metadata: authors: 0: author: Dasgupta, Susmita
1: author: Mody, Ashoka
2: author: Roy, Subhendu
3: author: Whe
docna: 0: docna: Environmental regulation and development : a
            cross-country empirical analysis
docty: Policy Research Working Paper
subtopic: Environmental Strategy,Social Policy,Legal Products,Environmental & Natural Resources Law,Judicial System Reform,Environmental Management,Common Property Resource Development,Hydrology,Food Security,Legal Reform,Legislation,Regulatory Regimes,Global Environment
teratopic: Macroeconomics and Economic Growth
abstracts: cdata!: The authors develop comparative indices
            of environmental policy and performance for 31 countries
            using a quantified analysis of reports prepared for the
            United Nations Conference on Environmental and Development.
            In cross-country regressions, they find a very strong,
            continuous association between their indicators and national
            income per capita, particularly when adjusted for purchasing
            power parity.  Their results suggest a characteristic
            progression in development.  Poor agrarian economies focus
            first on natural resource protection.  With increased
            urbanization and industrialization, countries move from
            initial regulation of water pollution to air pollution
            control.  The authors highlight the importance of
            institutional development.  Environmental regulation is more
            advanced in developing countries with relatively secure
            property rights, effective legal and judicial systems, and
            efficient public administration.
repnme: repnme: Environmental regulation and development :
            a cross-country empirical analysis
display_title: Environmental regulation and
            development : a cross-country empirical analysis
listing_relative_url: /research/1995/04/697495/environmental-regulation-development-cross-country-empirical-analysis
topicv3: Agriculture and Food Security m1326205 435,Water m1326522 137,Personal Property Rights m1326571 1907,Environmental Laws and Regulations
            m1326889 849,Environment, Natural Resources and Blue
            Economy m1327391 566
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Macroeconomics and Economic Growth
origu: Environment, Infrastructure and Agriculture Division
no_of_pages: 34
model_extractions: [POL I(Y RESI ARCII WORKING PAPER 1448

# Summary findings

l)asgupta, Mody, Roy, and Wheeler develop comparative indices of environmental policy and performance **for** 31 countries using a quantified analysis of reports prepared for the Ulnited Nations Conference on Environment **anid** Developmentn In cross-country regressions, they find a very strong, continuous association betwcen their indicators and national income per capita, particularly whcn adjusted for purchasing power parity.

natural resource protectin. With increased urhaniaiii'ue and industrialization, countrics move from initial regulation of water pollution to **air** pollution contrnl The authors highligilt **the** importance of institutional developmcnt. Environmental regulationi **is moBre** advanced in developing countries with relatively **secuirc** property rights, effective legal and judicial systems, and efficient ptublic **administration.** Their results suggest a charactcristic progression in development. Poor agrarian economies .ocus first on This paper **-** a product of the Environment, Infrastructure, and Agriculture Division, Policy Research Depat tment -- is part of a larger effort in the department to study the relationship between environmental regulation and economic development. Copies of the paper are available frec from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Elizabeth Schaper, room NIO-037. extension 33457 (27 pages). April 1995.

_The Policy_ **_Research_** _Working Paper_ **_Series_** _disseminates the findings of_ **_uwk_** _in pogress to encourage the exchange of idLas abIout development issues. An_ **_objectiuv_** _of_ **_the_** _series is to_ **_get the_** _findings out quickly. even if_ **_the_** _presentations_ **_are less_** _than_ **_fully polished. The_** _papers_ **_carry the names_** _of_ **_the_** _authors and should_ **_be_** _used and cited accordingly._ **_The findings,_** _interpretations. and conclusions_ **_are the_** _authors_ **_own_** _and should not_ **_be_** _attributed to_ **_the_** _World Bank._ its _F.recutive Board of Directors._ **_or_** _any of its mernber countries._ Produced by the Policy Research Dissemination Center
# ENVIRONMEMTAL REGULATION AND DEVELOPMENT: A CROSS-COUNTRY EMPIRICAL ANALYSIS

by Susmita Dasgupta* Ashoka Mody Subhendu Roy David Wheeler S. Dasgupta and S. Roy are Consultants and D. Wheeler is Principal Economist in the Environment, Infrastructure and Agriculture Division of the World Bank's Policy Research Department. A. Mody is Principal Economist in the Private Sector Development and Privatization Division of the World Bank's Cofinancing and Financial Advisory Services Department.
# **EXECUTIVE SUMMARY**

Since the Stockholm Conference on Environment and Development in 1972, many countries have taken steps to mitigate environmental damage. More systematic comparative analysis of countries' environmental performance would undoubtedly help clarify the major policy issues and options. Unfortunately, comparable data on regulatory measures are available only for developed countries, and even these data are frequently scanty.

In this paper, we undertake a comparative assessment using environmental reports presented to tlLe United Nations Conference on Environment and Development (UNCED, 1992) by 145 countries. From the information in these reports, we have developed a set of indicators which measure the status of environmental policy and performance. This paper describes our methodology, the indices, **aiid** some results from a statistical analysis of their relationship to other more conventional measures of socioeconomic development.

The UNCED reports are similar in form as well as coverage, and permit cross-country comparisons. To an impressive degree, they seem to reflect real environmental conditions and issues. For this exercise, we have randomly selected 31 UNCED reports from the total of 145 (see Table 2A, p. 6). These 31 countries range from highly industrialized to extremely poor, they are drawn from every world region, and they range in size and diversity from China to Jamaica.

Our analysis focuses on three dimensions of environmental policy and performance: Overall, "Green" sector, and "Brown" sector. We develop and test a set of hypotheses about regulatory development which can be summarized as follows:

- Overall environmental performance should be positively correlated with:

- 1) Income per capita;

- 2) Degree of popular representation;

- _3)_ Freedom of information;

- 4) Security of property rights;

- 5) Development of the legal and regulatory system.

Controlling for these variables,

- "Green" sector indices should be positively correlated with:

- 1) Rural population density;

- 2) Agricultural and forest production share of national output.
- E"Brown" sectors indices should be positively correlated with:

- 1) Particular focus on public health, indexed by life expectancy;

- 2) Urban share of total population;

- 3) Urban populaFion density;

- 4) Manufacturing share of national output.

Our analysis of overall regulatory performance reveals strong cross-country associations with income per capita, security of property rights, and general development of the legal and regulatory system. Surprisingly, however, we find only insignificant or perverse associations with degree of popular representation and freedom of information.

For both the Green and Brown indices, performance is again strongly associated with income per capita, freedom of property and (in small samples) measures of regulatory efficiency. The two specifically rural-sector variables (population density; proportion of GDP in agriculture and forestry) are only weakly associated with the Green index. T'e fit is much better for the Brown index: degree of urbanization, population density and manufacturing share in GDP all have the expected signs and relatively high significance. Life expectancy as a proxy for public health priority has no independent effect.

In summary, our findings suggest that a detailed, quantified analysis of the UNCED reports can yield comparable and plausible indices of environmental policy performance across countries. Cross-country variations in our environmental index are wellexplained by variations in income per capita, degree of urbanization and industrialization, security of property rights, and general administrative efficiency.
# 1. **Introduction**

Since the Stockholm Conference on Environment and Development in 1972, many countries have taken steps to mitigate environmental damage. General environmental legislation is already common, although detailed rules and regulations are still far from universal. In many developing countries, it is clear that enforcement of environmental laws has been hampered by inadequate staffing and funding. Anecdotes abound, but more systematic comparative analysis of countries' environmental performance would undoubtedly help clarify the major policy issues and options. Unfortunately, comparable data on regulatory measures are available only for developed countries, and even these data are frequently scanty.

At present, therefore, comparat:.ve analysis must begin with basic data construction. One promising source is the set of environmental reports presented to the United Nations Conference on Environment and Development (UNCED, 1992) by 145 countries. The reports are reasonably comparable because the UN imposed a standard reporting format.

Using a multidimensional survey of 31 national UNCED reports, we have developed a set of comparative indices for the status of environmental policy and performance. This paper describes our methodology, the indices, and some results from a statistical analysis of their relationship to other more 1
conventional measures of socioeconomic development. In the following section, we begin with a description of the UNCED reports. Section 3 explains our indexing method, while Section 4 sets out some preliminary hypotheses about the relationships linking environmental policy and performance to socioeconomic development. Section 5 reports and discusses some statistical tests of the hypotheses; and Section 6 concludes the paper.

# **2. The UNCED Reports**

As part of the preparations for the United Nations Conference on Environment and Development (UNCED - Rio de Janeiro, June 1992), all UN member governments were asked to prepare national environmental reports. Detailed preparation guidelines were laid down at the First Preparatory Committee meeting in Nairobi in August, 1990.' The UNCED secretariat suggested that the reports be prepared by working groups representing government, business and non-governmental organizations (NGO's). The guidelines recommended that the reports provide information on: (i) the drafting process; (ii) problem areas; (iii) past and present capacity building initiatives; (iv) recommendations and priorities for environment and development; {v) financial arrangements and funding requirements; (vi) environmentally sound technologies; ! United Nations General Assembly document A/CONF.151/PC/8 and A/CONF.lSl/PC/B/Add.1 2
(vii) international cooperation; and (viii) expectations about UNCED.

The resulting reports are similar in form as well as coverage, and permit cross-country comparisons. Undoubtedly, the participation of NGO's has helped assure that the UNCED reports are not mere government handouts. To a striking degree, they seem to reflect real environmental conditions and issues.

While we recognize that self-reporting always carries the risk of misrepresentation, we should also note that almost all currently available enivironmental information is self-reported by firms and governments. The UNCED reports differ principally in the absence 3f any formal sanction for misreporting.

# 3. **Quantifying Environmental Performance**

For this exercise, we have randomly selected 31 UNCED reports from the total of 145 (see Table 2A, p. 6). These 31 countries range from highly industrialized to extremely poor, they are drawn from every world region, and they range in size and diversity from China to Jamaica.

Our survey considers the state of policy and performance in four environmental dimensions: Air, Water, Land and Living Resources. We analyze the apparent state of policy as it affects the interactions between these four environmental dimensions and five activity categories: Agriculture, Industry, Energy, Transport and the Urban Sector. Although many overlaps 3
undoubtedly exist, we attempt to draw a separate assessment for the interaction of each activity category with each environmental dimension.

Our survey assessment uses twenty five questions to categorize the state of (i) environmental awareness; (ii) scope of policies adopted; (iii) scope of legislation enacted; (iv) control mechanisms in place; and (v) the degree of succeus in implementation.<sup>2</sup> The status in each category is graded "High, Medium, Low," with assigned values of 2, 1 and 0 respectively. For each UNCED country report, all twenty-five questions are answered for each element of the matrix in Table 1. With 20 elements in the matrix, 500 assessment scores are developed for each country.

We compute four composite indices by adding scores within each environmental dimension. We also calculate a total score to provide a composite index of the state of environmental policy and performance. Finally, we have used our scoring system to establish separate indices for three particularly interesting policy dimensions: the extent of environmental awareness; enactment of policies; and success in implementation. We use all three sets of indices for the cross-country analysis reported in Section 5.

2 The survey instrument is included in the Appendix. All country scores are available on request.

4
Table 1 Evaluation Format

|Sector/<br>Activity|Air|Water|Land|Living<br>Resources|
|---|---|---|---|---|
|Agriculture|||||
|Industry|||||
|Energy<br>__|__<br>____||||
|Transport||||_|
|Urban<br>_|-||_||

Using the four dimensional indices and a composite index, we summarize our results as country rankings in Table 2A. Actual values are displayed in Table 2B. Table 2A also ranks countries on the basis of per capita C-NP (PCGNP) and per capita GDP estimates compiled by the UN International Comparisons Program (ICPGDP) . The ICPGDP computation explicitly adjusts the standard income data to take account of purchasing power parity. Where countries in our sample are not covered in the most recent International Comparisons Program Study (Phase V, 1985), we have adopted a World Bank estimate. The 1985 figures have been extrapolated to 1990 using World Bank estimates of real per capita GDP growth.

Table 3 presents summary statistics for the four dimensional performance indices, whose possible maximum values are all 250. The results suggest fairly similar distributions with the exception of Air, which has a significantly lower mean and greater variance. Our statistical results suggest that air pollution gets relatively low priority in poor countries but 5
Table 2A Sample Counnry Runking.: Income **and** Envrcnnmental Perfonuance Indices

|Country|PCGNP|ICPGDP|Air|Water|Land|Living<br>Resources||
|---|---|---|---|---|---|---|---|
|Switzerland|I|I|.|2|2|I|2|
|FInland|2|3|4|3|3|4|4|
|Germany|3|2||1||2.||
|Netherlands|4|4|_3_|_4_|4|3|3|
|Ireland|5|5|5|5|4|5|5|
|ICora|6||7|7|B|7|7|
|Trinidad|7|6|10|II|1I|12|11|
|Brazil|8|IU|12|16|16f||15|
|SAfrica|9|9|8|9|9|10|9|
|Bulgana|10|7|6|6|6|6|6|
|Janmica|If|16||BI<br>8|7||X<br>S|
|Tunisia|12|13|9|10|10|11|10|
|Thailand|13|11|_15_|24|Is|23|19|
|Jordan|14|12|17|14|15|22|16|
|ParAguay|15|14|24|20|20|17|21|
|Papua<br>NG|16|21|28|27|29|30|29|
|Philippines|17|17|is|24|20|18|20|
|Egypt|lS|15|21|12|24|27|22|
|Zambia|19|26|'2|23|20|20|23|
|Ghana|20|20|18|19|Is|18|17|
|Pakistan|21|19|13|14|13|13|13|
|China|22|18|15|16|12|9|12|
|Kenya|23|24|23|16|16|16|18|
|India|24|23|13|13|_14_|i4|14|
|Nigena|25|22|26|21|25|24|24|
|Bangladesh|26|25|25|29|27|29|26|
|**Malawi**|27|27|Is|22|23|21|27|
|Bhuman|28|30|30|31|30|28|30|
|Ethiopia|29|31|31|30|31|31|31|
|Tanzania|30|29|29|28|28|26|28|
|Mozambique|31|28|27|26|26|25|25|

6
Tibil. 211 **Sample** Coiuniy **DR,Al** lnmonne **and** Env innmctital performance Indices

|**C'onltry**|I'tGNI'<br>.3I9W01|ICPODP<br>iIS I 'rXM_|Air|Waler|Land|I.iving<br>Resources|Env|
|---|---|---|---|---|---|---|---|
|Swucrlane3d|J2.,hH0|21 .o90|231|240|J3|238|947|
|linland|2h,040|15,620|214|229|231|220|894|
|mnany|22.320|16,920|236|242|241|_<br>232|951|
|Ncthcrlinds|17,320|14.600|219|220_j|229|226|90|
|lIcand|9.550|9.130|203|22 3|229|216|187|
|Korea|5.410)|7.190|-SO|170|189|177|686|
|Trinidad|3.610|8.510|I1l|149|159|13R|564|
|Brazil|2.680|4.780|113|127|130|123|15|
|S.Afnca|2.530|5.500|136|165|173|145|619|
|Bulgana|2.250|7,900|168|198|199|185|750|
|Jamaica|1.500|3.030|_114_|168|193|158|633|
|Tumnsia|1.440|3.979|128|158|161|142|589|
|Thailand|1.42D|4.610|98|113|129|109|449|
|Jordar|1.240|4,530|95|131|138|I10|474|
|Paraguay|I.110|3.120|84|117|123|119|443|
|Papua NG|860|1.500|54|91|100|84|329|
|Philippines|730|2.320|93|113|123|118|447|
|Egypt|600|3.100|92|134|118|97|441|
|Zambia|420|810|87|115|123|114|439|
|Ghana|390|1.720|93|124|129|118|464|
|Pakistan|380|1.770|[Os|131|144|128|SOB|
|China|370|1.950|98|127|_151_|153|529|
|Kenya|370|1,120|85|127|130J|121|463|
|India|350|1.150|105|132|143|127|507|
|Nigeria|290|1.420|75|106|114|105|400|
|Bangladesh|210|1,050|77|89|109|91|366|
|Malawi|20W|670|93|116|122|III|352|
|Bhutan|190|510|39|54|70|93|256|
|Ethopia|120|310|20|56|67|75|218|
|Tanzania|110|540|50|90|103|98|341|
|Mozambique|80|620|56|98|112|102|37_|

7
increases more rapidly in importance with income. By contrast, low income countries such as Tanzania, Mozambique, Bhutan and Bangladesh seem to focus first on the natural resources which are critical to their livelihood -- soils, forests and water.

Table 3 Indices of Environmental Policy-Summary Measures for 31 Countries

|Resource|Mean|s.d.|Maximum|Minimum|
|---|---|---|---|---|
|Air|113.84|56.61|236.0|20.0|
|Water|140.61|50.91|242.0|54.0|
|Land|149.03|48.26|241.0|67.0|
|Living|137.B4|46.70|238.0|75.0|

# **4. The Political Economy of Exvironmental Management: Some Preliminary Hypotheses**

Environmental degradation affects national welfare by damaging human health, economic activities and ecosystems. Because environmental problems represent a classic externality, some government regulation is generally warranted. From an economist's perspective, desirable regulation should weigh two factors: the benefits associated with reduced environmental damage and the opportunity cost of mitigation. In reality, the extent and focus of government intervention will also reflect national political and institutional considerations.

**8**
# **4.1 Benefits**

The demand for environmental quality should increase with income per capita, and we would expect this to be strongly reflected in the country scores. In addition, demographic and sectoral differences may play an important role. For example, economies with high rural population densities and heavy dependence on agriculture and forest extraction should be particularly concerned with agricultural water supply, soil erosion, and deforestation. In our Evaluation Format (Table 1), the relevant scoring cells are located at the intersection of Agriculture with Water, Land and Living Resources.<sup>3</sup> If environmental policy reflects basic economic considerations in resource-dependent economies, we would expect country scores in these dimensions to be positively correlated (ceteris paribus) with rural population density and the share of agricultural and forest production in national output.

By contrast, urbanized and industrialized economies should exhibit more concern with the potential health impacts of air and water pollution on densely populated areas. The relevant cells in this context are located at the intersections of the Air and Water columns with Industry, Energy, Transport and Urban. We would expect country scores in these dimensions to be correlated with the urban share of national population, urban population density, and the share of manufacturing in national output.

3 Agriculture includes wood production from plantations and primary forests.

9
# **4.2 Opportunity Costs**

Governments must make resource allocation decisions with constrained budgets, so we would expect the benefits of environmental improvement to be weighed against opportunity costs. In particular, environmental management lias to share a limited social welfare budget with public health, education and other needs. Therefore the poorer the country, the more limited environmental management resources are likely to be. This should be another source of positive correlation between income per capita and country scores.

# **4.3 Political Economy**

Political and institutional factors may also contribute significantly to cross-country variation in environmental policy and performance. Attention to environmental problems should reflect the political power of affected interest groups, the quality of their information about environmental damage, and the effectiveness of legal and regulatory institutions. Many environmental problems pit broad public interests against the profitable pursuit of manufacturing and extraction. Thus, we might expect our environmental performance indices to be correlated with measures of degree of popular representation, freedom of information and education. Performance should also be superior where legal and regulatory systems are relatively efficient. Finally, environmental objectives may be promoted 10
more strongly in economies where secure property rights lead to longer planning horizons.

# 4.4 Predicted Relationships

Within this simple framework, we can make some predictions about the probable strength and direction of empirical relationships across our sample countries. We consider crosscountry variations in three sets of indices: (1) Overall policy and performance, along with separate scores for Air, Water, Land and Living Resources; (2) a "Green" index (interaction of Agriculture with Water, Land and Living Resources) and (3) a "Brown" index (interaction of Industry, Energy, Transport and Urban with Air and Water). We have also decompnosed the Green and Brown indices into three subindices: Awareness of environmental problems; enactment of regulations; and success in implementation. However, as Table 4 indicates, the subindices are so highly correlated with the composite indices that more detailed analysis seems unnecessary.

Table 4 Correlation Matrix: Component Scores Green Subindices <!-- Start of picture text --> _ Composite Awareness Enactment iSuccess<br>Composite 1 l<br>Awareness .906 1 l<br>Enactment .982 .858 1<br>1Success .968 .866 .910 1<br><!-- End of picture text --> 11
Brown Subindices

||IComposit|eAwareness|Enactment|Suce7ess|
|---|---|---|---|---|
|Composite|1||_|_|
|Awareness|.953|1|||
|Enactment|.989|.926|1||
|Success|.984|.934|.951|1|

To summarize briefly, the following predictions are consistent with our hypotheses:

- Overall environmental performance should be positively correlated with:

- 1) Income per capita;

- 2) Degree of popular representation;

- 3) Freedom of information;

- 4) Security of property rights;

- 5) Development of the legal and regulatory system.

Controlling for these variables,

- G.reen indices should be positively correlated with:

- 1) Rural population density;

- 2) Agricultural and forest production share of national output.

- Brown indices should be positively correlated with:

- 1) Particular focus on public health, indexed by life expectancy4;

- 2) Urban share of total population;

- 3) Urban population density;

- 4) Manufacturing share of national output.

4 We recognize some risk of endogeneity, but we regard it as minimal in this case. Life expectancy is influenced by many policy and other variables which are not directly related to environmental concerns.

**12**
# 5. **Results**

# **5.1 Income and Environmental Performance**

The correlation between income and composite environmental rankings is clear in Table 2A. Comparisons of bivariate regressions on the two income measures, recorded in Tables 5A and 5B, reveal significantly tighter fits for ICPGDP. The income elasticity of environmental policy performance is positive and highly significant in all environmental dimensions. Air seems to have a much higher income elasticity than the others. The scatter of the composite environmental index (Env) against ICPGDP (Figure 1) indicates that the relationship is continuous over the entire range of incomes.

# **5.2 Political Economy and Institutional Variables**

For the reasons previously noted, effective environmental management may be seriously handicapped by lack of political, civil, and economic liberty; lack of an independent judicial system; and an inefficient or corrupt bureaucracy. To test these ideas, we have fitted regressions with several sets of institutional indicators previously used in the literature. In each case, limited availability of the indicators has forced us to run regressions on subsamples of countries.

Our first test employs a widely-used set of political, civil and economic liberty indicators developed by Gastil.5 These

**5** See Scully (1992) for details.

13
# Table 5A

# Impact of PCGNP on Environmental Indicators

|Dependent<br>Variable|Intercept|In PCGNP|Adjusted<br>R<sup>2</sup><br>.|
|---|---|---|---|
|ln Air|2.70<br>(11.93)|0.27<br>(8.70)|0.71|
|ln Water|3.55<br>(22.84)|0.19<br>(8.80)|0.72|
|ln Land|3.79<br>(27.70)|0.17<br>(8.75)|0.72<br>_|
|ln Living|3.73<br>(29.60)|0.16<br>(9.26)|0.74|
|ln Env|4.89<br>(34.80)|0.19<br>(9.78)|0.76|

* t-statistics in parentheses.

# Table 5B

# Impact of ICPGDP on Environmental Indicators

|Dependent<br>Variable|Intercept|ln ICPGDP|Adjusted<br>R<sup>2</sup>|
|---|---|---|---|
|ln Air|1.29<br>(4.06)|0.42<br>(10.59)|0.79<br>.|
|ln Water|2.59<br>(11.53)|0.30<br>(10.30)|0.78|
|ln Land|2.97<br>(14.52)|0.25<br>(9.82)|0.76<br>__|
|ln Living<br>l______________|3.03<br>(13.88)|0.23<br>(8.53)|0.71|
|ln Env|3.97<br>(18.72)|0.29<br>(10.79)|0.79|

14
# Figure 1

# Overall Environmental Performance vs.

# ICP Income Per Capita

<!-- Start of picture text --> 7.00<br>*.<br>I . *~~~~~~~~~~~~~.<br>9<br>6.50!<br>* 9<br>X 6.00 9<br>_- I 9 9<br>5.50<br>5.00 6.00 7.00 8.00 9.00 10.00 11.00<br>ln ICPGDP<br><!-- End of picture text -->

**15**
indicators are available for 29 of our selected 31 countries. Among the aspects that appear most relevant for our study are: freedom of property (FOP), freedom of information (FOI), freedom of print media (FPM), freedom of broadcast media (FBM), freedom of peaceful assembly (FPA) and the Gastil-Wright classification of types of economic system (TES) by degree of commercial freedom. In our regressions, only FOP and FOI are statistically significant (Table 6). Each of these indicators is coded 1 to 5, with higher scores for lower liberty, so the expected sign of the coefficients is negative for both indicators. Freedom of property has the expected sign, but the other result is quite surprising: Controlling for income and property rights, greater freedom of information is associated with lower environmental index values. We have no explanation for this anomaly, and we have dropped FOI from our final regressions (Table 9).

Table 6 Impact of Liberty Indexes on Environmental Indicators

|Dependent<br>Variable|Intercept|ln ICPGDP|ln FOP|ln FOI|Adjusted<br>R<sup>2</sup>|
|---|---|---|---|---|---|
|ln Air|1.42<br>(2.97)|0.41<br>(8.17)|-0.36<br>(-2.39)|0.27<br>(2.24)|0.80|
|ln Water|2.86<br>(9.54)|0.27<br>(8.44)|-0.26<br>(-2.80)|0.18<br>(2.38)|0.82|
|ln Land|3.17<br>(10.28)|0.23<br>(7.16)|-0.18<br>(-1.90)|0.12<br>(1.57)|0.77|
|ln Living|3.22<br>(9.57)|0.22<br>(6.27)|-0.27<br>(-2.57)|0.16<br>(1.90)|0.74|
|ln Env<br>.|4.18<br>__(13.43)|0.27<br>(8.25)|-0.26<br>(-2.72)|0.18<br>(2.25)|0.82|

16
As a second test, we have employed measures of bureaucratic delay and contract enforceability (or relative degree to which contractual agreements are honored) from Business Environmental Risk Intelligence, Inc. (BERI) ,h Scores for the BERI indicators are available for only fourteen of our thirty-one countries and are set so thlat positive relationships with environmental Table 7 Impact of BERI Indexes on Environmental Indicators

|Dependent<br>Variable|Intercept|ln<br>ICPGDP|ln Delay||<br>in<br>Contract|Adjusted<br>R2|
|---|---|---|---|---|---|
|ln Air|1.99<br>(3.48)|0.32<br>(3.23)|0.19<br>(0.56)||0.81|
|ln Water|3.21<br>(6.19)|0.18<br>(2.04)|0.31<br>(1.00)||0.72|
|ln Land<br>l__________|3.25<br>(6.18)|0.20<br>(2.19)|0.18<br>(0.57)||0.68|
|ln Living<br>____<br>__|2.99<br>(4.87)|0.21<br>(1.99)|0.24<br>(0.64)|.|0.66|
|ln Env<br>l__________|4.29<br>(7.96)|0.22<br>(2.40)|0.23<br>(0.72)||0.74|
|lnAir|2.05<br>(2.24)|0.32<br>(2.10)||0.16<br>(0.34)|0.81|
|lnWater|3.45<br>(4.15)|0.15<br>(1.11)||0.35<br>(0.82)|0.72|
|ln Land|3.43<br>(4.12)|0.18<br>(1.26)||0.22<br>(0.52)|0.68|
|ln Living<br>l__________|3.01<br>(3.06)|0.22<br>(1.34)||0.17<br>(0.33)|0.65|
|ln Env|4.42<br>(5.13)|0.21<br>(1.47)||0.23<br>(0.52)|0.73<br>_|

6 For a discussion of these indicators, see Keefer and Knack (1993).

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management would be consistent with our prior hypotheses about the effect of judicial and administrative efficiency. The regression coefficients are positive, as expected, but none are statistically significant (Table 7).

Finally, we have tested a set of indicators which directly reflect the efficiency of the legal and judicial system (LJS) and the level of red tape in the bureaucracy (RTB). These were developed by the Country Assessment Service of Business International, Inc.<sup>7</sup> Unfortunately, the measures are available for only twelve of the thirty-one countries in our sample. In separate regressions for this subset of countries, both LJS and RTB emerge as significant explanatory variables. Since they are collinear, we have computed their first principal component (PC1) and used it as a composite regressor. When it is included with ICPGDP (Table 8) the results show substantial improvement in the explanatory power of the regressions: The adjusted R<sup>2</sup> increases between 9% and 24%. The change in outliers indicates that the improvement is especially striking for Ireland, India and Thailand.

# **5.3 Green and Brown Indices**

For both Green and Brown indices, the regressions reported in Table 9 suggest that performance is again strongly associated See Wheeler and Mody (1992) for details.

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with income per capita, freedom of property and (in small samples) measures of regulatory efficiency. The two rural-sector variables (population density; proportion of GDP in agriculture and forestry) are only weakly associated with the Green index (Table 9a). The fit is much better for the Brown index: degree of urbanization, population density and manufacturing share in GDP all have the expected signs and relatively high significance (Table 9b). Life expectancy as a proxy for public health priority has no independent effect.

# **6. Summary**

Using a multidimensional survey analysis of the UNCED reports, we have developed a set of comparative indices of environmental policy and performance in thirty-one countries. We find a strong positive correlation between our environmental indicators and the level of economic development. The fit is substantially better when national incomes are adjusted for purchasing power parity. The income elasticity of the indices is positive and highly significant in all environmental dimensions. The pattern of elasticities suggests that protection measures for land and living resources precede those for water; action for reducing air pollution comes later.

Some impact for institutional development is also suggested by our results, although the information base is quite limited.

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Table 8 Impact of ICPGDP, LJS and RTB **oi** Environmental Indicators

|Dependent<br>Variable|Intercept|ln ICPGDP<br>_|PCi|Adjusted R<sup>2</sup>|
|---|---|---|---|---|
|ln Air<br>____________|1.60<br>(2.91)|0.38<br>(6.02)||0.76|
|In Air<br>l___________|3.35<br>(8.81)|0.18<br>(4.07)|0.26<br>(6.18)|0.95|
|In Water<br>l___________|2.59<br>(5.57)|0.29<br>(5.35)||0.72|
|ln Water|4.13<br>(16.68)|0.11<br>(3.73)|0.23<br>(8.37)|0.96|
|ln Land<br>____________|2.79<br>(6.19)|0.27<br>(5.16)||0.70|
|ln Land<br>____________|4.20<br>(13.15)|0.10<br>(2.78)|0.21<br>(5.96)|0.93|
|in Living|2.79<br>('.19)|0.27<br>(5.16)||0.70|
|ln Living<br>l___________|4.05<br>(9.12)|0.11<br>(2.15)|0.24<br>(4.91)|0.90<br>_|
|ln Env|3.77<br>(7.79)|0.31<br>(5.48)||0.73|
|ln Env<br>_L.<br>_<br>____(18.08|5.35<br>)|0.12<br>(3.58)|0.23<br>(7.15)|0.95|

The level of explanation in all regressions improves significantly with the addition of the Business International effectiveness indices for legal/judicial and administrative systems and the Gastil measure of property rights protection. Similar BERI measures are not significant, however. We also obtain insignificant or perverse results for all Gastil measures of degree of popular representation and freedom of information.

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Table 9a Regression Results for ln(Green)

|Intercept<br>_____|InPCGNP<br>_____|lnICPGDP|InPOP|ln(Shoro<br>of<br>agriculture<br>in<br>GDP)<br>P|In(Pop.<br>density)<br>_-_______|Adjusted<br>RI<br>_______nG|
|---|---|---|---|---|---|---|
|3.31<br>(25.55)|0.16<br>(8.66)||||_....|0.71|
|2.60<br>(12.29)||0.23<br>(8.65)||||0.71|
|2.75<br>(4.69)||0.20<br>(3.85)|-0.11<br>(-1.31)|_0.06_<br>(0.93)|0.09<br>(1.32)|0 64|
|3.27<br>(11.11)|. .|0.17<br>|<br>(5.38)|-0.16<br>(2.19)|_<br>_|0.09<br>(1.34)|0.73|

# Table 9b

Regression Results for ln(Brown)

|Intercp|lnPCGNP<br>________|lnICPGDP<br>____<br>____|ln FOP<br>_______|ln(Urban<br>/total<br>popula-<br>tion)|ln(Popu-<br>lation<br>density)|in<br>(Manuf.<br>share<br>of GDP)|ln(Life<br>expect-<br>ancy)<br>_<br>_<br>_<br>_|Adj Rz|
|---|---|---|---|---|---|---|---|---|
|3.81<br>(24.25)|0.21<br>(9.7S)|||||||0.76|
|2.73<br>(12.40|)|0.32<br>(11.75)||||||0.82|
|3.91<br>(2.63)||0.20<br>(2.27)|-0.19<br>(1.98)|0.14<br>(1.46)|0.06<br>(2.30)|0.16<br>(2.04)|-0.34<br>(-0.67)|0.82|
|2.94<br>(8.02)|.|0.16<br>_ !2.65)|-0.20<br>(2.20)|0.14<br>(1.46)|0.06<br>(2.25)|0.15<br>(1.95)|.|0.83|

Table 9c Green/Brown Impacts of ICPGDP, FOP and Regulatory Efficiency

|vYariable||ntercept|ln ICPGDP|ln FOP|tlnRTB|ln LSJ|Adj R<sup>2</sup>|
|---|---|---|---|---|---|---|
|ln(Green)<br>____________|3.84<br>1(9.37)|0.03<br>(0.52)|-0.17<br>(1.93)|0.39<br>j(3|.37)|0.93|
|ln(Brown)|3.95<br>(9.44)<br>1|0.09<br>(2.69)|-0.07<br>-<br>(1.09)|0.36<br>(4.20)|0.14<br>(1.07)|0.98<br>_<br>J|

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Decomposition of overall environmental performance into Brown and Green sectors yields some additional insight into the impact of demographics and economic structure on regulation. Controlling for income, comparative analysis of the Brown sector indices suggests a very significant country response to environmental pressures from industrialization and urbanization. However, our results do not reveal an equivalent response on the Green side beyond the effect of variations in income per capita.

In summary, our findings suggest that a detailed, quantified analysis of the UNCED reports can yield comparable and plausible indices of environmental policy performance across countries. Cross-country variations in our environmental index are wellexplained by variations in income per capita, de:-ree of urbanization and industrialization, security of property rights, and general administrative efficiency.

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# 7. **References**

- Keefer, P. and Knack, S., 1993, "Why Don't Poor Countries Catch Up? A Cross Country National Test of an Institutional Explanation", Center for Institutional Reform and the Informal Sector, University of Maryland at College Park, Working Paper No.60

- Scully, G.W., 1992, Constitutional Environments and Economic Growth, (Princeton: Princeton University Press)

- UNCED, 1990, Draft Format for National Reoorts (Geneva: United Nations Conference on Environment and Development)

- UNEP, 1992, Savinq Our Planet: Challenges and Hopes (Nairobi: United Nations Environment Programme)

- Wheeler, D. and A. Mody, 1992, "International Investment Location Decisions", Journal of International Economics, 33, pp. 57-76

- World Bank, 1992, World Development Report 1992: Development and the Environment, (World Bank, Washington D.C. and Oxford University Press, New York)

- World Resources Institute, 1992, World Resources 1992-93, (World Resource Institute, New York and Oxford University Press, New York)

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