The Determinants of Entry:

An Analysis of Entrants and Non-Entrants into the Market for MTBE

Jay Johnson

Southeastern Louisiana University Department of General Business

Hammond, LA 70402 Tel: (985) 549-3071 Fax: (985) 549-2881

Email: jjohnson@selu.edu

Abstract It is seldom possible to plausibly define and observe a pool of potential entrants to a market. This study overcomes that limitation by taking advantage of an opportunity to reasonably define the potential entrants into MTBE production, a rapidly growing environmental product from the mid-1980�s to mid-1990�s. Potential entrants are identified as those firms having access to specific assets that could provide them necessary raw materials for MTBE manufacturing. Once the potential entrant firms are identified, specific information is collected about each firm�s financial performance and other relevant forms of experience and technology that they may possess related to the new product market.

A specific framework is developed to organize the variables collected in the unique dataset into important categories of information about the firms. The categories relate to firm efficiency, size, and innovativeness and measures of specific firm experience and technology including environmental performance because of the nature of the product involved. Two estimation methods are used to model these categories in order to test their significance on the probability of entry and the timing of entry.

Estimation results show that productivity and relevant experience as opposed to firm size and innovativeness are the primary characteristics differentiating entrants from non-entrants in the MTBE market. Entrants are also more likely to possess specific experience, which seems to better condition them for entry than other types of firms in the potential entrant pool. One particular factor significant to entry is a firm�s environmental performance. Environmental releases are associated with the order of entry.

March 2003

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The Determinants of Entry: An Analysis of Entrants and Non-Entrants into the MTBE Market

I. Introduction

The classical view of free entry into product markets as a process of competing

away excess profits and converging to a unique equilibrium of equal-size firms,

predictable in number, and minimum efficient size, has been replaced by empirical

research. This research has focused on developing a richer and more complex view of

entry based on the heterogeneity of firms (differences in core capabilities), the

evolutionary product development process and innovation (learning-by-doing and

relevant experience), and the interrelationship between entry, growth and exit and the

resulting industry market structure (Jovanovic, 1982; Nelson, 1991; Klepper, 1996).

Such developments in the ideas about entry improve explanations of some seemingly

common phenomena such as large-scale entry followed by shakeout or exit whereas the

usual free entry approach fails to predict such phenomena.

The newer models of entry have provided a way to analyze the importance of a

firm�s experience and innovation rates in determining its eventual performance and to

make comparisons as to whether particular models such as learning-by-doing experience

are more or less important than innovation or efficiency. However, as Klepper and

Simons (1999) point out, most of the research in this area has focused on examining

differences in performance among all of the entrants into a market. They emphasize that

entrants into a market actually come from a pool of potential entrants that is not

unlimited.

Klepper and Simons� work (1999) on entrants into television production from a

pool of radio producers demonstrates how much can be learned by defining specific sets

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of potential entrants. Radio producers were a significant class of potential entrants that

came to dominate the TV production industry. Yet even this important class of entrants

only accounted for 32% of the entrants with the remaining entrants coming from some

unspecified pool. Other studies about the evolution of market structure and the shakeout

phase (Jovanovic and MacDonald, 1994; Carroll, et.al. 1996; Klepper and Simons, 2000)

also begin by looking at a pattern of entry and the performance of the entrants rather than

investigating the factors that conditioned entry in the first place. Despite the contribution

of these recent papers to the understanding of firm survival and industry structure,

Klepper and Simons are careful to point out that stronger inferences about the conditions

of entry itself cannot be drawn without a better defined set of potential entrants. For the

purpose of studying entry, though, defining the pool of potential entrants is very difficult.

The nature of the current study is to take advantage of a unique opportunity where

the pool of potential entrants into a new product market can be well defined by a specific

set of production factors. The manufacture of a chemical product, methyl tertiary-butyl

ether1 (MTBE), requires a unique set of assets and raw materials. MTBE is an important

gasoline additive in the production of reformulated (cleaner-burning) gasoline and can be

viewed as an environmental intermediate good. It was repeatedly described in chemical

industry trade journals in the early 1990�s as the fastest growing chemical product in the

U.S. and the world. MTBE was actually first introduced in 1979, but 1983 marked the

first year of any significant commercial production. The growth of MTBE production

was rapid from 1987 to 1994 and then leveled off. Because the set of potential entrants

into the production of MTBE can be well defined, new insights into the nature of entry

are possible.

In particular, my study will focus on the nature of the entrants from the defined

pool of potential entrants and how they are different from the non-entrants. A well-

defined pool makes it possible to investigate how the entrants were conditioned,

compared to potential entrants who did not enter (non-entrants), by their experience,

efficiency, environmental practices, and relevant technologies. The primary finding is

1Methyl tertiary-butyl ether is the trivial name for 2-methoxy-2-methylpropane. Its chemical formula can be written as CH3OC(CH3)3 where -CH3 is the methyl group, -C(CH3)3 is the tertiary-butyl group, and OC in the middle is the ether group. The presence of the ether is important for the compound to be classified as an oxygenate for increasing the oxygen content of gasoline.

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that firm productivity is the significant factor differentiating the entrants from the non-

entrants into the production of MTBE. Once productivity is controlled for, then firm

size, innovativeness, and environmental practices do not matter. Since different

technologies are available to integrate MTBE manufacture into a firm�s production mix, I

found that a type of �relevant� experience favored entry through one technology type that

is more closely integrated with gasoline production and distribution than the other

technologies.

The organization of the paper is as follows. Section II briefly discusses the

background and nature of the production and market for the additive, MTBE. Section III

develops a framework of factors that could matter for analyzing entry into a new product

market and the variables available for the analysis in the dataset constructed. Section IV

discusses the results of the empirical analysis and their implications. And finally Section

V offers concluding remarks and suggestions for future work.

II. Background and History

MTBE was first introduced as a gasoline additive in the U.S. in 1979 on a very

small scale. Interest in its use in gasoline was prompted by the search for a high-octane

component with which to replace lead additives in gasoline. The phase-out of lead in

gasoline, also during the early 1980�s, coincided with the realization that other chemical

additives being used and/or evaluated were having major problems. ARCO had been the

first to realize that MTBE had a large potential market as a gasoline octane enhancer, but

initially the United States Environmental Protection Agency (hereafter EPA) restricted

the use of non-oil based compounds in gasoline including MTBE. The EPA had first

issued a waiver in 1979 to allow up to 7% by volume of MTBE. However, with evidence

that oxygenated-type additives improved combustion and seemed to reduce emissions,

the EPA, in 1988, increased the allowable limit to 15% by volume. (Hälsig, et.al., 1991)

With restrictions eased, plus the growing awareness that the compounds could

produce an environmental benefit, the stage was set for a rapid expansion of MTBE

production. Then, in September of 1989, �ARCO Products Company stunned the

refining world with its introduction of �EC-1�, a new product designed to reduce ozone

smog and carbon monoxide pollution.� (McKay, 1992, p 207) EC-1 was the first product

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meeting the description of the newly coined term �reformulated gasoline� and its formula

included the additive MTBE. Other major gasoline producers and marketers followed,

and the changing gasoline market increased demand for oxygenated additives of which

MTBE became the dominant compound.

A critical factor in being able to identify the pool of potential entrants into MTBE

production is the availability of the necessary raw materials. Two chemical compounds

are used to manufacture MTBE: isobutylene and methanol.2 Both compounds are

available within existing methods of production for gasoline and petrochemical

feedstock. However, the existing pipeline and distribution system has not been set up for

widespread sale and transport of these critical raw materials. Therefore, if a firm were to

consider entering the MTBE market, the firm would first have to consider whether a

supply of isobutylene and methanol were available from its existing production

processes.

Isobutylene is a byproduct in any petroleum cracking process and its quantity as a

byproduct is dependent on how the unit is operated for its intended purpose. A cracking

process is one in which heavier or higher molecular weight components of crude oil are

�cracked� into lighter or lower molecular weight components that are more valuable as

blend components or feedstock for other chemical processes. Isobutylene has often been

mischaracterized as a waste product of cracking processes, but it does have alternative

uses both as a feedstock for additional gasoline component manufacture and as a

feedstock for other petrochemical production. So the availability of isobutylene as a

feedstock to any potential entrant into MTBE is predominately dependent on whether the

firm has previously invested in a particular production technology with isobutylene as a

byproduct.

Methanol is the other factor for MTBE manufacture. Methanol manufacture

benefits from large economies of scale and it is used in the manufacture of many other

chemical products often produced at the same plant. However methanol is not produced

in the same plants that would normally produce gasoline. Although the availability of

methanol is not as restricted as isobutylene is, if a firm were to produce MTBE on a very

2 Isobutylene or isobutene can be represented as (CH3)2C=CH2 and methanol as CH3OH. These two compounds are reacted together in the presence of a catalyst to make MTBE.

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large scale then the availability of methanol could be an important consideration.

Therefore the availability of methanol is also a critical factor for a potential entrant.

There are three alternative technologies in the production of MTBE: cat crackers

in gasoline refineries, steam crackers in petrochemical plants, and stand-alone units (see

Figure 1). Identifying the three technologies and some of the consequences of their

operations and markets will allow for the investigation of the importance of relevant

technologies and firm heterogeneity on the nature of entry. The first method is by

integration into current petroleum refining and gasoline manufacturing operations

(Technology 1 in Figure 1). This method entails using isobutylene from currently

available fluid catalytic cracking units (FCC or Cat Crackers) that are a major piece of

equipment in any gasoline-producing refinery. In this case, isobutylene is stripped out of

a mixture that would otherwise be used as a feed for an Alkylation Unit that is also a

producer of gasoline components. Using a cat cracker as a supplier of isobutylene for

MTBE production means scaling the MTBE unit to the size of the available feed typically

used for efficient gasoline production. MTBE units fed by cat crackers tend to be smaller

in size than the other two technologies in order to match existing equipment and unit

operations.

The second method of MTBE production is by integration into current

petrochemical production operations (Technology 2 in Figure 1). In this case, the supply

of isobutylene can come from one of two sources, a steam cracker unit (SC) used to make

many other petrochemical feeds or tertiary-butyl alcohol (TBA) that is a joint product of

propylene oxide production. MTBE units fed with steam cracker units are typically about

the size of cat cracker fed units. Production of propylene oxide is limited to a very few

large-scale producers and TBA yield is very high, so these plants tend to be about 3 or 4

times larger than cat cracker and steam cracker fed plants. In the data set, there are only

two MTBE units integrated with propylene oxide production and fed by TBA. One of

these units is the largest MTBE producer in the U.S.

The third method of MTBE production is what might be called a stand-alone

technology. More recent technological developments have made it possible to build a

unit that makes isobutylene directly from more widely available natural gas and/or

butanes. The stand-alone technology then allows a firm to build a plant outside of a

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preexisting refinery or chemical plant and produce isobutylene and methanol from natural

gas to be used to make MTBE. The stand-alone plants are also about 3 or 4 times larger

than cracker-fed MTBE plants. The stand-alone technology is still not independent of the

distribution system for gasoline production. Although physically located outside

refineries, they tend to be in close proximity to large concentrations of refining

operations.

Technology 1Gasoline-producing refinery

Cat Cracker Unit

Technology 2Petrochemical plant

Steam Cracker Unit

Technology 3Stand-Alone MTBE Unit

Butane Dehydrogenation Unit

Isob

utyl

ene

feed

Purchased Methanol for Technologies 1 & 2

Methanol Unit

MTBE

Isobutylene feed

Catalytic Distillation

Unit

Isob

utyl

ene

feed

FIGURE 1�MTBE Production Technologies

III. Model of Entry and the Selection of Variables

Several stylized facts have emerged about entry into markets. Using an

appropriate model of entry, their stories can be tested on data collected about a pool of

potential entrants into the market for MTBE. Comparisons can then be made between

those firms in the pool that did enter and those that did not (see Geroski (1991, 1995) and

Klepper (1996, 1999, 2000)). The model should include a way to test whether these

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stylized facts continue to hold in this market, and if there are other factors that are

significant but have not previously been observed. The works by Geroski (1991, 1995)

summarize characteristics about entry mostly at high levels of aggregation of industry

data and Klepper (1996, 1999, 2000) articles look at several specific industries and their

evolution. The Data Appendix reports the many sources used to construct the variables

(discussed below) used in the estimation of the model.

Logit and Hazard Models

The first method of analysis used to investigate MTBE entry will be to estimate

the probability of entry from a set of independent variables selected to test hypotheses

thought to matter for entry. Since the probability of entry is limited to the 0-1 interval, it

is estimated with a logit model as follows:

(1) ln [Pi /(1- Pi)] = α + β'X + µ

where Pi = Prob[Ei = 1] and Ei is the dichotomous dependent variable for whether or not

(1 or 0) the firm began producing MTBE in any year during the period from 1987 to

1997. X is the vector of independent variables, β is the vector of coefficients, and µ is an

error term. Significant results on the coefficients of the independent variables can be

interpreted as increasing or decreasing the probability of entry (that Ei =1). The dataset

includes observations of all years from 1987 to 1997. However to estimate the logit

model only the first year of observations, 1987, will be used because the observations of

the following years would have to be thought of as being conditionally determined by the

values from previous years. So the 1987 observations will be considered exogenous with

respect to the likelihood of entry for any of the following years.

The second method of investigation will be to estimate a survival time model.

The survival time model is used to examine whether the factors significant for the

probability of entry also affect the order or hazard of entry over time. A Cox

proportional hazards model is estimated for the hazard of entry for the same variables

reported in the logit model as follows:

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(2) h(t) = h0(t)exp[β'X]

where h(t) is the probability of entry of a firm in year t for the firms that have not entered.

It is assumed then that a baseline hazard, h0(t), exists for each year that shifts

proportionally by the vector of independent variables X and the corresponding vector of

coefficients β. The preceding methods can now be used on a specifically selected set of

variables that can be used to test various hypotheses about entry.

Firm Experience

One of the important facts that Geroski points out is that a firm�s size and age are

both positively correlated with survival and growth. The firm�s size and age are

considered to be representative of general experience and a key aspect of the study of

entry is how previous experience is related to the likelihood of entry. Klepper and

Simons (1999, 2000) typically report size and age of firms as measures of �experience�

when analyzing specific new markets and observe that generally larger firms are more

�experienced� and have larger scales in which to exploit further profit opportunities

based on that experience. In the current work, several variables are available as measures

of experience in a test for entry. Firm size as a function of its capitalization can be

expressed with various measures of assets as reported by Compustat (1998). The values

include Current Total Assets, Total Assets, Gross Assets, and Earning Assets. A positive

and significant coefficient on these variables might confirm that size or general

experience does matter to entry as well, and not just to survival and growth as reported by

Geroski. A negative and significant coefficient might suggest that some type of

difference may exist where innovation or some other more specific factor is more

important than a general measure of experience.

Some other proxies of experience available in the Compustat dataset are measures

of the value of Plants, Property, and Equipment. These variables might reflect more

specific types of experience in the firm than those measures based on the value of all

corporate assets. Significant coefficients on any of these variables would be evidence

about the nature of firms� experience from previous investments in productive goods as

opposed to the general availability of capital assets to the firm.

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Other measures of general experience that are often considered in the literature

include firm size based on Sales and Number of Employees. Significance on Sales would

be evidence of a firm�s market presence and ability to generate revenue from and in

support of their business activities, but Sales in general would not be able to differentiate

firms with more capability in manufacturing processes as opposed to firms that have core

capabilities in organizing their marketing and distribution activities. The Number of

Employees a firm has, if significant, could be evidence of the contribution of knowledge

of these employees or the importance of the capabilities the firm�s organization.

However, these factors might be best considered together as measures of firm efficiency

discussed below.

“Relevant” Experience

General experience might be a significant factor in a firm�s likelihood of entry

into new product market. However, it is also possible that more specific capabilities

within a pool of potential entrants are what determine the likelihood of entry. Klepper

and Simons (1999) have explored this aspect of entry by examining experience more

directly relevant to the type of product or market involved. Their study of entry into TV

production looked at the number of years of radio production and the types of radios

produced as evidence that firms had more relevant experience and knowledge related to

the emerging production of TVs. They found that a firm�s relevant experience was a

significant factor and inferred that this experience and knowledge gave firms with more

relevant experience had superior abilities to manage their R&D efforts in the developing

TV market.

Data on the pool of potential MTBE entrants can be explored for evidence of

types of relevant experience as well. Identifying the pool of potential entrants is made

possible by detailed data compiled from the Stanford Research Institute (SRI)

publications and the Energy Information Agency (EIA) of the United States Department

of Energy (DOE). Variables obtained include measures of the presence and size of

specific types of units or equipment that are integrally related to the production of MTBE

or gasoline. The pool of potential entrants was determined by whether a firm had at least

one type of unit necessary for the production of the key raw materials for MTBE

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production. However, the size of these units varies and the presence of other units allows

firms to integrate their productive activities in various ways that may influence their

likelihood to consider making MTBE in their process mix. The variables on unit size for

the Refinery Capacity, Cat Cracker Capacity, Steam Cracker Capacity, Alkylation Unit

Capacity, and Isomerization Units Capacity are not only indicators of specific experience

about such operations, but also of the importance of their balance to produce the desired

product mix. The most efficient relationship for employing these units within a firm

depend not only on technological knowledge of operations, but also on market

knowledge regarding the most valuable product mix given the resources available to the

firm. Significant coefficients on any of these variables would indicate the nature of

relevant knowledge that could condition a firm to move into the production of a new

product such as MTBE.

Another aspect of relevant knowledge that is important to potential entrants into

MTBE production is the increasing presence of environmental concerns. During the

growth phase of this market, MTBE was considered to be an environmentally friendly

product, because its use in gasoline contributed to cleaner-burning fuels and reduced

emissions. However, evidence later developed that MTBE was contaminating water

supplies around service stations led to the conclusion the MTBE was actually an

environmental hazard. Because of the negative aspect of MTBE use and the polluting

nature of petroleum refining and petrochemical industries, data on the environment

practices of these firms would be valuable. Data collected by the EPA and made

available to the public under the �Right-to-Know� statutes includes releases of toxic

compounds to the environment known as the Toxic Release Inventory (TRI). TRI data

were collected for all of the firms in the potential entrant pool for MTBE on a plant-by-

plant basis, and then compiled for the firm as a whole.

The release data can be interpreted as representative of the level of scrutiny that a

firm might receive from the EPA and also as an indicator of the potential for future legal

liability. An important aspect of a firm�s relevant knowledge is related to the extent of

releases. First, firms that produce hazardous emissions have to manage them well both

from the standpoint of technology about disposal and from the standpoint of dealing with

public opinion and legal risk. Second, from the perspective of technological efficiency, a

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refinery or chemical plant takes in raw materials (primarily oil, in terms of mass) and

converts it to a mix of useful products. Any mass that is emitted can be viewed as a

missed opportunity to convert organic chemical mass into a useful product rather than

waste. The efficiency perspective is predicated on the incredible reversibility of organic

chemical reactions and is determined by the technological capabilities of the firm and its

ability to manage the interrelationship among its materials and unit operations.

Given this perspective, measures of TRI emissions can be examined for their

significance on entry in MTBE. A negative and significant coefficient on any of the

release variables could be interpreted as evidence that a lower environmental profile

and/or more technological capabilities to reduce emissions and manage product mix is an

important factor in the entry into new products in this industry. A positive coefficient

would seem to indicate that firms with higher emissions levels, and perhaps little regard

for environmental impact, are the most likely entrants. Perhaps the costs of the emissions

are not sufficiently internalized by the firm to affect its behavior.

Firm Efficiency

An important stylized result about entry is that high rates of entry are associated

with high innovation rates and with increases in efficiency (Geroski, 1995, p 431). To

test whether or not the findings hold true in the market for MTBE, we can look at a

number of variables that would serve as measures of firm efficiency. Some measures of

firm efficiency that are available in my dataset include Sales per Employee, Sales per

$Asset Value, Return on Assets, Profit Margins, and TRI emissions per $Sales. Positive

and significant coefficients on these measures of efficiency would be evidence that more

efficient firms are more likely to enter. Because the structure of this industry is generally

regarded as oligopolistic, it would also be interesting to ask if this efficiency stems from

market power of the relatively small number of large firms populating the industry or if it

results from the lower costs of production from scale or scope economies and/or from

innovation of the firms relative to the marginal producers. Thinking about the question

regarding market power or reduced costs in conjunction with the firm size results noted

above, and with the results of the significance of innovation which is discussed below,

could give us some clues about the nature of entry.

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Innovation

High innovation rates are also associated with entry (Geroski, 1995, p 431). In

order to investigate this pattern in the market for MTBE measures of innovation are

included in the dataset. Three patent variables were collected for each parent firm from

the U.S. Patent Office. First, the total number of patents applied for in any given year by

the parent firm is a measure of overall innovativeness. Second, the number of patents

applied for in any given year regarding the use of various fuel additives including MTBE

measures more narrowly the types of innovation that a firm may be involved in from an

R&D perspective. Third, the number of patents applied for involving the manufacture or

production of ether and additive compounds measures all innovativeness related to

MTBE manufacture and use as an additive.

The patent variables give different measures of innovation and the focus of

innovative R&D on relevant technology. Significant results on any of these variables

would indicate that innovativeness is also an important condition of entry in this market

and that the focus or nature of innovative may play a role as well.

Other Factors

Some other variables that can be included in a model of entry in MTBE include

such variables as Retained Earnings or Dividends. If financing the growth and expansion

of new products and units were of importance, one might find a significant result on one

of these measures. However, with highly efficient capital markets today and high values

of assets owned by these firms, one would not expect to find significant results here. The

dataset also includes measures of firm income and some measures of expenses that are

being examined for potential use in the entry model.

IV. EMPIRICAL ANALYSIS OF ENTRY INTO THE MARKET FOR MTBE

As suggested above, a list of potential entrants into the market for MTBE was

constructed from SRI reports with the key criteria being that the firm had to have access

to specific assets that could provide them with the necessary raw materials for MTBE

13

manufacture. For each of the firms in the list of potential entrants, the financial

performance data, essential equipment data, patent data, and environmental data were

compiled into a unique dataset for analysis (see Data Appendix). The pool of potential

entrants includes 101 firms (see Appendix 2). Some of the general characteristics of the

firms in the pool are described below and are illustrated in figures attached after the

appendices.

Of the 101 potential entrants, 60 possessed refineries with cat cracking capability,

29 possessed steam-cracking capacity or propylene oxide manufacturing, and 19

manufactured methanol, these units being the sources of key raw materials for MTBE

production. Ten firms possessed 2 or more of these sources and 4 firms actually did not

possess any, but entered into MTBE production as a joint venture partners in a stand-

alone technology plant. The stand-alone technology plants provide the one anomaly that

prevents making the claim of a completely exhausted list of potential entrants.

The general pattern of entry and the growth of the market are illustrated in figures

2 and 3. Figure 3 is simplified to only include entry, cumulative entry, and exit. An

interesting pattern in entry is that the most firms entered in the years 1988 and 1992

which happen to correspond to two important regulatory changes. 1988 was the year

following the easing of restrictions on MTBE in gasoline by the EPA as described earlier.

1992 was the first year that oxygenated additives for cleaning-burning gasoline were

mandatory for certain nonattainment zones3 under the Clean Air Act Amendments of

1990.

Thirty-six firms entered MTBE production from the pool of 101 potential entrants

between 1987 and 1997. Figure 4 shows that the larger firms (greater than the median

asset value) constituted a larger number of the entrants. Twenty petroleum refining firms

entered by integrating with their cat cracking technology. Ten firms entered from

petrochemical production using their steam cracking or TBA capacity. And finally, 6

entered by way of the stand-alone technology. Figure 5 shows the percent of firms in

each technology type and how the entrants compare to the non-entrants. During the 11-

3 Nonattainment zones are designated by the EPA and are defined as areas that are not in compliance for the maximum allowable concentrations for six primary air pollutants. They are primarily limited to the major metropolitan cities and several surrounding counties such as around Los Angeles, Houston, and most of the counties along the Upper Eastern Seaboard from Boston, MA to Norfolk, VA.

14

year period of the dataset, 4 exits occurred, 1 by shutdown and 3 from being sold. Also,

of the 101 potential entrants, the 12 privately held firms are excluded from the analysis

because no financial performance data are available for them.

Estimation of the Probability of Entry

The first analysis is to estimate the probability of entry anytime during 1987 and

1997 period. The probability of entry is estimated using the logit model specification

described in Equation (1). The variables selected for the model include a measure of

productivity (Sales per Employee), firm size or general experience (Total Assets),

innovativeness (Total Number of Patents generated), environmental performance (Total

Releases of TRI compounds), and dummy variables for the presence of relevant

experience in the form of FCC or SC units. The results of that estimation are given in

TABLE 1.

The results of the first model show that the productivity of the firm and the

presence of the cat cracking technology significantly contribute to the likelihood that the

firm will enter into the production of MTBE. Unlike other studies, the characteristics of

productivity and cat cracking technology that are identified as significant are not simply

factors that make entrants different from incumbents or factors that affect survival or

TABLE 1 LOGIT MODEL for MTBE Entry

VARIABLE COEFFICIENT ESTIMATE (STANDARD ERROR)

Sales per Employee 0.001990** (0.0009189) Total Assets 0.000017 (0.000026) Total Patents -0.000208 (0.004514) Total TRI Releases -2.50e-06 (6.98e-06) FCC Technology Dummy 2.897424** (0.7962574) SC Technology Dummy 1.694879* (0.9591074) Constant -3.703723** (0.9308653)

Log Likelihood -27.019099 χ2 35.41 Pseudo-R2 0.3959 N 68

* p<.10, ** p<.05

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growth of entering firms. I can appropriately say that productivity and the cat cracking

technology differ significantly for entrants as opposed to non-entrants that have the basic

capabilities to produce MTBE. These characteristics also appear to be quite robust to

various changes in the specification of the model, but more extensive checks have been

left for further work.

The variables in this specification of the model were chosen according to the

criteria outlined in the previous section and, therefore, more can be said about what is and

is not significant in this model. First, with productivity controlled for, firm size does not

matter. Total Assets has often been used as a measure of firm size and a proxy for

general experience. (Klepper, 1999) It has been reported to be important in some studies

about entry, survival, growth, and R&D efforts. The pool of potential entrants in this

case is populated with several very large firms some of which entered (Exxon) but others

did not (GE). It appears that other specific factors regarding relevant experience are

more important to entry and will be examined further.

The significance of the dummy variable for the specific technology of cat

cracking suggest that relevant experience be examined by another specification of the

model. In the new estimation results shown in TABLE 2, the dummy for FCC was

TABLE 2 LOGIT MODEL for MTBE Entry including Relevant Experience

VARIABLE COEFFICIENT ESTIMATE (STANDARD ERROR)

Sales per Employee 0.003502** (0.001789) Total Assets -0.000012 (0.000050) Total Patents -0.014218 (0.016820) Total TRI Releases -1.39e-06 (1.94e-06) Refinery Capacity 0.000044* (0.000026) Cat Cracker Capacity 0.000312** (0.000137) Alkylation Capacity -0.000603** (0.000288) Steam Cracker Capacity 0.002895* (0.001520) Methanol Capacity -0.007011 (0.014269) Constant -4.343081** (1.374824)

Log Likelihood -11.3915 χ2 66.66 Pseudo-R2 0.7453 N 68

* p<.10, ** p<.05

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replaced with variables for the actual size of the FCC and related plant and equipment in

the form of the refinery capacity and size of the alkylation unit that is typically associated

with cat cracking units. The results indicate that the productivity of the firm is still

important. The significance level has dropped slightly, but it is still within a 10%

confidence interval and the magnitude of the coefficient is actually higher.

The importance of the findings can be interpreted within the framework described

for �relevant� experience. FCC units are specifically integrated within refineries to

enhance the production of components useful in the production of gasoline. The firm�s

possession of an FCC is almost completely predicated on the production, distribution, and

marketing of gasoline. The size of the FCC unit is therefore a proxy for the relative

experience in gasoline markets. Since the only significant use of MTBE is as an additive

in gasoline production, and firms with FCC�s make gasoline, then one might expect these

firms to be more likely to enter into MTBE production.

The FCC is a unit that is designed to produce a greater supply of components

useful for gasoline, of which isobutylene is one. Within a refinery the primary alternative

use for isobutylene is as a feedstock for the alkylation unit (hereafter referred to as �alky�

unit), which is also a producer of useful gasoline components. Among gasoline

producers that possess FCC and alky units, firms with larger alky units are significantly

less likely to enter MTBE manufacture even though the size of the alky unit also reflects

a measure relevant experience in gasoline markets. The lower likelihood of entry based

the alky unit size then should be interpreted as a higher opportunity cost of the

isobutylene component, which if used for making MTBE could result in a shortfall in

feed for the alky unit. If the opportunity cost in terms of a feed for the firm�s previously

existing alky unit is high enough, then one would expect these firms not to enter MTBE

manufacture and instead to purchase it as necessary for gasoline production. The

combination of significance on the relevant experience factors might be taken together as

evidence of the importance of the economies of scope necessary for managing the multi-

component and multi-product market environment for gasoline. As noted earlier, the

FCC-fed MTBE plants tend to be the smallest average size and are designed to take

advantage of a smaller available feed supply for MTBE production without adversely

affecting other units of gasoline production. Conversely, the MTBE units integrated in

17

petrochemical plants using steam cracker feed tend to be slightly larger accounting for

the fact that steam crackers yield higher percentages of isobutylene than do cat crackers,

but the petrochemical plants are not gasoline producers and there is no internal market for

the MTBE. Also, the TBA-fed and stand-alone MTBE plants are generally 3 to 4 times

larger and are also not associated with plants that produce gasoline. These types of

technologies for producing MTBE can then be thought of as taking advantage of larger

economies of scale in manufacturing MTBE, but have no use internally for the additive

and therefore sell it to gasoline producers. In fact, when a variable is included for the

size of the steam cracking unit in a petrochemical plant, it is significant at the 10% level

indicating that this relevant experience for a particular technology is somewhat important

as well.

The specification of the entry model in both TABLES 1 and 2 indicate that

innovativeness and environmental factors do not matter. Innovativeness is generally

thought to be important in terms of the incumbent firms� ability to survive changes in

market conditions and changing product demands. In terms of entry, if incumbent firms

rest on their laurels, then new entrants would be expected to bring innovations into the

product and manufacturing mix. (Jovanovic and Nyarko, 1996) The lack of significance

of the variable measuring innovativeness could be interpreted in two ways. In this model

the measure of innovativeness is the number of all patents issued to each firm.

First, in the context of productivity being significant and innovativeness not being

so, one could argue that productivity is picking up the important changes that are taking

place within the firm to adapt. In other words, productivity is where real innovativeness

matters and in this context innovative would include any type of innovation including

marketing techniques, trade secrets, etc. and not just patents. Patents could then be said

to be a measure of inventiveness, but not innovation where the ideas are made functional

in the marketplace. If patents do represent innovativeness then the productivity of the

firm captures the important aspects of these innovations and one cannot determine which

types of innovativeness are most affecting productivity.

Another way to think about the relationship between productivity and

innovativeness with respect to entry has to do with the distinction between innovative

entry and imitative entry. As Geroski (1991, pp 250-1) reminds us, entry is common but

18

real innovation is not, at least by entrants. His findings alone would lead one to conclude

that innovativeness is not likely to matter for entry, even though it may prove to be very

important to the survival and growth of a firm within an industry. A great deal of entry is

imitative. A new product is introduced to the market such as MTBE and it has a variety

of more or less suitable substitutes. Some variety of substitute production technologies is

available to make it, so the newer technologies are licensed quickly. Therefore entry is

basically imitative, and based on integration with product lines, production technologies,

and other firm capabilities within the marketplace. One would not expect entry to be

based on innovativeness on a wide scale. Even though innovative entry may be very

important to the evolution of an industry, it would be expected to be relatively rare when

compared to all possible entrants.

Do environmental factors matter for the probability of entry? At the beginning of

the 1990�s MTBE was considered to be environmentally friendly. It was a gasoline

additive that improved gasoline blends in a variety of ways and made possible the

production of large quantities of �cleaner-burning� fuels. By the end of the 1990�s the

outlook for MTBE had completely reversed. MTBE had been detected in ground water

in areas where reformulated gasoline was most widely used, was listed as a possible

carcinogen, and became known as a huge environmental threat (Miller, 2000). In the

case of MTBE, there was reason to believe that some environmental variables would be

important. The refining and petrochemical industries are heavily regulated and

monitored by the US EPA as well as by state level environmental agencies. Also, MTBE

itself had to have regulatory approval to be added to gasoline, and the 1990 Clean Air Act

Amendments made oxygenates in gasoline mandatory for areas of the country that were

nonattainment areas with respect to the emissions levels established.

For these reasons, data were collected through the EPA from the Toxic Release

Inventory (TRI) on emissions reported for each firm at the plant level and aggregated for

the parent firms. The TRI releases are thought to be measures of two aspects of

environmental factors. One factor is the level of scrutiny from regulatory agencies and

the public that a firm is likely to generate if TRI releases are high. One might expect that

high scrutiny may reduce the likelihood of entry into another chemical product. A

second factor is a measure a technological efficiency. Efficient firms could be expected

19

to generate less TRI releases per unit of input or output and that fact could be significant

in the market for gasoline and gasoline additives. Preliminary evidence using the logit

model is that the TRI releases are not significant determinants of entry. However,

additional tests were run using a model for factors on the hazard of entry and Total TRI

Releases does show significance with regard to hazard rate of entry. This result will be

discussed further below.

Entry Hazards

The measure of firm efficiency or productivity that is included in the model is

generated for the value of a firm�s sales per employee. The productivity of the firm is

positively significant and robust to various specifications of the logit model for the

probability of entry. However, the results reported have been developed using 1987 as

the base year on the likelihood of entry sometime during the 11-year period. Using the

Cox proportional hazards described in Equation (2), it is possible in investigate whether

the same factors also affect the hazard or order of entry. The results of the regression are

reported in TABLE 3.

TABLE 3 HAZARD MODEL for MTBE Entry including Relevant Experience

VARIABLE HAZARD RATIO (STANDARD ERROR)

Sales per Employee 1.000301** (0.000122) Total Assets 0.999997 (0.000012) Total Patents 0.994578 (0.004440) Total TRI Releases 0.999958** (0.000021) Refinery Capacity 0.999998 (2.55e-06) Cat Cracker Capacity 1.000004 (5.48e-06) Alkylation Capacity 1.000064 (0.000041) Steam Cracker Capacity 0.999954 (0.000673) Methanol Capacity 1.003639 (0.002857)

Log Likelihood -104.3150 χ2 44.82 N 85

* p<.10, ** p<.05

20

The significant variables in the hazard model indicate that productivity and the

environmental factor of TRI releases are important for the hazard or risk of entry. A shift

in the hazard function indicates that the more productive firms are also likely to enter

earlier than less productive firms. The significance of the TRI releases implies that firms

with lower reported total releases of TRI compounds are more likely to enter earlier into

MTBE production than firms with higher releases. As discussed above, it is not clear if

the relationship between TRI releases and earlier entry is related to having a lower

regulatory profile or if it is another method of measuring technological efficiency.

One argument can be made in terms of the hazard function results. If higher TRI

releases reduced the probability of entry over the time period, then it is more likely

related to environmental regulatory issues because during the period of time investigated

MTBE became under more and more environmental scrutiny. MTBE was supposed to

help clean the air, but it came known that it polluted the water. In such a case, it might be

likely that only the better performing firms in terms of environmental factors could enter

MTBE production in the face of a growing environmental risk. This argument is

speculative, but perhaps it can form the basis of a hypothesis for additional tests. One

possible way to resolve the interpretation between environmental performance and

technological efficiency is to examine releases per sales dollar or some other combination

that could be better interpreted as an efficiency measure than just total releases. It is

certainly not unexpected that entry into new chemical product markets might be related to

environmental factors and such a relationship will be investigated further in future work.

V. Concluding Remarks

Little is really known about entry because of the problem of selecting the sample

that can be legitimately described as a potential entrant into a particular product, market

segment, or industry. Much of what is known about entry is actually inferred from

studies that look at entrants and incumbents or examine the fate of entrants through the

survival, growth, or failure. Entrants do not come from anywhere, however, so when

reasonable limits can be used to define a set of potential entrants then an opportunity

really exists to study the differences between entrants and non-entrants.

21

This study is designed to investigate entrants compared to non-entrants in the

market for MTBE where the availability of rather unique raw materials is used to create a

dataset of a well-defined pool of potential entrants. The method of analysis follows from

previous studies, but extends the literature by examining a complete set of firms with the

potential for entry rather than being limited to an important class of potential entrants.

The investigation is conducted by estimating the probability of entry from a set of

variables selected to represent the factors that have most often been reported as

significant to entry, survival, and industry evolution. In addition other variables are

included in the model that are uniquely important to the production of an environmental

product such as MTBE, in particular the release of environmentally hazardous

substances.

Productivity appears to be the most critical difference between entrants and non-

entrants from the pool of potential entrants. Further evidence indicates that relevant

experience and technologies are also important and, interestingly, general measures of

size or experience and innovativeness are not. In other words, previously reported results

have shown that size and innovativeness (patenting) matter. However, when productivity

is controlled for, the size of firms and their patenting do not significantly affect the

probability of entry. These factors may be important to other issues such as survival and

growth, but the evidence here suggests that they should not be considered critical to

entry. Reinforcing the importance of productivity is evidence from estimating a hazard

model that shows that more productive firms are also more likely to enter earlier. And

finally, other studies have shown large firm to be more diverse presumably by entering

more products and markets. But evidence here is that large firms are not more likely to

diversify by entry, more productive firms are. Therefore, more productive firms may

grow and diversify by entry to become large firms.

Relevant experience to the product in question is also expected to be significant to

entry and survival. Within the set of potential entrants there are firms with three types of

technological and market experience. The amount of relevant experience where unit

sizes proxy for this amount is significant as firms appear to take advantage of scope and

scale effects in their entry decisions.

22

Additionally, the release of TRI compounds into the environment is a special case

of relevant experience in the industries of petroleum refining and petrochemical

manufacture. The TRI releases appear to play a significant role in the hazard of entering

MTBE manufacture. Given the unusual regulatory history of this environmental good,

the �environmental� experience of the firms producing MTBE merit continued

investigation.

Now an important set of differences in characteristics can be attributed

specifically to entrants as opposed to non-entrants into a new product market. The

characteristics of entrants can be considered distinctly from other characteristics that have

been attributed to entrants because of their impact on survival and growth.

23

REFERENCES

Anderson, Robert C. and Richard A. Rykowski. "Reformulated Gasoline", in Morgenstern, Richard D., Economic Analyses at EPA: Assessing Regulatory Impact, Washington, D.C.: Resources for the Future, 1997, pp. 391-418. Arora, Ashish and Gambardella, Alfonso. "Evolution of Industry Structure in the Chemical Industry," in A. Arora, R. Landau, and N. Rosenberg, eds., Chemicals and Long-Term Economic Growth: Insights from the Chemical Industry. New York: Wiley, 1998, pp. 379-413. Chang, Elaine. "Octane Improvers," vol. 158A, Process Economics Program, Menlo Park, CA: SRI Consulting, February 1992. Davenport, Robert E. "Gasoline Octane Improvers," Chemical Economics Handbook, Menlo Park, CA: SRI International, January 1999. Geroski, P. A. Market Dynamics and Entry. Cambridge MA: Blackwell, 1991. _____. "What Do We Know About Entry?" International Journal of Industrial Organization, 1995, 13, pp. 421-440. _____. "Thinking Creatively About Markets" International Journal of Industrial Organization, 1998, 16, pp. 677-695. Halsig, C-P.; Gregory, R. and Peacock T. "MTBE and TAME: From Specialty Chemicals to Oil Commodities," in P. H. Ogden, ed., Chemicals in the Oil Industry: Developments and Applications Cambridge, U.K.: The Royal Society of Chemistry, 1991, pp. 311-25. Hertzmark, Donald I. and John Ashworth. "Reformulated Gasoline and U.S. Energy Policy." in Dorian, James P. and Fereidun Fesharaki (eds.), International Issues in Energy Policy, Development, & Economics, Boulder, CO: Westview Press, 1992, pp. 183-205. Jovanovic, Boyan. "Selection and the Evolution of Industry." Econometrica, May 1982, 50(3), pp. 649-670. Jovanovic, Boyan and Glenn M. MacDonald. "The Life Cycle of a Competitive Industry." Journal of Political Economy, April 1994, 102(2), pp. 322-347. Jovanovic, Boyan and Yaw Nyarko. "A Bayesian Learning Model Fitted to a Variety of Empirical Learning Curves." Brookings Papers on Economics Activity, 1995 (1995) pp. 247-299.

24

Jovanovic, Boyan and Yaw Nyarko. "Learning by Doing and the Choice of Technology." Econometrica, November 1996, 64(6), pp. 1299-1310. Klepper, Steven. "Entry, Exit, Growth and Innovation over the Product Life Cycle." American Economic Review, June 1996, 86(3), pp. 562-583. Klepper, Steven and Simons, Kenneth L. "Dominance by Birthright: Entry of Prior Radio Producers and Competitive Ramifications in the U.S. Television Receiver Industry." Working Paper, Carnegie Mellon University, December 1999. Klepper, Steven and Simons, Kenneth L. "The Making of an Oligopoly: Firm Survival and Technological Change in the Evolution of the Tire Industry." Journal of Political Economy, August 2000, 108(4), pp. 728-760. Lieberman, Marvin B. "Market Growth, Economies of Scale, and Plant Size in the Chemical Processing Industries." Journal of Industrial Economics, December 1987, 36(2), pp. 175-191. Lucas, Robert E. "Making a Miracle." Econometrica, March 1993, 61(2), pp. 251-272. McKay, Daniel J. "Reformulated Gasoline: A Brief History, a Bright Future." in Dorian, James P. and Fereidun Fesharaki (eds.), International Issues in Energy Policy, Development, & Economics, Boulder, CO: Westview Press, 1992, pp. 207-219. Miller, K. Dexter. "MTBE Faces an Uncertain Future." Oil and Gas Journal, July 10, 2000, 98(28), pp. 52-55. Mitchell, Matthew F. "The Scope and Organization of Production: Firm Dynamics over the Learning Curve." RAND Journal of Economics, Spring 2000, 31(1), pp. 180-205. Nelson, Richard. "Why Do Firms Differ, and How Does It Matter," in The Sources of Economic Growth. Cambridge, MA: Harvard University Press, 1996, pp. 100-19. Panzar, John C. and Robert D. Willig. "Economies of Scale in Multi-Output Production." Quarterly Journal of Economics, August 1977, 91(3), pp. 481-493. Schmalensee, Richard. "Do Markets Differ Much?" American Economic Review, June 1985, 75(3), pp. 341-351. Young, Alwyn. "Invention and Bounded Learning by Doing." Journal of Political Economy, June 1993, 101(3), pp. 443-472.

25

APPENDIX 1―DATA SOURCE APPENDIX

VARIABLE 1987 mean

1987 std. dev.

1987-1997 mean

1987-1997 std. dev. SOURCE

Parent Company CW Firm Name SRI Private Firm 0.1188 0.325 .1191 .324 CW Parent's DUNS# TRI # Employees (thousands) 31.073 50.323 25.845 42.002 CS Sales (net of discounts, etc.) 12,342 21,602 14,638 25,653 CS Assets Total 12,518 19,136 15,979 31,092 CS Total Releases 84,676 546,889 15,333 167,436 TRI Alkylation Unit Capacity 11,953 23,869 11,912 23,228 EIA Steam Cracking Capacity 164.12 400.11 210.9 517.4 SRI Cat Cracking Capacity 56,073 109,492 56,093 105,409 EIA MeOH Capacity 19.76 59.01 22.68 64.70 SRI MTBE Capacity 753 3,638 1,839 5,121 SRI Refinery Operating Capacity 151,811 283,488 151,986 275,728 EIA # of MTBE units 0.109 0.372 .354 .736 SRI All Patents 53.1 142.6 58.0 182.4 USPTO

DATA SOURCES

Chemical Week (CW) Chemical Week. 138(1) to 159(48), New York, NY: Chemical Week Associates, Jan. 1/8, 1986-Dec. 24/31, 1997 Standard and Poor’s Compustat (CS) Standard and Poor�s Compustat PC Plus. Englewood, CO: McGraw-Hill Companies, 1997. Stanford Research Institute (SRI) Chang, Elaine. "Octane Improvers," vol# 158A, Process Economics Program, Menlo Park, CA: SRI Consulting, February 1992. Davenport, Robert E. "Gasoline Octane Improvers," Chemical Economics Handbook, Menlo Park, CA: SRI International, January, 1999. Heinen, Russell and Ed Gartner. Isobutylene and Ethylene Producers and Capacities, World Petrochemicals Program, Houston, TX: SRI Consulting, unpublished, Jan 2001. Toxic Release Inventory (TRI) Right-To-Know Network, http://www.rtk.net/, Jul 2001. RTK NET Environmental Databases, http://d1.rtknet.org/tri/, Jul 2001. US Energy Information Agency (EIA) US Energy Information Agency, Official Energy Statistics from the US Government, http://www.eia.doe.gov/, Sep 2000. US Patent and Trademark Office (USPTO) US Patent and Trademark Office, http://www.uspto.gov/main/patents.htm, Jun 2001.

26

APPENDIX 2―LIST OF FIRMS IN THE POOL OF POTENTIAL ENTRANTS Firm # Parent Firm Name Entrant Firm # Parent Firm Name Entrant

1 AIR PRODUCTS & CHEMICALS INC 0 52 MILLENNIUM CHEMICALS INC 0 2 AMERADA HESS CORP 1 53 MITCHELL ENERGY & DEV -CL B 1 3 AMERICAN CYANAMID CO 0 54 MITSUBISHI CHEM CORP -ADR 0 4 AMOCO CHEM 1 55 MITSUBISHI CORP -ADR 0 5 AMOCO CORP 1 56 MITSUI & CO LTD -ADR 1 6 ARCO CHEMICAL CO 1 57 MOBIL CORP 1 7 ASHLAND INC 1 58 MURPHY OIL CORP 0 8 ATLANTIC RICHFIELD CO 1 59 OCCIDENTAL PETROLEUM CORP 1 9 BARRETT RESOURCES CORP 0 60 OLIN CORP 0

10 BERRY PETROLEUM -CL A 0 61 PACIFIC RESOURCES INC 0 11 BORDEN CHEM&PLAST -LP COM 0 62 PENNZOIL CO 0 12 BRITISH PETROLEUM PLC -ADR 0 63 PETRO-HUNT GROUP 0 13 CALUMET INDUSTRIES INC 0 64 PETROLEOS DE VENEZUELA SA 1 14 CASTLE ENERGY CORP 0 65 PETROLITE CORP 0 15 CENEX HARVEST STATES CORP 0 66 PHILLIPS PETROLEUM CO 1 16 CHEMOIL REFINING 0 67 POWERINE OIL CO 0 17 CHEVRON CORP 1 68 QUAKER CHEMICAL 0 18 CLARK REFINING & MARKETING 0 69 QUAKER STATE CORP 0 19 COASTAL CORP 1 70 QUANTUM CHEMICAL CORP 0 20 CONOCO INC 1 71 REXENE CORP 0 21 CROWN CENTRAL PETROL -CL B 1 72 ROYAL DUTCH PET -NY REG 0 22 DIAMOND SHAMROCK INC 1 73 ROYAL DUTCH/SHELL GRP COMB 0 23 DOW CHEMICAL 0 74 SALOMON-PHIBRO INC 1 24 DU PONT (E I) DE NEMOURS 0 75 SHELL OIL CO 1 25 EASTMAN CHEMICAL CO 0 76 SINCLAIR OIL CO 0 26 EL PASO REFINERY -LP 0 77 SOUTHLAND CORP (CITGO) 1 27 ENRON CORP 0 78 SOUTHLAND OIL 0 28 ENRON OIL & GAS 1 79 STAR ENTERPRISE 1 29 ENTERPRISE PRODUCTS PLC -ADR 1 80 STERLING CHEMICALS HLDGS INC 0 30 EXXON CORP 1 81 SUN CO INC 1 31 FARMLAND INDUSTRIES INC 0 82 TENNECO INC-PRE FASB 0 32 FINA INC -CL A 1 83 TERRA INDUSTRIES INC 0 33 FLYING J CORP 0 84 TESORO PETROLEUM CORP 0 34 FMC CORP 0 85 TEXACO INC 1 35 FORMOSA CHEMICALS 0 86 TEXAS PETROCHEMICAL HLDGS 1 36 GENERAL ELECTRIC CO 0 87 TOSCO CORP 1 37 GEORGIA GULF CORP 0 88 TOTAL PETROLEUM OF N AMERICA 0 38 GIANT INDUSTRIES INC 0 89 ULTRAMAR DIAMOND SHAMROCK 1 39 GOODRICH (B F) CO 0 90 UNION CARBIDE CORP 0 40 HERMES CONSOLIDATED 0 91 UNION TEXAS PETRO HLDGS INC 0 41 HOECHST CELANESE CORP 0 92 UNITED REFINING 0 42 HOLLY CORP 0 93 UNOCAL CORP 0 43 HUNTSMAN CHEMICAL 1 94 USX CORP-CONSOLIDATED 0 44 HUNTWAY PARTNERS -LP 0 95 USX-MARATHON GROUP 1 45 KERR-MCGEE CORP 0 96 USX-U S STEEL GROUP 0 46 KOCH INDUSTRIES 1 97 VALERO ENERGY CORP 1 47 LUBRIZOL CORP 0 98 WAINOCO OIL CORP 0 48 LYONDELL PETROCHEMICAL 1 99 WESTLAKE GROUP 0 49 EQUISTAR 1 100 WILLIAMS COS INC 0 50 MAPCO INC 0 101 WITCO CORP 0 51 METHANEX CORP 0

27

Entry, Units, & Capacity of MTBE Production

0

10

20

30

40

50

60

82 84 86 88 90 92 94 96 98

Year

Num

ber o

f Firm

s/U

nits

newentr totentr totexit units mtbe/10000

FIGURE 2

Entry into MTBE Production

0

5

10

15

20

25

30

35

40

82 84 86 88 90 92 94 96 98

Year

Num

ber o

f Firm

s (~

% o

f Firm

s)

newentr totentr totexit

FIGURE 3

28

Cumulative Entry by Firm Size

0

5

10

15

20

25

30

35

40

82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97

Year

Num

ber o

f Firm

s

cumlarge cumsmall cumpriv

FIGURE 4

Entrants by Technology

0.0

20.0

40.0

60.0

80.0

100.0

82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97

Year

% o

f Firm

s

%tech1 %tech2 %tech3

All

Non

Entrants, All Firms, and Non-Entrants by Technology Type FIGURE 5