__/ PS 70HL POLICY RESEARCH WORKING PAPER 1704 Citizen Complaints China'5 exoer nce problem of relying on citizen as Environmental Indicators complaints for guidance in addressing poiiution problems Evidence from China when monitorin3g reso,_rces are scarce V)sible poiiutann get too rnuch attention ardci Susmnita Dasgupta communicies with I-..V leveis David Wheeler of literaq/ get too iilte. The World Bank Policy Research Department Environment, Infrastructure, and Agriculture Division January 1997 [POLICY RESEARCHT WORKING PAPER t170p4 Summary findings China's environmental regulators rt spond to more han Inspecton resources to less-educated, relatively "silent" 100,000 citizen complaints a year, 'I he complainit rcgions. process undoubtedly provides uie.ul infe-rmaltion Citizens' incomplete iriformatino creates the biggest hel-ps encourage corrmuniry participation in problem for regulators who retly on cornpiaints for enivironmental pol,cy. 13ut it also dir cts a bug sliate (.of guidance. To compensate for this probtlem, say Dasgupta inspecTion resources tO areas wh7ere people rend to and Wheele-, agencies should invest in public complai1n. environmental educationi targeted especially to treranyzig provincial data for 1987-93, Dasgupca comrlmuni;ties witih less schooling. 'Tlhey might also an 7heeler fir.d the subsequent allocation of remoources explore targeted Outreach programis, Since poorly biased, in terms of socil welfare. 'T he incidenict (of ed_ticattd people may ailso be more timid about comrplainis refiects potential abat!mncnf henefits and the comr,phlining. u,ntunsltv ow exposure to lilghly vIslb piollutants. More important, Dasgupta and( 'WXheeler recornmend Howevet, citi7en compkaints seem.. nor to be .ilfecrtd by giving ptrioritt-, tO rechnical r1sk- assessments in huarrnfI pollutants ,hat are iess L And al, deter -ining resoirce allocation. () L.r tine, citizen education seems to have a stror7g ;n nd-perdent etlteC 0. o Crsp ixntF sh.ot: d decline if regnilators establish strategic propensity to coimipl1ain. R iving on comnplaints a,one ri nou ocs and pursue ihem systematically, while wvould lead -o inappropriately lc,w aliocatiion of inainr ir:ing close contact with the communities affected. ' his paper -a producr ot ,lc Eu i ye!Otent, 1 otrastructuic, and Ag-iculture Division, Policv Ree arc.h Department-is par-tof a larger reffor t in1 the departrneot tf tditrstandl thae econoni 'cs ot Indnlstrril poillution co-ntro)l in developing cotmntries. I'he study was fundied by thie Ba!nk's F. -s'rrcr 8 ),p-o- t Budget un-der research project "'I'he Fconomi 5of [rtdistriai Pollution k-ootlrol in Developing Countri s (I-PO e780-`0). )Copies ofr this tar-r are available free front thle World Bank, 1818 H 8.rcreer NW, Washington. DC 4I PH. P it,lae cnt t :gtmF 0 I'Xivn de C .Stf . ronir NI 0-lO 9, telephorie 2()2 45'-9121, fax 202- 522-3210. Internet acidress ecca aro-. r ,ut irs i u k.org, fanuary I 00 ( p7 gf ) 1 he l'olicv Research Wotifking Plcer Se ies di,serniatcs t.e !InaJns w o,;k in progress to encoage the exchange of ideas abot develo ment issues. An objei rit be srt rcs :s to et f- the fingsd oit elo e n ifb he presentatro'o are less than fully polished. The papers carry the nimes of the aurhors lnI should he c ited accrordingly. 7he tndings, interpretations, and conclusions expressed in this puapep are entirely these crf the nath,es. Ih ievc ?mt niccssaroiy reobesent th' uicu ol the World Bank, its Executive Directors, or the countries they represent ,0,--eIj i 1.'.ti.-. t )st2wlet!f} Ceite"r CITIZEN COMPLAINTS AS ENVIRONMENTAL INDICATORS: EVIDENCE FROM CHINA by Susmita Dasgupta* David Wheeler PRDEI * Respectively Economist and Principal Economist in the Environment, Infrastructure and Agriculture Division, Policy Research Department, World Bank. This paper has been produced in a collaborative program supported by China's National Environmental Protection Agency (NEPA), the Tianjin Environmental Protection Bureau (TEPB) and the World Bank's Country Department EA2. Funding has been provided by the World Bank's Research Support Budget and the Social and Environmental Consequences of Economic Growth Fund. We are grateful to our colleagues Hua Wang and C. H. Zhang for their assistance in developing the data base for this study. Thanks also to Tom Tietenberg, Gunnar Eskeland and Mainul Huq for many useful comments. 1. Introduction Much of the pollution control literature assumes that government regulators act as sole agents for the public's environmental interest. l Taking the opposite tack, Coase and his followers have highlighted the conditions under which private agents can solve pollution problems without regulators.2 In this paper, we adopt an institutional perspective which pragmatically blends the two approaches. In practice, regulators often realize that they are ill-inforned about pollution problems because monitoring is costly. To fill the gap, they may solicit complaints from citizens or communities damaged by pollution. If these parties are also engaged in direct negotiations with polluters, they may enhance their bargaining position by threatening to complain to the regulators. Local conditions will determine the relative importance of direct regulation, responses to complaints, and community pressure in inducing pollution abatement.3 This mixed approach may be particularly important in developing countries, where monitoring resources are scarce or nonexistent. To compensate, pollution control agencies often focus their resources on responding to citizen complaints. For exarnple, FEEMA, the pollution control agency of Rio de Janeiro State (Brazil), currently devotes nearly 100% of its inspection resources to complaints. After setting aside 50% of its resources for targeting priority polluters, Sao Paulo's pollution control agency (CETESB) allocates the remainder to complaints. In Indonesia, the national pollution I For a comprehensive treatment, see Tietenberg (1995). 2See Coase (1960, 1988). 3For a more detailed discussion of community-plant interactions, see Afsah, Laplante and Wheeler (1996); Pargal and Wheeler (1996); and Hettige, Huq, Pargal and Wheeler (1996). control agency (BAPEDAL) has very few inspectors but allocates much of their time to its JAGATIRTA program for complaint response. And, as we will show, China's provincial and local regulators respond annually to more than 100,000 citizen complaints.4 Are complaints a good substitute for direct monitoring? To date, this question has not been systematically addressed. Complaints are undoubtedly a source of low-cost information, since polluting facilities are often apparent to their neighbors even if they are invisible to government agencies. There are also compelling social and political arguments for agency responsiveness to citizen complaints about polluters. However, there are good reasons for skepticism about complaint-driven resource allocation. Plaintiffs may lack sufficient information to distinguish between 'nuisance' emissions and those which are truly hazardous. Colorless, odorless toxics and heavy metals may escape notice altogether. Furthermore, some individuals or communities may have higher propensities to complain than others, regardless of the objective situation. If regulators respond passively to complaints, aggressive plaintiffs may capture most of the available resources. In this paper, we use a new panel data set to assess the role of citizen environmental complaints in China's pollution control system.5 Section 2 describes the pattern of complaints and agency responses. Section 3 develops a testable model of 4Complaint response systems in Brazil, China and Indonesia are familiar to the authors from collaborative work with FEEMA, CETESB, BAPEDAL and China's National Environmental Protection Agency (NEPA). 5In this paper, the term "province" refers to provinces, autonomous regions and municipalities which are directly affiliated with the central government 3 complaint generation based on individual utility maximization. Data sources and estimating equations are treated in Section 4; econometric results are reported in Section 5, along with simulations which explore the implications. The final section provides a summary and conclusions. 2. Environmental Complaints in China China's citizens are far from passive about the environmental performance of neighboring factories. During 1991-93 the environmental authorities received over 130,000 complaints per year, mostly related to air, water and noise pollution (Table 1). Plaintiffs visited provincial and local regulators over 79,000 times per year and sent more than 53,000 letters. Air pollution received the most attention, with over 20,000 letters and 15,000 visits per year. Noise pollution accounted for over 27,000 complaints, while water pollution dropped from 35,000 to around 23,000.6 Table 2 shows that the propensity to complain varies widely across China's provinces. In 1993, there were around 30 complaints per 100,000 individuals in Shanghai and Tianjin, but less than 5 per 100,000 in Gansu, Xinjiang and Inner Mongolia. A provincial map of the propensity to complain (Figure 1) shows that its geographic distribution is far from random. The incidence of complaints is generally highest in the urban/industrial centers of east China; lower in the middle provinces; and lowest in China's least-developed regions -- the western hinterlands. Across provinces, 6 We have no explanation for the fall in water pollution complaints, which seems to have affected personal visits but not letters. This could represent a lagged reaction to a large increase in water pollution charges which began in 1990. However, it seems very doubtful that the impact could have been this large. For an extensive discussion of Chinese water pollution charges and their impact, see Wang and Wheeler (1996). 4 the correlation coefficient of income per capita and environmental complaints per capita is .81. Complaints do not necessarily elicit agency action, but the data in Table 3 suggest that regulators are generally responsive. With the exception of Yunnan (1992) and Qinghai (1993), agency response rates were all between 70% and 100% during the sample period. The cross-provincial correlation with income per capita is relatively weak (.33), and the map in Figure 2 reveals no particular regional pattern. A variety of local institutional and historical factors may play important roles. Whatever the determining factors, the data in Table 3 make one thing very clear: China's environmental authorities respond to a very large number of complaints each year, absorbing much of their inspectors' available time. 3. Why Complain? Why do people complain to the authorities about pollution? We follow standard economic theory in suggesting that they do so when the expected benefits from agency action warrant their own investment of time and effort. However, we do not assume that expected benefits reflect accurate perceptions -- people may be very ill-informed about the pollution problems they face. Using a constant-elasticity utility specification, equation (3.1) represents the decision problem for a representative individual in province r. His expected utility from complaining depends on the expected pollution reduction from agency action; the value of this reduction (a function of income, existing pollution levels and perception of risk); and the individual's understanding of the problem (which 5 we hypothesize to be a function of education). The unit cost of a complaint is the opportunity cost of the individual's time (proxied by income). 6 (3.1) Ur = -p(c)r Er 2Yr3 - 4CrY, Ur = Net utility of complaining Cr = Complaints p (c)r = Pollution damage suffered by the individual Er = Education Yr = Income Equations (3.2) relate pollution in a given province to health damage. Expected damage per individual increases at the margin (O1 >1) with ambient pollutant concentration (rj). Concentration is in turn a function of total emissions (P), normalized by provincial area (T). Apart from transient disturbances, exposure should increase with elasticity t as more pollutant is discharged into a fixed volume of air or water. Thus, expected individual health damage can be modeled as a function of pollution per unit area (P/T), or pollution density. Pr = ooir I PrPr -o1 Pr~~~ where: o0 = 0040,o1 = 01 For the representative individual, we model the expected impact of complaints as: (3.3) - Cr T T 7 where C, = complaints per capita. Substituting (3.3) into (3.2), and the latter into (3.1), we obtain an expression for net utility as a function of Cr: (34) Ur=O0 T- P YcoI kEr r3-4CrY, The representative individual's utility-maximizing complaint level is given by (3.5), which is the solution to: aUr _O aCr (3.5)Cr=[jj-1 f 6 Er Y where 6 = 7o A + 1. For interpretation of the econometric results, it is useful to note that El 1 >0= 6 >1 It is also important to note an unstated theoretical implication of equation (3.5), which reflects private benefit-cost calculations. Plaintiffs invest their own time and effort in complaining, but are generally not compensated for the abatement benefits which successful complaints will generate for their neighbors. This will create some divergence between the actual level of complaints (and agency actions) and the socially-optimal level, even if citizens are fully-informed about their pollution problems. Nevertheless, econometric estimation of equation (3.5) can provide useful insights into the reliability of citizen complaints as guides to agency resource allocation. For greatest reliability, the estimated parameters should meet several conditions. First, 8 the incidence of complaints should be positively affected by intensity of exposure to each harmful pollutant. If only visible pollutants are significant, then complaints provide an incomplete damage index. Secondly, higher-income areas should have more complaints per capita because willingness-to-pay for environmental improvement increases with income. If the opposite finding holds, then complaints are a biased index of potential benefits from pollution abatement. Third, education should have no independent effect once controls are introduced for local income and pollution exposure. A positive effect would imply significant problems of information or, perhaps, 'intimidation' in poorly- educated populations. In either case, complaints would provide a biased guide to agency resource allocation. 4. Data Sources and Estimating Equation 4.1 Data Sources For the empirical analysis in this paper, we have constructed a province-level panel database from official yearbooks available in China: The China Environment Yearbook (1987-1993) and China Statistical Yearbook (1987-1993). Specific sources of data are reported in Table 4. 4.2 Estimating Equation With composite parameters (X), (3.5) yields an estimating equation for the incidence of complaints. Since our provincial data on complaints are not divided into air- and water-related categories, we introduce both air and water emissions densities: 9 (3.6) logCr = o +0 log j l+iog ) lA3 iogc logE +X5 gy +E where Cr* = Environmental complaints per 10,000 population ADr, Total airborne dust (particulate) emissions As,= Total airbome SO2 (sulphur dioxide) emissions Wcr = Total waterborne COD (chemical oxygen demand) emissions Tr = Provincial area Er = Provincial literacy rate Yr = Provincial real consumption per capita (the best available proxy for income) Er = A random error term To be a reliable environmental monitoring index, the incidence of complaints should meet the following conditions on signs and magnitudes of estimated parameters (the O3's are from (3.5)): l,j X2, X3>> 0;2 2=0; 13>1 + k5>1 5. Results 5.1 Regression Results We have estimated equation (3.6) using a random effects model which captures both intertemporal and interprovincial effects (Table 5). We have run two sets of regressions, since our data on SO2 emissions are available for a shorter period (1991- 1993) than the other emissions data. For the shorter period, we have included all three pollutants. Our results on variables other than SO2 density are very similar in both sets of regressions. Dust (suspended particulate) density has a consistently significant, large impact on the incidence of complaints. Our random effects estimates for the entire period 1987- 10 93 suggest an elasticity of approximately .20 for particulate density: An increase of 1% in air emissions induces an increase of approximately .2 % in citizen complaints to the environmental authorities. However, neither SO2 density nor COD density has any measured impact. Estimated income and education effects are both positive and highly significant. After the opportunity cost of time is accounted for, the income results suggest an elasticity of demand for environmental quality somewhat greater than 1.4 (p3 > 1 > 1). This is in line with previous work on China (Wang and Wheeler, 1996) and willingness-to-pay surveys in the OECD countries.7 The education results are particularly striking. Controlling for income and pollution density, they suggest a literacy-elasticity (P2) somewhat above the range 1.7-1.8 (P2> X3 > 0). Remarkably, a 1% increase in the literacy rate seems to induce a 2% increase in environmental complaints. 5.2 Simulation Results We explore the implications of our econometric results with simulations over the existing range of provincial income, pollution density and education. Dividing the twenty-nine Chinese provinces into two income groups, we use group medians (750 and 1330 yuan/year) to define low- and high-income prototypes. Within each income group, we use minimum and maximum levels of particulate pollution density and literacy to establish low and high classifications for these variables. The low-income group has literacy rates ranging from 60-84% and particulate densities from 0.1 - 2.0 tons/sq. km. 7We are indebted to our colleague Maureen Cropper for the latter point. 11 Corresponding ranges for the high-income group are 77-90% and 0.4 - 4.0 tons/sq. km., respectively. Using low and high measures for income, literacy and pollution, we generate simulation results for eight prototype provinces. We predict the incidence of complaints using the parameter estimates in Table 5.4 which exclude the two insignificant pollution density measures (COD, SO2). Our results (Table 6) suggest similar orders of magnitude for the impacts of the three variables.8 With air pollution density and literacy held constant, the estimated incidence of complaints in our high-income provinces is about 110% higher than in the low-income provinces. Pollution density also has strong effects, with a median increase in complaint incidence of 75% from lightly-polluted provinces to ones with high emissions densities. Tlhe most striking simulation result is the predicted impact of education. At constant pollution density, the predicted complaint incidence is 90% higher in poor, high- literacy provinces than in poor low-literacy provinces. The corresponding increase for rich provinces is 30%. Thus, for poor communities, an increase of literacy over the 8 Table 6 presents our results in three steps. First (Table 6a), we tabulate median values by category for income, particulate density, literacy and complaints per 100,000 inhabitants. In the second step (Table 6b), we recode these values as Low or High. Finally, we successively compute High/Low ratios for predicted complaints by deterninant, holding the other two determinants constant. Table 6b is organized to illustrate the computation for income. The first row has a Low value for income and Low values for both pollution and literacy; predicted complaints are 4.0 per 100,000. The fifth row has a High value for income, but Low values for the other variables; predicted complaints are 10.7 per 100,000. Division of 10.7 by 4.0 yields 2.7, the first High/Low ratio in the Income column in Table 6c. After division across four pairs of rows, the High/Low ratios are 2.7, 2.3, 1.9 and 1.7. The median High/Low ratio is 2. 10, reflecting a median increase rate of 110%. 12 existing range (60-84%) has an impact on complaints which is roughly equivalent to a doubling of income or a tenfold increase in air pollution density. 5.3 Implications Should citizen complaints guide regulatory resource allocation? On the positive side of the ledger, our results suggest that the incidence of complaints is positively related to willingness-to-pay for environmental improvement. The income parameter estimates in Table 5 incorporate three factors: The income-elasticity of demand for environmental quality (f2); the unit opportunity cost of time, which rises proportionately with income; and the individual's expected return from complaining (reflected in ycol,3l). Since the latter is positive (or no one would complain), the parameter 8 in (3.6) is greater than one. The implied income-elasticity of demand in our econometric result (Table 5, column 1.4) is greater than 1.44: As income rises, people complain more even though the opportunity cost of time rises proportionately with income. Controlling for other factors, the effect of income on complaints provides China's regulators with appropriate information about pollution control benefits. Our evidence also suggests that complaints are strongly affected by exposure to some forms of harmful pollution. Dust (particulate) intensity, a highly-significant determinant of complaints, has been identified by numerous international studies as a major source of human health damage. However, a strongly cautionary note must be added: It may well be the visibility of particulate pollution which induces complaints, rather than its damaging impact. Sulphur dioxide emissions and organic water pollution (COD), which are less visible than airborne dust, are not significant determinants of 13 complaints, even though there is good reason to believe that they cause significant damage in China.9 These results suggest that complaints are a significantly biased index of environmental darnage. Another cautionary note is introduced by our results for education. Provinces with relatively low literacy rates have significantly lower propensities to complain about pollution (ceteris paribus). Undoubtedly, part of this effect has to do with lack of information: Citizens will little or no formal education may not understand the harmful effects of pollutants. However, illiteracy may also have an important 'silencing' effect because people with little formal education have no confidence in their ability to influence the authorities. In either case, the education effect significantly reduces the value of complaints as a resource allocation signal to regulators. 6. Summary and Conclusions China's environmental regulators respond to over 100,000 citizen complaints per year. The complaints process undoubtedly provides some useful monitoring information, and an important avenue for community participation in environmental policy. However, it also directs a major share of China's inspection resources toward areas where individuals or communities have a high propensity to complain. 9While high levels of COD do not directly affect human health, they have undoubtedly depleted fish stocks in many Chinese rivers. Recent research on air pollution and health in China suggests that SO2 may have a greater impact than suspended particulates. For Beijing results, see Xu, Gao, Dockery and Chen, (1994); for Shenyang results, see Xu, Xu, Chen, Kjellstrom, et. al., (1995). The Beijing and Shenyang studies both use measures of suspended particulates, rather than fine particulates. Since fine particulates are now believed to cause most of the health damage, there is at least the possibility that the SO2 results are strong because of a correlation with fine particulate concentration. It may be the composition of fine particles, rather than their mere presence, which is the major determinant of health damage. This is still an open research question. 14 Unfortunately, our results suggest that the resulting allocation is subject to significant bias from a social welfare perspective. We do find that the incidence of complaints reflects abatement benefits and the intensity of exposure to highly visible pollutants. However, citizen complaints do not seem to be effected by harmful pollutants which are less visible. Furthermore, our results suggest that basic education has a strong, independent effect on propensity to complain. Reliance on complaints alone would result in inappropriately low allocation of inspection resources to less-educated, relatively silent' regions. We conclude with some potential policy implications of our results. First, incomplete information seems to be a major culprit in this affair. Regulators who rely on complaints should therefore consider large-scale environmental education programs, paying particular attention to communities with lower levels of schooling. Since poorly- educated people may also be more timid about complaining, targeted outreach programs in their communities could be explored. Secondly, our results imply that technical risk assessments should have priority status in determining agency resource allocation. Over time, citizen complaints should fall if regulators establish strategic priorities and pursue them systematically while maintaining close contact with affected communities. 15 References Afsah, S., B. Laplante and D. Wheeler, Controlling Industrial Pollution: A New Paradigm, Policy Research Department Working Paper (forthcoming), World Bank. Coase, R.H., 1988, The Firm, The Market, and the Law, (Chicago: Chicago Press) Coase, R.H., 1960, "The Problem of Social Cost", Journal of Law and Economics, 3, pp. 1-44 Hettige M., M. Huq, S. Pargal and D. Wheeler, 1996, "Determinants of Pollution Abatement in Developing Countries: Evidence from South and Southeast Asia," World Development, December. Pargal, S. and D. Wheeler, 1996, "Informal Regulation in Developing Countries: Evidence from Indonesia," Journal of Political Economy, December. Tietenberg, T., 1995, Environmental and Natural Resource Economics (Chicago: Scott Foresman, 4th Edition) Wang, H. and D. Wheeler, 1996, Pricing Industrial Pollution in China: An Econometric Analysis of the Levy System, Policy Research Department Working Paper No. 1644, World Bank. Xu, Xiping, J. Gao, D. Dockery and Y. Chen, 1994, "Air Pollution and Daily Mortality in Residential Areas of Beijing, China," Archives of Environmental Health, 49(4), 216-22 Xu, Z.Y., X. Xu, C.H. Chen, T. Kjellstrom, et. al., 1995, "Air Pollution and Daily Mortality in Shenyang" (mimeo.) 16 Table 1: Environmental Complaints in China 1991 1992 1993 Total Letters Received 55,775 55,340 53,752 Problem Area: Water Pollution 12,560 11,207 11,423 Air Pollution 20,481 20,625 19,586 Solid Waste 1,461 1,648 1,489 Noise 16,845 17,732 17,320 Others 4,428 4,128 3,934 Total Visits 79,313 79,112 84,743 Total Letters + Visits 135,088 134,452 138,495 Total Number of Issues from Visits* 55,584 39,969 44,455 Problem Area: Water Pollution 22,771 10,399 11,576 Air Pollution 15,859 14,402 15,999 Solid Waste 2,474 1,431 1,421 Noise 10,969 10,785 12,542 Others 3,511 2,952 2,917 * One complaint issue may involve more than one visit. 17 Table 2: Environmental Complaints per 100,000 Inhabitants Province 1987 1988 1989 1990 1991 1992 1993 Shanghai 55.0 43.4 31.3 43.6 34.9 32.1 31.2 Tianjin 26.2 24.9 24.6 26.2 19.8 16.9 28.4 Beijing 28.7 29.3 24.9 28.4 30.2 23.9 26.9 Guangdong 19.8 17.3 17.9 22.5 20.9 21.9 22.6 Zhejiang 29.7 22.8 21.5 22.0 22.0 19.3 21.5 Liaoning 15.7 16.4 20.2 18.5 20.9 20.3 21.4 Hainan -- 14.1 12.8 11.7 10.4 13.2 17.4 Heilongjiang 13.7 10.6 8.2 11.2 15.2 16.4 16.2 Jilin 17.5 18.7 21.4 17.2 14.7 13.7 15.4 Jiangsu 16.3 15.8 13.7 15.5 15.8 14.6 14.6 Jiangxi 6.0 9.0 9.7 7.3 9.2 10.6 12.1 Shandong 10.3 13.8 11.9 10.0 9.6 10.5 12.0 Shanxi 7.5 12.8 13.2 10.3 12.8 15.9 11.9 Hebei 13.0 13.1 14.0 10.7 13.3 11.3 11.3 Guangxi 12.0 9.4 9.4 11.4 11.8 12.1 11.2 Fujian 10.5 6.3 9.1 13.8 12.0 11.3 11.1 Hunan 22.3 16.7 14.4 15.7 15.0 14.2 10.8 Guizhou 6.5 5.8 6.2 9.2 13.4 7.4 10.0 Sichuan 11.3 8.8 7.9 9.0 7.7 7.3 8.0 Henan 14.9 12.1 13.1 11.0 8.1 7.3 7.2 Hubei 10.2 9.5 9.8 7.4 7.6 8.2 7.0 Ningxia 5.1 6.1 1.6 17.9 7.9 8.4 6.4 Qinghai -- 18.2 31.4 47.7 1.4 3.8 6.4 Shaanxi 7.3 10.3 7.7 10.9 9.6 7.2 6.3 Yunnan 4.8 3.0 3.3 4.4 4.0 4.7 6.0 Anhui 4.0 5.4 4.3 4.9 4.0 4.9 5.1 Inner Mongolia 6.2 5.7 6.3 5.3 7.0 5.8 4.8 Gansu 1.7 2.8 3.2 3.3 3.5 3.2 4.7 Xinjiang 3.9 3.5 3.41 3.6 3.6 2.6 3.8 18 Table 3: Percentage of Environmental Complaints That Generated an Agency Response Consumption Per Capita Province 1991 1992 1993 (yuan/yr) Beijing 77.0 99.3 99.8 1549 Shanghai 93.9 96.6 98.5 3262 Ningxia 89.3 100.0 98.0 810 Hubei 97.0 91.3 97.0 988 Tianjin 94.6 95.6 96.7 1654 Sichuan 86.1 95.2 95.9 747 Heilongjiang 92.0 85.6 95.7 1370 Liaoning 93.9 92.4 95.2 1505 Shandong 90.6 97.6 94.9 824 Inner Mongolia 81.9 83.4 94.6 863 Gansu 84.9 88.3 94.0 656 Guangdong 92.4 93.8 91.9 1546 Fujian 82.8 88.5 91.6 1323 Anhui 90.9 85.4 91.1 763 Hunan 94.7 93.0 90.2 889 Jiangsu 90.4 93.1 89.9 1109 Zhejiang 78.5 89.5 89.0 1295 Yunnan 83.6 55.9 87.4 838 Shaanxi 92.7 88.8 84.6 741 Hebei 85.6 90.5 84.4 853 Jilin 83.4 93.5 82.5 1143 Jiangxi 92.0 81.0 82.0 695 Shanxi 75.8 79.0 81.4 871 Henan 84.3 71.7 81.4 592 Guizhou 77.4 70.2 79.0 576 Guangxi 94.1 93.8 78.3 752 Xinjiang 83.9 88.8 74.8 1070 Hainan 82.8 75.8 73.7 1136 Qinghai 78.3 86.4 46.8 908 19 Table 4: Sources of Data for Twenty-Nine Chinese Provinces China Environment Yearbooks, 1987-1993 (1) COD (chemical oxygen demand) emissions (2) Dust (suspended particulate) emissions (3) SO2 emissions (4) Complaints registered with environmental authorities (5) Responses to complaints by environmental authorities China Statistical Yearbooks, 1987-1993 (6) Population (7) Provincial area (8) Consumption per capita (9) Literacy rate 20 Table 5: Regression Results Regression Variables C* = Environmental complaints per 10,000 inhabitants AD = Total airborne dust (particulate) emissions As = Total airborne SO2 (sulphur dioxide) emissions Wc = Total waterborne COD (chemical oxygen demand) emissions T = Provincial area E = Provincial literacy rate Y = Provincial real consumption per capita Equation 1.1 1.2 1.3 1.4 Period 1991-1993 1991-1993 1987-1993 1987-1993 Dependent Log C Log C Log C Log C Variable Random Effects Random Effects Random Effects Random Effects Coef t Coef t Coef t Coef t Intercept -10.80** -4.54 - 11.20** -5.16 -9.98** -3.70 -10.84** -4.54 Log (ADJT) 0.30** 2.85 0.33** 3.49 0.19** 3.34 0.21** 5.16 Log (AS/T) -0.08 -0.98 -0.07 -0.93 Log (Wc/T) 0.03 0.42 0.04 0.72 Log E 2.05** 3.44 2.16** 3.98 1.67** 2.53 1.83** 2.99 Log Y 0.30** 2.18 0.29** 2.16 0.42** 2.11 0.44** 3.11 No. of Obs. 87 87 203 203 Adjusted 0.84 0.85 0.73 0.73 R2 ** significant at 5% 21 Table 6: Simulation Results Table 6a: Group Medians Income Class Per Capita Air Pollution Literacy Rate Complaints Consumption Density (%) per 100,000 (yuan/year) (tons/sq. km.) Inhabitants Low 750 0.1 60 4.0 Low 750 2.0 60 7.5 Low 750 0.1 84 7.4 Low 750 2.0 84 13.9 High 1300 0.4 77 10.7 High 1300 4.0 77 17.4 High 1300 0.4 90 14.3 High 1300 4.0 90 23.2 Table 6b: Group Categories Complaints Income Class Air Pollution Literacy Rate per 100,000 Density Inhabitants Low Low Low 4.0 Low High Low 7.5 Low Low High 7.4 Low High High 13.9 High Low Low 10.7 High High Low 17.4 High Low High 14.3 High High High 23.2 Table 6c: Group High/Low Ratios for Complaints per 100,000 Inhabitants Income Class Air Pollution Literacy Rate Density 2.7 1.9 1.9 2.3 1.9 1.9 1.9 1.6 1.3 1.7 1.6 1.3 22 Figure 1 Environmental Complaints/ Population (10,000) M 50 11.0109to 1.621 KM> >.621 to 3,120 _ 0 500 1000 ort X Missing Figure 2 % of Complaints Received which generate Agency Response 1993 ^|l i %2d> 4 A < < C C l | ! 11 l@ ! ~~~~~~~Agency Response Rates # , ! W b S S tS8'~4881o 81.415 KM 495 233 to 99 804 0 500 1000 17 C Missing Policy Research Working Paper Series Contact Title Author Date for paper WPS1678 Financial Development ana Ecorsmic Ross Levine October 1996 P Sintim-Aboagye Growth Views and Agenda 38526 WPS1679 Trade and the Accumulatiorn :id P ier .,ario Pad oan November 1996 M Patena Diffusion of Knowledge 99515 WPS1680 Brazil's Efficient Payment S'< tr kcioberi Listfieid November 1996 1 ish!be A Legacy of High Inflation FnrnarMcrntes-Negrel 38968 WPS1681 lndia in the Global S-conun-i Miian Brahmbhatt NovenLer 1996 S. Crow '.' oriflivasian ) 73 WPS1682 is the "Japan Probleme Pee! r e, Qtsubc. q:vemnber 1996 J Queen How Problems in Japanrs Finar-:'i Mas;iaieo 1-sutiurr- 33'740 Sector Coulid Affect Develo'ncn Regions WPS1683 High Real InteresL Rates Q ,:&j;t2r J' t: November 1996 N Ca-t;lln'i Risk, and Bank Rfecapi`aiizit- .s t334 WPS1684 The Whys and Why Nors .XDOn t'vrmou;-hut Nniernoer 1996 S'i ir.nmAhnraqye Firms' Choice of Debt Matur J suiO,aV M .7rvir "6 4 WPS1687 Regionalismr versus Muit,iateNs- ..l iK . ;*'&tl's ,ner 10796 A e.-or,-Vvalters WPS1688 Risk, Taxpayers, and trie R.P;e ;A' 4 'sir :.'l-,. r'rfr-er 1996 Government in Project Sra,-'< i 0 WPS1689 Is Economic Ana!ysis of 6rn ,. ember 1996 K < ^.,f:>ader Still Useful? WPS1690 Stock Markets, S72a')s- . ro>