As a first step in our endeavour to examine the existence (or lack thereof) of a Suicidal Kuznetscurve, we plot average suicide rates and average logged per capita GDP across genders and age groups in Figures 1-6. A visual inspection of these scatter plots, which also include the median splines, reveals some interesting patterns. In particular, countries with low per capita income (e.g. Nicaragua, Armenia, Georgia, Paraguay and Croatia) are associated with low suicide rates. Then countries with per capita GDP at the sample mean of per capita GDP distribution exhibit the highest suicide rates (e.g. Lithuania, Russia, Hungary, Latvia, Estonia and Bulgaria). Countries with per capita GDP above the sample mean of the distribution experience low suicide rates (such as Malta, Portugal, Greece, Spain, Puerto Rico and Israel). Finally, countries at the highest quantiles of the per capita GDP distribution (such as Finland, Norway, Denmark, Sweden, Iceland, Switzerland, Luxembourg, the United States and Austria) experience higher suicide rates compared to those in the previous group, but higher to those in the sample mean of the distribution. Thus, this visual inspection of the scatter plots points to the direction of either an inverted U -shaped or an N-shaped Suicidal Kuznetscurve. Yet, only a formal empirical analysis can convincingly reveal the real pattern (provided it exists) of the Suicidal Kuznetscurve.
Abstract. Theoretical models of the KuznetsCurve have been purely analytical with little contribution to the timing of the process and to the presence of additional mechanisms affecting its timing. This paper proposes an agent-based version of Acemoglu and Robinsons model of the political economy of the KuznetsCurve. In extending their analytical framework we include heterogeneity of agents’ income and a mating mechanism that together represent elements of social mobility. These two simple changes proved to be enough to shed light on the length and timing before high inequality implies regime change. Thus, this work may contribute to an effective empirical assessment of the Kuznetscurve as it explicitly considers the time dimension of the process and the effects of considering social dynamics.
The underlying presumption in all these lines of thinking (except for the neo-Malthusians) is that environmental quality deteriorates in early stages of economic development and improves in the latter stages as income increases, thereby leading to an inverted-U shaped kind of relationship usually referred to as the Environmental KuznetsCurve 1 (EKC) because of its resemblance with the curve that Kuznets (1955) observed in his study of the relationship between income inequality and development. The EKC hypothesis is intended to represent a long-run relationship between environmental quality and economic growth. The process is such that, as economic development accelerates at the take off stage with the intensification of agriculture and resource extraction, the rate of resource depletion begins to exceed the rate of resource regeneration and waste generation increases in quantity and toxicity (Dinda, 2004). At
and GDP, usually proxied by per capita income. This inverted U-shaped rela- tionship is known as the empirical Kuznetscurve (EKC). The pollution levels of a country can be linked with its level of development. According to the EKC hypothesis countries initially pollute more, e.g. through pollution-intense pro- duction technologies, but after reaching a certain level of income, they pollute less. One reason is that consumers are able to demand more environmentally friendly products. Another reason is that with increased trade pollution-intense productions are outsourced to so-called pollution havens (Dinda 2004).
This paper theoretically analyzes the dynamics of economic growth and the environmental Kuznetscurve. This curve states an inverse U-relationship between pollution and income. The presented model specifically shows how a dynamic environmental Kuznetscurve 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 Kuznetscurve. Additionally, the simulations demonstrate that taxes reduce the level of pollution by pulling down the environmental Kuznetscurve. Lastly the numerical exercises highlight that the pollution level of the social planner problem is less than that of the representative agent.
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 KuznetsCurve.
The second line of research focuses on the validity of the Environmental KuznetsCurve (EKC) hypothesis. The EKC hypothesis postulates that the relationship between economic development and the environment resembles an inverted U-curve (e.g. Ang, 2007; Arouri et al., 2012; Saboori et al., 2012). That is, environmental pollution levels increase as output increase, but begin to decline as rising incomes pass beyond a turning point. However, a higher level of national income does not necessarily warrant greater efforts to contain the CO2 emissions. Arouri et al. (2012) investigated the Environmental KuznetsCurve (EKC) hypothesis for MENA countries over the period 1981-2005. The results show that real GDP exhibits a quadratic relationship with CO 2 emissions for the region as a whole. However,
Several studies showed the relationship between economic development and environmental degradation. Stern (2004) said that through a curve named Environmental KuznetsCurve (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.
Himani (2010) conducted a study on the evidence of the Environmental KuznetsCurve taking data of 2004 -2008 of 24 Indian states. Taking four pollutants namely Suspended Particulate Matter, Respirable Suspended Particulate Matter, Sulphur dioxide and Nitrogen Oxide and then relating the pollutants to state domestic product for factor cost the researcher finds that for Nitrogen Oxide and Suspended Particulate matters an inverted „U‟-shape relationship exists though its exactness varies from state to state.
In this subject one strand of literature focuses on testing the growth and environmental pollution nexus that tests the environmental Kuznetscurve (EKC) hypothesis which proposes a U-type relationship between environmental quality and economic growth. They tried to answer the question whether continued increase in economic growth will eventually undo the environmental impact of the early stages of economic development. Many related studies are available in Stern (2004) and Dinda (2004). More recent examples are those of Dinda and Coondoo (2006), Akbostanci et al. (2009), Lee and Lee (2009), Fodha and Zaghdoud (2010) and Narayan and Narayan (2010). Their results differ substantially and are inconclusive.
Our study belongs to the third group. Indeed, the control variables of the environme nta l Kuznetscurve hypothesis in the third group remarkably have identical features. For instance, some of these studies use exports, imports, and trade openness as a proxy for international trade in both developed and developing countries (e.g., Bento and Moutinho, 2016, for Italy; Halicioglu, 2009, for Turkey; Jayanthakumaran et al., 2012, for China and India). However, not only the volume of trade, but also the diversity of export products can significantly affect CO 2
The theoretical underpinnings of the relationship between economic growth and energy consumption with emissions have been discussed in the previous section. The relationship between economic growth and energy pollutants is termed as environmental Kuznetscurve. The EKC hypothesis reveals that economic growth increases energy emissions initially. The main reason is that the principal objective of public and private sectors is to support the pace of economic growth through their contribution by creating more jobs without caring about the environmental cost. Above a certain level of per capita income, the economy starts to adopt environment-friendly technology to enhance output in the country due to the rising demand of cleaner environment as people are more conscious now about environmental quality. This implies that the relationship between economic growth and energy emissions should be inverted U-shaped termed as environmental Kuznetscurve (EKC).
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 Kuznetscurve (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-
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 Kuznetscurve (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 paper revisits the Environmental KuznetsCurve (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
All variables are I (1), therefore Granger-Causality test can be used to examine the direction of causality between GDP and energy emissions. The results reported in Table-5 indicate that the GDP (GDP 2 ) affects the CO2 emissions in the long run. These results also confirm the existence of Environmental KuznetsCurve (EKC). The evidence is in line with the findings of Zhang and Cheng (2009) and Jalil and Mahmud (2009) for China, Ghosh (2010) for India, and Shahbaz et al. (2010c) for Pakistan.
Although the concept of EKC is a relatively recent phenomenon, there is a vast literature on it. The original Kuznetscurve tries to establish the relationship between economic growth and income inequality. Grossman and Krueger (1991) pioneered it application to environmental issues. The study investigated the environmental impact of a North America Free Trade agreement. An EKC was estimated for Sulphur dioxide (SO 2 ) and Suspended Particles Matter (SPM). An inverted U-
There is an increasing interest in investigating the environmental Kuznetscurve (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
The link between intelligence and air pollution is subject to controversy. Some studies report that intelligence has insignificant effect in reducing the greenhouse gas emissions. By using carbon dioxide (CO2) emissions for a large set of countries we present further novel empirical evidence on the relation between level of intelligence and air pollution. Our findings suggest that the relation follows a U-shape pattern and resembles environmental Kuznetscurve.
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 KuznetsCurve (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