Environmental Accidents and Industry Structure

Transcription

1 Envronmental Accdents and Industry Structure by Chrstopher S. Decker Mark E. Wohar Department of Economcs College of Busness Admnstraton Unversty of Nebraska at Omaha Omaha, NE February 18, 2005

2 Envronmental Accdents and Industry Structure Abstract Ths paper nvestgates how ndustry concentraton affects the potental for and frequency of envronmental accdents. We develop a theoretcal model and employ probt and count estmaton procedures for annual ndustry data for the years Whle controllng for other relevant nformaton, we fnd that greater competton reduces both the probablty and frequency of envronmental accdents. Ths result obtans rrespectve of whether concentraton s measured by the Herfndahl-Hershman Index, the eght-frm concentraton rato, or the number of frms n an ndustry. We also fnd that as frms become more complant there s a much lower lkelhood that an envronmental accdent wll occur. In addton, we fnd that the number of nspectons conducted n the year pror to an envronmental accdent has no sgnfcant effect on the lkelhood that at least one accdent occurred durng our sample perod. Our results suggest that polces that foster competton may perform better than perodc envronmental nspectons at fosterng fewer envronmental accdents. Furthermore, there may be unntended consequences to levyng envronmental taxes on the offendng pollutng frm. To the extent that such polces may result n ext from an ndustry leadng to hgher level of ndustry concentraton could result n a hgher lkelhood or frequency of accdents. 1

3 1. Introducton Accordng to the Unted States Envronmental Protecton Agency s (US EPA) Accdental Release Informaton Program Database (ARIP), between 1990 and 1999, there were 9,538 accdental chemcal releases nvolvng over 3,000 personal njures, over 700 hosptalzatons, and nearly 30 deaths. 1 Accdental toxc releases nto the ar, water and land amounted to 37 mllon pounds and, at least accordng to the data n ARIP, costng releasng facltes a total of roughly $204 mllon dollars n remedaton. 2 Whle most of these accdents occurred n certan manufacturng ndustres that utlze a number of chemcals as producton nputs, such as n the chemcal manufacturng (Standard Industral Classfcaton (SIC) 28), petroleum refnng (SIC 29), pulp and paper (SIC 26), and food processng ndustry (SIC 20), a number of accdents occurred n other manufacturng and non-manufacturng ndustres such as the ron and steel, transportaton, and the electrc utltes ndustres. 3 Hence, the data suggests that envronmental accdents are a possblty n a varety of dfferent markets, although to varyng degrees. The purpose of ths paper s to determne whether or not the potental for, and frequency of envronmental accdents are senstve to ndustry structure. There s a lterature that has looked at envronmental accdents from an envronmental justce perspectve. Dereznsk, Lacy, and Stretesky (2003), for nstance, nvestgates the 1 Ths envronmental accdent data can be obtaned at the US EPA s Accdental Release Informaton Program (ARIP) web page Whle ths database does contan a feld ndcatng the total cost of the accdent, there seems to be some dscreton on the part of those completng the survey as to whether or not ths feld s flled n. 2 Whle the ARIP database does contan a feld ndcatng the total cost of the accdent, there seems to be some dscreton on the part of those completng the survey as to whether or not ths feld s flled n. Therefore, ths cost fgure mght well underestmate the true cost borne by accdental releasers. 3 Due to data lmtatons regardng other varables used n the analyss that follows, non-manufacturng ndustres are excluded from the analyss. 2

4 locaton of ARIP recorded accdents and fnd that acute health rsks assocated wth these accdents s greater when they occur n lower-ncome census blocks. There s also a substantal emprcal lterature that has attempted to measure the mpact of envronmental varables on company valuaton. Perhaps two of the most well known envronmental dsasters were the 1984 Unon Carbde chemcal accdent n Bhopal Inda and the 1989 Exxon Valdez ol tanker groundng. The methyl socyanate leak n Bhopal klled or njured thousands of local resdents and ultmately cost Unon Carbde $470 mllon n damages pad to njured partes, at least another $100 mllon n legal fees, as well as costs assocated wth dramatc corporate restructurng (Goldsmth, 1996). Smlarly, Mansur, Cochran, and Phllps (1991) report substantal losses n Exxon s equty returns as a result of the Exxon Valdez groundng, although nterestngly, found lttle losses n equty n other major ol transportng and processng companes. In an nvestgaton of the relatonshp between hazardous waste lawsuts and stockholder returns, Muoghalu, Robnson, and Glascock (1990) use event study technques and fnd that frm s stockholders suffer on average a 1.2 percent loss n market value (about $33 mllon) when a sut s fled aganst a frm for volaton of sold waste management laws. Konar and Cohen (2001) show that, ceters parbus, a company s envronmental performance s nversely related to that frm s ntangble asset value. They fnd that a 10 percent decrease n a frm s toxc chemcal releases can result n a $34 mllon ncrease market value. The emprcal lnk between envronmental performance and ndustry structure appears less well researched. 4 Farber and Martn (1986) nvestgate both theoretcally and emprcally the lnk between polluton abatement expendtures and market structure. 4 However, n Carraro, Katsoulacos, and Xepapadeas (1996), a seres of theoretcal papers nvestgate the relatonshp between envronmental polcy (taxes, standards, ncentve structures) and market structure. 3

5 Although ther theoretcal model returns an ambguous relatonshp between polluton abatement expendtures and the number of competng frms, they suggest that the effect s most lkely to be negatve snce fewer compettors results n larger per-frm producton, larger per-frm profts, and therefore greater ablty and ncentve to control polluton releases. They also present emprcal evdence suggestng that, ceters parbus, larger perfrm operatng and captal polluton abatement expendtures are assocated wth hgher ndustry concentraton (as measured by the four-frm concentraton rato). Although mpled, hgher polluton control expendtures do not necessarly mply superor polluton control performance or fewer envronmental dsasters. Moreover, other measures of envronmental performance, such as nnovaton efforts, suggest a dfferent relatonshp. One mght expect that, n the Schumpeteran tradton, that a less compettve envronment mght, ceters parbus, reduce nnovaton ncentves. Indeed, Brunnermeer and Cohen (2003) recently demonstrated that frms competng n more concentrated ndustres record fewer envronmental patents. The debate surroundng the lnk between ndustry structure and frm behavor toward product and process safety ssues s far from settled. As a case example, consder the deregulaton of the arlne ndustry n Some argued that the benefts of deregulaton (lower fares prompted by entry nto the ndustry) would be offset by reductons n safety as ncreases n the number of flghts could lead to ncreases n ar congeston and arplane accdents. In addton, aggressve competton and tghter proft margns would n turn prompt arlnes to cut mantenance and equpment upgrade expendtures to unsafe levels. However, accordng to data presented n Kaplan (1986) and Walters (1993), fatal arlne accdents were actually lower after deregulaton. 4

6 Accordng to Kaplan (1986), between 1975 and 1978, there were fatal arlne accdents per 100,000 departures. Between 1979 and 1984, that rate fell to Whle t s dffcult to attrbute ths reducton n arlne travel rsk to ncreased competton, many studes have demonstrated arlne dsasters can have a sgnfcant and lastng negatve effect on the fnancal well-beng of the company (see, e.g. Chance and Farrs, 1987, and Borensten and Zmmerman, 1988). When makng decsons regardng accdent avodance, whether t be arlne crashes or envronmental damage avodance, frms balance the expected costs they ncur n the event of an accdent wth the costs of preventng such accdents from happenng. In a compettve envronment, as market shares declne and frms face addtonal pressures to ncrease proft margns through cost reductons, t may be more cost-effectve to take more care to avod accdents f the expected cost of such an accdent s suffcently hgh. In ths paper we address from both a theoretcal and emprcal perspectve, what effect ndustry structure has on the probablty and frequency of envronmental accdents occurrng. As a prevew of our results, we fnd that, when controllng for other relevant nformaton, greater competton reduces both the probablty and frequency of envronmental accdents. Ths result obtans rrespectve of how ndustry competton s measured. The paper s organzed as follows. In secton 2, we present a theoretcal model llustratng the essental elements that Cournot-competng frms mght consder when makng envronmental accdent avodance nvestments. In secton 3, we descrbe the data and the estmatng equaton based on our theoretcal model. In secton 4, we address some relevant econometrc ssues encountered n estmatng the emprcal model. In secton 5, we summarze our prmary fndngs and we conclude wth secton 6. 5

7 2. A Smple Theoretcal Model Consder an ndustry that conssts of N dentcal Cournot compettors facng a lenear ndustry demand curve, P = a bq, where Q s market demand. Snce we assume frms are dentcal, then Q= Nq for =1 N, where q equals ndvdual frm s output. For smplcty, assume zero fxed and margnal producton costs. However, producton does generate dangerous byproducts that prove harmful to the surroundng natural envronment f accdentally released. If such a release occurs and s ether dscovered by or reported to regulatory authortes, the frm s held accountable and s subject to penalty and s requred to remedate any damages caused. It s reasonable to assume that a frm can nvest n an effort to lower the probablty of an accdent occurrng. We defne the probablty that, n a gven tme perod, the frm s able to successfully avod a potentally costly envronmental accdent as p [0,1]. Hence, the correspondng probablty of an accdent of occurrng s 1 p. Clearly, the frm would lke to maxmze p. However, dong so s costly. Allow xp ( ) to represent the cost a frm ncurs n an effort to ncrease the probablty of avodng an envronmental accdent wth the followng propertes: x'( p ) > 0, x''( p ) 0, x(0) = 0, x(1) = x. 5 Ths cost we refer to as pre-accdent avodance costs. Consstent wth many exstng models, we assume that the envronmental damages generated as the result of an accdent occurrng, Cq ( ), are ncreasng n output, 5 Ths modelng conventon s not uncommon n the economcs lterature (see, e.g. Nelson and Km, 2001). We assume that the frm can acheve complete accdence avodance at a cost of x. Note, however, that ths cost could be very hgh and ndeed, could n theory approach nfnty. In what follows, however, we assume an nteror soluton such that p (0,1). 6

8 .e. C'( q ) < 0, C"( q ) 0. Agan, f regulatory nsttutons are able to hold the frm accountable for any damages caused, the expected costs to the frm of an envronmental accdent occurrng s EC( p, q ) = (1 p ) C( q ). For smplcty, we assume Cq ( ) = cq, where c s the post-accdent remedaton cost the frm ncurs per unt output. To ensure that nonzero proft maxmzng output levels are chosen by frms n ths ndustry, we make the standard assumpton that demand s suffcently large to warrant producton,.e. a > c. The objectve, of a representatve frm, can be expressed as: q, p [ ] max π = a bq b( N 1) q (1 p ) c q x( p ), (1) where q represents output decsons from all other frms, not. In standard Cournot fashon, each frm smultaneously chooses a level of output and a level of accdent avodance effort to maxmze (1). 6 Assumng nteror solutons results n the followng 2N frst order condtons: a (1 p ) c N 1 q 1 q = 0, for = 1... N, (2) 2b 2 cq x'( p ) = 0, for = 1... N. (3) Equaton (2) s the famlar Cournot expresson that defnes each frm s best response functon n output. Equaton (3) represents each frm s optmal envronmental accdent avodance condton. Each frm wll nvest up to the pont where the beneft assocated 6 The reader wth recognze that the p s are ndependent,.e. the probablty of an envronmental accdent occurrng at frm s ndependent of an accdent occurrng at, say, frm j. Whle a reasonable assumpton, t should be ponted out that, to the extent that frms strategcally manage polluton control, that s, wth deference to what ther compettors are dong, t s at least possble that the p s are nter-related. See, e.g., Decker and Pope (2004). Wth respect to accdents and accdent-control nvestments specfcally, we are unaware of any emprcal verfcaton of such a correlaton across frms. Ths, however, would be an nterestng avenue for future research. 7

9 wth avodng an envronmental accdent, cq, equal the margnal cost of avodng such an accdent, x'( p ). Snce frms are dentcal, (2) can be expressed as q a (1 p ) c =. bn ( + 1) (4) Substtutng (4) nto (3) and re-arrangng yelds frm s equlbrum accdent avodance effort condton: ca ( (1 p) c) = x'( p) bn ( + 1). (5) Equaton (5) llustrates the effect that ndustry structure has on the frm s optmal accdent avodance decsons. The left-hand sde of (5) embodes, n part, the benefts of nvestng n p,.e. avodng c. The rght-hand sde embodes the margnal cost of accdent avodance, nvolvng both x'( p ) and N. Relatve to, say, a monopolst s decson, now the margnal cost of avodance ncludes a type of spll-over cost. Wth ncreased competton, pressures by ndvdual frms to control costs to acheve maxmal market share and proftablty are ncreased. However, whether or not ncreases n p result from ncreases n N depends on the relatve costs nvolved. Dfferentaton of equaton (5) wth respect to p and N yelds dp = x'( p ) b, ''( ) ( + 1) 2 dn c x p b N (6) whch s ambguous n sgn. However, snce the source of the ambguty s n the denomnator of (6), t s clear that the relatonshp between p and N depends on the relatve magntudes of the expected post-accdent remedaton costs (.e. c) relatve to the ncrease n the margnal pre-accdent avodance cost (.e. x''( p )). The key to understandng ths relatonshp, not surprsngly, depends on the mpact ncreased 8

10 competton places on controllng costs, whether those costs are pre-accdent avodance costs or post-accdent remedaton costs. Case 1. If c s suffcently large relatve to x''( p ), then an ncrease n the number of compettors wll prompt frms to ncrease ther potental for avodng an accdent. Or, stated dfferently, an ncrease n competton wll result n fewer envronmental accdents. Wth relatvely large envronmental remedaton costs, ncreased competton places a hgher premum on the part of frms to avod ncurrng post-accdent remedaton costs n an effort to avod excessve loss of market share. Hence dp dn > 0. Case 2. If c s small relatve to x''( p ), then ncreased competton wll result n a hgher probablty of accdents occurrng. Or, an ncrease n competton wll result n more envronmental accdents. Wth relatvely large accdent avodance costs, ncreased competton places a hgher premum on frms to lmt pre-accdent costs n an effort to avod excessve loss of market share. In a sense, frms are more nclned to take ther chances of experencng and beng forced to remedate an envronmental accdent snce the cost of remedaton s relatvely small. Therefore, dp dn < 0 The theoretcal ambguty hghlghts the need for emprcal analyss. Data on xp ( ) s not generally avalable. Although there s some nformaton on the cost of remedatng an envronmental accdent, c, the data s by no means unversally complete. However, there s relable data for the Unted States on both envronmental accdents (frequency, number and sze) and ndustry structure that can be used to ascertan whch costs (remedaton or accdent avodance) are lkely to domnate. In the secton to follow, we attempt to determne the effect that ndustry structure has on the probablty, frequency, and sze of envronmental accdents. 9

11 3. The Emprcal Model and Data The basc emprcal model to be estmated s y = f (ln( INDSTR ),ln( SHIP ),ln( TRI / SHIP ),ln( INS ), t t t t t t 1 ln( COMP ), SIC20, SIC26, SIC28, SIC29, DMY93, DMY94, e ), t 1 t (7) where y t represents one of two dfferent varables we use to measure envronmental accdents. As stated above, the prmary source of envronmental accdent data used as the dependent varable n the emprcal secton of ths study s the US EPA s Accdental Release Informaton Program (ARIP) Database. Whle ths database has been used by many other researchers (see, e.g. Deresnsk, Lacy, and Stretesky, 2003) some further detal on ths database s warranted. Varous US envronmental statutes have authorzed the US EPA to collect and make known to the publc nformaton on the frequency and sze of chemcal release accdents occurrng at US manufacturng plants on an ongong bass. In constructng the ARIP database, the US EPA uses data from ther Emergency Response Notfcaton System (ERNS) database to target certan releasers to provde addtonal nformaton va ther ARIP questonnare. ARIP targets accdental releases at fxed facltes that ultmately generate health and safety problems and envronmental damages off ste. The prmary focus of ths database s on sgnfcant accdental chemcal releases nto varous meda (land, ar, water, ext) that resulted n death, njury, or severe envronmental degradaton. 7 Clearly, then, ARIP does not capture the unverse of accdental releases. It may reasonable to suppose that the applcaton of ARIP data here 7 It should be ponted out that what has been consdered a sgnfcant accdental release has changed over tme. Pror to 1993, the crtera was the quantty of materal released. Snce then, focus has been on off-ste mpact and envronmental damages. To be sure, ths may rase potental statstcal problems. However, as s commonly done n such crcumstances, we nclude yearly dummy varables n part to control for ths change. 10

12 clouds the lnk between the theory and the emprcs snce t s true that our model does not dstngush between sgnfcant and less-sgnfcant accdents. However, the model does not preclude sgnfcant accdents ether. Hence, the basc predctons of the model are stll qute reasonably tested even though the focus n the data s on major accdents. 8. From ARIP then, we aggregated, by year, chemcal release nformaton by fourdgt Standard Industral Classfcaton (SIC). In ths study we consdered the number and amount of total releases rrespectve of where the releases occurred (.e. land, ar or water). 9 The dependent varable y t s measured n two ways. Frst, we created a bnary varable, ACCIDENT_BI, equal to one f at least one chemcal accdent occurred n a partcular ndustry n a gven year, zero otherwse. 10 Equaton (7) was then estmated usng a probt model. Second, we counted the total number of chemcal accdents, called ACCIDENT, whch occurred n a partcular ndustry n a gven year. Equaton (7) was then estmated usng regresson technques applcable to count data. The varable ln(indstr) s a measure of the structure of the ndustry n whch the accdent(s) s (are) occurrng. From the perspectve of the model presented n the prevous secton, the obvous emprcal measure for ln(indstr) would be the number of 8 That sad, t would be a worthy avenue for future research to consder the unverse of data n ERNS. Indeed, the emprcal lnks usng ARIP mght be stronger gven the compettve ncentves mpled n the model to lmt envronmental accdents. Usng the ERNS data may mtgate some of the hypotheszed effects. However, usng ERNS for ths type of exercse s problematc for a couple of reasons. Frst, the US EPA does not track ndustry classfcaton n the ERNS database and felds that lnk plant releases to specfc companes are not always complete. Therefore, lnkng an accdent to a specfc company n a specfc ndustry may lead to sgnfcant data nconsstences. Second, accordng to US EPA s ARIP fact sheet (1998) there are many releases reported n ERNS that are not the result of an accdent. Ths would further cloud the lnk between our model (wth ts focus on accdents and ndustry structure) and emprcal fndngs. 9 To date, nearly all of the US EPA databases stll collect and categorze nformaton by SIC, rather than the US Census Bureau s recently mplemented North Amercan Industry Classfcaton System (NAICS). As dscussed later, ths wll have some ramfcatons for the analyss to follow, mostly n terms of the tme frame over whch we conduct our analyss. 10 The tme subscrpts have been dropped for notatonal convenence. 11

13 producers, N. In equaton (7), we wll frst treat ln(indstr) equal to ln(n) and would expect by condton (6) a lower propensty for, and frequency of, envronmental accdents wth hgher N f the cost of an envronmental accdent, c, were relatvely hgh, and all frms are of equal sze. We would expect the opposte to hold f the cost of an accdent were relatvely low. However, there are other popular measures of ndustry structure, such as the Herfndahl-Hershman Index (HHI) and the eght-frm concentraton rato (CR8). In addton, then, we estmate equaton (7) substtutng the ln(hhi) and ln(cr8) for ln(n). We would expect to see a lower propensty for, and frequency of, envronmental accdents to be assocated wth lower HHI (CR8) f the cost of such an accdent were relatvely hgh snce a lower HHI (CR8) ndcates a more compettve ndustry structure. The data on N, HHI, and CR8 come from the US Census of Manufactures, Bureau of the Census. 11 A number of addtonal control varables are ncluded n equaton (7). The total real ($1996) dollar value of shpments by four-dgt SIC (measurng n $mllons), obtaned from the US Bureau of Economc Analyss at the US Department of Commerce, ln(ship) s ncluded to control for ndustry sze. 12 As equaton (5) suggests, for a suffcently hgh c, ndustres that produce more output, perhaps n response to hgher 11 Ths data can be obtaned at 12 Ths data can be obtaned at The data contans shpments of manufacturng ndustres by four-dgt SIC ndustry, three-dgt SIC ndustry group, and two-dgt SIC major group. Current dollar estmates, chan-weghted quantty ndexes, and chan-weghed prce ndexes are ncluded. We obtaned the four-dgt nomnal shpments data and deflated each seres by the correspondng chan-weghted prce ndex for each ndustry to obtan a real ($1996) value of shpments fgure. 12

14 demand, are lkely to experence a hgher propensty for, and frequency of envronmental accdents. 13 Addtonal control varables are also ncluded as they are lkely to mpact the probablty and frequency of envronmental accdents. The varable ln(tri/ship) measures the volume (measured n pounds) of toxc chemcal releases (TRI) reported by ndustry per $mllon dollars worth of ndustral shpments. The TRI data, compled and made avalable by the US EPA, s part of the US s 1986 Emergency Response and Communty Rght to Know law, requrng that facltes meetng certan sector and sze crtera report releases of over 650 toxc chemcals nto the ar, water, land, underground, or shpped off-ste. We aggregated total TRI releases by four-dgt ndustry classfcaton and year. 14 We expect that hgher pollutng ndustres, as measured by ncreases n TRI emssons per shpment dollar, are more prone to envronmental accdents and therefore expect a postve coeffcent to obtan. Two addtonal control varables are ncluded to test the mpact of montorng and enforcement of envronmental regulatons mght be havng on accdent rates. The varable ln(insp t-1 ), made avalable from the US EPA s Offce of Enforcement and Complance Assurance (OECA), measures the total number of nspectons conducted n a 13 dp c From equaton (5), we see that =, whch s lkely to be negatve for large c. 2 da c x''( p ) b( N + 1) Hence, hgher demand (hgher a) results n a lower probablty of accdent avodance, ceters parbus. 14 We obtaned ths data from the US EPA s onlne query program at For some four-dgt ndustres there were no reported TRI releases. Ths may be because no frms n those sectors had releases n a gven year or t may be because the SIC feld n the database was not flled n by the reportng faclty (we can safely rule out, however, that these zero observatons are because the law requrng TRI reportng does not apply to that sector. TRI reportng s requred of all manufacturng sectors and these are the sectors whch comprse our database). Unfortunately, there s no way to determne f the latter s true to any apprecable degree so we presume that the data s reasonably accurate. For those ndustres that presumably had no TRI releases, when takng the natural log of TRI/SHIP one would loose those observatons. To avod ths, consstent wth Gray and Dely (1996) for nstance, we add one to TRI/SHIP across all ndustres so that n equaton (7) ln(tri/ship+1) replaces ln(tri/ship). 13

15 partcular ndustry by both state and federal authortes for Clean Ar Act, Clean Water Act, and Resource Conservaton and Recovery Act (RCRA sold waste), complance one year pror to the occurrence of an envronmental accdent. 15 One mght expect that greater scrutny by regulators mght nduce greater care by frms and should reduce subsequent accdents. Addtonally, we nclude ln(comp t-1 ) n equaton (7), whch measures overall ndustry complance rates wth CAA, CWA and RCRA, one year pror to an accdent occurrng. 16 We constructed ths varable by takng the dfference between the total number of nspectons conducted and the total number enforcement actons (ENF) leved n an ndustry n a gven year and dvdng that dfference by total nspectons. 17 We 15 Both the nspecton and enforcement data were obtaned va OECA s Integrated Data for Enforcement Analyss (IDEA) database. For detals regardng ths database and access to t, nterested readers are drected to The data we obtaned was aggregated to the three-dgt SIC level for the years 1991 to 2000 and was provded n December, Measurng complance as an aggregate measure across three dfferent envronmental statutes provdes a very complete measure of overall envronmental complance behavor wthn an ndustry. It s possble, for nstance, that some frms n some ndustres have hgher levels of complance for CAA regulatons but very low complance levels for RCRA regulatons. Focusng on just one statute as a measure of complance may be ncomplete from the perspectve of capturng the complance effect on accdent rates. However, as a matter of future research, t may be worth ncludng a measure of ndustral complance for all three statutes separately. The data made avalable to us, unfortunately, dd not have ths statutory breakdown so further costly data collecton would be requred. 17 An enforcement acton s a closed admnstratve or cvl judcal government acton that has been taken aganst a faclty for volatng envronmental laws and that has been entered nto federal data systems. Strctly speakng, ths may not be a completely accurate measure of complance. For nstance, many nspectons that reveal noncomplance may not result n a formal recorded enforcement acton. They may be handled nformally, or a volator may receve a notce of volaton (NOV), whch are not tracked n IDEA. However, two ponts are necessary here. Frst, there are few alternatves to measurng complance and t s reasonable to assume that sgnfcant volatons, ether n magntude or n frequency of volaton, are met wth a formal enforcement acton. Second, one mght be concerned that t s possble for years to pass between nspectons detectng volatons and a resultng enforcement acton. Whle possble, ths s very rare. In most cases, enforcement actons are recorded wthn a year of dscovered noncomplance (the ssue of court hearngs, penalty assessments, and fnal decson can, however, take years or even decades to complete. However, ths s less of a concern for the study conducted here). 14

16 would expect that those ndustres wth better complance records to have fewer subsequent envronmental accdents. 18 In addton, we nclude four broadly defned two-dgt SIC dummy varables (SIC20, SIC26, SIC28, and SIC29) equal to one f the ndustry can be classfed under chemcal manufacturng (SIC 28), petroleum refnng (SIC 29), pulp and paper (SIC 26), and food and kndred products processng (SIC 20), and zero otherwse. These ndustres both utlze and generate as producton byproducts a large volume of toxc chemcals, have recorded frequent envronmental accdents durng the 1990s, and are consdered hgh prorty ndustres for enforcement and complance by the US EPA. We are lkely to see more frequent envronmental accdents n these ndustres. Fnally, two tme dummes, DMY93, and DMY94 are ncluded to control for any tme-related effects that mght be nfluencng accdent rates. The data for ths paper covers the perod 1992 to The major reason for ths s that we are usng ndustry concentraton data from the 1992 Census of Manufacturers (see footnote 4). Wth the US Census Bureau s change to the NAICS classfcaton system and the US EPA s contnued use of the SIC, and gven that the correspondence between the two s not exactly drect, we felt that we should be consstent wth the SIC code. Also, gven the rate of both consoldaton and entry that occurred n many ndustres n the 1990s, and gven that the company count and ndustry concentraton data are avalable only n fve-year ncrements, we felt that t would be far too strong of an 18 Followng common econometrc practce, both INSP and COMP are lagged one year n equaton (7) to mtgate some concerns over potental endogenety. For nstance, t s qute possble that current year nspectons may be hgher because an envronmental accdent occurred earler that same year. Moreover, contemporaneous complance may be mpacted f an accdent occurred that same year. It should be noted, however, that n some cases laggng varables may not solve ssues of potental endogenety. We therefore conducted a Hausman test wth these lagged varables and detected no statstcal support for endogenety. 15

17 assumpton to assume that the 1992 HHI, CR8, and N data would be applcable to envronmental data much past that year. Moreover, snce our nspecton and enforcement data are avalable only back to 1991 and we needed to nclude lagged values of these varables, we were forced to start our analyss wth accdents that occurred no earler than Econometrc Methodology and Issues As evdent n Table 1, the low averages and the preponderance of zeros n the accdents varable hghlght the dscrete nature of the data. Ths suggests usng estmaton technques approprate for count data. However, there are a number of ndustres that dd not experence an envronmental accdent. The excessve number of zero observatons suggests that, n addton to the count data estmaton, t s necessary to conduct a probt or logt analyss where the dependent varable s treated as bnary equal to one f at least one accdent occurred n a partcular ndustry n a gven year, zero otherwse. Ths wll help ease concerns that the results obtaned n the count data procedures are beng drven by a few very accdent-prone ndustres. We employ both a probt estmaton procedure and a count modelng procedure to estmate equaton (7). The probt procedures are qute common and relatvely easy to mplement. Count data estmaton procedures are somewhat less prevalent and, whle farly straghtforward to mplement as well, there s a key feature of such models that we address below. The most basc count data model utlzes the Posson densty functon to perform maxmum lkelhood estmaton of the β coeffcents. Typcally, when 16

18 maxmum lkelhood estmaton s performed on count data usng the Posson (or any other) dstrbuton, the ndependent varables defnng the condtonal mean of the dependent varable enter the log-lkelhood form of the chosen densty functon n the followng way: y = g( y x, β ) = exp( x' β ), (8) where g(.) s the functon defnng the condtonal densty of y, x s a matrx of ndependent varables as defned n (7) and β s a vector of estmated coeffcents. 19 Therefore, t s readly apparent that the resultng estmated coeffcents can be nterpreted as sem-elastctes snce, for a gven ndependent varable : y/ y x = β. (9) Consstent wth much of the exstng lterature, f we wsh to obtan elastctes, the varables defnng x can be ncorporated, as we do n equaton (7), nto the estmaton n ther logarthmc representaton. 20 The Posson densty functon, however, has the defnng characterstc that the condtonal mean of the outcome s equal to the condtonal varance, a characterstc rarely exhbted n appled analyss. It s most often the case that the data s overdspersed; that s, the condtonal varance exceeds the condtonal mean. In fact, nspecton of the sample mean and varance on ACCIDENT n Table 1 suggests that over-dsperson s qute lkely n our data. Falure of the equ-dsperson assumpton nherent n the Posson dstrbuton has consequences for the estmated standard errors on the β coeffcents smlar to those that result when heteroskedastcty s present n 19 See Cameron and Trved (1990) and Greene (1993) for detals regardng such econometrc procedures. 20 The exceptons, of course, are the bnary year and ndustry dummy varables. 17

19 standard lnear regresson models. That s, the estmated varances on the vector of coeffcent estmates wll be based estmators of the true varance of these estmated parameters, thus makng statstcal nference unrelable. 21 Under such a scenaro, the Posson model s usually rejected n favor of the Negatve Bnomal (NB) regresson model whose dstrbutonal propertes allow for over-dsperson. 22 There are several ways of testng for over-dsperson. When performng maxmum lkelhood estmaton wth the NB dstrbuton, n addton to the vector of β coeffcents, an addtonal shape parameter, r, s estmated as well. As Cameron and Traved (1998, p ) dscuss, the sgn of the r coeffcent s postve and statstcally sgnfcant, then we can reject the null hypothess of equ-dsperson comfortably utlze the NB Estmaton Results Both the probt and count model results are presented n Tables 2 and 3 respectvely. The L-R statstc from Table 2 suggests that when tested aganst the restrcted model where all slope coeffcents are assumed to be zero, the probt model as defned by equaton (7) s statstcally sgnfcant. Hence, the emprcal model s provdng some nformaton as to the probablty of an envronmental accdent occurrng. Wth respect to the frequency of envronmental accdents occurrng, we estmated equaton (7) usng the NB dstrbuton for the count model. As we can see from Table 3, smlar to the probt results, the L-R statstc ndcates that the varous ndependent varables 21 In fact, Cameron and Trved (1998) llustrate that the magntude of the standard error bas n a count model that fals to correct for over-dsperson can be much larger than a standard regresson model that fals to correct for heteroskedastcty. 22 It can be shown that the Posson densty functon s a specal case of the NB densty (see Cameron and Trved, 1998). 23 Alternatvely, one can test the approprateness of the NB model by estmatng equaton (7) usng both the Posson and the NB and perform a lkelhood rato test between the restrcted (Posson) and unrestrcted (NB) model. We conduct ths test as well. 18

20 taken together are statstcally sgnfcant determnants of the frequency of envronmental accdents. Moreover, the shape parameter r s shown to have a postve and sgnfcant effect when N and HHI are used to measure market structure. Ths ndcates that the accdent data are most lkely over-dspersed suggestng that the NB dstrbuton s more approprate than the Posson dstrbuton. The coeffcent on r, whle postve, s nsgnfcant when CR8 s used as a measure of ndustry structure. However, the resultng p- value s suggestng that t s near sgnfcant at the 10 percent level. Hence, we are comfortable that the accdent data s best modeled usng the NB. 24 We now turn attenton to the varous ndependent varables effect on envronmental accdents. Table 2 presents the results of our probt estmaton. As stated above, we employ three dfferent measures of concentraton; N, HHI, and CR8. Our results are smlar for all three measures of concentraton. Wth respect to the number of nspectons conducted n the year pror to an envronmental accdent (INS) we fnd that ths varable has no sgnfcant effect on the lkelhood that at least one accdent occurred durng the perod Ths suggests that nspectons have not had ther ntended effect of reducng the lkelhood of an envronmental accdent. The effect of complance (COMP) on the lkelhood of at least one accdent s negatve and sgnfcant, ndcatng that, as theory suggests, the more complant a frm s, the less lkely that an envronmental accdent wll occur. Ths result s robust to the measure of concentraton used. Our proxy for market demand (a n the theoretcal model) s the total (real) value of ndustral shpments (SHIP). Regardless of the measure of 24 We also conducted for each emprcal model a L-R test testng whether or not the restrcted Posson regressons (where the r coeffcent was forced to be zero) resulted n a statstcally sgnfcantly lower maxmzed value of the resultng lkelhood functon when compared to the NB results. The resultng L-R statstcs were when N s used, when HHI s used, and when CR8 s used. These 2 statstcs, dstrbuted χ wth one degree of freedom (one restrcton), are all sgnfcant at one percent or better suggestng that the maxmzed value of the Posson lkelhood functon s sgnfcantly smaller than the NB. Hence, we can reject the null of equ-dsperson. 19

21 concentraton used, we fnd that there s a postve and statstcally sgnfcant correlaton between SHIP and the lkelhood of at least one accdent. The effect of total pounds released of TRI chemcals per mllon dollars worth of shpments (TRI/SHIP) has a postve and sgnfcant coeffcent, ndcatng that the more pollutng s an ndustry, the hgher the lkelhood of at least one accdent occurrng n that ndustry. Ths s also robust to the measure of concentraton employed. Wth respect to the measure of concentraton, we fnd that all three measures used have ther hypotheszed sgn and are statstcally sgnfcant. We fnd that as the number of frms n an ndustry (N) ncreases, the lkelhood that at least one accdent occurrng decreases. Wth respect to the HHI and CR8, we fnd that as these measures of concentraton ncrease, the lkelhood of at least one accdent ncreases. The coeffcents assocated wth the dummy varables for the food and kndred products processng (SIC20), and chemcal manufacturng (SIC28), and petroleum refnng (SIC29) ndustres, are postve and sgnfcant n all three specfcaton, regardless of the measure of concentraton, and ndcate that n these ndustres, there s a hgher propensty of an envronmental accdent relatve to other ndustres. The coeffcent assocated wth the dummy varable for pulp and paper (SIC26) s sgnfcant and postve n the specfcatons usng HHI and CR8 as measures of concentraton but postve and nsgnfcant n the specfcaton employng N as the measure of concentraton. (However, the p-value s 0.11) Gven that these ndustres both utlze and generate a large volume of toxc chemcals as byproducts of ther producton and have recorded a large number of envronmental accdents n the 1990s, these ndustres are consdered hgh-prorty ndustres for enforcement and complance by the US EPA. Our results ndcate that these ndustres have a hgher 20

22 propensty of accdents relatve to other ndustres n our sample. The coeffcents assocated wth the 1993 and 1994 dummy varables are negatve and sgnfcant n all three specfcatons ndcatng that the lkelhood of at least one envronmental accdent has declned n 1993 and 1994 relatve to We next turn to our count estmaton results that are presented n Table 3. These results are largely consstent wth our fndngs n the probt estmaton. However, as dscussed above, the coeffcents assocated wth the ndependent varables n ths estmaton procedure can be nterpreted as elastctes. We begn our dscusson wth the degree of concentraton varable. We fnd that wth respect to the number of frms n an ndustry that f the number of frms n an ndustry ncreases by 10 percent the frequency of occurrence of an envronmental accdent s reduced by 3.4 percent. Usng the HHI as a measure of concentraton, we fnd that when the HHI ncreases by 10 percent the frequency of an accdent ncreases by 3.3 percent. The specfcaton employng the CR8 ndcates that a 10 percent ncrease n ths rato results n a 7.26 percent ncrease n the frequency of an accdent. Thus, consstent wth our probt results, we fnd that the less concentrated the ndustry, the hgher the frequency of an envronmental accdent. Interestngly, unlke the probt model results, the number of nspectons conducted n the year pror to an envronmental accdent has a postve and statstcally sgnfcant effect 25 Indeed, the ARIP data show that the number of envronmental accdents has dropped over the decade of the 1990s. Whle ths drop can be attrbutable to a number of thngs (such as technologcal nnovatons, etc.) t mght also be attrbutable to ndustry structure. Consder two ndustres, food processng (SIC 20), and chemcal manufacturng (SIC 28). As noted above, these are two ndustres that are qute prone to envronmental accdents. As stated earler, drect comparsons between N, HHI, and CR8 publshed usng the recently adopted NAICS and the tradtonal SIC are at best dffcult to make. However, t s nterestng to note that accordng the US Census Bureau, the number of companes n the food manufacturng ndustry (SIC 20) was 16,972 n In 1997 (under NAICS 311) that number ncreased to 21,958. Moreover, n the chemcal manufacturng ndustry (SIC 28), the number of companes lsted by the Census Bureau was 9055 n In 1997 (under NAICS 325), that number was 9,626 (ths data can be obtaned at the followng web page: Hence, despte the fact that many mergers took place durng the 1990s, some ndustres appear to have wtnessed some ncrease n competton. 21

23 on the frequency of envronmental accdents. Indeed, we fnd that gven a 10 percent ncrease n the number of nspectons there s between a 2.56 percent and 3.38 percent ncrease n the frequency of accdents, dependng on the measure of concentraton employed. Ths s a rather counter-ntutve result as one would expect that f montorng s to have a deterrng effect of lax envronmental performance, then greater regulatory scrutny should result n fewer envronmental accdents. These results seem to run counter to ths proposton. Indeed, they mght smply be suggestng that regulators gve more attenton to those sectors more prone to accdents outsde of ther control n the hope that, rather than resultng n fewer accdents, smaller accdents occur and remedaton begns more quckly. Turnng attenton to COMP, we fnd that a 10 percent ncrease n prevous complance rates results n a subsequent decrease n the frequency of accdents between 72 percent and 79 percent, dependng on the measure of concentraton employed. Efforts on the part of frms to mprove complance, then, appear to be havng a benefcal effect of reducng subsequent accdents. Moreover, the degree of complance appears to be the most mportant varable nfluencng the frequency of envronmental accdents. Wth respect to ndustry shpments, we fnd that a 10 percent ncrease n SHIP results n an ncrease n the frequency of accdents between and 8.87 percent. A 10 percent ncrease n the total pounds of TRI chemcals released per mllon dollars worth of product shpments, results n an ncrease n the frequency of accdents between a 4.5 percent and 4.86 percent, dependng on the measure of concentraton. The coeffcents assocated wth the dummy varables for the food and kndred products processng (SIC20), and chemcal manufacturng (SIC28), and petroleum refnng (SIC29) ndustres, are postve and sgnfcant n all three specfcaton, regardless of the 22

24 measure of concentraton. The coeffcent assocated wth the dummy varable for pulp and paper (SIC26) s sgnfcant and postve n the specfcatons usng HHI and CR8 as measures of concentraton but postve and nsgnfcant n the specfcaton employng N as the measure of concentraton, smlar to our probt results. The coeffcent assocated wth SIC20 s the largest, whle the coeffcent assocated wth SIC26 s the smallest. The results suggest that the food and kndred product processng ndustry (SIC20) has about a 2.6 percent hgher frequency of accdents relatve to other ndustres. The chemcal manufacturng (SIC28), and petroleum refnng (SIC29) ndustres have about a 1.6-to-1.7 percent hgher frequency of accdents relatve to other ndustres. The pulp and paper (SIC26) ndustry has about a 0.7 percent hgher frequency of accdents relatve to other ndustres n our sample. The coeffcents assocated wth our tme dummy varables for 1993 and 1994, ndcate that 1993 had about a 1.8 percent lower frequency of accdents relatve to 1992, whle there were about a 3.2 percent lower frequency of accdents n 1994 relatve to Concluson Whle prevous research has nvestgated the lnk between envronmental accdents and locaton, frm equty and frm asset value, etc., there has been lttle emprcal nvestgaton lnkng envronmental performance and ndustry structure. The purpose of ths paper s to address ths by nvestgatng how ndustry concentraton affects the potental for and frequency of envronmental accdents. When makng accdent avodance decsons, frms wll balance the expected postaccdent remedaton costs wth ther margnal pre-accdent avodance costs. In a compettve envronment, as market shares fall and frms face addtonal pressures to 23

25 ncrease proft margns through cost reductons, t may be more cost-effectve to take more care to avod accdents f the expected cost of such an accdent s suffcently hgh. Our theoretcal model lnks these costs wth ndustry structure wth a condtonal outcome obtanng. If post expected post-accdent remedaton costs are large relatve to ncreased margnal pre-accdent avodance costs, then an ncrease n competton wll result n fewer envronmental accdents. If expected post-accdent remedaton costs are small relatve to ncreased margnal pre-accdent avodance costs, then an ncrease n competton wll result n more envronmental accdents. In order to ascertan whch effect mght domnate we nvestgate envronmental accdent ncdence emprcally by nvestgatng the determnants of both the probablty and the frequency of envronmental accdents occurrng usng three dfferent measures of ndustral structure (N, HHI, and CR8). Our man fndng s that, when controllng for other relevant nformaton, greater competton reduces both the probablty and frequency of envronmental accdents. As the number of frms n an ndustry ncreases, the lkelhood that at least one accdent occurrng decreases. Wth respect to the HHI and the CR8, we fnd that as these measures of concentraton ncrease, the lkelhood of at least one accdent ncreases. In addton, we fnd that the number of nspectons conducted n the year pror to an envronmental accdent has no sgnfcant effect on the lkelhood that at least one accdent occurred durng the perod Interestngly, the degree of complance appears to be the most mportant varable nfluencng the frequency of envronmental accdents. The effect of complance on the lkelhood of at least one accdent s found to be negatve and sgnfcant, ndcatng that, as theory suggests, the more complant a frm s, the less lkely 24

26 that an envronmental accdent wll occur. We fnd that there s a postve and statstcally sgnfcant correlaton between our proxy for market demand and the lkelhood of at least one accdent. The effect of total pounds released of chemcals per mllon dollars worth of shpments has a postve and sgnfcant coeffcent, ndcatng that the more pollutng s an ndustry, the hgher the lkelhood of at least one accdent occurrng n that ndustry. Our results may have some polcy mplcatons. Generally speakng, economc regulatons desgned to ncrease producton and lower product prces are often vewed as at odds wth envronmental regulatons desgned to restrct producton and ncrease prces. However, f the envronmental externalty manfests tself n the form of an envronmental accdent, then ncreased market competton may tself be suffcent to lmt the propensty for such occurrences f the cost mposed on frms responsble for envronmental accdents s suffcently hgh. Moreover, f we extend ths lne f reasonng, there may be unntended consequences to levyng Pgovan-type taxes on pollutng frms. Taxng n such a way may drve some frms out of an ndustry leadng to hgher concentraton and n turn resultng n a hgher lkelhood or frequency of accdents. 25

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