What is Driving the Pollution Abatement Expenditure Behavior of Manufacturing Plants in Korea?

What is Driving the Pollution Abatement Expenditure

Behavior of Manufacturing Plants in Korea?

JEAN ADENThe World Bank, Washington, DC, USA

AHN KYU-HONGKorea Institute of Science and Technology, Seoul, South Korea

and

MICHAEL T. ROCK *

Winrock International, Arlington, VA, USA

Summary. Ð Relatively little is known about the environmental behavior of manufac-turing plants in Korea. We address this lacuna by reporting the results of a surveydesigned to assess the scope of plant-level pollution abatement expenditures, the in-tensity of plant-level exposure to regulatory actions and community pressure, and theimpact of each on abatement expenditures. Survey results reveal substantial expendi-tures on pollution abatement and signi®cant exposure to regulatory actions and com-munity pressure. Two-stage least squares (TSLS) estimation of a responsive regulationtype model suggests that Korean regulators may be engaged in responsive regulationthat works and that plant characteristics (size, productivity, and ownership) and com-munity pressure also a�ect plant-level abatement expenditures. Ó 1999 Elsevier ScienceLtd. All rights reserved.

1. INTRODUCTION

From the late 1960s through most of the1990s, Korea's development performance hasbeen little short of astonishing. Growth in in-come per capita averaged 7.1% per year during1965±95 (World Bank, 1996, p. 189 and WorldBank, 1990, p. 179). Few, if any, other coun-tries grew so fast for so long. Rapid growth wasaccompanied by low income inequality, a rapiddecline in the incidence of poverty, substantialstructural transformation of the economy, andan explosion in manufactured exports. Notsurprisingly, this performance has attractedconsiderable attention and it has sparked alively debate on the role of the state in devel-opment (Amsden, 1990 and World Bank,1993).

Much less has been written about the envi-ronmental consequences of Korea's high-speed

growth or of environmental policies designed tomitigate pollution. Some (Bello and Rosenfeld,1992 and Eder, 1996) have questioned thewisdom and sustainability of the country's``grow ®rst, clean up later'' environmentalpractices. Others (O'Connor, 1994) have de-scribed the evolution of environmental policyand suggested that it may be having an impact.But little or no empirical research has beencarried out to determine what, if anything, isdriving the environmental behavior of thecountry's manufacturing plants.

The purpose of this paper is to present resultsof a survey on one important aspect of plant-level environmental behaviorÐplant-levelpollution abatement expenditures. The surveywas designed to identify the scope of such

World Development Vol. 27, No. 7, pp. 1203±1214, 1999Ó 1999 Elsevier Science Ltd

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* Final revision accepted: 2 January 1999.

1203

expenditures; measure the exposure of plants tocommunity and regulatory pressure; and assessthe impact of these on abatement expenditurebehavior. The paper is organized in ®ve sec-tions. Section 2 describes the evolution ofenvironmental policy in Korea. Section 3 de-scribes the data used for hypothesis testing.Section 4 presents a simple responsive regula-tion model for testing hypotheses about plant-level pollution abatement expenditures andreports statistical results. Section 5 summarizes®ndings and draws implications.

2. THE EVOLUTION OFENVIRONMENTAL LAW, REGULATION,

AND POLICY

Korea, like its counterparts in the rest of theworld, pursued a ``grow ®rst, clean up later''environmental strategy. The country's ®rstmajor environmental law, the EnvironmentalPreservation Act was not enacted until 1977.1

This law established a broad regulatoryframework for: setting environmental stan-dards, maintaining air and water quality; con-trolling noise and vibration; managing solidand hazardous wastes; and protecting the nat-ural environment. The government created anEnvironmental Management Bureau in theMinistry of Public Health (MOPH) to imple-ment the new law. In 1980, this bureau wasupgraded to a subcabinet agency, the Envi-ronment Administration (EA) of the MOPH.Initially, local authorities were vested with en-forcement responsibilities but in 1987, six re-gional o�ces of the EA were created andcharged with enforcement. For a variety ofreasons, neither local authorities nor the re-gional o�ces of the EA engaged in much in-spection or enforcement.

Democratization and growing public concernfor the environment ultimately led to the cre-ation of a cabinet-level Ministry of the Envi-ronment in 1994. This was followed by theenactment of a new set of environmental laws,including a new basic framework law, the BasicEnvironmental Policy Act (BEPA). The BEPAadded to existing legislation by, among otherthings, endorsing the polluter pays principleand establishing joint and several liability ofindustrial plants for pollution damages. In 1990and 1991 the National Assembly passed legis-lation governing air, water, hazardous chemi-cals, and solid wastes.2 Another new statuteestablished a Central Environmental Dispute

Co-ordination Committee to mediate environ-mental damage claims. Following a seriouspollution incident in the Nakdong River, theAssembly passed The Special Act to PunishEnvironmental Crime in 1991. Finally, in 1993an Environmental Impact Assessment Act wasestablished. With this, the basic legal frame-work for environmental regulation in Koreawas set.

Implementation of the country's new envi-ronmental laws was vested with a cabinet levelMinistry of the Environment (MOE). To assistit, the MOE created six regional o�ces andmade them responsible for permitting, moni-toring, and enforcement.3 The MOE was alsogiven responsibility for managing the publicsector Environmental Management Corpora-tion (EMC). The EMC ®nances, constructs,and operates waste-water treatment facilities inindustrial estates. The MOE is assisted by KEI(the Korea Environmental Institute) whichdoes research on environmental policy andenvironmental impact assessment; the NationalInstitute for Environmental Research (NIER)which does ambient environmental monitoringfor the MOE; and a Central EnvironmentalPolicy Advisory Committee (CEPAC). CEPACis composed of prominent representatives frombusiness, government, and the academic/re-search community and it is organized into 13subcommittees. It advises the MOE on ambientand emissions standards. Although the MOE'sambient standards are not legally binding, itsemissions standards are. Both broadly mirrorpractices in the OECD. Because media speci®cemissions standards have potentially importanteconomic impacts on polluters, the MOE con-sults with other ministries, particularly theMinistry of Commerce, Industry, and Energy(MOCIE) in setting those standards.

To date, implementation of environmentalstatutes has followed a command and controlapproach based on quality or concentrationstandards. Facilities expecting to emit pollu-tants are required by law to obtain separatepermits for air, water, and noise from theMOE. Permits are issued on the basis of facilitysize (the tons of coal equivalent used per yearand cubic meters of waste-water discharged perday).4 When emissions are expected to exceedlegal limits, polluting plants are required toinstall ``certi®ed'' pollution abatement equip-ment. Once a polluting facility is authorized tobegin operations, it is required to operate andmaintain its pollution control equipment and toself-monitor the performance of abatement

1204 WORLD DEVELOPMENT

equipment. This includes keeping records of thetime periods of operation of abatement equip-ment, the amount of pollutants emitted, themaintenance of the abatement equipment, andthe person in charge. Self-monitoring recordsare to be kept for three years. Facilities whichcannot meet emissions standards must reportthis to authorities. Those who do so are exemptfrom administrative and criminal sanctions, butKorea's noncompliance penalties apply.5

Ultimately, the force of the country's envi-ronmental regulations depends on a combina-tion of public and community pressure, thelaw-abidingness of polluters, and whether pol-luters believe that the MOE has the monitoringand enforcement capacity to credibly threatenthose who violate emission standards. All threehave undergone substantial change. As Korea'smiddle class has expanded, public concern forthe environment has grown. In 1982 only 14%of those surveyed nationally thought the envi-ronment important. By 1990, this number hadrisen to 64% (Eder, 1996, p. 75). This occurredin tandem with another shift in public opinionof equal import. In 1982, 68% of those surveyedthought the government was working to pro-tect the environment. By 1990, this dropped to24% (Eder, 1996, p. 76). Public reporting on theenvironment experienced a similar surge. Byone account (Eder, 1996, p. 77), there were only479 environmental stories in major newspapersin 1982. By 1992, this had jumped to 8,884. Oneconsequence of all of this has been developmentof e�ective NIMBY (not in my backyard)campaigns by local activists, communities, andNGOs (nongovernment organizations) toforestall infrastructure projects (Eder, 1996,p. 107). Another manifestation of growingpublic concern for the environment is thegrowth in public complaints regarding envi-ronmental damage. These were virtually un-heard of prior to democratization. Since thenthere has been an explosion in complaints.6 Intwo recent serious incidents (Nakdong Riverphenol spills in 1991 and 1994), the publicoutcry was so strong that the Minister and ViceMinister of the Environment and the chairmanof the corporation (the Doosan group) re-sponsible for the spill were forced to resign.

This change in public attitudes toward theenvironment and the public pressure attendingit has no doubt strengthened the ability of theMOE to develop the capacity to maintain anambitious monitoring, inspections, and en-forcement program. It appears to have mademajor progress over its predecessors in this

area. Part of this is due to signi®cant increasesin resources allocated to the MOE. In 1980, thesta� of the Environment Administration was238 and its budget equaled 343 hundred millionwon. By 1994, the MOE had a sta� of 1,100and a budget of 2697 hundred million won.7

Because of this, the MOE and its regional of-®ces have been able to undertake a substantialbasic accounting of the number, kinds, andlocation of major air and water polluters.

By 1993, the MOE had identi®ed 25,808major facilities emitting pollutants into the air(MOE, 1994, p. 11). These facilities have beenidenti®ed by location (province), pollutant(SOx, NOx, CO, HC, and TSP), and source(heating, industry, transportation, power gen-eration) of pollutant. Plants emitting pollutantsinto the air have been classi®ed into four types(blue, green, yellow, red) based on the scale ofoperations and the frequency of violations.Larger facilities and those found in more fre-quent violation of standards have been ratedeither yellow or red and are inspected morefrequently. The MOE now routinely inspectsabout 25,000 air pollution emitting facilities peryear. Inspections of these facilities increasedfrom 32,921 in 1989, to 52,566 in 1991 and57,854 in 1993 (MOE, 1994, p. 23). Of these,roughly 10% per year were found to be in vio-lation of emissions standards. The regional of-®ces of MOE responded to violations by issuingwarnings; ordering improvements; suspendingoperations; shutting down operations; andrecommending to prosecutors that criminal in-dictments be brought.8 Actual indictmentsequaled 553 in 1989; 1655 in 1991; and 1942(MOE, 1994, p. 23).

Industrial waste-water dischargers have beenidenti®ed by location (province/river) and in-dustry sector. Waste-water emitters are classi-®ed into one of four color categories (blue,green, yellow, and red) based on the status oftheir abatement facilities and the results of in-spections. Facilities with completely installedand operating abatement equipment and withfew `ùnintentional'' violations are rated blue orgreen. Those with incomplete abatement facil-ities and/or more, or more severe, and/or in-tentional violations are rated yellow or red.Inspection intensity varies with a facility's rat-ing. Blue facilities tend to be inspected once peryear, green facilities two times per year, yellowthree, and red four times per year. The numberof waste-water discharge inspections has in-creased from 25,624 in 1988 to 61,639 in 1990,to 72,239 in 1993 (World Bank, 1995a, p. 33).

POLLUTION ABATEMENT EXPENDITURE 1205

Violations of emissions standards averagedaround 20% in 1988±89 and 10% in 1992 and1993. MOE inspectors responded to waste-wa-ter emissions standards violations by issuingimprovement orders; suspending operations;revoking permits; and seeking criminal prose-cutions.9

One other element of environmental policydeserves mention. Since 1983 environmentalregulators have imposed a noncompliancepenalty on facilities found in violation of air orwater emissions standards. The penalty is basedon the duration and severity of the violation.The basic charge is a ¯at fee that varies withfacility size. (It varies from 500,000 won to fourmillion won.) In addition, repeated violationsare charged an additional penalty. The currentpenalty rate is 1.3 times the base rate for thesecond o�ense; 1.3 times 1.3 (1.69) for the thirdo�ense; and 1.3 times 1.3 times 1.3 (2.19) forthe fourth o�ense and so on. While there issome question as to whether the noncompli-ance penalty has a deterrent e�ect, there is littledoubt that it is a substantial revenue raiser. In1993, collected noncompliance charges totaled13.5 billion won (World Bank, 1995a, p. 41).

A range of circumstantial evidence suggeststhat public pressure and regulatory actions arehaving some e�ect on the behavior of polluters.During 1985±93 industrial process-generatedBOD increased by 2.7 times but BOD dis-charged into Korean rivers increased by only20% (World Bank, 1995a, p. 4). Time-seriesdata suggest that ambient air quality for severalcriteria pollutants (SO2, NO2, TSP, and CO) isimproving (O'Connor, 1994, p. 106). Moreoversurvey data on ®rm-level pollution control ex-penditures suggest that ®rms are making sub-stantial investments in pollution control.During 1991±93, investments in pollution con-trol averaged 7.2% of total investment (WorldBank, 1995a, p. 47).

3. THE SURVEY DATA

The picture presented above suggests thatgrowing public concern over the environmentand public pressure on polluters and on gov-ernment regulators alongside a much strength-ened Ministry of the Environment is nowmaking a di�erence in the pollution abatementbehavior of Korea's manufacturing plants. Togain a clearer sense of the interrelationshipsbetween plant-level abatement expenditures,regulatory actions, and public pressure, we

undertook a survey of 92 manufacturing plantsin two high-polluting sectors (textiles andplastics/resins/petrochemicals) located in ®vedi�erent industrial estates in three regions(north, south central, and southeast) of Korea.Fifty-three of the surveyed plants were in thetextile sector and 39 were in the plastics/resins/petrochemical (PRPC) sector. The choice oflocations re¯ected the prevalence of industrialestates, the major jurisdictions of the KoreanMinistry of the Environment, and the locationof industry in all of Korea's large urban areas.

Almost 90% (81) of the surveyed plants hadincurred some level of abatement expenditures.Of those 81 plants, 47 are in the textiles sectorand 34 are in the PRPC. The average age ofthose plants was 16 years and age ranged fromthree to 75 years. The average employment ofplants was 353 employees with a range from 10to 4900 employees. Average sales were $10.39million with a range from $152,000 to $6.7billion. Average annual expenditures (capitaland operation and maintenance) for pollutionabatement over 1988±93 was $1.1 million witha range from $612 to $43.5 million. Approxi-mately 90% of these plants (72) were fullyowned by the Korean private sector.

As might be expected, these averages(Table 1) concealed large di�erences betweentextile and plastics/resins/petrochemical plants(PRPC). The average PRPC plant employedmore than three and one-half times as manypeople (607 to 168) as the average textile plant.Average sales in PRPC plants were a little morethan 40 times larger ($472 million to $11.6million) than that in textile plants. Averagepollution abatement expenditures of PRPCplants were 38 times higher than that for textileplants ($2.68 million versus $70,541). In addi-tion, a larger percentage of the PRPC plantswith some level of abatement had some foreignownership (15% to 8.5% for textile plants).

Because of these di�erences, we expected thatindustry sector might be an important deter-minant of abatement expenditures. There wereseveral other reasons for thinking that sector ofplant might matter. The textile sector is a de-clining sector in Korea whereas the PRPCsector has been favored by government. Thismight make it easier for regulators to punishtextile plants and harder for them to imposecostly sanctions on PRPC plants. There is someevidence that something like this is happeningin both Taiwan and Singapore.10 This is con-sistent with arguments made by Ayres andBraithwaite (1992), p. 5) to the e�ect that


industry context often a�ects the behavior ofboth regulators and the regulated industry.

What do we know about the level of expo-sure of these plants to regulatory and publicpressure? We answered this question by con-structing a number of indices of plant-levelexposure to each of these. With regard to reg-ulation, we were interested in exposure to anintensity of government monitoring variableand an intensity of sanctions variable. Designof questions to capture these was based on ac-tual Korean experience and suggestions inAyres and Braithwaite (1992), pp. 35±39) thatregulation works best when regulators have attheir disposal a hierarchy of enforcementstrategies (sanctions) and a hierarchy of inter-vention (monitoring and inspection) strategies.

We constructed a hierarchy of governmentmonitoring (GM) variable by weighting andadding up the frequency of monitoring andinspections visits. The actual GM index wasconstructed as follows:

GM � (FGM) + 1.5 * (FGINS)+ 2 * (UNINS)

where FGM � the frequency of governmentmonitoring visits in the last 12 months,FGINS � the frequency of government in-spections in the last 12 months,UNINS � 1 if inspections were unan-nounced and 0 otherwise.

A regulatory sanctions index (SN) was con-structed as follows:

SN � (VW + ERO) + 2 * (NCP)+ 3 * (FI) + 4 * (CRIM) + 5 * (Close),

whereVW � number of verbal warnings,ERO � number of emission reduction or-ders,NCP � number of noncompliance charges,FI � number of other ®nes,CRIM � number of criminal actions re-quested by MOE,Close � number of temporary closures.

Ayres and Braithwaite (1992), p. 5) alsosuggest that responsive regulators start rela-tionships with regulated ®rms by assuming thatthey will cooperate with regulators. We usedtwo variablesÐactual abatement expendituresand the frequency (over the past 12 months)with which plants reported self-monitoring(SM) results to regulatorsÐas measures of co-operation.

With regard to community pressure, we wereinterested in assessing the impact of directcommunity pressure on plant-level pollutionabatement expenditures. Several case studies(Hsin-Huang, 1998; Cribb, 1990; and Khator,1991) suggest that at least some polluters re-spond positively to complaints, protests, orrequests by neighbors to reduce emissions ei-ther by installing pollution control equipmentor by agreeing to do so in a negotiated pollu-tion control agreement. The e�ect of commu-nity pressure on emissions has been con®rmedin several statistical studies (Hettige et al., 1996and Pargal and Wheeler, 1996) which foundthat proxies for direct community pressure(community income levels and education levels)

Table 1. Descriptive statistics a

Mean Std. Dev. Max/Min

Text. PRPC Text. PTPC Text. PRPC

PAE 0.70t 2.68m 117t 7.48m 75t/1.2t 43.5m/612EMP 168 607 215 888 1385/11 4900/10AGE 16.1 15.5 11.3 7.4 75/3 30/3S/E 79.3t 592.5t 130.7t 606t 901/2.6 2.8m/63tOWN 0.91 0.85 0.28 0.35 1/0 1/0GM 13.2 24.8 15.01 29.71 60/0 150/0SN 5.49 9.17 7.17 11.74 36/0 51/0SM 5.96 35.16 15.55 104.2 99/0 365/0CP 0.32 0.68 1.29 1.57 8/0 8/0

a PAE is annual pollution abatement expenditures in US$; EMP is plant-level employment; AGE is age of the plant;S/E is plant-level sales (US$) per employee; OWN is a dummy variable for ownership (OWN � 1 for domestically-owned plants and OWN � 0 for any level of foreign ownership); GM is an index of government monitoring of aplant; SN is an index of government sanctions imposed on a plant; SM is a measure of plant level self-monitoring ofemissions; and CP measures community pressure on a plant to reduce emissions. Sample size for textiles is 47. Samplesize for PRPC plants 34.


have signi®cant e�ects on plant level emissions.But, as far as we know, no one has tested forthe impact of direct community pressure asde®ned above on either a plant's abatementexpenditures or its emissions. Because of this,we constructed a simple straightforward inten-sity of community pressure variable (CP) bysumming up the number of community re-quests made of plants to abate pollution andthe number of pollution control agreementsthat exist between a plant and a given com-munity. Thus we de®ned community pressure(CP) as

CP � NCRPA � NPCA;

whereNCRPA � the number of community re-quests made of a plant to abate pollution,NPCA � the number of pollution controlagreements between a plant and a commu-nity.

One ®nal point deserves mention. As canreadily be seen in Table 1, there appear to besigni®cant sectoral di�erences in intensity ofexposure to government monitoring, regulatorysanctions, self-monitoring, and communitypressure. The mean value of the intensity ofgovernment monitoring (GM) is 24.8 for PRPCplants and 13.2 for textile plants. The meanvalue of the intensity of regulatory sanctions is9.1 for PRPC plants and 5.48 for textile plants.The average frequency with which plants reportself-monitoring results to regulators is 35.1 forPRPC plants and 5.96 for textile plants. Themean value of exposure to community pressureis 0.68 for PRPC plants and 0.32 for textileplants. Said another way, a higher percentageof PRPC plants have been exposed to regula-tory and community pressure. The intensity ofexposure to each of these is also higher forPRPC plants.

4. STATISTICAL TESTS

Our survey data suggest that manufacturingplants in Korea have made signi®cant expen-ditures for pollution abatement, and are subjectto substantial regulatory actions and commu-nity pressures. This made it possible to formallytest hypotheses regarding the impact of regu-latory and community pressure on plant-levelpollution abatement expenditures. Statisticaltests were based on a model developed by

Hettige et al. (1996), Pargal and Wheeler(1996), and Pargal, Mani and Hug (1997). Likethem, we test for the in¯uence of plant char-acteristics (size of plant, age of plant, plant-level productivity, and ownership of plant) andcommunity pressure on plant-level expendi-tures on pollution abatement.

We make several basic amendments to theirmodel. First, instead of focusing on emissions,our dependent variable is plant-level expendi-tures (annual average capital expendituresplus annual average operation and mainte-nance expenditures) for pollution abatement.Thus we ask, what drives manufacturingplants in Korea to spend resources on pollu-tion control? Second, we measure communitypressures on plants directly rather thanthrough proxies (community level incomesand/or education levels) as they do. Third, wetest for the direct impact of formal regulatorypressures on plant-level abatement expendi-tures.11 Finally, because there is some evi-dence that regulators in the Korean Ministryof the Environment treat regulated plants ina ``tit-for tat'' (TFT) way as suggested byAyres and Braithwaite (1992), we develop anadmittedly crude test of a TFT regulatorystrategy.12

Ayres and Braithwaite argue that a TFTregulatory strategy, or what they also call re-sponsive regulation, di�ers from traditionalregulation by recognizing that sometimes ®rmsand industries e�ectively self-regulate. Whenthis happens, they propose that regulatorscomplement deterrence (sanctions) with gentlepersuasion and cooperation. But once ®rms failto cooperate, regulators should fall back ondeterrence. Ayres and Braithwaite (1992),p. 19±25) also hypothesize that a TFT strategyworks best when regulators have at their dis-posal a range of credible and increasingly in-trusive regulatory strategies and a range ofequally credible and increasingly costly sanc-tions. In this view, deterrence works best tostimulate cooperation and compliance whenregulators use increasingly graduated responsesto noncompliance.

We incorporate cooperation (the ®rst part ofTFT) into our model by hypothesizing thatregulators ``go light'' on Korean plants (bysanctioning them less) the more those plantsabate pollution by investing in pollution con-trol expenditures and the more they report®ndings from their own self-monitoring ofemissions to regulators.13 We incorporategraduated responses to repeated noncompli-


ance (the second part of TFT) by using theweighted indices of government monitoring(GM) and regulatory sanctions (SN) as inde-pendent variables in a model of formal regu-lation.

More precisely, we tested the followingsimultaneous two equation model:

PAE � f �EMP ; AGE; SALES=EMP ; OWN ;

SN ; CP�; �1�

SN � f �PAE; GM ; SM�; �2�

where PAE is annual pollution abatement ex-penditures in US$; EMP is plant-level em-ployment, a proxy for plant size; AGE is the agein years of the plant; SALES/EMP is sales (inUS$) per employee of the plantÐan admittedlycrude measure of plant productivity. OWN is adummy variable of whether the plant is owneddomestically (OWN � 1) or by foreigners(OWN � 0 for any level of foreign ownership).SN is an index of the intensity of governmentsanctions imposed on polluters for failing tomeet emissions standards. CP measures com-munity pressures on polluters (the sum of thenumber of community requests of plants toabate pollution plus the number of pollutioncontrol agreements between plants and com-munities). GM measures the intensity of gov-ernment monitoring of plants, and SM re¯ectsthe frequency of self-reporting of emissions byplants to regulators.

Eqn. (1) estimates the impact of plant char-acteristics, regulatory sanctions, and commu-nity pressures on abatement expenditures.Eqn. (2) estimates the determinants of regula-tory sanctions. In Eqn. (1), we expect pollutionabatement expenditures to be a positive func-tion of plant size, productivity, communitypressure and sanctions and a negative functionof plant age and ownership. In Eqn. (2), weexpect sanctions to vary negatively with thefrequency of plant-level reporting of self-mon-itoring results to regulators and with currentabatement expenditures. What this means inpractice is that, all other things being equal, weexpect regulators to ``go light'' on ®rms that arecooperating with regulators (those with higherlevels of abatement expenditures and higherlevels of self-reporting of emissions). All otherthings being equal, we expect sanctions to varypositively with the intensity of governmentmonitoring.

(a) Equation estimation

Because plant-level abatement expendituresand regulatory pressure (sanctions) are simul-taneously determined in a two equation model,estimation of both the abatement expenditureequation and the sanctions equation is by two-stage least squares (TSLS).14 Except for thedummy variable on ownership (OWN) and thecount variables (GM, SN, SM, and CP), esti-mation is of log-log regressions. Because itis reasonable to suspect that governmentmonitoring (GM), self-monitoring (SM), andcommunity pressure (CP) might also be si-multaneously determined, Hausman (1978)speci®cation tests were used to test for possibleendogeniety of those variables. Chi-square testsrevealed that each of those variables can betreated as exogenous and that is how they aretreated here. Because Chow F tests indicatedthat there were not signi®cant di�erences be-tween the sectors, both equations were esti-mated for the full sample.

Results appear in Table 2. In addition toreporting regression coe�cients, t tests, andadjusted R2, we also report results of tests forspeci®cation error and for heteroskedasticity.As is well known, the latter tends to be quitecommon in cross-section estimation. Speci®ca-tion error might be an important problem ifsome or all of the cross-plant variation inabatement expenditures is due to unmeasureddi�erences in production processes acrossplants. Since our sample includes a wide rangeof intraindustry di�erences within each sector,this might, in fact, be the case. While we wereunable to identify a proxy variable to allow usto include a measure of di�erences in produc-tion processes in Eqn. (1), we take some com-fort in the fact that the Ramsey Reset F test, awidely used test for speci®cation error, suggeststhat neither Eqn. (1) nor Eqn. (2) appears to besubject to speci®cation error.15 Finally, eventhough heteroskedasticity was not a problem,White's heteroskedasticity-consistent standarderrors are reported.

(b) Empirical results

What did we ®nd? Starting with the abate-ment expenditure equation (Eqn. (1) inTable 2), plant-level pollution abatement ex-penditures are positively associated with plantsize, plant-level productivity, and a dummyvariable for ownership (OWN � 1 for do-mestic ownership). Each of these variables is


statistically signi®cant. Except for the regres-sion coe�cient on ownership, these ®ndings arebroadly consistent with those reported else-where (Hettige et al., 1996). The positive rela-tionship between abatement expenditures andownership is puzzling because it suggests thatdomestically owned ®rms spend more onabatement than ®rms with some level of foreignownership. While we do not have a good ex-planation for this ®nding, it may well re¯ect thelow popular support for the country's large®rms (chaebols) that dominate industrial pro-duction and the responses by those ®rms toinsulate themselves from public criticism. Inaddition, abatement expenditures are a positivefunction of the intensity of regulatory sanctions(SN). This suggests, as expected, that a hierar-chy of sanctions exerts substantial in¯uence onabatement expenditure behavior. Finally,community pressure also exerts a positive in-¯uence on abatement expenditures.

Taken together, these variables explain 69%of the variation in abatement expenditures

across sampled ®rms. Calculation of normal-ized regression coe�cients shows that plant size(beta equals 0.52) and plant-level productivity(beta equals 0.44) exert more in¯uence onabatement expenditures than regulatory sanc-tions (beta equals 0.19), community pressure(beta equals 0.11), or ownership (beta equals0.10). Moreover, a one standard deviation in-crease in regulatory pressure (SN) exerts twiceas much impact on abatement expenditures as aone standard deviation increase in communitypressure (CP).

Turning to the determinants of regulatorysanctions (Eqn. (2) in Table 2), SN is a positivefunction of the intensity of government moni-toring and a negative function of the frequencyof plant-level self-monitoring reports. Both ofthese variables have the sign of the regressioncoe�cient that we expected and they are sta-tistically signi®cant. The positive relationshipbetween the intensity of government monitor-ing and the intensity of sanctions suggests thatKorean regulators appear to have incorporated

Table 2. Two-stage least squares regression equations a

log (PAE) SN

Constant ÿ2.76 (1.21) 2.98 (6.06)(2.29) �� (0.42)

log (EMP) 1.01 (0.14)(7.08) ��

log (AGE) ÿ0.29 (0.24)(1.20)

log (SALES/EMP) 0.73 (0.12)(6.44) ��

OWN 0.72 (0.39)(1.85) ��

SN 0.046 (0.02)(1.94) �

CP 0.17 (0.08)(2.14) ��

log (PAE) 0.0005 (0.59)(0.0008)

GM 0.24 (0.065)(3.62) ��

SM ÿ0.013 (0.005)(2.17) ��

Adjusted R2 0.69 0.31Chow F statistic 1.03 0.76White's NR2b 14.81 13.87Ramsey reset F b 0.56 0.66

a Numbers in parentheses under regression coe�cients are t values. Numbers in parentheses beside regression co-e�cients are White's heteroskedasticity-consistent standard errors.b White's NR2 is White's heteroskedasticity test statistic. Ramsey Reset F is for speci®cation error. N � 81.� Signi®cant at the 0.10 level.�� Signi®cant at the 0.05 level.�� Signi®cant at the 0.01 level.


important elements of responsive regulation intheir behavior. Both government monitoringand the sanctioning of plants re¯ect graduatedresponses. Tougher sanctions follow more in-tensive and intrusive monitoring. The negativerelationship between frequency of reporting ofself-monitoring results and sanctions, suggeststhat Korean regulators may also be following atit for tat (TFT) strategy. That is, they ``golight'' on those plants that more frequently re-port results to regulators. Taken together, thesetwo variables account for 31% of the variationin regulatory sanctions. The normalized re-gression coe�cients suggest that the intensity ofgovernment monitoring (beta equals 0.57) ex-erts substantially more in¯uence on regulatorysanctions (SN) than self-reporting (beta equals0.09).

5. IMPLICATIONS OF FINDINGS

What are the policy implications of our®ndings? Four seem particularly important.First, plant characteristics matter. Larger andmore productive plants appear to spend moreon abatement than older, smaller, less pro-ductive plants. This ®nding is not particularlysurprising. Larger plants tend to use both morefuel and more water than smaller plants and sothey need to build and maintain bigger andmore costly air and waste-water treatmentsystems. Larger plants also tend to be morevisible to both regulators and communities.This probably compels them to abate pollu-tion, or at least to appear to be doing so byinvesting in pollution control. This may beparticularly important if environmental repu-tation matters. Because smaller plants tend tobe less visible, these considerations are proba-bly less important for them. Similarly, moreproductive plants presumably have more re-sources to work with than less productiveplants and this too should make it easier forthem to allocate more resources to abatementequipment. But we did uncover one surprisingresult. Domestically-owned plants spend moreon abatement equipment than plants with somelevel of foreign ownership. While further studyis necessary to sort out why this is the case, itmay well re¯ect the low regard the public holdsKorea's chaebols and the attempts by thechaebols to protect themselves from publiccriticism.

Second, formal regulation matters. Weknow that stringent regulations and equally

tough monitoring and enforcement by envi-ronmental agencies have made it possible tobreak the link between economic growth andpollution in developed countries. Because ofthis, it should not be surprising that somethingsimilar to this can occur in developing coun-tries such as Korea once governments decideto get serious about reducing pollution. Twoother ®ndings about regulation matter. Wefound some support for responsive regulationhypotheses. Our results suggest that Koreanregulators appear to be acting as if plantsknow that failure to comply will be met by anincreasingly intrusive monitoring program andescalating sanctions. In addition, it appearsthat government regulators in Korea may beengaging in important elements of a tit for tat(TFT) regulatory strategy. Third, communitypressure also matters. Because this has loomedlarge in the Japanese experience and becauseJapan has been looked to by others in Asia,including Korea, it is not surprising thatcommunity pressure matters. What is perhapssurprising, is that it exerts an independent in-¯uence after taking the e�ect of size, produc-tivity, sector, and formal regulation intoaccount. In fact, as far as we know, this is the®rst study to demonstrate statistically that di-rect community pressure can be an importantcomponent of a tough formal regulatory pro-gram.

This leads to our last ®nding of import. Atleast in our log±log regressions, sector does notmatter. Yet as Table 1 shows, regulators spentsigni®cantly more time monitoring PRPCplants and they imposed more sanctions onPRPC ®rms. PRPC ®rms also did substantiallymore self-monitoring. Given this and the largedi�erences in means for most variables betweentextiles plants and PRPC plants, this ®nding ispuzzling. Closer inspection suggests that it maybe an artifact of the form of estimation. Whenwe estimated non-log log regression equationsof the form

PAE � f �EMP ; AGE; SALES=EMP ; OWN ;

SN ; CP�:Chow F tests suggest that there are important

di�erences between sectors.16 But non-log logregression estimation was subject to anothersigni®cant problem. Large outliers for some ofthe variables (particularly for pollution abate-ment expenditures, employment and sales)meant that robust relationships could only beuncovered by eliminating those outliers. While


converting to log-log regressions eliminated thisproblem, it also made sector unimportant. Be-cause of this, we conclude that sector maymatter, but it is not possible to see with thissample. We encourage further testing for thesigni®cance of sector.

We close with a word of caution about theweaknesses of this study. To begin with, ourmeasures of formal regulation and communitypressure are crude, as is our measure of plant-level productivity.17 Other problems may arise

because of our focus on plant-level abatementexpenditures rather than emissions. Unless thetwo are tightly correlated, results reported heremay overstate plant-level improvements in en-vironmental performance. This can happen ifplants put visible pollution control equipmentin place but fail to either run it, run it properly,and/or maintain it. Finally, both theorizing andempirical testing in this area remain weak.Until both improve, results should be inter-preted with caution.

NOTES

1. Korea's industrial policy dates from 1962. Much of

what follows draws from World Bank (1995a).

2. This included an Air Environment Preservation Act,

a Water Environment Preservation Act, a Noise and

Vibration Control Act, a Toxic Chemical Substance

Control Act, and A Solid Waste Management Act.

3. Over 1990±94, authority for monitoring and en-

forcement shifted back and forth between the regional

o�ces of the MOE and local government. This re¯ected

the broader discussion in Korea about the need to

decentralize government and devolve power. Following

a second phenol spill in the Nakdong River, ultimate

responsibility for monitoring and enforcement was

vested with the regional o�ces of the MOE in 1994

(World Bank, 1995a, p. 9).

4. For air pollution, the classes are as follows: Class 1

businesses use more than 10,000 tons of coal equivalent

per year; Class 2 uses between 2000 and 10,000 tons of

coal equivalent per year; Class 3 uses between 1000 and

2000 tons of coal equivalent per year; Class 4 uses

between 200 and 1000 tons of coal equivalent per year;

and Class 5 uses less than 200 tons of coal equivalent per

year. For water emissions, Class 1 businesses discharge

more than 3000 cubic meters of waste-water per day;

Class 2 discharges between 1000 and 3000 cum per pay;

Class 3 discharges between 500 and 1000 cum per day;

Class 4 discharges between 50 and 500 cum per day; and

Class 5 discharges less than 50 cum per day (World

Bank, 1995a, p. 27).

5. The noncompliance penalty is discussed below.

6. The number of formal complaints received by the

MOE increased from 1033 in 1990 to 2133 in 1993

(MOE, 1994, p. 227).

7. But much of this increase in budget has gone for

construction of waste-water treatment plants (World

Bank, 1995a, p. 9).

8. Warnings equaled 1459 in 1991 and 1147 in 1993.

Orders for improvement equaled 1039 in 1989; 975 in

1991; and 1051 in 1993. The MOE suspended operations

in 676 facilities in 1989; 702 facilities in 1991; and 738

facilities in 1993. Five hundred and seventy-two opera-

tions were shut down in 1990; 670 were shut down in

1991; and 738 were shut down in 1993 (MOE, 1994,

p. 23).

9. The MOE issued 3,808 improvement orders in 1989;

3451 in 1991; and 3592 in 1993. It suspended 1005

operations in 1989; 1339 in 1991; and 487 in 1993. It

revoked 61 permits in 1989; 70 in 1991; and 159 in 1993.

It sought 566 criminal prosecutions in 1989; 317 in 1991;

and 80 in 1993 (World Bank, 1995a, p. 38).

10. Based on interviews in Singapore and Korea in

November 1996 and World Bank (1995b).

11. They (Hettige et al., 1996, p. 1801) argue that

because formal regulation does not work very well in

many developing countries, it is more important to test

hypotheses about informal regulation.

12. Three pieces of evidence suggest that Korean

regulators may be engaged in TFT regulation. For

one, as mentioned in Section 3, regulators in the MOE

have adopted a color-coded system for use with regu-

lated plants. Plants rated red for more frequent viola-

tions are inspected more frequently, while those found to

be in compliance are rated blue or green and are

inspected less frequently. Second, under the MOE

Environmentally Friendly Companies Program, plants


certi®ed as `ènvironmentally friendly'' are exempted

from MOE's routine inspections program. Third,

MOE's sanctions against plants are graduated in

response to the results of monitoring and inspections.

13. As one reviewer suggested, strictly speaking TFT

refers to a game theoretic set-up where regulators

choose between two approaches (lenient and strict)

depending on the actions and reactions of regulated

plants. In order to detect this, one would need to collect

information on the sequence of moves and counter-

moves of regulators and polluters as it unfolds over

time. While our cross-plant tallying of aggregate orders,

®nes, penalties, and self-monitoring reports over a 12-

month period is indicative of TFT, it is by no means

conclusive.

14. For this, the variables EMP, AGE, SALES/EMP,

OWN, GM, SM, CP and ®ve locational dummy

variables (LOC1, LOC2, LOC3, LOC4, LOC5) are used

as instruments.

15. We took further comfort from the fact that existing

interindustry and intraindustry statistical studies

(Hettige et al., 1996; Pargal and Wheeler, 1996; and

Pargal, Mani and Hug, 1997) of the determinants of the

abatement behavior of manufacturing plants do not

appear to su�er from speci®cation error.

16. The Chow F for a structural break in the sample

for di�erent sectors for this equation is 2.92 and it is

statistically signi®cant at the 0.01 level.

17. One reviewer went so far as to state that our

community pressure variable is badly conceptualized.

As she/he stated, `Ì found in my research in Asia that

what matters is the pressure as perceived by plant

owners/managers. Communities would sometimes liter-

ally attack and set ®re to or loot polluting factories.

This news would reverberate through industry circles in

the region, a�ecting abatement behavior of plants in

the vicinity. Since managements weren't asked, we do

not know if (this kind of) community pressure in¯u-

enced management environmental decision making.''

While we agree with the intent of this comment and

have found some statistical evidence of this kind of

response by plant managers/owners to the kind of

community pressure she/he describes in a just complet-

ed study in Indonesia (Aden and Rock, 1998), this does

not mean that community requests and actual agree-

ments between communities and plants do not a�ect a

plant owner/managers' decision to install pollution

abatement equipment. The statistical signi®cance of

our community pressure variable suggests otherwise.

Moreover, our work in Indonesia suggests that pressure

as de®ned by our reviewer can in fact result in formal

pollution control agreements between communities and

polluters.

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What is Driving the Pollution Abatement Expenditure Behavior of Manufacturing Plants in Korea?