e C ity Ta n k e r, Tra n s p o rt Tru c k 1 5 0 ,0 0 0 1 .5 % 9 .4 %

A tla s O il Ta y lo r W o lve rin e , B u c k e y e , S u n 2 7 3 ,0 0 0 2 .7 %

B P O il C om pany Tay lor B uc k ey e 264,000 2.6%

C o u s in s P e tro le u m Ta y lo r B u c k e y e , W o lve rin e 1 9 0 ,0 0 0 1 .9 %

M ic h ig a n M a rin e Te rm in a l R ive r R o u g e B u c k e y e , W o lve rin e 2 1 6 ,0 0 0 2 .1 %

W a te rfro n t P e tro le u m Te rm in a l D e a rb o rn p ip e lin e b a rg e 3 0 ,0 0 0 0 .3 %

T a b le 1 - T e rm ina l C a p a c ity a nd M a rk e t S ha re in M ic hig a n

Source: 1997, 1999, and 2001 Petroleum Terminal Encyclopedia, Oil Price Information Service

Because the Petroleum Terminal Encyclopedia did not report capacity figures for some

terminals, some capacity figures are estimated. Equilon’s Romulus terminal is assigned the

average capacity of the Detroit area terminals. MAP’s Detroit terminal is given a small capacity

because it is supplied by truck. The UDS terminal at Traverse City and Amoco’s terminal at

Cheboygan are given a small capacity because they are distant from large population centers. 

The UDS terminals at Lansing and Bay City distributed refined products from the Alma refinery,

which produced about 10 percent of Michigan’s needs. These terminals were assigned a

capacity slightly below 10 percent of the terminal capacity in Michigan. The Amoco refinery at

Napoleon was assigned a capacity roughly consistent with similar terminals. 
19

Control City Flint Lansing Saginaw-Bay 

City

Grand RapidsMuskegon Jackson KalamazooBattle Creek

Elkhart-Goshen, IN 0.10 -1.44 0.66 0.39 1.15 1.06

(0.63) (0.67) (0.64) (0.62) (0.72) (0.61)

South Bend, IN -0.43 -1.96 0.13 -0.13 1.01 0.54

(0.63) (0.65) (0.62) (0.61) (0.74) (0.61)

Table 3 - Estimated Merger Effects(Full Specification)

Brand Flint Lansing SaginawBay City

Grand RapidsMuskegon Jackson KalamazooBattle Creek

Marathon Ashland Petroleum 23% 17% 9% 10% 5% 10%

 Speedway-SuperAmerica 12% 13% 6% 8% 3% 8%

 Marathon 11% 4% 3% 2% 2% 2%

UDS (Total) 7% 13% 10% 2% 8% 7%

BP-Amoco 4% 4% 6% 11% 3% 6%

Equilon (Shell-Texaco) 3% 7% 3% 10% 8% 16%

Citgo 3% 1% 1% 1% 0% 3%

Clark Refining & Marketing 6% 7% 13% 5% 10% 14%

Mobil 2% 8% 2% 9% 3% 3%

Sunoco 19% 1% 6% 2% 0% 0%

Others 32% 43% 50% 50% 64% 42%

MAP/UDS Share 30% 30% 19% 12% 13% 17%

Total Number of Stations 94 119 105 249 39 117

Table 2 - Market Share by Brand

Standard errors in parentheses

Significant estimates in bold
20

Variable

Flint Lansing Saginaw-Bay 

City

Grand RapidsMuskegon Jackson KalamazooBattle Creek

Merger -0.43 -1.96 0.13 0.13 1.01 0.54

(0.63) (0.65) (0.62) (0.61) (0.74) (0.61)

Midwest Gas 0.20 1.50 0.89 1.07 -0.32 1.12

(2.13) (2.09) (2.07) (1.83) (2.48) (1.89)

Wolverine Rupture 3.72 5.70 2.03 4.38 4.57 2.89

(1.21) (1.24) (1.19) (1.15) (1.42) (1.16)

Lemont Outage -0.54 -2.99 1.42 -0.63 -1.63 0.09

(1.54) (1.55) (1.51) (1.40) (1.81) (1.43)

Constant 1.88 2.90 1.63 2.30 1.22 1.84

(0.43) (0.45) (0.43) (0.42) (0.51) (0.43)

rho 0.48 0.52 0.49 0.56 0.49 0.55

Table 4 Individual City Regressions (Control South Bend, In)

Control City Flint Lansing Saginaw-Bay 

City

Grand RapidsMuskegon Jackson KalamazooBattle Creek

Elkhart-Goshen, IN 0.45 -0.96 0.93 0.84 1.91 1.37

(0.63) (0.77) (0.61) (0.67) (0.73) (0.60)

South Bend, IN -0.02 -1.44 0.46 0.36 1.43 0.89

(0.64) (0.77) (0.61) (0.69) (0.76) (0.63)

Table 5 - Estimated Merger Effects (No Supply Shocks)

Standard errors in parentheses. 

Significant estimates in bold

Standard errors in parentheses.

Significant estimates in bold.

South Bend 

Niles 

Kalamazoo

Indiana

Granger

Ferrysburg 

Grand -

Rapids

Lansing 

N. Muskegon 

Marshall 

Battle -

Creek

Cheyboygan 

Traverse City 

Bryan

Toledo 

Jackson 

Dearborn 

Napoleon 

Bay City 

Saginaw

Owosso Flint 

Mount Morris

Midland

Detroit 

Ohio

Romulus Woodhaven 

Taylor 

Oregon 

River Rouge

Michigan

Figure: 2

Refined Product Terminals in 1999

Terminals Owners: 1999

MAP

other

UDS
Figure 3

The Retail Price of Gasoline in Lansing and Flint Relative to South Bend (no tax)

-5

05

1015

4/1/977/1/9710/1/971/1/984/1/987/1/9810/1/981/1/994/1/997/1/9910/1/991/1/004/1/007/1/0010/1/001/1/014/1/017/1/0110/1/011

Cents per Gallon

12 per. Mov. Avg. (Lansing - South Bend) 12 per. Mov. Avg. (Fli

MAP - UDS Transaction Wolverine Pipeline 

12 Week Moving Average (Lansing - South Bend) 12 Week Moving Average