URBAN AIR POLLUTION: AN ANALYSIS OF THE ENVIRONMENTAL KUZNETS CURVE IN ASIAN CITIES docx

Anderson and Brooks 1996 note the implications of having the two most populous cities of the world in Asia---- the exponential increase in pollution levels given the magnitude of economi

A Thesis Paper

On the

URBAN AIR POLLUTION:

AN ANALYSIS OF THE ENVIRONMENTAL KUZNETS CURVE

In partial fulfillment of the requirements in Economics 171: Economics Research I

February 2011

INTRODUCTION

A Background of the Problem

Sustainable development has been one of the alarming concerns in the twenty-first century Anderson and Brooks (1996) discus how given the fact that “the supply of most natural resources and environment services” are limited, it is of urgent concern to monitor and control resource usage for one to even hope for continued economic activity in the years

to come Furthermore, the incessant population and per capita growth exacerbates the problem as they are indicative of the continuous growth in economic activity (Anderson & Brooks, 1996)

Sustainable development has significant implications on the extent of economic activity in the future Anderson and Brooks (1996) elaborate saying, “scientific basis supporting the relationship between business activity, resource depletion and the environment has grown stronger in recent years.”After all, economic activity is limited and defined by the state of the environment in which businesses operate, get raw materials from, etc

The call for sustainable development has been even more urgent for Asian countries where majority of economic growth is happening and where two of the most populous countries in the world - China and India - are located Anderson and Brooks (1996) note the implications of having the two most populous cities of the world in Asia the exponential increase in pollution levels given the magnitude of economic activity in the area, as well as the alarming damage it may cause to human beings given the high population level in the region

In spite of the magnitude of importance of studying and determining the mechanisms between income and the environment in Asia, there have been limited studies on the subject matter As discussed during an interview with Ms May Ajero of Clean-Air initiative for Asian Countries (CAI-ASIA), there is no quantitative study yet which analyzes the empirical relationship between income and air pollution levels (2010)

B Objective of the Research

In line with the importance of establishing or disproving the income-environment relationship in Asia, this paper will conduct a regression analysis of three air pollutants (PM-

10, SO2, and NO2) on per capita income through the Environmental Kuznets Curve (EKC) equation The regression will be made for a panel data of seven Asian countries observed for

a period of eight years The contribution of this paper is the creation of a scientific relationship between income and pollution backed by empirical data This is not only of academic importance; rather, it brings significant policy implications After all, research studies are one of the bases of policies made For instance, observations of the EKC in certain countries lead to the assumption that environment depletion will eventually subside as income increases This perspective is highly problematic as it automatically assumes that the environment becomes better as income increases Furthermore, one of the criticisms of the EKC is that it has an anti-environmentalist tone because it downplays the urgency of the environment problem and provides an escape route in the explanation that with higher income levels, pollution will inevitably decrease (Escobar, 2011) In line with the results of the regression, this study will also discuss possible reasons for the relationship as well as

recommend policies for the care of the environment

C Statement of the Hypothesis

According to the Environmental Kuznets Curve (EKC):

At low levels of development measured by per capita GDP, environment pollution will increase As a country reaches a certain level of GDP, environmental pollution tends to decrease as income increases

The Environmental Kuznets Curve (EKC) basically describes the relationship between the concentrations of air pollution in the country relative to its gross national income per capita It is stated that as a country starts to develop (as depicted by the increase of GNP/capita), air pollution level rises due to the increase in production of commodities At a certain income per capita, pollution levels begin to decrease due the country being able to

invest in more efficient technologies and production methods

D Methodology

Air pollution measurements for seven Asian countries (China, Hong Kong, India, Japan, South Korea, Singapore and Thailand) over eight years (1998-2005) were obtained through CAI-ASIA There were three air pollutants observed: PM-10, SO2 and NO2 National income and population levels used to compute for income per capita were obtained from the World Bank database Population density, industrialization level, R&D expenditure, Gross capital formation and road sector energy consumption data were obtained from the World Bank database The pollutants were regressed on the of income per capita (its square and cubic forms), 3-year lag GDP per capita (its square and cubic), population density, industrialization level, R&D expenditure, gross capital formation and road sector energy consumption levels of the seven countries for eight years The regression equation used was the Grossman and Krueger EKC equation Panel regression was conducted while holding for fixed effects to control for time-constant factors that affect Y

However, as the cubic coefficients are observed to be insignificant, they are dropped altogether and analysis focuses on the squared form of the equation

E Scope and Limitations

The study will contribute to the field of both economic and environment study as it will provide empirical basis to support or negate the EKC phenomenon for Asian countries The empirical study will result in a quantitative association between income and environment pollution levels, particularly the relationship of income with three widely monitored air pollutants: PM-10, SO2 and NO2 The study will also look into the effect of other variables such as population density, gross capital formation, road sector energy consumption and other variables which may significantly affect pollution levels Furthermore, the study is made for pollution levels with a span of eight years, resulting in a larger data base and more strongly based regression results

However, the study will not analyze the possible reasons for the evolution of pollution levels It will not conduct an econometric study of pollution levels on a wide array of non-income variables as it first needs to establish the soundness of the EKC equation for the simple per capita income Hence, it will not be able to determine an empirically based relationship between variables such as education, literacy, policy applications, etc on pollution levels

II REVIEW OF RELATED LITERATURE

A Theoretical

According to Bruvoll and Medin (2002), the Environmental Kuznets Curve (EKC) was postulated due to the increasing concern on the relationship between economic growth and the environment (i.e., increase air, water and land pollution, etc)

The EKC describes the relationship between the concentrations of pollution to a country’s income per capita; as a country starts to develop, air pollution level rise However, after a certain income per capita, pollution levels begin to decrease as the country is able to invest in more efficient technologies and production methods

Figure 1: Environmental Kuznets Curve having an inverted-U shape Shows the relationship of air

pollution relative to the level of development of a country (Peters & Murray, 2006)

The EKC is associated with the development stages of a country During the agricultural stage, a country has low levels of income per capita at the same time it also has low levels of pollution As it approaches the industrial stage, there is an increase in the production of goods and as such increase in air pollution This is mainly brought about by factory outputs and the use of excessive fossil fuel to run the machines for production An improvement in air quality begins to follow as a country stars to invest in technology This is clearly depicted by the diagram below As one can see, the quality of air pollution depends on the level of income per capita Furthermore, based on the theory it follows an inverted-U shape

High Technology applied

Development of air pollution problems in cities according

to development status WHO Guideline or national standard Stage 0

 Figure 2: Relationship between air pollution problems in cities and the level of development As a

city experiences development, the air pollution problems in the city increase rapidly, before stabilizing and declining as air pollution controls are implemented (Peters & Murray, 2006)

There are three main economists suggesting the relationship between income and the environment as well as the reasons for the inverted-U shape of the model: Grossman (1995), Borghesi (1999) and (Yandle et al., 2004)

Grossman (1995) offers three main explanations as to how exactly income affects the environment First, is the ‘scale effect of income on the ‘environment’ As more outputs are produced, more inputs (natural resources included) are required and more wastes and emissions as by-products are created during the process Thus, resulting in the use of more natural resources to provide inputs and at the same time more polluting by-products leading

to the degradation of the environment Second, is the technology composition effect This refers to the technology as a percent of GDP A higher technology composition effect improves the state of the environment as there are more efficient means of manufacturing and producing goods A higher technology composition is assumed to imply more sophisticated end efficient technology that is beneficial for the environment Last, is the technique effect Technique pertains to the research and development (R&D) of a country Countries with better techniques experience improving environment conditions as R&D enables the country

to discover means and ways of doing things that are more efficient That is, technique leads

to the substitution of crude production processes to more efficient and cleaner ones The first

effect demonstrates the negative effect of development on the environment, happening during the early stages On the other hand, the last two shows how the environment would improve

as brought about by more economic progress

Furthermore, Borghesi (1999) suggested that market signals or the ‘existence of an endogenous self-regulatory market mechanism for the use of natural resources’ may also explain the shape of the EKC According to him, during the early stages of development there

is heavy exploitation of natural resources leading to a reduction of natural capital However,

at a certain time, there comes an increase in the price of natural resources This leads to a reduction in its exploitation Furthermore, there is an ‘accelerated shift towards less resource-intensive technologies’

In addition, (Yandle et al., 2004) offers another reason as to why the EKC is shaped,

as it is According to his reasoning, environment quality is a luxury good at higher levels of income This indicates that ‘the income elasticity of demand for environmental resources varies with the level of income’ As a country is at its early stages of development, the income elasticity for such is less than one However, after a certain threshold the income elasticity becomes greater than one That is, the change in demand for high quality environment becomes larger than the change in income The increasing demand for good quality environment results in an improvement in the environment

Regarding the limitations of the EKC, Stern (2004) offers a comprehensive study regarding of its theoretical confines First, there is ‘no feedback from environmental damage

to economic production given that income is given as an exogenous variable” It is immediately assumed that any economic activity done by the country is sustained by the environment This might seem problematic because environmental damage might reduce economic activity; thus, potentially stopping economic growth and development ‘If higher levels of economic activity are not sustainable, attempting to grow fast during the early stages

of development, when environmental degradation is rising, may prove to be counterproductive’ Second, the decrease in some air pollutant levels as brought about by greater investment in technology might only mean a shift in the kind of air pollutant now being produced In other words, although specific air pollutant levels might be decreasing, the aggregate might still be the same or even worse

Third, the effects of trade are not considered in the theory According to the Hecksher-Ohlin trade theory, under free trade countries would tend to specialize on economic activities that the country has abundant resource on Thus, developed countries would concentrate on labor and service production while developing countries would put emphasis

on human capital and manufactured capital-intensive activities As such, this might explain for the further degradation of environment of the latter, while improvement for the former

Lastly, stringent environmental policies of the developed countries might lead to polluting activities gravitating towards developing countries As a result, ‘these effects would exaggerate any apparent decline in pollution intensity with rising income along the EKC’

B Empirical

In an empirical analyses of the EKC, two topics are of main interest: first, the calculation of the threshold where environmental quality improves with rising per capita income and second, whether a given indicator of environmental degradation displays an inverted- U relationship in association with rising levels of per capita income

In terms of the calculated threshold, studies done by Grossman and Krueger (1991), Shafik and Bandopadhyay (1992) and Selden and Song (1994) would be used as basis of comparison due to their extensive research and well documented study

Grossman and Krueger (1991) analyzed the EKC relationship in the context of the North American Free Trade Agreement (NAFTA) and used the EKC-based hypothesis to argue that a NAFTA-based trade expansion would protect the environment They used sulfur dioxide and dark matter (smoke) suspended in the air in order to estimate the environmental conditions Their results showed that turning point came when per capita GDP was in the range of $4,000 to $5,000 measured in 1985 U.S dollars, which is approximately $6,700 to

$8,450 in 2003 dollars Unlike the relationship found for sulfur dioxide and smoke, no turning point was found for suspended particulates In this case, the relationship between pollution and GDP was monotonically increasing As GDP per capita rose, so did this form of pollution (Yandle et al., 2004) Furthermore, Grossman and Krueger’s study looked into the effect of other factors such as population density and the type of land on pollution levels As these factors are not correlated to income level, they are not necessary to make the equation unbiased However, Grossman and Krueger noted that the addition of these variables “reduce residual variance and make the coefficients more precise.” Lastly, the Grossman and Krueger included the “cubic of average GDP per capita in the preceding three years to proxy for the effect of permanent income, and because past income is likely to be a relevant determinant of current environmental standards” (Grossman and Kruegar, 1995) That is, income three years

before the time period analyzed has an effect on the time period’s pollution levels as machinery, equipment and activities employed at the current time is a product of income in the recent past GDP per capita and the average GDP per capita for the preceding three years were cubed to allow for greater flexibility in defining the relationship between income and pollution levels

Shortly after Grossman and Krueger, Shafik and Bandopadhyay (1992) released their study done on EKC They estimated the relationship between economic growth and several key indicators of environmental quality reported in the World Bank’s cross-country time-series data sets They found a consistently significant relationship between income and all indicators of environmental quality they examined As income increases from low levels, quantities of sulfur dioxide, suspended particulate matter, and fecal coliform increase initially and then decrease once the economy reaches a certain level of income The turning-point incomes in 1985 U.S dollars for these pollutants are $3,700, $3,300 and $1,400 respectively.9 (In 2003 U S dollars, the turning points would be about $6,200, $5,500 and

$2,300.) (Yandle et al., 2004)

After two years, Selden and Song (1994) examined the two air pollutants studied by Grossman and Krueger, along with oxides of nitrogen and carbon monoxide Their results lend support to the existence of an EKC relationship for all four air pollutants (sulfur dioxide, dark matter, nitrogen oxides and carbon monoxide) The EKC turning point (in 1985 U.S dollars) for sulfur dioxide was nearly $9,000, and in the vicinity of $10,000 for suspended particulate matter (In 2003 dollars, the figures would be about $15,200 and $16,900.) Both the figures are significantly higher than the estimates from Grossman and Krueger Seldon and Song attribute the higher turning points to the use of aggregate air-quality data, which includes readings from both rural and urban areas, rather than the urban data used by Grossman and Krueger The turning-point for environmental pollution was discovered to be

over $10,000 for oxides of nitrogen, while carbon monoxide peaked when income levels were a little over $15,000 (or approximately $16,900 and $25,300 in 2003 U.S dollars) (Yandle et al., 2004)

In summary, a long series of studies have investigated the relationship between income and pollution as defined by the Environmental Kutznets Curve Papers by Grossman and Krueger (1991), Shafik and Bandyopadhyay (1992) and Selden and Song (1994)

presented evidence that some pollutants have historically followed an inverted U-curve with

respect to income Although these and other empirical studies point to a correlation between income and pollution, the causal relation is not observed for all sets of data That is, there seems to be a highly specific and controlled environment under which the EKC condition can

be observed As such, some research like those done by Harbaugh, Levinson and Wilson (2002), Carson (2009), etc do not agree with the EKC model due to the limitations of the theory and the assumptions incorporated in it

In terms of the shape of the EKC, debates and further studies have shown other variations from the inverted-U shape originally proposed: cubic function and L-shaped curves

Torras and Boyce (1998) suggested that instead of a quadratic function, the EKC actually follows a cubic one This allows for the possibility that a downturn in pollution (at the peak of the inverted U) can be followed by a later upturn, that is, a reversal of the tendency for pollution levels to decline with further increases in per capita income These findings imply that beyond some point, high-income levels, rather than being conducive to further improvement in air and water quality, can have the opposite effect One possibility is that the scale effect overshadows the composition and technology effects

Figure 3: Environmental Kutznets Cruve: Cubic Function (Torras and Boyce 1998)

Furthermore, a study done by Lucinda Peters and Frank Murray (2006) revealed an shaped EKC as compared to the traditional inverted-U when applied to the Asian context Air quality and Gross National Income (GNI) per capita data were collected to create simple EKC graphs for Asian cities and the air pollutants of SO2, NO2, CO, PM-10 and TSP The

L-“L-shape” could be indicative of the traditional EKC inverted U curve, with the original pollution” stage no longer applicable in most Asian countries (Peters & Murray, 2006)

“pre-Results show that for Asian countries, Sulphur Dioxide decreased at $520 (US) GNI per capita; Nitrogen Dioxide on the other hand has either no obvious EKC emerging from the data Carbon Monoxide, Particulate Matter (PM10) and Total Suspended Particulates decreased at approximately $500 (US) GNI per capita (Peters & Murray, 2006)

The study may indicate that for urban air pollution in Asian cities, the typical EKC shape may not be applicable The data suggest a lowering of the income turning points for selected pollutants indicating that at low economic development, Asian cities are implementing effective air pollution control measures Instead of the inverted U curve synonymous with the typical EKC curve, the graphs indicate the emergence of an “L-shape” EKC for air pollutants in Asian cities It is proposed that this is due to lowering of income turning points and the shortening of the stages of economic development accompanying deteriorating air quality Furthermore, it is a possible that the “L-shape” EKC is due to the low number of countries in Asia experiencing the earliest stages of economic development

and consequential high levels of urban air pollution This could result in the majority of countries being near the EKC turning points or in the descending curve, creating the appearance of an “L-shape” (Peters & Murray, 2006)

Figure 4: Traditional representation of environmental quality Kuznets inverted U curve (red)

versus envisioned EKC (“L-shape”) for selected air pollutants for Asian cities in a modern environment regulation context (blue) (Peters & Murray, 2006)

C Contribution of Paper to the Study of Economics

This research paper, given the recent data of the different air pollutants (PM-10, SO2

and NO2) in several cities in Asia, will utilize the Environmental Kutznets Curve in order to determine a two-fold goal: first, if the EKC model exists in the Asian context and second, the GNI per capita that each pollutant would start to decline if ever it does exist As compared to the study published by Lucinda Peters and Frank Murray in 2006, this paper is grounded on scientific data obtained from the Clean Air Initiative- Asia That is, it will be able to establish

an econometric relationship between income and environment levels for Asian countries Furthermore, it would elaborate on possible explanations based on the existence or non-existence of the EKC It will more specifically define the relationship between income and pollution, as well as the impact of Research and Development (R&D) Expenditure, Road Energy consumption, Capital Formation, and Population Density on pollution levels The highly specific relationship that would be obtained could greatly help in the formulation of timely and essential policies to improve the state of the environment

III THEORETICAL FRAMEWORK

The Environmental Kuznets Curve states that at the early stages of development as depicted by low levels of per capita income, one can expect rising pollution levels The rapid depletion of the environment at low income levels is a result of the increasing use and depletion of natural resources, rise in emission of pollutants, the operation of less efficient and relatively dirty technologies, the high priority given to material output, combined with the low priority and even disregard of the environmental consequences of growth However,

as economic growth continues and income per capita increases, the EKC projects a slowdown

in environmental pollution and depletion That is, after a certain income is achieved, pollution decreases, resulting in the inverse-U shaped curve As such the EKC is described by the equation:

Ln(Pollutant) = a + b ln(Git)+ c[ln(Git))^2]+ u

Pollutants can be any air, water or soil particles that are considered detrimental to the environment For this study, 3 of the most widely monitored pollutants are used: PM10, SO2 and NO2 Taking the logarithm of the pollutant results in a slightly different interpretation of results -the coefficient would be indicative of the effect of the change in the independent variable on the change in the pollutant A positive coefficient means that an increase in the rate of change of per capita GDP results in a similar increase in the rate of change of pollutant levels This is different from the interpretation for level variables where a positive coefficient implies that an increase in the independent variable results in an increase

in the dependent variable The squaring of the GDP per capita will allow for the determination of an inverse-U shape as it will reveal the decreasing effect of high levels of per capita GDP on pollution levels After all, at high income per capita levels (GDP per capita) the negative sign of the coefficient of GDP per capita squared will have a decreasing effect on pollutant levels resulting in the downward turn of the U-shaped curve

For this study, the Grossman and Krueger variation of the EKC equation was used

to incorporate more factors that could affect income A more in depth discussion will be conducted in the methodology section

IV METHODOLOGY

A Regression Model

One of the most prominent econometric models formulated to quantify the Environmental Kuznets Curve (EKC) is that of Grossman and Krueger’s (1995) The theoretical model states that at the low levels of per capita income, where development and industrialization is intensive, one can expect rising pollution levels The rapid depletion of the environment at low income levels is a result of the increasing use and depletion of natural resources, rise in emission of pollutants, the operation of less efficient and relatively dirty technologies, the high priority given to material output, combined with the low priority and even disregard of the environmental consequences of growth However, as economic growth continues and income increases, the EKC projects a slowdown in environmental pollution and depletion That is, after a certain income is achieved, pollution decreases, resulting in the inverse-U curve

Grossman and Krueger defines the Environmental Kuznets Curve as:

Source: Grossman and Krueger (1991), Economic Growth and the Environment

The EKC is said to exist if β1 has a positive sign andβ2 has a negative sign, resulting

in the inverse-U shaped curve The Cubic part is there only to provide for a more accurate measure of the relationship If indeed there is a U-shaped curve, β3 will have the same negative sign as β2, implying it will continue to decrease pollution levels Or alternatively, an insignificant β3 also shows that the square is a sufficient indicator of the income-pollution relationship

In addition to the population density factor looked into by Grossman and Krueger, this paper added 3 other variables: Industry value (% of GDP from industrial sector), Road Sector Energy Consumption, and Gross Capital Formation R&D Expenditure pertains to the amount of money invested in R&D in relation to the country’s total GDP The World Bank defines Road Sector Energy consumption as the “total energy used in the road sector including petroleum products, natural gas, electricity, and combustible renewable waste.” This is indicative of the level of vehicle activity which inevitable affects pollution levels Last, this paper also looks into gross capital formation or the “outlays on additions to the fixed assets of the economy plus net changes in the level of inventories.” (World Bank) The level

of capital formation is indicative of industrial and economic activity including “land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings Inventories are stocks of goods held by firms to meet temporary or unexpected fluctuations in production

or sales.” That is, higher capital formation is indicative of higher industrial and economic construction resulting in pollution a few years hence

The equations used for this study are as follows:

The dependent or endogenous variable is the pollutant level, PM10, SO2 and NO2, while the independent or exogenous variables are the Gross Domestic Product (GDP) per capita as represented by Git, the square of Git, the cube of Git, Git or the 3 year GDP per capita lag variable (computed as the average of GDP per capita 3 years before time t), Git^2, Git^3 and Xit Grossman and Kruegar used Xit as a representation for population density, land use, and distance from desert areas For this study, Xit stands for population density, industrial level, Road Sector Energy Consumption and Gross Capita Formation

Environmental condition is depicted by the level of air pollutant while development is captured by the income per capita The square measures nonlinearities in the time path of pollution while the cube allows for flexibility in determining the relationship between income and pollution An EKC relationship will result in an insignificant coefficient for the cubic factors, as well as a positive sign for income per capita and lagged income per capita, and a negative sign for their respective squares Thus, supporting the inversed U-shape of the theory

The potential source for the fragility of the results can be brought about by collinearity As might be expected, there is a high degree of correlation between the per capita income, its square, cube and lagged versions

multi-B Data

For the Yit or the pollutant level, Particulate Matter (PM-10), Sulfur Dioxide (SO2) and Nitrogen Dioxide (NO2) levels would be utilized The data was gathered from Clean Air Initiative- Asia (CAI-Asia, 2010)

According to literature, among air pollutants, these three are the more documented ones as these are some of the ones earlier discovered leading to the development of capacity

to measure such compounds Also, it is important to consider the three pollutants due to their pressing effects on health and their impact on society First, PM10 is a major pollutant in Asian cities—with the average of annual average PM10 concentrations over three times above the WHO guidelines since 1993 (CAI-Asia, 2010) PM-10 is produced through natural activities (e.g Volcanic eruptions, fire, living vegetation, etc.) and man-made (e.g use of fossil fuels and other industrial activities) It is made up of a number of components, including acids, organic chemicals, metals, and soil or dust particles The size of particles is inversely proportional to their potential for causing health problems That is, smaller particles are more harmful as it is more difficult for these to be removed from the body system These particles stay longer in the body and cause more harm The United States Environmental Protection Agency (US EPA) is concerned about particles that are 10 micrometers in diameter or smaller because those are the particles that generally easily through the throat and nose and enter the lungs Once inhaled, these particles can affect the heart and lungs and cause serious health effects (2010) The largest sources of SO2 emissions are from fossil fuel combustion at power plants and other industrial facilities Smaller sources of SO2 emissions

include industrial processes such as extracting metal from ore, and the burning of high sulfur containing fuels by locomotives, large ships, and non-road equipment Exposure to this pollutant causes an array of adverse respiratory effects including bronchoconstriction and increased asthma symptoms (US EPA, 2010) Third, NO2 forms quickly from emissions from cars, trucks and buses, power plants, and off-road equipment In addition to contributing to the formation of ground-level ozone, and fine particle pollution, NO2 is linked with a number

of adverse effects on the respiratory system (US EPA, 2010)

The Gross Domestic Product was calculated at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources Data are in current U.S dollars Dollar figures for GDP are converted from domestic currencies using single year official exchange rates For a few countries where the official exchange rate does not reflect the rate effectively applied to actual foreign exchange transactions, an alternative conversion factor is used The data was sourced from World Bank national accounts data, and OECD National Accounts data files Using this data, the lagged variables were easy to determine (World Bank, 2011)

Industry value, Road Sector Energy consumption and Gross Capital Formation data were all obtained from the World bank database

The seven countries observed for PM-10 and SO2 are: China, Hong Kong, India, Japan, Korea, Singapore, and Thailand For NO2, the five countries observed are: Hong Kong, India, Japan, Singapore and Thailand While the NO2 regression involved: Hong Kong, Japan and Singapore For all regressions, data for years 1998-2005 were used The timeframe

of the paper’s analysis is only for eight years due to the constraints in pollutant level data

Furthermore, the capital of the country was chosen to represent that nation’s status of air quality as this city contains the most data

Regression for panel data was conducted, controlling for time differences through the fixed effects model That is, the data points were taken as non-random occurrences, and the model controlled for factors in such a way that characteristics of the data do not change over time

The negative sign of Lagged_GDP for PM-10 (the only case where the variable was significant) is interpreted as: an increase in the average GDP per capita in the 3 preceding years will result in a decrease in pollution levels However, at high income levels, the positive sign of Lagged_GDP_2 for PM-10 is interpreted as resulting in an increase in pollution levels in the long-run This results in a U-shaped curve, instead of the inverse-U defined by the EKC This may be explained by the fact that the low-income countries (China, India and Thailand) are not primarily agricultural economies with low level of pollution On the contrary, China, India and Thailand actually have industrial activities of a similar magnitude to developed countries such as Hong Kong, Japan, Singapore and Korea That is, the low income countries are not agricultural economies expected to emit low level of pollutants The EKC phenomenon assumes that there is a low level of pollution at low income levels because the low income level is a result of an agricultural economy which emits less pollutant However, this clearly does not hold for the data points where there is a low income level At the low income level data points, there are high pollution levels as well

as high industry activity, high energy consumption and capital formation

The negative sign of the coefficient of the Road Sector Energy consumption variable for PM-10 and SO2 data indicates that an increase in energy consumption results in a decrease in pollution levels This is quite counterintuitive as more energy consumption usually results in an increase in pollution level because of by-products of the activity However, more efficient car technology may explain for this phenomenon More efficient car technology (which is becoming the norm in high income countries) harness other sources of energy (electricity, water, etc.) leading to a decrease in pollution levels amidst rising energy consumption Evidence of this can be seen in the increase in hybrid cars, more energy efficient, etc