Ecological Economics 26 (1998) 31–41



### ANALYSIS


# Can capital markets create incentives for pollution control?

Paul Lanoie a 

### , Benoı ˆt Laplante b, 

### *, Maite  ́ Roy a

a E

 ́ cole des Hautes E  ́ tudes Commerciales
, Montre  ́al
, Que  ́bec
, H 3T 2 A 7
, Canada

b The World Bank
, Policy Research Department
, 1818 H Street
, N

. W
., Washington
, D

. C

. 20433
, USA

Received 21 January 1997; received in revised form 12 April 1997; accepted 16 April 1997

Abstract

It has been observed that upon trading-off the costs and benefits of pollution control, profit-maximizing firms may choose not to invest their resources in pollution abatement since the expected penalty imposed by regulators falls considerably short of the investment cost. Regulators have recently embarked on a deliberate strategy to release information to markets (investors and consumers) regarding firms’ environmental performance in order to enhance incentives for pollution control. In this paper, we analyze the role that capital markets may play to create such incentives. Evidence drawn from American and Canadian studies indicates that capital markets react to the release of information, and that large polluters are affected more significantly by such release than smaller polluters. This result appears to be a function of the regulator’s willingness to undertake strong enforcement actions as well as the possibility for capital markets to rank and compare firms with respect to their environmental performance. © 1998 Elsevier Science B.V. All rights reserved.

Keywords : Capital markets; Pollution control

1. Introduction

A large number of authors have pointed out the lack of appropriate monitoring activities andweak enforcement pertaining to the implementation of environmental regulations. Resources devoted to monitoring activities allow regulators to perform only a limited number of those activities. Moreover, when compliance with the standards is found to be lacking, it is generally acknowledged that fines or penalties (as imposed by regulators and courts) are too low (compared to pollution abatement costs) to act as effective deterrents. For example, Russell (1990) writes: ‘Efforts to monitor regulated behaviour appear to have been inadequate to the task—a very difficult * Corresponding author. Fax: **+** 1 202 5223230.

0921-8009 **/**98 **/** $19.00 © 1998 Elsevier Science B.V. All rights reserved.
PII S0921-8009(97)00057-8P

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. **/** Ecological Economics 26 (1998) 31–41 32

task in many instances—and typical enforcementpractices appear to have been insufficiently rigorous’. The General Accounting Office of the United States has repeatedly reported deficiencies in the monitoring and enforcement activities of the United States Environmental Protection Agency (see GAO, 1987, 1991, 1993, 1994).If indeed the expected penalty for non-compliance, as imposed by environmental regulators and courts were so low, one would have difficulty in explaining the generally high level of compliance with regulation in developed countries, and thevery large variance in the environmental performance of plants in developing countries. Hencethere must be other incentives than those provided by regulators and courts that could explain a polluter’s environmental performance. As such,the potential role and impact of local communities and markets (including consumers and investors) are the object of increasing scrutiny. Afsah et al. (1996) have recently developed a new paradigm for controlling industrial pollution in developing countries which explicitly includes, assources of incentives, local communities and markets. Once the role and potential impact of theseagents are properly acknowledged, once the conditions under which the action of these agents may be effective are identified, fines and penalties imposed by regulators and courts may not appear to be in many circumstances the most appropriate or effective incentives for pollution control. In fact, the USEPA has recently pointed out that‘EPA’s job should grow from primarily the ‘enforcer’ to include greater emphasis on helping citizens make informed choices in their daily lives’ (EPA, 1991).

Hence, while there is a growing concern that fines and penalties imposed on agents out ofcompliance are not severe enough to have a deterrence effect, some authors have challenged theconclusion that polluters therefore have no incentives to comply with environmental standards. In particular, in view of the increasing facility of access and exchange of information, markets (both consumers and investors) bear an increasingamount of attention as to their capacity to generate incentives for pollution control. A significant amount of research and experiments remains to be performed in order to identify the circumstances under which the activities of these agents may be effective, the conditions under which the incentives they generate may substitute for or complement ‘typical enforcement practices’, and the proper role of the regulator to empower these agents. In this paper, our purpose is to discuss and examine how in **6**estors have reacted to therelease of public information regarding the environmental performance of specific plants, as observed and measured by fluctuations on the stockmarket. [A related but different question of interest is whether or not firms with good environmental performance have a higher market valuation than firms with bad environmental performance,other things being equal. On analysis of this nature, see Cormier et al. (1993) and the referencestherein.] While some of this information is revealed through regular coverage by newspapers, italso includes a deliberate use and release of information by regulators regarding the environmental performance of individual plants. In the next section, we discuss the nature of the role of capital markets with respect to providing incentives for pollution control. In Section 3, we briefly describe the methodology typically used to measure the reaction of investors to the release ofenvironmental information. In Section 4, we review the results of the studies that have examined the reaction of investors to the announcement of environmental incidents (such as lawsuits, fines, accidents, etc.), or list of polluters (e.g. Toxics Release Inventory). We also present the results ofa new study that examines the reaction of investors to the publication of lists of firms in British Columbia that either fail to comply with environmental regulations or that are of concern to the Ministry of the Environment of British Columbia. We conclude in Section 5.

2. The role of capital markets

Unanticipated events, or new information may lead capital markets to revise their expectations regarding the profitability of an enterprise. Changes in market values thus provide estimates of changes in the net present value of expectedP

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profits as a result of the event, or new information, relative to the situation where the event would not have occurred or the information would not have been available.It has been argued earlier that penalties imposed by regulators and courts are generally set too low to act as effective deterrents and preventviolation of environmental regulations. For example, in the United States, the EPA pursues civil enforcement actions (as opposed to administrativepenalties or criminal enforcement actions) to respond to the more serious or recalcitrant violators. In FY1990 (fiscal year), civil penalties totalled $61329237 imposed in 1400 cases, for an average penalty of $43806. In FY1991, civilpenalties were $72835251 in 1419 cases; the average penalty increased to $51330. The average penalty imposed under the Clean Water Act has steadily increased since 1986 to reach $405436 in 1991. The maximum civil penalty imposed in FY1990 was $15000000 and $6184220 inFY1991. In Canada, data on the number of prosecutions, convictions, and penalties are sparse and not necessarily comparable across provinces. For example, upon completing an extensive study of the environmental regulation in the Canadian pulp and paper industry, Sinclair (1991) wrote ‘the data available on prosecutions are limited’. Nonetheless, it is interesting to note that penalties in Canada are typically much lower than in the United States. In Alberta, 14 prosecutions were initiated by the Attorney General’s Office in 1990;total fines levied were $37275 against 8 companies. In Ontario, total fines levied increased from $605668 in 1985-1986 to $3633095 in 1992. Giventhe number of convictions, average penalties increased from $9330 to $14250. As noted by Saxe (1989), despite the increase, fines remain low. In British Columbia, 79 convictions were obtainedover the period April 1–September 30, 1992; average fines were then slightly less than $3000 (Environment Policy and Law, March 1993). More recently, over the period October 1 1995 to March 30 1996, total fines of $219200 were levied inBritish Columbia on 116 convictions for an average of less than $2000 (the maximum fine was $20000 and there were 59 fines of $500 or smaller). Criminal actions, in which the regulator typically seeks imprisonment of the defendant(s), remain rare events. Given the small size of those penalties, markets are more likely to revise their estimates of the present value of a firm only to the extent that theinformation leads them to revise their expectations regarding future production costs (including the pollution control costs) or the ability of the firm to generate revenues at the levels originallyexpected. Information about the pollution efficiency of the firm and its environmental performance may act as a signal for its expected long-term profitability: a superior environmental performance may indicate a greater ability toincrease revenues and generate cost savings. Environmental information may play an important signalling role. It is interesting to note that this information may concern solely a given enterprise or may directly or indirectly allow a comparison of the environmental performance of an enterprise to the performance of other firms (such as lists of firms ranked in one way or another by their environmental performance). Information of both natures, which we may call indi**6**idual information and comparati**6**e information respectively, may affect expectations regarding production costs and revenues. However, we would argue that indi**6**id

ual information is more likely to have a relatively larger impact on expectations of production costs (as opposed to revenues), while comparati**6**e information is more likely to have a larger impact onexpectations of revenues (as opposed to production costs). Indeed, in most cases individual information takes the form of an announcement of an event that is generally not favourable to the enterprisesuch as a violation of regulation, the announcement of an incident causing damages to the environment (such as a spill), the announcement of a lawsuit against the enterprise, etc. As mentioned earlier, given the size of the penalties imposed by courts and regulators, it is unlikely upon such an announcement that changes in market values, if any, would solely reflect expectations regarding the size of a potential penalty. These changes are more likely to reflect expectations that the firm may be the target of closer scrutiny and further enforcement actions, that citizens and communityP

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groups may pressure the firm to reduce its emissions (even below environmental standards) and, as a result, that it may have to invest largeresources (financial and others, e.g. time) in pollution control. We would therefore expect changes in market value, if any, to be larger (potentially much larger) than traditional penalties imposed by courts and regulators. Though in a different context, Jarrell and Peltzman (1985) found that capital markets penalise producers of recalled drugs and cars far more than the direct costs. A further question of interest therefore is whether or not these large observed changes in market value, caused by the provision of new information,provide enough incentives for investments in pollution control.

While individual information may also lead consumer groups to boycott the good(s) produced by the enterprise, thus leading to a revision of the expectations on future revenues, the degree of substitution that is taking place may be limited due to the absence of information regarding the environmental performance of other enterprises. On the contrary, comparative information which compares firms with bad performance to those with good performance is more likely to allow thissubstitution to take place since it gives an alternative to those consumers who want to substitute away from the firms with a bad environmental performance. Moreover, as pointed out by Porterand van der Linde (1995), since pollution efficiency is often associated with overall production efficiency, comparative information indirectly (and perhaps imperfectly) allows a comparison ofthe overall efficiency of the enterprise. This explains why we expect comparati**6**e information to have a greater impact on expectations of future revenues than indi**6**idual information.

Whether or not markets react to the release ofnew information regarding the environmental performance of firms remains ultimately an empirical issue. In the next section, we briefly discuss the methodology used to measure market reactions. In Section 4, we present a number of empirical studies and discuss the results of those studies in view of the hypotheses developed above. 3. Event-study methodology

The methodology used in this field of research is akin to event-study analyses which is based onthe assumption that the capital market is sufficiently efficient to evaluate the impact of new information (events) on expected future profits ofthe firms. The methodology was originally developed by Fama et al. (1969) and Fama (1976). It has been used to analyze the reaction of investors to numerous events of a different nature: product liability suits (Viscusi and Hersh, 1990), airline crashes (Borenstein and Zimmerman, 1988; Chance and Ferris, 1987) and workplace safety violations (Fry and Lee, 1989). The reaction to the announcement of an event is obtained by predicting a ‘normal’ return for each firm during an ‘event window’ (usually the day prior to the event, the day of the event, and anumber of days after the event), and then subtracting this predicted normal return from the actual return observed on those days following the announcement of the event. Normal returnsare generated by estimating a version of the capital assets pricing model (CAPM):

R it **=** (1

**− b**  i )R ft **+ b**  i Rmt **+** e it (1)

where R it is the rate of return on security i for day
t ; R ft is the rate of return on a risk-free asset; Rmt is the rate of return of a market index (such as the Dow Jones market index); **b** i is the estimated parameter; and e it is the error term for security i on day t . The CAPM model is estimated for each firm over a number of days before the event window (usually between 120 and 210 days). In the absence of unexpected information, therelationship between the firm’s return, the market’s return and the return of the risk-free asset should be unchanged. Hence, these returns can be used to forecast the normal return for the firm. A prediction error is generated when unexpected information affects the return for the firm without affecting the market’s return and the risk-freeasset’s rate of return. The prediction error, commonly referred to as the abnormal return (AR ) for security i at time t (AR it ), is computed as the following:P

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AR it **=** R it **−** R ft **− b**  **.** i (Rmt **−** R ft ) (2)
The day the event is announced is referred to as day 0, and all other days are measured relative today 0. The average abnormal return is then computed across firms:

AAR t **=** (1 **/**N t ) **%**

N

t

i **=** 1 AR it (3)

where N t is the number of securities in a given subsample. A statistical test ( t -test) is then used to determine the level of significance of abnormal returns for a given subsample. The test uses the estimated standard error of the returns computed for the estimation period:

t **=** AAR t **/**s ˆ (AAR t ) (4)

where s ˆ (AAR t ) is the estimated standard error of abnormal returns during the estimation period. A number of alternative models can be used to test the robustness of the results (e.g. the single-index market model or the market adjusted returns model). Henderson (1990) points out that these alternative tests yield results of a similar nature as those obtained by using the CAPM. Note finally that abnormal returns are typically calculated on the day of announcement and the subsequent one to three days. Confounding events prevent the calculation of abnormal returns beyond this window.

4. Empirical analyses

Following these lines of argument, a number of papers have investigated, using the event-study methodology, how capital markets can provide incentives for pollution control. Muoghalu et al.(1990) examine the impact of environmental enforcement measures related to the American RCRA (Resource Conservation and Recovery Act) and the Superfund Acts on firms’ financial value. Their sample consists of 128 initial lawsuits against firms and 74 case settlements (involving a fine) announced in the print media (generally the Wall Street Journal) between 1977 and 1986. Theevent-study results indicate that stockholders suffer on average a statistically significant loss of 1.2% in market value at the filing of the lawsuit,with no significant abnormal returns at the disposition of the suit. Interestingly, they compute that the abnormal losses due to announcements of lawsuits translate into an average loss of $33.3 million in equity value. Given the small penalties typically imposed by courts and regulators, thisresult confirms our hypothesis that losses of market value, if any, are likely to be significantly larger than the traditional penalties. Lanoie and Laplante (1994) perform a similar analysis with nine announcements of lawsuits and 13 announcements of suit settlements in Canada during the period 1982-1991. Interestingly, they find results that contrast with those of Muoghalu et al., 1990; i.e. they observe abnormal losses between 1.65 and 2% when the firm is found guilty (and fines are imposed), but no losses when lawsuits are initiated. This difference may be dueto the conciliating approach that Canadian environmental authorities have traditionally adopted in comparison with their American counterparts (Marchant, 1990). As pointed out earlier, it is also interesting to note that the recovery of economic benefits realised as a result of non-compliance is not a common practice in Canada while it is explicitly incorporated in the assessment ofpenalties in the United States. The fact that Canadian shareholders do not react to the announcement of lawsuits may indicate little or no worry as to the outcome of the legal procedure, while American environmental authorities seem to have been more successful in designing enforcement mechanisms in which a lawsuit can impose a credible threat on investors.

While negative information may adversely impact the market value of a firm, Klassen and McLaughlin (1996) also find that environmentalawards, denoting public recognition of strong environmental performance, had a positive impact on market valuation. Based on a sample of 140 events (announcement of an environmental award) collected over the period 1985-1991 in the United States, these authors found that market valuation increases on average by 0.82% upon announcement of the award; this translates into an average increase of over US$80 million. They also find, based on a sample of 22 events collectedP

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over the same period of time, that the announcement of an environmental crisis resulted in an average decline in market valuation of 1.5%; this translates into an average loss of over US$390million for the firms involved. Note that the information used in these three studies would classify

as indi**6**idual information.

In contrast with the preceding research, two studies have analysed the deliberate provision of information to the markets (by regulators or third parties), and its impact on firms’ value. This information is based on rankings of polluters and can thus be qualified as comparati**6**e information. Shane and Spicer (1983) use studies conducted by the council of economic priorities (CEP) of firms’environmental performance in four industries (paper, power, steel, and oil) to analyse the reaction of investors to the release of the results of those studies. They examine eight studies released by the CEP between 1970 and 1975. They find that firms’ market value is adversely affected by therelease of this information. Perhaps more interestingly, they also find that firms identified as serious polluters suffered greater loss of market value than those with a better ranking. Given these results, these authors conclude that investors usethe information to discriminate between companies on the basis of their environmental performance records. Hamilton (1995) examine how financial markets have reacted to the first edition of the ‘toxic release inventory’ (TRI) in June 1989. The TRI reports information on manufacturing facilities, with 10 or more employees, that produce or use above a threshold amount of chemicals on a list of over 300 toxic chemical substances identified by EPA. For each chemical, the facility submits a form listing releases to the environment brokendown by emission pathways: air, land, underground injection, etc. Furthermore, the TRI data contains information on facility name and parentownership so that media coverage can link operating facilities with their parent company. Firms are ranked from large to small polluters on the basisof their absolute levels of emissions, thus, allowing a direct comparison of their environmental performance. The event-study conducted by Hamilton is based on a sample of 436 enterprises reporting TRI pollution figures. Unsurprisingly, most of these enterprises (75% of the sample) are in the manufacturing sector (chemicals, paper, primary metals, petroleum and textiles) with 12% in the chemical industry. Results show that these firmsexperienced negative, statistically significant abnormal returns between 0.2 and 0.3% upon the first release of the information. These abnormal returns translated into an average loss per firm of$4.1 million in stock value on the day the pollution figures were released, with firms in the primary metals industry experiencing a smaller loss of market value (presumably because these firms were already perceived as large polluters by the market). He also found that the larger the number of chemicals a firm reported to produce or handle at its facilities, the larger the loss the firm suffered in its market value: for each additional chemical, Hamilton measures a loss of $236000.

Perhaps more interestingly, Konar and Cohen (1997) recently found that firms with the largest decline in stock value on the day the informationcontained in the TRI was made public, subsequently reduced their emissions more than other firms in the same industrial sector of activities.These results partly support a former EPA director’s claim that ‘(...) the Toxics Release Inventory is fast becoming one of the most powerful tools we have to reduce toxic emissions’. (New York Times, October 13, 1991). On the basis of thislater result, it would therefore appear that financial markets may provide firms with incentives toimprove their environmental performance. Referring to the TRI, J.S. Naimon of the InvestorResponsibility Research Center is quoted as saying: ‘(...) companies that emit a lot of toxic waste do not have good financial indications in the long term’ (New York Times, October 13, 1991).

4.1. New results

Since July 1990, every six months or so the Ministry of the Environment of British Columbia(BC, Canada) publishes a list of polluters identified into two categories: (1) firms that are currently not complying with an environmentalP

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Table 1 Public enterprises identified in the lists of polluters

List 2 List 3 Enterprises List 4 List 1 List 5

12-12-90 22-07-91 24-01-92 12-07-90 06-10-92

c,ppp c,p Alcan Aluminium Ltd. c,p c,pp a c,p p c,p p c,p B.C. Sugar Refinery Ltd. c,p c,p c Canadian Pacific Forest Products Ltd. c c,p c

— — — — Canadian Pacific Ltd. p

— ccc Canfor Corp. ccc — c c,pp cc,pppp c,ppp ccc,ppp Cominco Ltd. c,ppp — p Equity Silver Mines Ltd.

— p —

cc c ccc c Flectcher Challenge Canada Ltd. c

c c George Weston Ltd.

— c — c,p cc c c Imperial Oil Ltd. (Esso Petroleum Canada) —

ccc— International Corona Corp. c
c,ppp ccc c,ppp cccc MacMillan Bloedel Ltd. cccc,p

— — Methanex Corp.

— — c p p p p Noranda Inc. p p c Placer Dome c c —

c c c c Repap Entreprises Inc.

— — cc,pp Shell Canada Ltd.

— — c

— — c,pp — Westar Group

— p c —p Westmin Resources Ltd. p

aThe number of letters indicate the number of times that the enterprise appeared on the list. p: plants not complying with pollution standards; c: plants of concern to the Ministry.

standard or permit; and (2) firms that are of

concern to the Ministry because their environmental performance is near the regulatory threshold, or because their level of pollution is abnormally high in a sector of activity which is not regulated. Since these lists do not provide a ranking of enterprises, and do not allow for a comparison of their environmental performance, we classify this information as indi**6**idual information. In the following, we examine the impact of the first five lists of polluters on the equity value offirms appearing on these lists. Our analysis complements that of Hamilton (1995) in two different ways: (1) it is based on a Canadian list providing a different set of informations than those released in the TRI; and (2) we investigate how investorstreat the information about firms appearing successively on more than one list, while Hamilton focused exclusively on the first release of the TRI.

Table 1 presents a list of 19 firms quoted on the stock market and appearing on any of these first five lists. This table shows whether a firm has been identified as ‘out of compliance’ or as ‘of concern’. Furthermore, it indicates that multi-plants firms may appear more than once on the same list if many of their plants are either non-complying or of concern.

We use the SIMM (single-index market model) version of the standard event-study technique to analyze investors’ reaction to the publication of the lists. A three days event window (day

**−** 1, day 0 and day **+** 1) is considered, where day 0 refers to the publication date of the list. Certain companies were discarded in the analysis because of confounding events such as an announcement of dividend pay-off, profits, merger, take-over or new share emissions. We first look at the whole sample of firms appearing on each list. Then, we examine more specifically the firms that are of concern versus those that are out of compliance, and the firms that have appeared once on a given list versus those that have appeared several times.Finally, to investigate how investors react to successive appearances on different lists, we performP

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an analysis in which only firms that appeared on all lists (whether being of concern or out of compliance) are considered.

Table 2 reports the results obtained using the whole sample of firms at the publication of each list. There is no statistically abnormal loss on any day of the event window for any of the list. Contrary to what was observed by Hamilton (1995) and Shane and Spicer (1983), this suggests that appearing on the BC polluters’ list has no impact on a firm’s equity value.

A number of reasons may explain this result. First, it may be that BC’s lists of polluters do notprovide new or unexpected information to investors. Canada is a much smaller market than the United States, with only a very few large public enterprises. The first release of the TRI provided a set of detailed information on releasesof a large number of severe pollutants, information more likely to be unknown to the investors than that provided by the BC list. Moreover, it is important to note that in any given list, theMinistry of the Environment does not systematically report all firms out of compliance or of concern to the Ministry. A firm may be out of compliance (or of concern) and yet never appear on the lists, or appear only after a number of listshave been published: not being listed is not necessarily an indication of good environmental performance. As we have noted before, this feature of the BC’s lists of polluters does not allow investors to rank firms according to their environmentalperformance. Furthermore, given the characteristics of the economy of British Columbia, unsurprisingly the companies listed in BC’s lists are mostly in the primary sector (resources) of the economy, whose main market consists of themanufacturing sector; therefore, any potential decline in demand resulting from an adversarial reputation effect may be less important than in Hamilton’s sample which covered firms in a broader set of activities. Finally, investors may believe that appearing on BC’s lists does not represent any significant threat for the companiesinvolved. Given our earlier discussion, the difference between the American results and those presented here may again indicate that Americanenvironmental authorities have been more successful in designing policy mechanisms that create a credible threat for firms.

Tables 3 and 4 provide a more detailed analysisin which different categories of firms are distinguished. In Table 3, firms that are out of compliance and those that are of concern are analyzed separately. One could expect that firms out of compliance would be under a more important threat than those of concern. On the other hand,the fact that firms are of concern for the environmental authorities could be new information to the market; this could have more impact on the value of firms reported under this heading. Asshown in Table 3, however, no statistically significant abnormal losses can be detected in either category. In Table 4, we distinguish between firms that appear once on a given list and those that appearmore than once. One would expect that for environmental authorities, the pressure to take actions against a polluter may be ‘cumulative’ so that firms appearing more than once on a given list could experience more important abnormal losses.The results seem to confirm this hypothesis. Indeed, we obtain statistically abnormal losses on day

**−** 1 and day **+** 1 for firms appearing more than once on the second list:

**−** 0.1 % on day

**−** 1 and

**−** 1% on day **+** 1. Such abnormal negative returns for firms appearing several times on the second list may indicate that investors required strong signals about a firm’s bad environmental Table 2 Whole sample results

Day

**−** 1 Size of List Day **+** 1 Day 0 sample

t . stat t . stat t . stat

0.0017 0.003 L1 0.0026 13 (0.543) (0.9199) (0.8381) L2

**−** 0.005 0.0029 0.0037 12 (0.7146) (0.5623) (

**−** 0.9373) L3

**−** 0.006 0.0033

**−** 0.009 7 (

**−** 0.7932) (0.5623) (

**−** 1.27)

**−** 0.007

**−** 0.004 L4 0.0006 7 (

**−** 0.8972) (

**−** 0.5353) (0.0084) L5 10 0.0018 0.0042

**−** 0.01 (

**−** 1.527) (0.2756) (0.6684)P

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Table 3 Out of compliance vs. of concern

List Plants of concern Plants out of compliance

Day 0 Day **+** 1 Size of sample Day

**−** 1 Day 0 Day

**−** 1 Day **+** 1 Size of sample

t . stat t . stat t . stat t . stat t . stat t . stat

L1

**−** 0.002 0.01486** 0 4 0.0179* 0.0064 0.0097 3 (2.123) (0.05831) (1.92) (

**−** 0.2694) (0.6777) (1.033) 0.0079 L2

**−** 0.004 0.0039 4 0.01014 0.01277

**−** 0.003 4 (1.028) (

**−** 0.5575) (0.5074) (1.11) (1.399) (

**−** 0.3323)

**−** 0.0125 0 4

**−** 0.0136

**−** 0.002 0.0026 L3

**−** 0.0308 1 (

**−** 0.6513) (

**−** 0.0341) (

**−** 0.2761) (

**−** 0.1111) (0.0538) (

**−** 0.656)

**−** 0.007

**−** 0.009 2 0.0015 0.01149

**−** 0.004 L4 0.0056 1 (0.7123) (

**−** 0.4538) (

**−** 0.532) (0.1043) (

**−** 0.2595) (0.3896) 0.0013

**−** 0.007 4

**−** 0.003 L5 0.0013

**−** 0.002

**−** 0.0144 3 (0.1528) (

**−** 0.8416) (

**−** 0.2965) (

**−** 0.265) (0.1351) (

**−** 1.485)

* Statistically significant at the 90% level. ** Statistically significant at the 95% level.

performance before revising the expected value attributed to this firm.

Table 5 provides further evidence that investors may have reacted in the way we just described. In this Table, we consider a sample of firms that have appeared on every list so as to investigate how investors handle the information contained in successive appearances on the list. There weretwo such firms. Again, the only significant abnormal loss appears for the second list on day **+** 1 (a loss of 2%), suggesting that investors neededstrong indications before changing their expectations. No abnormal losses beyond the second listmay mean that appearing on the list has a oncefor-all effect, and that successive appearance does not provide significant new information.

5. Concluding remarks

It has been observed that upon trading-off thecosts and benefits of pollution control, profitmaximizing firms may choose not to invest theirresources in pollution abatement since the expected penalty imposed by regulators falls considerably short of the investment cost. This however ignores that markets and communities can also create incentives for pollution control to the extent that they possess information regarding a polluter’s environmental performance. Regulators have recently embarked on a deliberate strategy torelease information to markets (investors and consumers) and communities regarding firms’ environmental performance in order to enhance incentives for pollution control. It shall bepointed out that it may require considerable political backbone to pursue this strategy. Indeed, for such a strategy to be effective, the information used and revealed by the regulator has to be accurate. Moreover, the regulator may be under pressure from the regulated community not to reveal such information. Finally, by revealing the environmental performance of firms, the regulator makes itself more transparent, and simultaneouslyreveals its own ability (or inability) to bend polluters toward pollution abatement. In this paper, we analyze the role that capitalmarkets may play to create such incentives. Evidence drawn from American and Canadian studies indicates that capital markets react to the release of information, and that large polluters are affected more significantly from such release than smaller polluters. Hence, regulatory agencies can use, in addition to traditional regulatory mea-P

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Table 4 Frequency of apppearance

List Firms appearing more than once Firms appearing once

Day 0 Day **+** 1 Size of sample Day

**−** 1 Day

**−** 1 Day 0 Day **+** 1 Size of sample

t . stat t . stat t . stat t . stat t . stat t . stat

L1 0.0048 0.011096* 0.00406 7 0.00381 0

**−** 0.0022 6 (0.7902) (1.814) (0.6622) (0.5021) (

**−** 0.051) (

**−** 0.2851) 0.00263 0.0009 7

**−** 0.0011* 0.0086 0 L2

**−** 0.01091* 5 (1.333) (0.4052) (0.1426) (

**−** 1.677) (

**−** 0.007) (

**−** 1.712)

**−** 0.01159

**−** 0.0035 4

**−** 0.0067 L3 0.006

**−** 0.003

**−** 0.01012 3 (

**−** 1.6174) (

**−** 0.1885) (

**−** 0.8977) (

**−** 0.1426) (0.7953) (

**−** 1.347) 0.0059 L4

**−** 0.0053

**−** 0.001 2

**−** 0.01183

**−** 0.004 0.0009 5 (

**−** 0.4748) (

**−** 0.05241) (

**−** 1.38) (

**−** 0.4156) (0.1042) (0.5241) 0.0017

**−** 0.01026 7 0.015537

**−** 0.003 0.0091 L5

**−** 0.0039 2 (0.2495) (

**−** 0.4383) (

**−** 1.504) (1.501) (0.8876) (

**−** 0.3767)

* Statistically significant at the 90% level. ** Statistically significant at the 95% level.

sures, information-oriented approaches so as to harness the power of communities and markets to put pressure on polluters. This result howeverappears to be a function of the regulator’s willingness to undertake strong enforcement actions(United States vs. Canada), as well as the possibility for capital markets to rank and comparefirms with respect to their environmental performance (Council of Economic Priorities and TRI vs. British Columbia’s lists of polluters). Further research in this area will indicate thecircumstances under which the release of information can create incentives for pollution control by empowering the agents that can bearpressure on polluters. In particular, current research will indicate whether or not capital markets in de**6**eloping countries can create incentives for pollution control. Further research should also indicate whether or not this information not only has an impact on market valuation, but ultimately whether or not it affects a polluter’s environmental performance.

Acknowledgements

We are grateful to Jean-Francois L’Her, JeanMarc Suret and David Wheeler, and anonymous referees for their comments. Financial assistancewas provided by the Fonds FCAR. Usual disclaimers apply.

References

Afsah, S., Laplante, B., Wheeler, D., 1996. Controlling industrial pollution: a new paradigm. World Bank, PolicyResearch Department, Working Paper No. 1672, Washington, D.C. Table 5 Enterprises appearing on the first five lists

Day

**−** 1 List Day 0 Day **+** 1

t . stat t . stat t . stat

L1 0.002476 0.011362 0.004622 (1.149) (0.2519) (0.4706) L2

**−** 0.00592 0.008302

**−** 0.020457** (0.8019) (

**−** 0.571) (

**−** 1.969)

**−** 0.010403 L3 0.009997

**−** 0.014264 (

**−** 1.079) (1.034) (

**−** 1.48)

**−** 0.00159

**−** 0.0044 L4

**−** 0.01294 (

**−** 0.1407) (

**−** 0.3889) (

**−** 1.145)

**−** 0.00933 0.009816 0.024394* L5 (l.893) (

**−** 0.7249) (0.7527)

* Statistically significant at the 90% level. ** Statistically significant at the 95% level.P

. Lanoie et al

. **/** Ecological Economics 26 (1998) 31–41 41

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