Environmental Kuznets Curve

The Environmental Kuznets Curve (EKC) posits that environmental degradation increases at the initial stages, but declines as the economy achieves a certain level of economic growth, measured in per capita income terms. This postulated relation produces an inverted U- shaped curve. The topic has drawn much research attention for both developed and emerging economies. Over the past few decades Bangladesh has been achieving remarkable rates of economic growth. A dense population along with a growing industrial base has raised the specter of a looming environmental crisis. The present study empirically investigates the EKC hypothesis for Bangladesh using data from 1971 to 2010. The Autoregressive distributed lag (ARDL) approach to cointegration has been implemented for a long run relation; and the Granger causality within the vector error correction model (VECM) for the short run dynamics. The series are found to be cointegrated. We find that energy consumption is a major contributor to CO2 emissions. Trade openness improves environment, but urbanization worsens it. Economic growth, energy consumption, trade and urbanization Granger cause CO2 emissions. Knowledge of the existence of an EKC relation can help craft appropriate policies to promote economic growth and identify the turning point, and help preserve the environment.

Netherlands, West Germany, the United Kingdom, and the United State. They found that economic growth has had a positive effect on pollutant emissions. The empirical results of Martinez-Zarzoso and Begochea-Morancho (2004) are consistent with the EKC hypothesis. In addition, Coondoo and Dinda (2008), Akbostanci et al. (2009), and Lee and Lee (2009) investigated the time series dynamics between output and pollutant emissions to deduce the direction of causality. The empirical results appear to be inconclusive. Additionally, Jaunky (2010) examined the Environmental Kuznets Curve Hypothesis for a sample of 36 high- income countries (including Bahrain, Oman and UAE) covering the period 1980-2005, the findings show that there is evidence of unidirectional causal relationship running from economic growth to pollutant emissions in both the short-run and the long-run. While, Holtz- Eakin and Selden (1995) and Shafik (1994) found a monotonic rising curve and an N-shaped curve has been found by Friedl and Getzner (2003). In addition, Richmond and Kaufmann (2006) found that there is no causal significant relationship between economic growth and pollutant emissions. Moreover, Pao and Tsai (2010) studied this relationship for the BRIC countries over the period 1971-2005, the empirical findings find a unidirectional causal relationship running from emissions to economic growth.

This paper theoretically analyzes the dynamics of economic growth and the environmental Kuznets curve. This curve states an inverse U-relationship between pollution and income. The presented model specifically shows how a dynamic environmental Kuznets curve can emerge by introducing pollution and abatement technology in a public spending model of endogenous economic growth. We also derive the turning point in function of the parameters of the model. The numerical section demonstrates that when taxes are below some threshold, the turning point decreases with taxes but it increases when taxes are above the threshold point given some ex- planations about an N-shaped Kuznets curve. Additionally, the simulations demonstrate that taxes reduce the level of pollution by pulling down the environmental Kuznets curve. Lastly the numerical exercises highlight that the pollution level of the social planner problem is less than that of the representative agent.

This paper examines the relationship between economic growth and environ- mental sustainability in the People’s Republic of China, PRC, by empirically es- timating environmental Kuznets curve (EKC) models using national data from 1994 to 2014. The results show that there exists an inverted-U shaped relation- ship as hypothesized by the EKC model between per capita GDP and per capita emissions (or discharges) of domestic water pollution, PM 2.5 microparticle emis-

For example, Dijkgraaf and Vollenbergh (1998), Stern (1998), Perman and Stern (1998) attempted to compare pooled/cross-sectional data results in relation to results obtained from time-series while Cole et al (1997), Moomaw and Unruh (1997) Roberts and Grimes (1997) and List and Gallet (1999) found evidence supporting the proposition that substituting time series data for cross/sectional data or replacing world data with regional/country data leads to different turning points of the EKC and in some cases no establishment of turning point at all for the Environmental Kuznets Curve.

Several studies showed the relationship between economic development and environmental degradation. Stern (2004) said that through a curve named Environmental Kuznets Curve (EKC), environmental degradation and pollution would increase in the early stages of economic development, but beyond some levels, economic growth will lead to environmental improvement. Thus, Arouri et al (2012) stated that real GDP had a significant impact on long-term toward carbon dioxide emission. Their research also showed that real GDP and carbon dioxide emissions had a quadratic relationship. Moreover, Farhani et al (2014) who investigating the dynamic relationship between carbon dioxide emissions, output, and trade, found that energy consumption, trade, GDP, and quadratic GDP caused CO 2 emissions.

Review of literature reveals that research work on the Environmental Kuznets Curve is insufficient. There are two reasons behind this; firstly the hypothesis is comparatively new in economics as it was formulated only in 1995. Secondly research work to test the validity of this hypothesis requires sufficient time series and panel data but reliable data required for this purpose,especially data on environmental indicators is not available. Use of cross section data of different countries can be made use as substitute of time series data. Research work conducted using cross section data is also very insufficient.

The process of globalization has become advantage for emerging nations to foster their economic progress through production and investment that also uplift the amount of environmental pollution (Ahmed and Long 2013; Katircioǧlu 2014). In recent literature, studies have shown that Environmental Kuznets curve (EKC) is best known hypothesis that explain the effects of rapid economic growth on environmental degradation. The theory stated that at first stage of economic development, environmental pollution tends to increase until it reaches a point in which further increase in economic growth reduces environmental pollutions (Kuznets 1955; Dinda 2004). Therefore, for better policy making to achieve sustainable development, it become necessary to know the relationship between economic development and environmental condition of developing economies.

The short run dynamics are reported in Table-5 and results indicate that linear and non-linear terms of real GDP per capita have positive and negative impact on energy emissions indicating the validation of environmental Kuznets curve (EKC). Energy consumption has positive and strong effect to increase energy pollutants. By consequence, if the communist regime tolerated the energy emissions in order to obtain a high output level, but with expensive costs, the actual democratic authority must stimulate energy efficiency, with a low amount of energy emissions. In this way, the Romanian actions follow the EU general energy policy.

This paper revisits the Environmental Kuznets Curve (EKC) hypothesis with the aim of determining a definite shape of the income-pollution relationship for a sample of 49 African countries for the period 1990-2010. Recent orientation of the literature has led to the use of non- and semi-parametric methods which are robust to functional form misspecification and potential parameter heterogeneity as it allows the data dynamics to determine the true shape of the relationship contrary to widely used parametric methods which assumes ex ante specified functional forms. Using the STIRPAT model as its analytical framework and the semi-parametric panel fixed effects estimator of Baltagi and Li (2002) which mitigates against functional form misspecification, the true relationship between income and two atmospheric air pollutants, namely carbon dioxide (CO 2 ) and suspended particulate matter

Kuznets [1] postulated that income inequality first rises and then falls with economic growth. Name after him, the Environmental Kuznets Curve (EKC) is a hypothesized relationship between environmental degradation and income per capita. The basic idea is simple and intuitive. In the early stages of economic growth, environmental degradation and pollution tend to increase. After certain level of income has been achieved, economic growth declines environmental degradation and pollution. Hence, the model is specified in quadratic form of income. Environmental degradation under this approach is a monotonically rising function in income with an "income elasticity" less than unity.

Enhancement of economic growth and search for better environmental quality has been the primary objectives of the government since past many years. The empirical Studies regarding the relationship between environmental degradation and economic growth have received less attention in Pakistan. In this study, an attempt has been made to examine the linkage among environmental degradation and economic growth in Pakistan over the period 1972-2011. The main concern of this study is to test the environmental Kuznets curve in case of Pakistan. The study used Autoregressive Distributed Lag (ARDL) model to determine the robustness of long-run relationship among environmental degradation and economic growth. The results show that the inverted U-shaped relationship between economic growth and environmental degradation is valid in case of Pakistan. The long run results suggest that population density has positive impact on per capita carbon emission. Moreover, an increase in energy consumption leads to environmental degradation. Following the methodology of Lipford and Yandle (2010) this study finds out the value of total carbon efficiency and per capita carbon efficiency for Pakistan economy. The values of total carbon efficiency (35.94) and Per Capita Carbon Efficiency (0.0002) of Pakistan are relatively low as compare to other developing and developed countries like in the region. The Tipping Point of EKC in case of Pakistan is 338.34.

This article investigated the dynamic linkages between energy consumption, economic growth and carbon emissions in the case of Namibia over the period of 199:q1-2016:q4. The study applied the ADF and the PP unit root test to test the non-stationarity of the variables. Also, the ARDL bounds testing approach to cointegration was employed to investigate the long run relationship between the variables. The current study has significant policy implications for the Namibian economy. The findings confirmed that all the variables are cointegrated which implies that there is a long run relationship among them and that they were robust. Energy consumption was proven to be the primary contributor to carbon emissions (energy pollutants). An increase in economic growth raises energy consumption. The results also confirmed the existence of the environmental Kuznets curve (EKC) in both long run and the short run in Namibia. Additionally, the results also show bi-directional causality between economic growth and carbon emissions, the square of economic growth and carbon emissions and energy consumption and carbon emissions. The results also show that there is unidirectional causality between economic growth and energy consumption running from energy consumption to economic growth. Lastly, the results show independence between energy consumption and the square of economic growth in the short run.

growth, energy consumption and foreign trade based on the environmental Kuznets curve (EKC) hypothesis for Indonesia during the period 1971 – 2007. The Auto regressive distributed lag (ARDL) methodology is used as an estimation technique. The results do not support the EKC hypothesis, which assumes an inverted U-shaped relationship between income and environmental degradation. The long-run results indicate that foreign trade is the most significant variable in explaining CO 2 emissions in Indonesia followed by Energy consumption and

Since the seminal paper of Grossman and Krueger (1991) on the potential environmental impacts of NAFTA, the work of Shafik and Bandyopadhyay (1992), which provided the backbone for the 1992 World Development Report, and that of Panayotou (1993) for the International Labour Organization, the environmental Kuznets curve (EKC) hypothesis has generated extraordinary research enthusiasm. The EKC hypothesis is based on the existence of an inverted U – shaped relationship between pollution and economic growth. This implies that environmental degradation increases when per capita income is relative low and decreases once a threshold level of per capita income is reached.

This study examines the validity of the Environmental Kuznets Curve (EKC) in the developing economies of West Africa using a total of 32 cross sectional observations for each of the 16 countries of West Africa given a balance panel of 512 observations covering the periods 1980 through to 2012. The study estimated both the fixed effect and random effect model but however, the Hausman test shows that the estimates of the random effect are more consistent. The empirical results from this study provide evidence of the existence of the EKC for West Africa Countries as a group with income turning point ranging between US$4,240.83 and US$4,698.91. The study thus recommends that developing countries should not wait until they reach this high income turning point to reconcile economic growth and environmental improvement. The policy implication is that an induced environmental policy response is necessary for EKC to exist.

There is an increasing interest in investigating the environmental Kuznets curve (EKC) hypothesis because it suggests the existence of a turning point in the economy that will lead to a sustainable development path. Although many studies have focused on the EKC, only a few empirical studies have focused on analyzing the EKC with specific reference to Indonesia, and none of them have examined the potential of renewable energy sources within the EKC framework. This study attempts to estimate the EKC in the case of Indonesia for the period of 1971-2010 by considering the role of renewable energy in electricity production, using the autoregressive distributed lag (ARDL) approach to cointegration as the estimation method. We found an inverted U-shaped EKC relationship between economic growth and CO 2 emissions in the long run. The estimated turning

In this study, building a simple model that incorporates static and dynamic elements, the relationship of financial development and economic growth on the environmental degradation is investigated together with the validation of the Environmental Kuznets Curve (EKC) hypothesis. Our analysis is based on an unbalanced panel data set covering the OECD countries over the period 1970-2014. Our approach strongly accounts for the presence of cross-sectional dependence between the sample variables and utilizes second generation panel unit root tests in order to investigate possible cointegration relationships. The empirical findings do indicate that local (NO X per capita emissions) and global (CO 2 per capita emissions) pollutants redefine the

The relationship between economic development and environmental quality is one of the most topical issues that have exercised the minds of contemporary development and environmental policy makers. This has particularly been so since the beginning of the 1990’s when concerns regarding global warming, climate change and environmental degradation took centre stage after the publication of the 1992 World Development Report (World Bank, 1992). The common thinking is that there is an inverted-U shaped relationship between economic activity - usually measured in terms of per capita income - and environmental quality, usually measured in terms of air quality. That is, at the initial stages of economic development, environmental degradation increases as income increases. However, after a certain level of income (turning point), environmental degradation begins to decrease as development progresses. This hypothesized relationship between economic development and environmental quality is what has been dubbed as the Environmental Kuznets Curve (henceforth, EKC), apparently because it mirrors the relationship between economic development and income inequality first observed by Kuznets (1955).

Since historical times, the pursuit of higher growth and economic prosperity has remained an important objective of government policies. However, the attainment of higher growth entails the use of natural resources (e.g. energy resources), leaving in its wake some debilitating effects on the environment. Hence achieving sustainable development – continuing improvements in the present quality of life at lower intensity of resource use without compromising future generations – has continued to received worldwide attention than ever, especially with global warming, climate change and other environmental problems becoming more and more serious. In particular, an urgent subject for policy makers charged with environmental policies is to understand and predict how the environmental quality will evolve over time. One hypothesis that is extensively used in Environmental Economics literature to empirically model the growth- environmental degradation trajectory is the so called Environmental Kuznets Curve (EKC for short). The EKC hypothesis postulates an inverted U-shaped relationship between environmental degradation and income per capita 4 . In other words, environmental degradation is expected to increase with income up to a certain threshold beyond which environmental quality will be enhanced by higher income per capita. A typical EKC is as displayed in Figure 1 below.