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ANALYSIS

Economic growth, industrial pollution and human development in theMediterranean Region

Serkan Grlk

UludaUniversity Agricultural Faculty, Department of Agricultural Economics, 16059 Bursa, Turkey

a b s t r a c ta r t i c l e i n f o

Article history:

Received 19 June 2008

Received in revised form 2 March 2009Accepted 3 March 2009

Available online 1 April 2009

Keywords:

Mediterranean Sea

Environmental Kuznets curve

Human development index

Industrial pollution

Economic growth

This paper investigates the role of human development on the economic development paths of

Mediterranean countries. An environmental Kuznets curve (EKC) analysis is employed to explain the

relationships between economic growth and industrial pollution in the European, Euro-Asian and African-

Mediterranean countries, which have different economic and institutional backgrounds. A modified human

development index (MHDI) is applied to measure the effects of human development in different countries.

The MHDI includes many related social variables such as health effects, political rights, civil liberties,

enrollment rate, and adult literacy rate. Apart from France, all countries follow increasing logarithmic or

inverse-logarithmic curves that keep on the industrial pollution path. The outcomes of the research

presented in this paper clearly point out the differences between the Northern and Southern Mediterranean

countries. Human development should be the first objective of economic development in the Southern

countries of the Mediterranean.

2009 Elsevier B.V. All rights reserved.

1. Introduction

Economic growth is one of the most controversial issues of theeconomic history of the world. A nature-friendly development path

that started with agriculture replaced excessive use of naturalresources after the industrial revolution. During the industrial path,an endless stream of production and process innovations stimulatedthe exploitation of more and more natural resources. In variousperiods of the world history, scarcity and pollution of natural

resources made societies aware of the fact that the economy dependson energy and ecological services provided by the natural resources(Ward, 2006). Until recently many authors examined these issues inthe economics literature. Apart from Malthus's predictions which are

not suitable for economic development, neoclassical growth modelsfocus on capital and labor by ignoring natural resources. Moderngrowth theory (endogenous growth theory) accepts human develop-ment, technological progress, and natural resources as the forcesbehind economicgrowth. In this context, recent economic studies deal

with optimality of the growth, how economic growth and environ-mental conservation are compatible in the long term, sustainabledevelopment, consequences of environmental policy for growth(Smulders, 1999).

The analysis of environmental Kuznets curve (EKC) is one of themost controversial theories examining the interactions betweeneconomic growth and environmental degradation. The logic of EKCanalyses is rather appealing. In the first stages of economic growth

(industrialization stage) natural resources are degraded intensively, and

environmental pollution grows rapidly (Harbaugh et al., 2002). In this

period, policy makers and households are more interested in highermaterial output, employment rates and income rather than environ-mental conservation. With technological improvements and increasingknowledge, rapid economic growth results in greater use of natural

resources, which in turnput more pressure on the environment. In laterstages of industrialization, as economic growth and consequentlyincome increase, humans give attention to the environment. In thesestages, governmental institutions work more efficiently and stringent

environmental policies are implemented, and consequently environ-mental quality starts to increase. Such evidences are recognized bymany authors (Enevoldsen et al., 2007). Therefore the EKC analysisindicates a well-defined relationship between economic growth and

environmental degradation (Dasgupta et al., 2002). A turning point forevery country could be estimated if one can obtain an inverse U-shapedcurve between environmental degradation and economic growth. Theconsequences of the EKC analyses show that economic growth could be

compatible with the environment by implementing efficient environ-mental policies (Bruyn and Heintz,1999; O'neill et al., 1996; Ezzati andSinger, 2001; Suri and Chapman, 1998).

The fundamentals of EKC theory are based on research carried by

Simon Kuznets, Nobel Laureate in Economics in the 1950's. Hedesigned an inverted U-shaped relationship between per capitaincome and income inequality, and shed light on the advent of EKCtheory. Many researchers,in the early 1990's,stated that there is also a

similar relationship between environmental pollution level and percapita income and approved that such analysis be called EKC analysis(Grossmann and Krueger, 1995; Shafik and Bandyopadhyay, 1992;

Ecological Economics 68 (2009) 23272335

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E-mail address: [email protected].

0921-8009/$ see front matter 2009 Elsevier B.V. All rights reserved.

doi:10.1016/j.ecolecon.2009.03.001

Contents lists available at ScienceDirect

Ecological Economics

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Panayatou, 1993; Selden and Song, 1994). Since then many studieshave been carried out on different pollution types and in differentcountries which have different economic development paths.

Some papers focused on turning point estimations while some

focus on improving statistical techniques. Some papers are interestedin only policy implications with respect to economic growth. Torrasand Boyce (1998) stated that literacy, political rights and civil liberties

are found to have particularly strong effects on environmental qualityin low-income countries. Agras and Chapman (1999) studied therelationship between energy demand and income, and emphasizedthat there was no such relationship between these two variables.

Hettige et al. (2000) found that the industry share of national outputfollows an EKC relationship while the others do not. Andreoni andLevinson (2001) stated that the EKC does not dependon the dynamicsof economic growth, political and institutional structure of a country

and could depend on market failure or efficiency. Koop and Tole(2001) studied on relationships between deforestation, growth, andintergenerational equity, and found that more Gross Domestic

Products (GDP) is associated with less deforestation in the countrieswhere the equity is an important phenomenon. Lindmark (2002)stated that developing countries have experienced the same path thatdeveloped countries experienced earlier. McPherson and Nieswiad-omy (2005) examined endangered species and income relationship.

Richmond and Kaufman (2006) examined the relationships ofincome, energy use and carbon emissions and stated that a turningpoint is not an important factor in the relationships among thosevariables. Culas (2007) investigated institutional factors and forest

sector policies, and found that export policies of forest products affectthe deforestation rates.

Several authors focus on emerging human development debates inenvironmental economics. Anand and Sen (2000), attempt to explain

the importance of human development in all components of economic

development path such as equity, sustainable development, optimal

growth, and pure time preferences. Costantini and Monni (2008) statethat a sustainable economic development path is provided by adoptinga human development perspective. Environmental quality would notbe affected negatively by the economic growth if such a perspective is

adopted. Ranis et al. (2000), state that there exists a strong connectionbetween economic growth and human development. In addition,economic growth provides resources to permit sustained improve-

ments in human development. Economic reforms are importantphenomenon, but human development must be included in any reformprogram. Economic growth itself will not be sustainable unlessaccompanied by improvements in human development. Gangadharan

and Valenzuela (2001) state that investment in education and health isa process that produces human capital. Noorbakshs (1998) discussed amodified human development index for measuring human develop-ment. New index considers the diminishing returns to the educational

indicators. However those papersdo not measure the impacts of humandevelopment on economic growth. Recent study highlights the impactsof human development index (HDI) by investigating industrial

pollution in selected Mediterranean countries, which have differenteconomic backgrounds.

The HDI is an important indicator on the measurement of humandevelopment (Raghbendra and Murthy, 2003). Since first released bythe United Nations Development Program (UNDP), it distilled various

concepts that had been raised in earlier development discussions intoa unified theme of human development (Sagar and Najam, 1998).The HDI includes the impacts of social variables such as health effects,political rights, civil liberties, and education level. Education level

affects political rights and civil liberties positively. Population densityalso depends on the education index in the HDI. As long as educationlevel increased in a country, population increase rate and conse-quently pressures on the natural resources would decrease. So the

impacts of the many variables mentioned above are examined under

the frame of the HDI in the EKC analyses.

Fig. 1. Pollution points along the Mediterranean coast (source: UNEP/MAP, 2004).

2328 S. Grlk / Ecological Economics 68 (2009) 23272335


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Recent study employed the MHDI by subtracting the share of GDP.This procedure is explained in the third section of the paper. An EKCanalysis is applied to explain the relationships between economic

growth and industrial pollution in the Mediterranean countries. Inthis context, the main aims of this paper are: to describe themacroeconomic indicators and industrial pollution in the Mediterra-nean countries; to test the effects of the MHDI above Biological

Oxygen Demand (BOD) with respect to industrial pollution; and tocompare the relationships between BOD and per capita GDP inEuropean, Euro-Asian and African-Mediterranean countries, whichhave different economic and institutional backgrounds. This investi-

gation may help local policy makers to define their environmentalpolicies more clearly and effectively. In addition, outcomes of thepaper present new approaches and political instruments for the

Mediterranean Sea policy of the European Union and other interna-tional institutions. Such a comparative study has not yet been carriedout for this region, and the relationship between economic growthand industrial pollution has not been examined in the EKC analyses

around the Mediterranean Sea.The paper proceeds as follows: The second section of the paper

gives the background information of the industrial pollution in theMediterranean Region including European, Euro-Asian and African-

Mediterranean countries. Section 3 examines theoretical reviews oftheEKC analysiswith data andmodel specifications used in this paper.Results and discussion are given in Section 4, which is followed by a

conclusion in Section 5.

2. Background information

The Mediterranean Region is recognized as one of the richest andmost vulnerable in the world regarding its biodiversity, in particular.Marine components in the region reflect great diversity in theMediterranean Sea. However economic development efforts in the

Mediterranean countries have led to serious environmental problems.Environmental pollution has arisen from point sources such asdischarge of sewage or leakage from unsanitary landfills, and non-point sources such as fertilizer and pesticides run-off due tounsustainable agricultural practices. In addition, municipal and

industrial discharges to the bodies of water are considerable problems

that cause environmental problems in the region. The environmental

problems also intensely affect coastal zones of the region. The coastalzones have experienced severe human pressure because such zones

support the countries' economy considerably. In fact, all pollutionsources mentioned above have affected the most productive areas ofthe Mediterranean marine environment, including estuaries andshallow coastal waters. In a study carried out by the United Nations

Environment Program (UNEP), 131 critical points polluted by humanactivities have been identified. At those points, it was determined that

environmental pollution jeopardizes the Mediterranean coastal andmarine habitats of vital importance in maintaining a healthyecosystem. The critical pollution points along the Mediterranean Seaare given in Fig. 1.

The critical pollution points are located all coastal zones of the

Mediterranean, but there are some differences between developedcountries and developing countries in terms of industrial decomposi-tions and regulations:

The coastal zones are occupied by the industrial establishments inall countries. However in the African-Mediterranean (AM) coun-

tries,the establishments located in the coastal zones form 75%of thewhole industry.

The pollution is characterized by heterogeneity in the industrialstructure in developed countries. The sectors depend on mostly

agribusiness and textile in the developing countries (Table 1). Many unit familyenterprises or traditional craft business exist in the

coastal zones, and they do not use modern production andtreatment methods.

While developed countries of the region face stringent environ-

mental policies, environmental legislations for industrial pollutionare characterized by only for recommendation in the AM and Euro-Asian Mediterranean countries. The environmental legislations areoften characterized by contradictions and overlapping.

The Mediterranean countrieshave a long history of cooperation forenvironmental conservation despite of political, economic, social,cultural, and technological differences. Many international meetingsand conferences have been arranged for solving the environmental

problems mentioned above. One of them is the InternationalConference on the Problems of the Mediterranean Region of 2002held in the Nicosia-Cyprus (EPMR, 2002). The concluding remarks ofthat conference emphasize that:

Coastal zones are fragile ecosystems, which can easily be

jeopardized by surface and groundwater run-off and dischargessuch as industrial, oil and wastewater. Water quality managementpractices and broad monitoring in the rivers should be improvedby adopting integrated water resources management.

In addition to this international conference, several national levelstudies such as Choliz and Duarte (2005) in Spain, Angelakis et al.(2003) in Greece, Fradin (2006) in France, Giordano et al. (2007);Grlk and Rehber (2006), and Alpaslan et al. (2006) in Turkey

emphasize the importance of sustainability, monitoring, and humandevelopment to prevent environmental issues such as industrialpollution. In addition to these national level studies, many interna-tional initiative programs are available in the region.

The European Union (EU) has produced efficient policies toprovide water quality for the Mediterranean countries (EU, 2008).European Neighborhood Policy, launched in 2004, is one of suchpolicies including Algeria, Egypt, Israel, Jordan, Lebanon, Morocco,

West Bank and Gaza, Syria, and Tunisia. This policy reinforces theEuro-Mediterranean Partnership, while using all its institutions andmechanisms. Another important EU Policy for the MediterraneanRegion is Initiative Horizon 2020 which is comprehensive environ-mental strategy. The main aim of the Horizon 2020 is to improve the

quality of life for the average citizen, by the cleaning up of the

Mediterranean Sea by 2020 (European Commission, 2006). The object

Table 1

Industrial subsectors affecting the BOD emissions.

Regions Industrial shares in the BOD emissions

Chemical Clay and

glass

Food Metal Paper and

pulp

Textile Wood Other

Euro-Med. countries

France 13a 0 50 7 14 3 2 11

Spain 9 0 40 7 21 9 4 10

Italy 11 0 31 9 17 15 4 13

Greece 9 0 55 8 10 12 2 4Albania 6 0 74 14 1 5 0 1

Malta 12 6 15 0 10 11 1 42

Slovenia 8 0 24 34 15 11 2 7

Euro-Asian Med. countries

Turkey 8 0 44 11 5 26 0 5

Syria 4 1 70 4 1 19 0 0

Cyprus 9 9 37 0 9 7 8 19

Israel 10 0 46 4 22 6 2 10

African-Med. countries

Egypt 8 0 50 12 8 19 0 3

Algeria 6 1 60 23 2 8 1 1

Morocco 8 6 22 1 3 43 2 14

Tunisia 5 0 36 3 6 43 2 5

Source: World Bank Group, Data and Research Department, www.worldbank.org

(World Bank, 2008).a % of total BOD emissions.

2329S. Grlk / Ecological Economics 68 (2009) 23272335
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of this policy is to decrease industrial pollution, municipal waste, andparticularly urban wastewater. The Horizon 2020 offers the following

activities to resolve environmental issues:

Common projects will be carried out to reduce industrial and urbanpollution, which are responsible for up to 80% of Mediterranean Seapollution.

Supports will be released to implement environmental laws andcreate national environmental management system of the Medi-

terranean countries. European Commission's Budget will be used to carry out research

projects to develop greater knowledge of environmental issuesrelevant to the Mediterranean.

Environmental indicators will be followed to monitor the success ofHorizon 2020.

Other international initiative policies are undertaken by the United

Nations Environment Program. Mediterranean Action Plan (UNEP/MAP) is one of such initiative policies. The MAP includes 20 countriessurroundingthe Mediterranean Sea as well as the EU. TheMAP createsaction plans to meet the challenges of environmental degradation in

the sea and coastal areas in order to provide sustainable resourcemanagement with development. The Program for the Assessment andControl of Marine Pollution (MED POL) is the scientific and technicalsection of the MAP. The MED POL assists the countries to implement

programs and precautions to assess and eliminate pollution. Medi-terranean Strategy for Sustainable Development (MSSD) is anotherinternational initiative strategy that brings together the Mediterra-nean countries and EU. The MSSD offers action plans, which provide

sustainable development goals, addressing the threats and weak-nessesin the region. It also takes into consideration theneed to reducethe gap between developed and developing countries in the region.

Although much progress has been made at the international level,

there is a growing awareness that current development trends areunsustainable in the Mediterranean Region. The main weakness ofthose international programs is that they do not focus on human

development in their strategies. Small and medium-size enterprisesform the majority of the industrial activity in the region. Those

enterprises work with scarce capital and knowledge. People living incoastal areas are reluctant to enhance environmental quality. If

country specific economic instruments are supported by humandevelopment activities, sustainable resource use might be provided inthe log run. The disparities between Northern and Southern countriesintensify these undesired economic development paths (European

Commission Report, 2004). The EU policies present considerableopportunities to challenge environmental issues in a sustainabledevelopment way. The main strategy for all Mediterranean countriesshould be work with coordination and joint progress in the fields of

human and economic development and environmental protection.The next sections of this paper shed light on these normative opinionswith positive approaches.

3. Methodology

3.1. Data and research hypotheses

The paper estimates the relationship between biochemical oxygen

demand (BOD) and per capita gross domestic production (GDP) byexamining the effects of the HDI of the UNDP. The BOD is referred to asthe main reason for industrialand urbanwater pollution. EnvironmentalPollutionAgency of theUSA (EPA,2008) statesthe BODas the amount ofoxygen thatbacteria in water will consume while breaking down waste.

Overloaded pollution in fresh water resources exhausts the dissolvedoxygen content that aquatic animals need. Low levels of dissolvedoxygen in water can impact the health of aquatic resources andecosystems. The BOD of a water sample from the rivers, given in

kilograms per day, is usually measured by monitoring the change in

dissolved oxygen concentration, in a laboratory environment, in a 5-dayperiod, and at a fixed temperature. The difference between the final

dissolved oxygen concentration and the initial dissolved oxygenconcentration represents the oxygen consumed (or BOD) in breakingdown the organic materials in the sample. The dataset of this paperfocuses on organic water pollution resulting from industrial activities

measured by the BOD (WRI, 2008). Organic matter can also come fromsources that are not as easily identifiable as those associated with

industrial activities. Such sources that are known as non-point sourcescan contribute significantly to the oxygen demand in water and are notrepresented by the data displayed here.

GDP is the total annual output of a country's economy, here incurrent US dollars. GDP per capita is the total market value of all final

goods and services produced in a country in a given year, equal to totalconsumer, investment, and government spending, divided by the mid-year population.

The HDI is a summary measure of human development. The HDI

measures the average achievements in a country in three basicdimensions of human development:

Life expectancy index: The life expectancy index measures therelative achievement of a country in life expectancy at birth.

Education index: The education index measures a country's relative

achievement in both adult literacy and combined primary, second-ary and higher gross enrollment.

GDP index: The GDP index is calculated using per capita in US$. Theper capita US$ is adjusted with respect to purchasing power parity

terms in US dollars.

For each of those dimensions, an index value is computed on a

scale of 01 where 0 corresponds to the minimum, and 1 to themaximum assigned value for the corresponding indicator. Individualindex for a given country is computed as the following generalformula:

Dimension index :

actual value minimum value = maximum value minimum value :

The HDI is then calculated as a simple arithmetic average of the

three indexes (Sagar and Najam, 1998; UNDP, 2008). The HDI formulaconsists of three index abovementioned:

HDI = 1 = 3 Life expectancy index + 1 = 3 Education index + 1 = 3 GDP index :

Recent study modifies conventional HDI by subtracting the GDPshare from the formula. Thus the MHDI does not include the incomefactor, and eliminates multicollinearity issues between the BOD and the

GDP in the regression analysis. A similar approach was tested byCostantini and Monni (2008) in the relation between sustainabledevelopment and economic growth. Therefore the MHDI is expressed

by a simple average of the two dimension index, which, in this study,are life expectancy at birth and education index. The education index isthe combination of two-thirds weight of the adult literacy rate and one-third weight of primary, secondary and higher gross enrollment ratio.

This paper, therefore, examines the relationship between per

capita GDPand modified HDI as factors in explaining thedifferences inenvironmental degradation in different economic background coun-tries. Research hypotheses are set as following:

H1. There is a significant nonlinear explanatory relationship betweenmacroeconomic indicators and biological oxygen demand in theMediterranean countries.

H2. There is a significant nonlinear explanatory relationship betweenmodified human developmentindex and biological oxygen demandin

the Mediterranean countries.



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A quadratic functional relationship is expected between per capitaGDP and BOD in developed countries, and a logarithmic increasingrelationship is expected between per capita GDP and BOD in de-

veloping countries of the region. Negative coefficient signs areexpected between modified human development index and biologicaloxygen demand in studied countries. In other words, an increase inMHDI causes the decrease in the BOD amounts.

In the EKC analyses, it is very important to study with sound data.The World Resource Institute (WRI, 2008), Food and AgricultureOrganization's (FAO, 2008) water resources data base (AQUASTAT),Global Environment Monitoring System (GEMS, 2008) and European

Environment Agency's long term water and air quality data system(EU, 2008) are used to achieve country data in this study.

3.2. Model specifications

Conventional EKC studies employ functional forms where resultscan be evaluated with respect to the presence or absence of a turning

point (TP) and the significance of the parameters computed (Agrasand Chapman, 1999). The following equation shows that a reducedfunctional form is applied to find out the best possible relationshipsbetween environmental pollution level and economic growth:

Yit = i + 1Xit + 2X2it + 3X

3it + 4Zit + it 1

where Y is environmental indicators, X is incomeand Z relates toother variables of influence on environmental degradation. Here, thesubscript i is a country, t is time, is constant, is error termwhile k is the coefficient of the k explanatory variables (Chow,

2006; Dinda, 2004; Ekins,1997; Shafik, 1994). Eq. (1) provides us witha method to test several forms of environment-economic develop-ment/growth relationships.1 Then TP is estimated via partialderivations.2

The econometric time series models are implemented in the EKCanalysis. When a time series model is created,it is necessaryto know ifthe derived stochastic path can change over time. If the characteristics

of stochastic path change over time (non-stationary), the time seriesmodel cannot specify the past and future structures of the series witha simple mathematical function (Maddala, 1992). Current paper seeks

correlogram of autocorrelation and partial autocorrelation functionsto be able to estimatethe stationary issue (Frstenberger and Wagner,2007). In the non-stationary case, mathematical transformations(logarithms, etc.) are applied to provide a stationary condition. In

addition,it is likely to observe unsteadyfluctuations in thetime series.Unsteady fluctuations can appear whenever natural factors exist.Exponential smoothing, which is a weighted average method thatgives positive weights to past and/or current values of a time series, is

applied to remove such an issue.We take into consideration fifteen countries which are separated

into three regions including European, Euro-Asian (EA) and AMregions. Those regions include France, Italy, Spain, Greece, Albania,

Malta, Slovenia, Turkey, Israel, Syria, Cyprus, Egypt, Morocco, Algeria,and Tunisia. Data periods vary between 1970 and 2006. Appendix Aprovides information about the periods of data used in this paper. By

using Eq. (1), various econometric functions aretested tofind the bestmodel specifications mentioned above. Table 2 gives summarystatistics while Table 3 shows details of variables and modelspecifications employed in the analyses.

4. Results and discussion

Regression results are given in Table 4. The results of Hypothesis 1showed that there is a significant nonlinear functional relationshipbetween macroeconomic indicators and biological oxygen demand inthe Mediterranean countries. However expected quadratic functional

relationship was not significant at various significance levels fordeveloped countries of the Mediterranean Region apart from the caseof France. The model France follows a quadratic function (the EKCrelationship) and has a turning point. In the beginning, per capitaincome increases the BOD amounts and then reduces it after income

reaches a certain level. This point is the level of 22161 US$ for theFrance. The remaining countries of the European Mediterranean (EM)Region follow either logarithmic increasing or inverse-logarithmicincreasing function between the BOD amounts and per capita GDP.

The models of the EA Mediterranean countries also have conven-tional statistical significance levels, and follow nonlinear relationship.The models Turkey, Israel, and Syria follow logarithmic increasingrelationship between the BOD and per capita GDP while Cyprushas inverse-logarithmic functional relationship. The trend of the

Cyprus might be turned to an EKC relationship if economical and

1 10 and 2=3=0. A monotonic increasing relationship or a

linear relationship between X and Y. 1>0 and 20 and 20. A cubic polynomial

or N-shaped figure. 10 and 3


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environmental policies of the EU are followed effectively. In factstringent environmental policies of developed countries are likely toregulate their environmental problems. Similar situations are avail-

able for Turkey as well. Probable EU membership gives opportunitiesto Turkey in implementing stringent environmental policies. If suchenvironmental policies are implemented on the water pollution,

Table 3

Variables and model specifications.

Country Model specification Dependent variable Explanatory variables

European Mediterranean countries

France Quadratica Biological oxygen demand (BOD)b Gross domestic products (GDP)c, square of GDP and MHDId

Spain Logarithmice L ogarithmic tr ansf orm at ion of BO D GD P and MHD I

Italy Logarithmic Logarithmic transformation of BOD GDP and MHDI

Greece Inverse logarithmicf BOD Logarithmic transformation of GDP and MHDI

Albania Inverse logarithmic BOD Logarithmic transformation of GDP and MHDI

Slovenia Inverse logarithmic BOD Logarithmic transformation of GDP and MHDIMalta Logarithmic Logarithmic transformation of BOD GDP and MHDI

Euro-Asian Mediterranean countries

Turkey Logarithmic Logarithmic transformation of BOD GDP and MHDI

Cyprus Inverse logarithmic BOD Logarithmic transformation of GDP and MHDI

Syria Logarithmic Logarithmic transformation of BOD GDP and MHDI

Israel Logarithmic Logarithmic transformation of BOD GDP and MHDI

African-Mediterranean countries

Egypt Logarithmic Logarithmic transformation of BOD GDP and MHDI

Algeria Logarithmic Logarithmic transformation of BOD GDP and MHDI

Tunisia Logarithmic Logarithmic transformation of BOD GDP and MHDI

Morocco Logarithmic Logarithmic transformation of BOD GDP and MHDI

a A quadratic function is specified as y = a + bx + cx2.b Industrial pollution is stated as biological oxygen demand.c Gross domestic product of a country.d

Modified human development index is expressed by subtracting the GDP index from conventional HDI.e A logarithmic function is specified as log (y) = a +bx.f An inverse-logarithmic function is specified as y = a + blog(x) + cx.

Table 4

Model results for the Mediterranean countries.

Countries Constant GDP GDP2 Log (GDP) MHDI Adjusted R-squared F-statistics

European Mediterranean Countries

France 3,311,688 17.729 0.0004 2,937,640.6 0.975 325.00

(5.36)a (6.1) (7.13) (5.85)

Spain 5.51 0.4 105 0.0327 0.672 37.83

(749.17)

(5.33)

(

2.75)

Italy 6.288 2.1 105 1.044 0.904 173.80

(105.31) (12.82) (11.79)

Greece 16,0891.6 17,522.5 31,460.2 0.990 1870

(20.2) (7.4) (15.5)

Albania 309,254.85 30,367.90 225,404.14 0.985 910.15

(26.77) (7.8) (24.85)

Slovenia 186,121.95 2670.32 140,555.04 0.989 715

(44.73) (1.53) (12.76)

Malta 10.27 0.0001 7.592 0.994 3379.60

(12.485) (4.16) (6.56)

Euro-Asian Mediterranean Countries

Turkey 5.175 0.0001 0.277 0.682 34.27

(128.42) (3.189) (1.97)

Cyprus 12,108.9 682.21 22,971.48 0.985 1549.42

(4.9) (1.178) (4.40)

Israel 2.942 3.8 10

6

1.990 0.997 7235.50(26.22) (3.25) (14.34)

Syria 5.005 12.8 105 0.958 0.984 1444.66

(87.25) (4.55) (23.99)


Algeria 4.693 2.1 105 0.305 0.973 545.44

(353.66) (4.86) (15.648)

Morocco 3.006 1.4 105 3.172 0.995 3603.25

(133.90) (0.151) (18.62)

Egypt 5.108 1 104 0.632 0.978 563.50

(166.38) (3.10) (2.453)

Tunisia 4.381 8.8 105 0.167 0.984 845.14

(349.70) (8.67) (5.02)

Significant at 1% confidence level.Significant at 5% confidence level.Significant at 10% confidence level.a

Statistics for t-Students.



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Turkey firstly would be able to follow an inverse-logarithmicincreasing path and then reach a turning point. The Hypothesis 1

and its sub hypothesis were significant for the AM countries. Thosecountries follow logarithmic increasing functional relationship. Suchfunctional relationships are revealed through inadequate environ-mental infrastructure due to development efforts of developing

countries. The developing economies have lower GDP, and this limitedeconomic resource is allocated to other sectors rather than environ-

mental infrastructure. Also they need to produce more withoutenvironmental awareness. Review report of Horizon 2020 also statesthis insight. The report emphasizes that developing countries ofMediterranean have inadequate environmental infrastructure, alsocurrent systems have not worked efficiently due to high costs and

weak maintenance. The developing countries of the EA Mediterraneancountries and all AM countries have experienced industrializationpath and consequently natural resources have been exploitedintensively. Those countries have not yet had any turning point in

the industrializing path. Developed countries testing the long-runeffects of environmental degradation enforce more and morestringent environmental policies. On the contrary, developing coun-tries which are interested in fast economic growth are likely to allow

less stringent environmental policies. However, installing clean high-tech production techniques would necessitate considerable amountsof funds for developing countries (Jones and Manuelli, 1997; Moraet al., 2006; Nixon et al., 2000).

The developed countries of the Mediterranean Region have entereda desired path in terms of industrial pollution. However recent BODconcentrations in those countries are still at higher levels compared todeveloping countries of the region. The income elasticity of pollution,

gives important insights. The income elasticityof pollution is 2.60, 0.147and 0.558 for the European, EuropeanAsian and AfricanMediter-ranean countries, respectively. Results suggest that developed countriestend to pollute much more compared to developing countries at the

region. The income elasticity of pollution has negative value for the AMcountries. It points out that economic development process stilldepends on agriculture rather than industrial sector.

The second hypothesis of the paper was related with MHDI. The

results justify the second hypothesis. The MHDI is an importantexplanatory variable and expected signs are provided by theequations. However the effects of the MHDI on the BOD amounts

were different among the EM countries. In the France, Greece,Slovenia and Albania models, when the MHDI is increased the amountof BOD decreases in a greater rate. Results indicate the importance ofhuman development for the AM countries such as Algeria and Egypt.

In the Morocco and Tunisia, the MHDI has no negative effects on theBOD amounts. The weak effects of political and civil rights might beinvestigated individually rather than combined MHDI in thesecountries for interpreting the impacts of human development.

Human development has played an important role in sustainableeconomic development for developing countries such as Algeria,Egypt, and Tunisia. At the first periods of the development path, the

human capital accumulation would not be available due to weakeconomic resources. Table 5 gives the MHDI's impacts on BODamounts in some periods according to percentage changes. Forinstance, 5% increase in the MHDI causes 8.52% and 138.90%decreasesin the periods of 197080 and 19962006, respectively.

The excessive resource exploitation at the first periods ofdevelopment path is linked to low investments in human develop-ment, and takes the country to unsustainable path (Costantini andMonni, 2008). Current paper supports this idea. If effective policies areimplemented to human capital by investing educational infrastruc-

ture, developing institutional structure in a democratic environment,developing countries would not experience unsustainable path. Thespecific role of globalization process enables the improvement ofhuman development in developing economies such as African-

Mediterranean countries. With the globalization process, easy-access

to knowledge may help to get the some advantagessuchas not to waitfor a long time for human development. In other words theglobalization speeds up the human development more and more.Increasing investments in education and health produce valuable

human capital and less pollution-intensive than that of producingphysical capital.

The outcomes of this paper clearly point out differences betweenNorthern and Southern countries of the Mediterranean countries. The

Northern countries of the Mediterranean are mostly EU members,industrialized and pollution exporting countries while the Southernand East Mediterranean countries are based on textile and foodprocessing industries with weak physical and institutional infra-

structures. African and Asian Mediterranean countries have advan-tages because the Mediterranean Sea is of common interest for the EUcountries. Comprehensive and initiative Mediterranean policies of theEU such as Horizon 2020 have potentials to regulate the environ-

mental problems, and support such countries in terms offinances andinstitutions.

5. Conclusions

Mediterranean Region is a common habitat for many countries. In

addition it has Mediterranean Sea and unique environmental services,biological diversity, and natural beauty. Many environmental problems

such as water pollution could be resolved in the Mediterranean Regionifrelated countries come together with common environmental policies.

Developed countries of Mediterranean Region, which have high levelindustrial pollution concentrations, could help to find environmentalfunds for developing countries, which have relatively lower industrialpollution concentrations in that region. The EU funds have the potential

to support local regions such as the Mediterranean Region.This paper has examined the relationships between biological

oxygen demand (BOD) and per capita gross domestic products (GDP)in European, Euro-Asian and African-Mediterranean countries, which

have different economic and institutional backgrounds. An environ-mental Kuznets (EKC) curve analysis has been carried out to exploresustainable resource use paths of those countries. This paper hasprovided some political and analytical results with respect to the

sustainability of development paths of the Mediterranean countries.The paper emphasizes that the modified human development index

(MHDI) is a comprehensive policy indicator that will be able to apply tothe EKC analyses because it includes many social variables such as

health effects, political rights, civil liberties, enrollment rate, and adultliteracy rate. The paper clearly points out differences between Northernand Southern countries of the Mediterranean countries. Humandevelopment should be the first objective of economic developmentin the Southern countries of the Mediterranean. The globalization

process may help the developingcountries to get someadvantages suchas not to wait for a long time for human development.

The developed countries of the Mediterranean Region have enteredthe desired economic development paths. Those countries enforce

more stringent environmental policies, and have higher technology

level that will enable cheaper environment friendly products. The

Table 5

The MHDI's impacts on BOD amounts in some periods of selected countries.

Countries 1%a 5%a

19701980 19962006 19701980 19962006

France 1.70 27.78 8.52 138.90

Italy 0.04 11.25 0.20 45.00

Spain 0.07 4.86 0.39 24.34

Turkey 0.06 8.00 0.28 32.00

Algeria 0.42 22.49 2.12 89.96

Tunisiab

0.50 3.41 2.50 13.67a Percentage increases in MHDI.b Periods are 19801985 and 20002006.



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developing countries of the Mediterranean Region have experiencedindustrialization path and consequently natural resources have been

exploited intensively. Those countries have not yet had any turningpoint in the industrializing path. However recent BOD concentrations indeveloped countries are at high levels compared to the developingcountries of Mediterranean Region. Consequently it should be con-

sidered that the EKC analyses give ideas about countries' trends ratherthan current pollution concentration levels.

The paper has some limitations due to unavailable data. Especiallythebiodiversity indicators related to Mediterranean Seawill help us tounderstand many environmental issues such as industrial pollution.Biological diversity could be important variable for further study.

The interaction between economic growth and environmental

degradation is one of the most controversial issues of the environ-mental economics literature. Although evidence of existence of theEKC has raised many questions, the subject is open-ended and itcontinues to be used widely in different regions of the world.

Acknowledgements

The author is grateful to Mrs. Sylvia Beuhler, from Agricultural

Economics and Business Department of the New Mexico StateUniversityUSA, who smoothed the paper on an earlier version. Iwould like to thank specially the editor and two referees for his/hervaluable comments and suggestions.

Appendix A. Data information

References

Agras, J., Chapman, D., 1999. A dynamic approach to environmental Kuznets curve

hypothesis. Ecological Economics 28, 267

277.Alpaslan, A.H., Ata, A., Yeil, N., 2006. River basin management plans in Turkey during

the accession period to European Union'. International Congress on River BasinManagement. Ankara, Turkey.

Anand, S., Sen, A., 2000. Human development and economic sustainability. WorldDevelopment 28, 20292049.

Andreoni, J., Levinson, A., 2001. The simple analytics of the environmental Kuznetscurve. Journal of Public Economics 80, 269286.

Angelakis, A.N., Bontoux, L., Lazarova, V., 2003. Challenges and prospectives for waterrecycling and reuse in EU countries. Water Science and Technology: Water Supply 3,5968.

Bruyn, S.M., Heintz, R.J., 1999. The environmental Kuznets curve hypothesis. In: van denBergh, C.J.M. (Ed.), Handbook of Environmental and Resource Economics. EdwardElgar, Cheltenham, UK.

Chow, Y., 2006. Economic Growth and Environmental Quality: Case study of Taiwan.Unpublished PhD thesis from the State University of New York, USA, 144pp.

Choliz, J.S., Duarte, R., 2005. Water pollution in the Spanish economy: analysis ofsensitivity to production and environmental constraints. Ecological Economics 53,325338.

Costantini, V., Monni, S., 2008. Environment, human development and economicgrowth. Ecological Economics 64, 867880.

Culas, R.J., 2007. Deforestation and the environmental Kuznets curve: an institutionalperspective. Ecological Economics 61, 429437.

Dasgupta, S., Laplante, B., Wang, H., Wheeler, D., 2002. Confronting the environmentalKuznets curve. Journal of Economic Perspectives 16, 147168.

Dinda, S., 2004. Environmental Kuznets curve hypothesis: a survey. EcologicalEconomics 49, 431455.

Ekins, P., 1997. The Kuznets curve for the environment and economic growth:examining the evidence. Environment and Planning 29, 805830.

Enevoldsen, M.K., Ryelund, A.V., Andersen, M.S., 2007. Decoupling of industrial energy

consumption and CO2-emissions in energy intensive industries in Scandinavia.Energy Economics 29, 665692.European Commission,2006. Developmentof the Mediterranean de-pollution initiative

Horizon 2020. European Commission Report December 2006, Athens, Greece.European Commission Report, 2004. The European Economic and Social Committee

report on the Implementation of Council Directive 91/271/EEC concerning UrbanWaste Water Treatment, Brussels, Belgium.

EPA, 2008. Environmental Protection Agency of the USA. www.epa.gov/waterscience/pollcontrol.

EPMR, 2002. Official Web Page of the International Conference on the Problems of theMediterranean Region. Web Page: http://epmr-2002.neu.edu.tr/.

EU, 2008. European Union Official Web Site. http://ec.europa.eu/environment/.Ezzati, M., Singer, B.H., 2001. Towards an integrated framework for development and

environment policy: the dynamics of environmental Kuznets Curves. WorldDevelopment 29, 14211434.

FAO, 2008. Food and Agriculture Organization of United Nations, AQUASTAT Web Page.http://www.fao.org/nr/water/aquastat/main/index.stm.

Fradin, G., 2006. Integrated water resource management at river basin level in France aparticipatory way to finance & monitor water investments in a sustainable manner.

International Congress on River Basin Management, Ankara, Turkey.Frstenberger, G.M., Wagner, M., 2007. Exploring the environmental Kuznets hypoth-

esis: theoretical and econometric problems. Ecological Economics 62, 648660.Gangadharan,L., Valenzuela, M.R., 2001. Interrelationships between income, healthand

the environment: extending the environmental Kuznets curve hypothesis.Ecological Economics 36, 513531.

GEMS, 2008. Global Environmental Monitoring System Official Web Page. www.gemswater.org .

Giordano, R., Passarella, G., Uricchio, V.F., Vurro, M., 2007. Integrating conflict analysisand consensus reaching in a decision support system for water resourcesmanagement. Journal of Environmental Management 84, 213228.

Grossmann, G.M.,Krueger,A.B., 1995. Economic growth and the environment. QuarterlyJournal of Economics 110, 353377.

Grlk, S., Rehber,E., 2006. Evaluationof an integratedwetlandmanagementplan: caseof Uluabat (Apollonia) Lake, Turkey. Wetlands 26, 258264.

Harbaugh, W., Levinson, A., Wilson, D.M., 2002. Re-examining the empirical evidencefor an environmental Kuznets curve. The Review of Economics and Statistics 84,541551.

Hettige, H., Mani, M., Wheeler, D., 2000. Industrial pollution in economic development:the environmental Kuznets curve revisited. Journal of Development Economics 62,445476.

Jones, L.E., Manuelli, R., 1997. The sources of growth. Journal of Econo mic Dynamics andControl 21, 75114.

Koop, G., Tole, L., 2001. Deforestation, distribution and development. Global Environ-mental Change 11, 193202.

Lindmark,M., 2002.An EKC-pattern in historicalperspective: carbon dioxide emissions,technology, fuel prices and growth in Sweden 18701997. Ecological Economics 42,333347.

Maddala, G.S., 1992. Introduction to Econometrics. Macmillan Publishing Company, NY,USA.

McPherson, M.A., Nieswiadomy, M.L., 2005. Environmental Kuznets curve: threatenedspecies and spatial effects. Ecological Economics 55, 395407.

Mora, N.H., Llamas, R., Cortina, M.L., 2006. Misconceptionsin Aquifer Over-exploitation: Implications for Water Policy in Southern Europe , Edition bookby Cesare Dosi: Agricultural Use of Groundwater. Kluwer Academic Publisher,London, UK.

Nixon, S.C., Lack, T.J., Hunt, D.T.E., 2000. Sustainable use of Europe's waters? European

Environment Agency Environmental Assessment Series, No:7, Kopenhag, Denmark,p. 34.

Noorbakshs, F., 1998. A modified human development index. World Development 26,517528.

O'neill, R.V., Kahn, J.R., Duncan, J.R., Elliott, S., Efroymson, R., Cardwell, H., Jones, D.W.,1996. Economic growth and sustainability: a new challenge. Ecological Applica-tions 6, 2324.

Raghbendra, J., Murthy, K.V.B., 2003. An inverse global environmental Kuznets curve.Journal of Comparative Economics 31, 352368.

Ranis, G., Stewart, F., Ramirez, A., 2000. Economic growth and human development .World Development 28, 197219.

Richmond, A.K., Kaufman, R.K., 2006. Is there a turning point in the relationshipbetween income and energy use and/or carbon emissions? Ecological Economics56, 176189.

Panayatou, T., 1993. Empirical Tests and Policy Analysis of Environmental Degradationat Different Stages of Economic Development, World Employment ResearchProgramme, Working Paper. International Labour Office, Geneva, p. 42.

Sagar, A.D.,Najam, A.,1998. The human developmentindex: a critical review. EcologicalEconomics 25, 249264.

The countries are selected and included in the analyses according to data availability.

European Mediterranean Countries

France 19702006

Spain 19702006

Italy 19702006

Greece 19702006

Albania 19842006

Malta 19702006

Slovenia 19902005

Euro-Asian Mediterranean countries

Turkey 19752006

Syria 19802002

Cyprus 19802003

Israel 19752006


Egypt 19812006

Algeria 19752005

Morocco 19752006

Tunisia 19802006

http://www.epa.gov/waterscience/pollcontrolhttp://www.epa.gov/waterscience/pollcontrolhttp://epmr-2002.neu.edu.tr/http://epmr-2002.neu.edu.tr/http://ec.europa.eu/environment/http://ec.europa.eu/environment/http://www.fao.org/nr/water/aquastat/main/index.stmhttp://www.fao.org/nr/water/aquastat/main/index.stmhttp://www.gemswater.org/http://www.gemswater.org/http://www.gemswater.org/http://www.gemswater.org/http://www.fao.org/nr/water/aquastat/main/index.stmhttp://ec.europa.eu/environment/http://epmr-2002.neu.edu.tr/http://www.epa.gov/waterscience/pollcontrolhttp://www.epa.gov/waterscience/pollcontrol


9/9

Selden, T.M., Song, D.S., 1994. Environmental quality and development: is there aKuznets curvefor air pollution emissions? Journal of Environmental Economics andManagement 27, 147162.

Shafik, N., 1994. Economic development and environmental quality: an econometricanalysis. Oxford Economics Paper 46, 757773.

Shafik, N., Bandyopadhyay, S., 1992. Economic Growth and Environmental Quality:Time-Series and Cross-Country Evidence. World Bank Working Papers, WPS 904,Washington, vol. 52, p. 13.

Smulders, S.,1999. Endogenous growth theory and the environment. In: van den Bergh,C.J.M. (Ed.), Handbook of Environmental and Resource Economics. Edward Elgar,Cheltenham, UK.

Suri, V., Chapman, D., 1998. Economic growth, trade and energy: implications for theenvironmental Kuznets curve. Ecological Economics 25, 198208.

Torras, M., Boyce, J.K., 1998. Income, inequality and pollution: a reassessment of theenvironmental Kuznets curve. Ecological Economics 25, 147160.

UNDP, 2008. Human Development Report. United Nations Development ProgramOfficial Web Page. www.undp.org.

UNEP/MAP, 2004. Reference Handbook on Environmental Compliance and Enforce-ment in the Mediterranean Region UNEP MAP Technical Report Series No 150Athens 2004.

Ward, F.A., 2006. Environmental and Natural Resource Economics. Prentice-Hall.World Bank, 2008. World Bank Group Official Web Page. www.worldbank.org.WRI, 2008. World Resource Institute Official Web Page. www.wri.org.

http://www.undp.org/http://www.worldbank.org/http://www.wri.org/http://www.wri.org/http://www.wri.org/http://www.worldbank.org/http://www.undp.org/

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