Alexandra-Anca Purcel
email: alexandra.anca.p@gmail.com

New insights on the environmental Kuznets curve hypothesis in developing and transition economies. A literature survey

Keywords: environmental Kuznets curve hypothesis, developing and transition economies, literature survey. JEL Classification: Q53, Q56, Q43

New insights into the environmental Kuznets curve hypothesis in developing and transition economies : a literature survey

I. Introduction

Recently, one of the major concerns of nations has become global warming, and particularly the adverse effects that this phenomenon produces on Earth and implicitly on the quality of life. Along with the start of the Industrial Revolution, there are significant changes at the global level, both economically and socially, which also reflects on the environment.

As an answer to the concerns related to environmental degradation-economic growth nexus, and the desire to synthesize them into a general mission of the population and the competent bodies, the World Commission on Environment and Development (1987) in the report entitled Our Common Future (i.e. Brundtland Report), shaped the definition of sustainable development.

According to this publication, ''sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs'' (United Nations General Assembly, 1987, p. 41) 1 . Indeed, this may not be the first and the perfect attempt to define what sustainable development constitutes, but we surely can argue that is one of the most used and debated explanation in the related literature (see e.g. [START_REF] Seghezzo | The five dimensions of sustainability[END_REF][START_REF] Ciegis | The Concept of Sustainable Development and its Use for Sustainability Scenarios[END_REF][START_REF] Stoddart | A pocket guide to sustainable development governance[END_REF]Holden et al. 2014, among others). Furthermore, if we look back in history, before the Brundtland report, [START_REF] Malthus | An Essay on the Principle of Population, as it affects the future Improvement of Society, with Remarks on the Speculations of Mr[END_REF], in his book ''Essay on the Principle of Population'' outlines some important future changing in nations' economic structure. He argues that the world's population grows at a geometric rate while the food supply increases at an arithmetic rate, leading over time to exhaustion of natural resources. Later, a report writes by [START_REF] Meadows | The Limits To Growth; a Report for the Club of Rome's Project on the Predicament of Mankind[END_REF], and suggestively named ''The Limits to Growth'' brings to light the same issues related to the excessive increases in population and economy due to industrial expansion, while natural resources follow a downward trend. Authors such as [START_REF] Basiago | Economic, social, and environmental sustainability in development theory and urban planning practice[END_REF] and [START_REF] Sandmo | The Early History of Environmental Economics[END_REF] highlight the importance of these two studies as fundamental pillars in the development of environmental and energy economics as an autonomous field.

Consequently, the importance of awareness of environmental protection and its interdependence with specific indicators at the macro-and micro-economic level have become an important topic in the early literature. Besides, along with the development of new theoretical concepts, more and more empirical studies have begun to emerge. Nowadays, as a result of the increase in data availability and the development of more sophisticated statistical techniques, there is a substantial flow of research papers related to the field of environmental and energy economics.

This study aims to review in an integrated framework the key theoretical aspects and give an updated empirical overview of the relationship between environmental degradation and economic growth via the Environmental Kuznets Curve (hereafter EKC) hypothesis. In doing so, first, we tackle the theoretical knowledge regarding the EKC, by stating the most well-known rationales behind its prevalence. Next, we move across towards the research design in terms of EKC testing and provide some details about its fundamental components, namely the model specification, assumptions, econometric methodology, and identification strategy. Second, we survey the empirical papers published in the last decade (i.e. from 2010 to 2019) that focus on developing2 and transition economies and investigate the validity of the EKC hypothesis.

Therefore, comprising together the latest published research, we would have a more homogeneous picture of the EKC literature. Moreover, along with the rapid development of more advanced statistical techniques and the increase in data availability and quality, the EKC testing approaches have also changed [START_REF] Dasgupta | Confronting the Environmental Kuznets Curve[END_REF][START_REF] Lieb | The Environmental Kuznets Curve-A survey of the Empirical Evidence and of Possible Causes[END_REF]. As such, we are inclined to believe that, on the one hand, the recent studies are more accurate vis-à-vis the research design, while, on the other hand, the increased data quality has improved the prediction of EKC both in terms of parameters and turning point estimates. Relying on this intuition, and opposite with the review of [START_REF] He | Is the Environmental Kuznets Curve hypothesis valid for developing countries? A Survey[END_REF], who targets the SO2 EKC hypothesis for the developing and transition economies and [START_REF] Shahbaz | Environmental Kuznets Curve for CO2 Emissions: A Literature Survey[END_REF], who concentrate on the CO2 EKC hypothesis, we survey the papers independent of pollution indicator used in EKC testing. Also, compared to the survey of [START_REF] Tiba | Literature survey on the relationships between energy, environment and economic growth[END_REF] on the relationship between energy, environment, and growth, we focus solely on the EKC hypothesis works and provide an updated review of the related literature.

Our findings are as follows. First, several studies reveal a long-term relationship between environmental pollution and income. Thus, the long-run character of EKC seems to prevail and strengthen the belief that the EKC is rather a phenomenon that may be observed over a relatively long period, all the more that the effects of environmental policy are visible after years from implementation. Second, it is encouraging to see that the bell-shape pattern between pollution and growth seems to emerge frequently for some developing and transition states-perhaps contrary to the general intuition that it is more challenging for these countries, compared to developed ones, to reach the optimal level of growth that could ensure the decline of pollution level, i.e. inducing an upward bending curve. Overall, this may suggest that less-developed nations might improve their environmental quality by avoiding and learning from the mistakes made by developed countries, and even switch pollution trends in favor of the environment for a lower income level [START_REF] Munasinghe | Is environmental degradation an inevitable consequence of economic growth: tunneling through the environmental Kuznets curve[END_REF][START_REF] Dinda | Environmental Kuznets Curve Hypothesis: A Survey[END_REF][START_REF] Yao | Renewable energy, carbon emission and economic growth: A revised environmental Kuznets Curve perspective[END_REF]. However, the mixed results are expected when spanning different periods and using different pollution indicators, even for the same country or group of countries. Third, in some cases, the estimated turning point lies outside the income sample values. As such, this may imply, on the one hand, a possible monotonically increasing pattern between indicators (see e.g. [START_REF] Cole | The Environmental Kuznets Curve : an empirical analysis[END_REF]Stern and Common, 2001;[START_REF] Lieb | The Environmental Kuznets Curve-A survey of the Empirical Evidence and of Possible Causes[END_REF] and, on the other hand, might reveal potential weaknesses in the identification of EKC (see e.g. [START_REF] Bernard | Environmental Kuznets Curve: Tipping Points, Uncertainty and Weak Identification[END_REF]. Regarding the latter, it becomes imperative for the researcher to determine the minimum set of assumptions to identify the genuine causal effects between variables and if we refer to the parametric approach to identify the parameters point estimate. Also, a broader perspective in terms of the statistical methods may provide further insights into EKC and narrow some of the related uncertainties. In this fashion, the methods designed to minimize the model assumptions, such as semi-, and non-parametric techniques3 , along with the ones that go beyond the time-domain approach, such as wavelet techniques related to the time-frequency domain, may provide a sound basis of comparison for the traditional econometric tools, or vice-versa (i.e. parametric methods should be seen as complementary to these methods). Ultimately, a valuable alternative to achieve robustness is when the results of different techniques incline, more or less, towards the same conclusion. For example, based on our short nonparametric descriptive exercise, China exhibits an increasing pattern between CO2 and GDP, a result also suggested by several time-series and panel studies included in our empirical review-although the sign of the associated income coefficients indicate a bell-shape pattern, some studies find turning points that lie outside the income sample range, thus, indicating a positive relationship4 .

The rest of the paper is organized as follows. Section 2 discusses the theoretical arguments that constitute the basis of the bell-shaped pattern between pollution and economic growth, Section 3 explores the potential patterns between CO2 emissions and economic growth descriptively, Section 4 reviews the empirical studies on EKC, and Section 5 concludes and provide some policy implications.

II. Theoretical aspects of EKC

Presumably, one of the most tested hypotheses in the literature that stresses the relationship between environmental degradation and economic growth is the EKC hypothesis. The assumption that the link between pollution and economic growth follows a bell-shape pattern is first introduced in the literature by [START_REF] Grossman | Environmental Impacts of the North American Free Trade Agreement[END_REF]. In their seminal paper, the authors analyze the implications that the North American Free Trade Agreement (NAFTA) has on the environment through the medium of economic growth. Based on the empirical findings, they conclude that the form of the relationship between economic growth and environmental degradation is inverted Ushaped. Thus, the quality of the environment tends to deteriorate along with economic growth until an income threshold is reached, from which the trend is reversed in favor of the environment.

Approximately during the same period, [START_REF] Shafik | Economic growth and environmental quality: Time series and cross-country evidence Washington, DC: The World Bank[END_REF] and [START_REF] Panayotou | Empirical tests and policy analysis of environmental degradation at different stages of economic development[END_REF] also search into the implications of economic growth on the environment, while the latter named the relationship between these two macro-indicators the EKC.

The rationale behind the EKC hypothesis

Throughout the years, the number of studies that have approached both theoretically and empirically the EKC hypothesis and its extensions have increased considerably. Most researchers have tried to answer the following question: Which are the drivers that shape the relationship between environmental degradation and economic development? Some authors provide potential explanations based on economic intuition. In contrast, others develop well-grounded theoretical models around a series of assumptions and/or restrictions which at least theoretically generate a bell-shaped pattern between pollution and economic growth. In the following, we look at some well-known rationale behind the EKC hypothesis provided by the existing literature, from both the side of economic intuition and theory, and briefly discuss them.

First, [START_REF] Grossman | Environmental Impacts of the North American Free Trade Agreement[END_REF] argue that the scale, structural, and technological effect may explain the nexus between pollution and growth. The scale effect manifests as a result of economic activity expanse, which in turn induces a rise in the pollution levels. In contrast, structural or compositional effect accounts for the structural changes that take place within the economy. Furthermore, once nations attain industrial apogee, they focus more on the development of information-based industries and services. Thus, as a state becomes intensive in services, it ensures a higher economic growth rate, and eventually, a steady decline in environmental degradation. Besides, in the post-industrial phase, countries have the necessary resources to invest in research, development, and innovation programs, and due to technological advancement, old technologies are gradually replaced with more efficient and less polluting ones [START_REF] Panayotou | Empirical tests and policy analysis of environmental degradation at different stages of economic development[END_REF][START_REF] Panayotou | Economic growth and the environment[END_REF].

Second, the nation's economic development also implies an increase in the population income. As such, if the quality of the environment is regarded as a normal good, its demand may be influenced positively. In the related literature, some researchers have empirically confirmed the presumption that environmental quality is a normal good (see e.g. [START_REF] Kristrom | Is the income elasticity of environmental improvements less than one?[END_REF][START_REF] Bruneau | The poor are green too[END_REF][START_REF] Martini | Is the environment a luxury? An empirical investigation using revealed preferences and household production[END_REF], while researchers such as [START_REF] Pearce | Public and private spending for environmental protection: a crosscountry policy analysis[END_REF] and [START_REF] Ghalwash | Demand for Environmental Quality: An Empirical Analysis of Consumer Behavior in Sweden[END_REF] have argued that the quality of the environment is more a luxury good. Consequently, the soundness of the EKC hypothesis may be a consequence of these fluctuations in the income elasticity of demand for environmental improvement.

Third, along with the rise in income, the individual's perception of the adverse effects of environmental degradation on quality of life also increases. As an overall outcome, compared to poorer countries, developed states tend to adopt more stringent environmental policies and regulations. Hence, in developing states, environmental regulations are fewer, and they are prone to become pollution havens for dirty industries that migrate from developed ones [START_REF] Lucas | Economic development, environmental regulation, and the international migration of toxic industrial pollution: 1960-88[END_REF]. Also, authors such as [START_REF] Stern | Economic growth and environmental degradation: a critique of the environmental Kuznets curve[END_REF], [START_REF] Suri | Economic growth, trade and energy: implications for the environmental Kuznets curve[END_REF][START_REF] Suri | Economic growth, trade and energy: implications for the environmental Kuznets curve[END_REF][START_REF] Stern | The environmental Kuznets curve. Online Encyclopedia of Ecological Economics Stern DI (2004) The Rise and Fall of the Environmental Kuznets Curve[END_REF], among others, advocate that the bell-shaped pattern for developed nations may be explained through the implications of trade. Moreover, researchers such as [START_REF] Dasgupta | Confronting the Environmental Kuznets Curve[END_REF], among others, argue that improvements in environmental quality are possible even in developing countries. Besides, the pollution may follow a downward trend for a lower level of income than those experienced by developed countries, considering the increase in the availability and novelty of methods to combat pollution.

Fourth, in the early literature, some authors provide theoretical models that attempt to explain the EKC behavior. In this fashion, some of these early theoretical works are discussed in the well-know study of Stern (2004). Likewise, more recently, [START_REF] Kijima | Economic models for the environmental Kuznets curve: A survey[END_REF] provide a comprehensive and valuable survey on both theoretical static and dynamic models behind the EKC hypothesis with detailed mathematical explanations, along with a review on empirical analysis. In Table 1, we summarize these theoretical contributions concerning the EKC hypothesis as they appear in [START_REF] Kijima | Economic models for the environmental Kuznets curve: A survey[END_REF].

Table 1. Theoretical studies on EKC based on [START_REF] Kijima | Economic models for the environmental Kuznets curve: A survey[END_REF]

Static models

Model type

Authors Models with macroeconomic production functions [START_REF] Lopez | The environment as a factor of production: the effects of economic growth and trade liberalization[END_REF], [START_REF] Lopez | Corruption, pollution, and the Kuznets environment curve[END_REF]. Models with utility functions only [START_REF] Mcconnell | Income and the demand for environmental quality[END_REF], [START_REF] Andreoni | The simple analytics of the environmental Kuznets curve[END_REF], [START_REF] Lieb | The environmental Kuznets curve and satiation: a simple static model[END_REF], Di Vita (2004).

Dynamic models

Resource allocation [START_REF] John | An overlapping generations model of growth and the environment[END_REF], [START_REF] John | Short-lived agents and the long-lived environment[END_REF], [START_REF] Selden | Neoclassical growth, the J curve for abatement and the inverted U curve for pollution[END_REF], [START_REF] Lieb | The environmental Kuznets curve and flow versus stock pollution: the neglect of future damages[END_REF], [START_REF] Dinda | A theoretical basis for the environmental Kuznets curve[END_REF], [START_REF] Chimeli | A capital scarcity theory of the environmetal Kuznets curve[END_REF], [START_REF] Prieur | The environmental Kuznets curve in a world of irreversibility[END_REF]. Technology and resource selection [START_REF] Stokey | Are there limits to growth?[END_REF], [START_REF] Hartman | Sustainable growth and the environmental Kuznets curve[END_REF], [START_REF] Tahvonen | Economic growth and transitions between renewable and nonrenewable energy resources[END_REF]. Tax policy [START_REF] Jones | Endogenous policy choice: the case of pollution and growth[END_REF], [START_REF] Egli | A dynamic model of the environmental Kuznets curve: turning point and public policy[END_REF]. Real options approach [START_REF] Wirl | Pollution thresholds under uncertainty[END_REF], [START_REF] Kijima | EKC-type transitions and environmental policy under pollutant uncertainty and cost irreversibility[END_REF].

In addition to this theoretical works, [START_REF] Brock | The Green Solow model[END_REF] taking stock of the earlier theory literature (e.g. [START_REF] Stokey | Are there limits to growth?[END_REF] Green Solow model) which provide a theoretical setup that may explain the bell-shaped pattern between pollution and economic growth through the same forces that assure the course of economic growth, namely the law of diminishing returns and the advancement of new technology [START_REF] Brock | The Green Solow model[END_REF]. Subsequently, as [START_REF] Kijima | Economic models for the environmental Kuznets curve: A survey[END_REF] argue, the Green Solow model is ''a macroeconomic dynamic model in which total production is allocated to consumption and abatement expenditure'' [START_REF] Kijima | Economic models for the environmental Kuznets curve: A survey[END_REF](Kijima et al., , p. 1193)) In this sub-section, we review some notable empirical and theoretical works that target the pollution-growth nexus and seek directly, or at least indirectly, into the rationale that may explain the bell-shaped pattern between the indicators. However, as also suggested by these studies, the reasons behind the validity of the EKC hypothesis are more diverse, and in the related theoretical and empirical literature, the views are also mixed. Among the researchers who provide literature surveys, critics and search into the rationale of EKC hypothesis, we mention the works of [START_REF] Stern | Economic growth and environmental degradation: a critique of the environmental Kuznets curve[END_REF], [START_REF] Borghesi | The Environmental Kuznets Curve: A Survey of the Literature[END_REF], [START_REF] Lieb | The Environmental Kuznets Curve-A survey of the Empirical Evidence and of Possible Causes[END_REF], [START_REF] Dinda | Environmental Kuznets Curve Hypothesis: A Survey[END_REF], Stern (2004), [START_REF] He | Is the Environmental Kuznets Curve hypothesis valid for developing countries? A Survey[END_REF], [START_REF] Carson | The Environmental Kuznets Curve: Seeking Empirical Regularity and Theoretical Structure[END_REF], [START_REF] Bo | A Literature Survey on Environmental Kuznets Curve[END_REF], [START_REF] Pasten | The Environmental Kuznets Curve: A Survey of the Theoretical Literature[END_REF], Kaika and Zervas (2013a), Kaika and Zervas (2013b), [START_REF] Stern | The environmental Kuznets curve after 25 years[END_REF], and [START_REF] Tiba | Literature survey on the relationships between energy, environment and economic growth[END_REF].

Model specification, assumptions, econometric methodology, and identification strategy

Model specification

The classical and probably the most used empirical strategy to model the link between environmental degradation and economic growth is through the polynomial equations of the second-, and third-degree (see e.g. Grosman and Krueger, 1991;[START_REF] Panayotou | Empirical tests and policy analysis of environmental degradation at different stages of economic development[END_REF] and the more recent studies of [START_REF] Miyama | Global environmental emissions estimate: application of multiple imputation[END_REF][START_REF] Lazăr | Pollution and economic growth: Evidence from central and eastern European countries[END_REF]Chen et al., 2019b; among others).

The use of quadratic function allows testing the traditional EKC hypothesis (i.e. the potential bellshaped pattern between pollution and growth), while the specification of a higher polynomial order, such as the cubic function, allows the representation of multiple patterns. These patterns cover the N-shape (a potential extended EKC when the coefficient of income, squared income and cubic income is positive, negative and positive, respectively, and statistically significant), the traditional bell-shape pattern (the coefficient of income and squared income is positive and negative, respectively, and statistically significant), and also a monotonic increasing (decreasing) relationship when only the income coefficient is statistically significant and positive (negative).

Indeed, modeling the EKC through the parametric approach implies that the functional form and also the distribution is already assumed5 [START_REF] Miyama | Global environmental emissions estimate: application of multiple imputation[END_REF]). Thus, for example, an imposed shape of the relationship through the introduction in the equation of a squared or cubic income term, when the relationship is linear, could induce weak identification, and also could bias the turning point [START_REF] Bernard | Environmental Kuznets Curve: Tipping Points, Uncertainty and Weak Identification[END_REF]. However, to reduce the bias that may potentially arise from imposing a specific functional form, econometrically one may (i) assume the largest polynomial, i.e. cubic specification, and estimate sequentially also the quadratic and linear equation to show consistency in coefficients significance (for example, if the income terms are statistically significant in a third-order polynomial equation, intuitively in the second-order polynomial equation they should lack statistical significance; see e.g. [START_REF] Lazăr | Pollution and economic growth: Evidence from central and eastern European countries[END_REF], (ii) use specific tests for the presence of a potential nonlinear relationship (see e.g. [START_REF] Lind | With or Without U? The Appropriate Test for a U-Shaped Relationship[END_REF], or (iii) employ simultaneous with the parametric techniques also the semi-, and nonparametric alternatives to assure robustness, or at least to deduce a pattern between variables descriptively (see e.g. [START_REF] Millimet | The Environmental Kuznets Curve: Real Progress or Misspecified Models[END_REF]Ordás Criado et al., 2011;[START_REF] Bernard | Environmental Kuznets Curve: Tipping Points, Uncertainty and Weak Identification[END_REF]among others). Besides, it is worth noting that not only the results obtained for the income coefficients signs, but equally, the presence or absence of a turning point helps in determining the pattern followed by the data.

A second strand of studies (see e.g. [START_REF] Millimet | The Environmental Kuznets Curve: Real Progress or Misspecified Models[END_REF]Tsurumi andManagi, 2010a, 2010b;Ordás Criado et al., 2011;[START_REF] Chen | The Estimation of Environmental Kuznets Curve in China: Nonparametric Panel Approach[END_REF][START_REF] Sen | Identification and Estimation of the Environmental Kuznets Curve: Pairwise Differencing to Deal with Nonlinearity and Nonstationarity[END_REF][START_REF] Zhang | An integrated specification for the nexus of water pollution and economic growth in China: Panel cointegration, long-run causality and environmental Kuznets curve[END_REF][START_REF] Luzzati | A multiscale reassessment of the Environmental Kuznets Curve for energy and CO2 emissions[END_REF]; among others) have challenged the classical parametric approaches, which most are based on an imposed order for the polynomial equation, by estimating the pollutionincome nexus using more flexible empirical strategies, such as semi-, and non-parametric methods.

In this regard, the findings of [START_REF] Millimet | The Environmental Kuznets Curve: Real Progress or Misspecified Models[END_REF] and Ordás Criado et al. (2011) show that compared to parametric counterparts, the semi-, and non-parametric alternatives are preferred when modeling the data. Although the amount of semi-and non-parametrical EKC literature has increased over the years, it remains relatively low compared to parametric one. First, one of the reasons may be related to the well-known curse of dimensionality issues in fully nonparametric models, induced when many factors are included in the equation. Bearing in mind a crucial and well-debated econometric objection about EKC, namely the omitted variable bias (see e.g. Stern, 2004), there is a need to account for at least the most influential factors of pollution along with the income (e.g. energy consumption, trade, foreign direct investments, structure of economy, globalization, economic freedom-to mention just a few of them), to obtain reliable and consistent results. Consequently, the curse of dimensionality could be a plausible impediment in applying nonparametric methods, but it can also be alleviated by working with semi-parametric methods.

Second, the graphical representation results of semi-and non-parametrical models may be more complex and harder to interpret, thereby most researchers seem to prefer more straightforward results, such as point estimates. Third, the insufficiency of clear-cut statistical inference procedures in the nonparametric field could influence its soundness and applicability. Forth, usually in economics and also in energy and environmental economics sub-fields, the vast majority of studies rely on some theories or prior empirical evidence. Therefore, in most cases, the specification of the model is already predefined. Furthermore, these theories and empirical regularities-some of the well-known mentioned in the above sub-section, come along with different (parameters) assumptions and/or restrictions, which may be more convenient to address through parametric techniques. Some of these possible deficiencies of semi-, and non-parametric models are also acknowledged in the context of EKC estimation by authors such as Tsurumi and Managi (2010a) and [START_REF] Bernard | Environmental Kuznets Curve: Tipping Points, Uncertainty and Weak Identification[END_REF], among others.

Model assumptions and econometric methodology

Although in the last two decades, some theories regarding the validity of EKC have emerged in the literature, the vast majority of the studies rely mostly only on econometric assumptions and/or restrictions (e.g. exogeneity, long-, and/or short-run homogeneity and heterogeneity, order of integration-for the independent factors; equal variance, lack of autocorrelation, normality-for residuals; persistence, order of integration-for endogenous variable; among others), in modeling the relationship between pollution and economic growth.

On the one hand, the potential econometric issues (e.g. cross-sectional dependence; timesseries properties, such as stationarity and cointegration; endogeneity bias caused by simultaneity, omitted variables, models misspecification, dynamic endogeneity or data measurement errors;

among others) that can arise in estimating the pollution-growth nexus and produce biased estimates, if they are neglected, could be reduced by considering a (minimum) set of assumptions.

However, it is generally acknowledged that both the data and sample characteristics play an essential role in dictating the choice of the most appropriate model specification and also the optimum econometric strategy. For instance, in testing EKC, the parameters homogeneity assumption in panel data models may be too restrictive, and the overall results may not describe the real general or individual pattern for each panel member (see e.g. [START_REF] Stern | Between estimates of the emissions-income elasticity[END_REF]Kaika and Zervas, 2013). Therefore, if the turning point occurs at the panel level, the behavior does not need to be preserved at the country-level, and the turning point could be well above the observed income values. As [START_REF] Bernard | Environmental Kuznets Curve: Tipping Points, Uncertainty and Weak Identification[END_REF] point out, when working with a panel composed of different countries, disaggregation may be a valid solution to mitigate the bias of data pooling.

In the view of the previous, recent studies, such as [START_REF] Barra | Investigating the non-linearity between national income and environmental pollution: international evidence of Kuznets curve[END_REF], illustrate for a sample of 120 countries spanned over 2000-2009 that once considering the nonstationarity property of the data, the evidence of an inverted U-shape relationship between CO2 emissions and GDP vanishes in favor of a monotonic increasing one. Besides, to overcome the different sample composition issues, the authors eliminate alternatively from the sample the same geographical region and income distribution states. Overall, the estimates suggest that the sample composition reshapes the main findings. Furthermore, [START_REF] Miyama | Global environmental emissions estimate: application of multiple imputation[END_REF], among others, suggest that excluding low-income countries from analysis due to data availability may alter the results. As such, to deal with missing data problems and its undesirable consequences on EKC estimation, they propose a series of imputation methods. Also, Stern and Common (2001) suggest that the inclusion or exclusion of developing states from the analysis may influence the occurrence of a turning point.

On the other hand, the development of novel panel6 estimators that allow for different long-, and short-run slope assumptions (see e.g. the panel ARDL technique with the associated Pooled Mean-Group, Mean-Group, and Dynamic Fixed Effects estimators discussed in [START_REF] Pesaran | Pooled mean group estimation of dynamic heterogeneous panels[END_REF], which are also robust to various potential econometric problems, such as the different order of integration for regressors and variables cointegration (see e.g. [START_REF] Pesaran | Estimating long-run relationships from dynamic heterogeneous panels[END_REF][START_REF] Pesaran | Estimation and inference in large heterogeneous panels with a multifactor error structure[END_REF][START_REF] Eberhardt | Cross-section Dependence in Non-stationary Panel Models: A Novel Estimator[END_REF][START_REF] Eberhardt | Productivity analysis in global manufacturing production[END_REF], cross-sectional dependence (see e.g. [START_REF] Pesaran | Estimation and inference in large heterogeneous panels with a multifactor error structure[END_REF][START_REF] Eberhardt | Cross-section Dependence in Non-stationary Panel Models: A Novel Estimator[END_REF][START_REF] Eberhardt | Productivity analysis in global manufacturing production[END_REF][START_REF] Chudik | Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors[END_REF][START_REF] Chudik | Long-Run Effects in Large Heterogeneous Panel Data Models with Cross-Sectionally Correlated Errors. Essays in Honor of Aman Ullah[END_REF], and endogeneity (see e.g. [START_REF] Pesaran | Pooled mean group estimation of dynamic heterogeneous panels[END_REF][START_REF] Chudik | Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors[END_REF][START_REF] Chudik | Long-Run Effects in Large Heterogeneous Panel Data Models with Cross-Sectionally Correlated Errors. Essays in Honor of Aman Ullah[END_REF], facilitate the EKC estimation. Besides, the preliminary analysis techniques, such as stationarity and cointegration tests, have also been developed to deal with cross-sectional dependence, parameter heterogeneity, among other potential econometric issues.

Nonetheless, taking note of the aspects mentioned above is ultimately the task of the researcher to properly formulate the set of assumptions and adapt the methods to sample particularities.

Identification strategy

The assumptions and restrictions consider by the researcher help in shaping the proper identification strategy and inference. In the light of previous EKC literature, which provides no consensus on its validity and the associated turning point, the recent landmark study of [START_REF] Bernard | Environmental Kuznets Curve: Tipping Points, Uncertainty and Weak Identification[END_REF] waves a red flag regarding the weak identification of both EKC and the related turning point. More specifically, the authors investigate the estimation precision of the EKC turning point using Delta and Fieller method, while controlling for a wide set of potential econometric issues (i.e. endogeneity, persistence, and functional form). The overall findings show that the estimation of the EKC turning point lacks precision (i.e. the associated confidence intervals are very large) and, thus, the policy implications based on EKC may be altered. However, the results suggest that precision is higher when considering local pollutants, a long-term perspective, or nonparametric alternatives.

In the same manner, few years before the study of [START_REF] Bernard | Environmental Kuznets Curve: Tipping Points, Uncertainty and Weak Identification[END_REF], the seminal work of [START_REF] Wagner | The carbon Kuznets curve: A cloudy picture emitted by bad econometrics?[END_REF] and [START_REF] Vollebergh | Identifying reduced-form relations with panel data: The case of pollution and income[END_REF] highlights some of the most prominent weaknesses of EKC econometrics since its grounding, and raise the relevance of its identification, respectively.

On the one hand, [START_REF] Wagner | The carbon Kuznets curve: A cloudy picture emitted by bad econometrics?[END_REF] discusses two econometric issues that lately have governed the panel data EKC literature, namely the stochastic properties of nonlinear terms of integrated variables and the cross-sectional dependence. In particular, the author shows that employing standard nonstationary panel data techniques, which do not take into account the nonlinear transformations of integrated variables and cross-sectional dependence, the bell-shaped pattern between emissions and income holds. However, when using stationary de-factored data to deal with the problems mentioned above and appropriate estimation techniques, the EKC hypothesis seems to be invalidated (all the more, these findings are robust for a comprehensive set of tests, and when the poolability assumption is relaxed). The estimations are conducted on a reduce model between CO2 (SO2) and GDP for a panel of 100 ( 97 and further control for the potential issues caused by nonstationarity, employing nonlinear nonstationary parametric and nonparametric techniques. The overall findings indicate that the time effects do not have the power to detract the positive income effects, pointing out that the regional CO2 EKC hypothesis is not at work for the period 1950-2010.

Here we discussed some of the latest most influential studies that couple the EKC with the relevance of identification procedures. The general idea of these studies lies in the fact that a large part of the empirical EKC literature lacks in providing a (reasonable) identification strategy, which reflects in misleading findings concerning its validity and the computation of associated turning point. Consequently, the identification of the pollution-growth nexus should no be ''taking as is given'', but rather assembled through convincing assumptions and investigated using appropriate econometric tools.

III. CO2 emissions stylized facts: a short descriptive empirical exercise

Clear evidence of deterioration in the quality of the environment is the sharp increase in greenhouse gas (GHG) emissions following human activities, in the post-industrial period, compared to the levels recorded prior to it. Also, CO2 is considered to be the greatest environmental threat, given the rapidity that its concentrations have increased over the years.

During the pre-industrial period, the atmospheric CO2 concentration resulting from the combustion of fossil fuels is about 280 parts per million (ppm) respectively. However, in 2016, the CO2 emissions decline in the Russian Federation (-2.1%), US (-2.0%), Japan (-1.2%) and China (-0.3%), while an increase is registered in India (4.7%) and the EU(28) (0.2%) [START_REF] Olivier | Trends in global CO2 and total greenhouse gas emissions report[END_REF]. Besides, the CO2 emissions are just an example of an air pollutant that contributes to the degradation of the environment, but the spectrum is much broader (e.g. air, water, land, noise, and light pollutants). Indeed, a vast majority of empirical studies have used CO2 emissions as a proxy for environmental degradation (see e.g. Table 2 and Table 3 in the next section). Perhaps, its importance to climate change and data availability have determined the researchers to focus more on its related impacts, in comparison to other types of pollutants.

Consequently, considering four out of six top CO2 emitters mentioned above [i.e. China, India, the Russian Federation, and the EU( 28)], and also the global level (i.e. the World), we illustrate the relationship between CO2 emissions and GDP per capita descriptively 9 , using both descriptive and nonparametric statistical techniques. Regarding the nonparametric techniques, we employ the local linear, local polynomial, and lowess nonparametric regressions models to better disentangle the pattern between CO2 pollution and economic growth. In doing so, we consider the standard specification of a general nonparametric model as follows:

𝑦 = 𝜙(𝑥) + ɛ (1)
We proxy environmental degradation by CO2 emissions per capita and economic growth by GDP per capita. The data are collected from the World Bank ( 2018) and the Janssens-Maenhout et al.

(2017), for the period 1970-2016 10 . Next, equation (1) becomes:

𝐶𝑂2 = 𝜙(𝐺𝐷𝑃) + ɛ (2)
The CO2 is the endogenous variable, GDP is the predictor variable and ɛ~𝑁𝐼𝐷(0, 𝜎 2 ) the error term. 𝜙(. ) denotes the unknown smooth continuous function, whose functional form is not specified, i.e. is estimated based on data11 .

Column [A] from Figure 1 displays the evolution of CO2 emissions and GDP for each country. In contrast, column [B] and column [C] shows the scatter plot between indicators, and the curve fitting of nonparametric regressions 12 , respectively. First, we can observe that China, India, and the World exhibit a relatively smooth monotonically increasing relationship. At the same time, in the EU(28), and the Russian Federation, the nonlinearities are more pronounced. Second, overall, the pollution decreases with economic development in the EU(28), and we note the opposite in the remaining cases. Third, judging at the descriptive level, the EKC hypothesis seems to hold only for the Russian Federation. Altogether, the straightforward descriptive analysis from Figure 1 emphasizes some important disparities related to the relationship between CO2 emissions and growth among countries considered. In the next section, we aim at presenting more in-depth empirical findings related to pollution-growth patterns of some recent studies that have tested the EKC hypothesis.

IV. Empirical literature review on EKC hypothesis

Our survey attempts to bring together some of the papers that have stressed the relationship between pollution and growth through the EKC hypothesis for developing and transition states, and are published in the literature during the period from 2010 to 2019 13 . In this respect, first, we divide our empirical literature review into three parts, namely panel data analysis, time-series analysis, and the last part, which addresses some of the new perspectives on modeling environmental degradation and economic growth nexus. The first two parts are related to the timedomain approach 14 , while the last one lies both in time-and time-frequency-domain. Moreover, each of these parts corresponds to one standalone sub-section as below. Second, related to each paper, we provide information about the authors and the year of publication, sample, time-span, empirical methodology, endogenous variable, pollution-growth pattern, and the estimated income turning point value.

Panel data analysis

Table 2 displays the studies that use panel data models to explore the EKC hypothesis. For a more homogeneous view, we split the items based on the specific technique approached, namely cointegration techniques and other panel data methods.

The first strand of studies uses larger groups of countries, which are further divided according to income level, and test the EKC hypothesis for the sub-samples of developing and/or transition countries (see [START_REF] Albulescu | FDI, income, and environmental pollution in Latin America: Replication and extension using panel quantiles regression analysis[END_REF]Chen et al., 2019;[START_REF] Kim | Carbon Dioxide Emissions and Trade: Evidence from Disaggregate Trade Data[END_REF][START_REF] Ridzuan | Inequality and the environmental Kuznets curve[END_REF][START_REF] Alvarado | Environmental degradation and real per capita output: New evidence at the global level grouping countries by income levels[END_REF][START_REF] Luzzati | A multiscale reassessment of the Environmental Kuznets Curve for energy and CO2 emissions[END_REF][START_REF] Omri | Entrepreneurship, sectoral outputs and environmental improvement: International evidence[END_REF][START_REF] Ulucak | A reinvestigation of EKC model by ecological footprint measurement for high, middle and low income countries[END_REF]. The majority of these works use CO2 emissions as the leading indicator of environmental pollution, except [START_REF] Ulucak | A reinvestigation of EKC model by ecological footprint measurement for high, middle and low income countries[END_REF], who proxy environmental degradation with the ecological footprint, and Chen et al. (2019) and Rizduan (2019) who use local pollutants. Moreover, two studies out of eight, namely [START_REF] Omri | Entrepreneurship, sectoral outputs and environmental improvement: International evidence[END_REF] and [START_REF] Ulucak | A reinvestigation of EKC model by ecological footprint measurement for high, middle and low income countries[END_REF], employ cointegration techniques, and both provide evidence in favor of the traditional EKC hypothesis. Likewise, the remaining works employ other panel data models, such as FE, RE, 2SLS, quantile regression models or semi-, and non-parametric models. Overall, the findings indicate a bell-shaped pattern between pollution and growth (with the notable exception of [START_REF] Luzzati | A multiscale reassessment of the Environmental Kuznets Curve for energy and CO2 emissions[END_REF], who find a monotonically increasing pattern for CO2 emissions and a U-shaped pattern for total primary energy supply). Regarding the turning point, Chen et al. (2019), for the inverted U-shaped curve, estimate that its value in per capita terms equals 9112.90 US$ (PM2.5), 8102.51 US$ (PM10), and 9901.53 US$ (SO2), while [START_REF] Luzzati | A multiscale reassessment of the Environmental Kuznets Curve for energy and CO2 emissions[END_REF], for the U-shaped curve, find that its value is 498 US$ (total primary energy supply).

The second strand of studies investigates the EKC validity considering almost exclusively developing and transition economies samples. In this regard, [START_REF] Leblois | What has Driven Deforestation in Developing Countries Since the 2000s? Evidence from New Remote-Sensing Data[END_REF] examine the deforestation rate EKC hypothesis for a group of 128 developing countries over the period 2002-2010. Based on the FE estimator, the results suggest the lack of a significant statistical link between environmental degradation and economic growth. In the same vein, [START_REF] Culas | REDD and forest transition: Tunneling through the environmental Kuznets curve[END_REF] explores the relationship between the rate of deforestation and growth for 43 tropical developing nations, categorized by geographical region, namely, Latin America, Africa, and Asia. The findings reveal a bell-shaped pattern for Latin America and Africa, with a turning point computed at 6072 and 1483 US$ per capita, respectively. For Asia, the relationship is found to be U-shaped, and the level of GDP for which the rate of deforestation switches its trend is about 2320 US$ per capita. Also, [START_REF] Joshi | Democracy and carbon dioxide emissions: Assessing the interactions of political and economic freedom and the environmental Kuznets curve[END_REF] point out that the relationship between CO2 emissions and growth for 87 non-OECD countries is monotonically increasing. [START_REF] Hove | An Investigation of the Environmental Kuznets Curve in Emerging Economies[END_REF] and Özokcu and Özdemir (2017) also test the EKC hypothesis for 24 and 52 emerging countries, respectively. The former authors show that the pattern is inverted U-shaped (U-shaped) for nitrous oxide emissions (CO2 emissions and fossil fuel consumption). In contrast, the latter authors unveil an N-shape pattern for CO2 emissions.

Furthermore, to examine the pollution-growth pattern several researcher use specific group of countries, namely MENA or Middle East states [START_REF] Arouri | Energy consumption, economic growth and CO2 emissions in Middle East and North African countries[END_REF][START_REF] Ozcan | The nexus between carbon emissions, energy consumption and economic growth in Middle East countries: A panel data analysis[END_REF][START_REF] Charfeddine | The impact of economic development and social-political factors on ecological footprint: A panel data analysis for 15 MENA countries[END_REF], BRIC states (Pao andTsai, 2010, 2011), African states [START_REF] Osabuohien | Beyond the Environmental Kuznets Curve in Africa: Evidence from Panel Cointegration[END_REF][START_REF] Awad | Does economic integration damage or benefit the environment? Africa's experience[END_REF], ASEAN or Asian states [START_REF] Hanif | Fossil fuels, foreign direct investment, and economic growth have triggered CO2 emissions in emerging Asian economies: Some empirical evidence[END_REF][START_REF] Nasir | Role of financial development, economic growth & foreign direct investment in driving climate change: A case of emerging ASEAN[END_REF], CEE states [START_REF] Lazăr | Pollution and economic growth: Evidence from central and eastern European countries[END_REF], SAARC states [START_REF] Waqih | Rising environmental degradation and impact of foreign direct investment: An empirical evidence from SAARC region[END_REF], or newly industrialized states [START_REF] Destek | Investigation of environmental Kuznets curve for ecological footprint: The role of energy and financial development[END_REF]. As such, [START_REF] Arouri | Energy consumption, economic growth and CO2 emissions in Middle East and North African countries[END_REF] validate the CO2 EKC hypothesis for 12 MENA states covering the period 1981-2005. The turning point of CO2 emissions is found for a GDP level of 37,263 US$ per capita. [START_REF] Charfeddine | The impact of economic development and social-political factors on ecological footprint: A panel data analysis for 15 MENA countries[END_REF] test the EKC hypothesis for ecological footprint using a sample of 15 MENA countries observed over the period 1995-2007. The empirical findings suggest a bell-shaped pattern for the whole sample and oil-exporting countries and a U-shaped pattern for non-oil-exporting countries. Likewise, the results provided by [START_REF] Ozcan | The nexus between carbon emissions, energy consumption and economic growth in Middle East countries: A panel data analysis[END_REF], based on the FMOLS estimator, unveil a U-shaped pattern between CO2 emissions and growth, with an income threshold equals to 8.23 in logs. The study is conducted for 12 Middle East nations, span over the period from 1990 to 2008. Also, using cointegration techniques, Pao andTsai (2010, 2011) confirm the presence of the bell-shaped pattern between CO2 emissions and growth in BRIC countries. The computed income turning points for the convex curve are 5.638 and 5.393 in logs, respectively. Moreover, [START_REF] Awad | Does economic integration damage or benefit the environment? Africa's experience[END_REF] for 46 African states and [START_REF] Osabuohien | Beyond the Environmental Kuznets Curve in Africa: Evidence from Panel Cointegration[END_REF] for 50 African states find evidence in favor of the EKC hypothesis, both for CO2 emissions and air pollution measured as mean annual exposure, and CO2 and PM10 emissions, respectively. In the same vein, for 15 developing Asian states using the ARDL approach, [START_REF] Hanif | Fossil fuels, foreign direct investment, and economic growth have triggered CO2 emissions in emerging Asian economies: Some empirical evidence[END_REF], validate the CO2 EKC hypothesis, while [START_REF] Nasir | Role of financial development, economic growth & foreign direct investment in driving climate change: A case of emerging ASEAN[END_REF] for 5 ASEAN economies using FMOLS and DOLS estimators unveil a monotonically increasing pattern. Besides, the findings of [START_REF] Destek | Investigation of environmental Kuznets curve for ecological footprint: The role of energy and financial development[END_REF] for 11 newly industrialized countries, and [START_REF] Waqih | Rising environmental degradation and impact of foreign direct investment: An empirical evidence from SAARC region[END_REF] for 4 SAARC countries, using panel cointegration techniques, reveal a bell-shaped pattern for ecological footprint and CO2 emissions, respectively. Also, Lazăr et al.

(2019) unveil a monotonically increasing pattern between economic growth and a series of pollution indicators, such as CO2 emissions, SO2 emissions, biocapacity, and ecological footprint.

The authors employ a series of heterogeneous panel estimators, namely MG-FMOLS, MG, and AMG, for CEE states over the period 1996-2015. On this last point, it is worth noting that all these papers use panel cointegration techniques to investigate the pollution-growth nexus pattern.

The third strand of works uses panel data models to investigate the pattern between pollution and growth for Chinese provinces. In this regard, a group of studies shows that EKC is at work for Chinese provinces [START_REF] Du | Economic development and carbon dioxide emissions in China: Provincial panel data analysis[END_REF][START_REF] Chen | The Estimation of Environmental Kuznets Curve in China: Nonparametric Panel Approach[END_REF][START_REF] Hao | Does the Environmental Kuznets Curve for coal consumption in China exist? New evidence from spatial econometric analysis[END_REF][START_REF] Li | Environmental Kuznets Curve in China: New evidence from dynamic panel analysis[END_REF][START_REF] Wang | Is there an Environmental Kuznets Curve for SO2 emissions? A semi-parametric panel data analysis for China[END_REF][START_REF] Zhang | An integrated specification for the nexus of water pollution and economic growth in China: Panel cointegration, long-run causality and environmental Kuznets curve[END_REF][START_REF] Chen | The impact of environmental regulation, shadow economy, and corruption on environmental quality: Theory and empirical evidence from China[END_REF]Hao et al., 2018b;[START_REF] Wenbo | Assessing the efficiency of China's environmental regulation on carbon emissions based on Tapio decoupling models and GMM models[END_REF][START_REF] Liu | Is China's development conforms to the Environmental Kuznets curve hypothesis and the pollution haven hypothesis?[END_REF], while other studies reveal either an inverted N-shaped pattern [START_REF] Liu | Urbanization, economic growth, and carbon dioxide emissions in China: A panel cointegration and causality analysis[END_REF][START_REF] Kang | Environmental Kuznets curve for CO2 emissions in China: A spatial panel data approach[END_REF][START_REF] Li | Spatial effects of economic performance on the carbon intensity of human well-being: The environmental Kuznets curve in Chinese provinces[END_REF][START_REF] Zhao | The impact of growth, energy and financial development on environmental pollution in China: New evidence from a spatial econometric analysis[END_REF] or a monotonically increasing pattern [START_REF] Yang | The fragility of the Environmental Kuznets Curve: Revisiting the hypothesis with Chinese data via an ''Extreme Bound Analysis[END_REF]. More specifically, evidence in favor of EKC hypothesis is found for CO2 emissions [START_REF] Du | Economic development and carbon dioxide emissions in China: Provincial panel data analysis[END_REF][START_REF] Chen | The Estimation of Environmental Kuznets Curve in China: Nonparametric Panel Approach[END_REF][START_REF] Li | Environmental Kuznets Curve in China: New evidence from dynamic panel analysis[END_REF][START_REF] Chen | The impact of environmental regulation, shadow economy, and corruption on environmental quality: Theory and empirical evidence from China[END_REF][START_REF] Wenbo | Assessing the efficiency of China's environmental regulation on carbon emissions based on Tapio decoupling models and GMM models[END_REF][START_REF] Liu | Is China's development conforms to the Environmental Kuznets curve hypothesis and the pollution haven hypothesis?[END_REF], CO2 emission intensity [START_REF] Wenbo | Assessing the efficiency of China's environmental regulation on carbon emissions based on Tapio decoupling models and GMM models[END_REF], SO2 emissions [START_REF] Wang | Is there an Environmental Kuznets Curve for SO2 emissions? A semi-parametric panel data analysis for China[END_REF], coal consumption [START_REF] Hao | Does the Environmental Kuznets Curve for coal consumption in China exist? New evidence from spatial econometric analysis[END_REF], wastewater and solid waste emissions [START_REF] Li | Environmental Kuznets Curve in China: New evidence from dynamic panel analysis[END_REF], COD and NH3-N emissions [START_REF] Zhang | An integrated specification for the nexus of water pollution and economic growth in China: Panel cointegration, long-run causality and environmental Kuznets curve[END_REF], and soot and dust emissions [START_REF] Chen | The impact of environmental regulation, shadow economy, and corruption on environmental quality: Theory and empirical evidence from China[END_REF]. Moreover, the inverted N-shaped pattern occurs for CO2 emissions [START_REF] Liu | Urbanization, economic growth, and carbon dioxide emissions in China: A panel cointegration and causality analysis[END_REF][START_REF] Kang | Environmental Kuznets curve for CO2 emissions in China: A spatial panel data approach[END_REF], SO2 emissions and solid waste [START_REF] Zhao | The impact of growth, energy and financial development on environmental pollution in China: New evidence from a spatial econometric analysis[END_REF], and carbon intensity of human wellbeing [START_REF] Li | Spatial effects of economic performance on the carbon intensity of human well-being: The environmental Kuznets curve in Chinese provinces[END_REF]. Besides, [START_REF] Yang | The fragility of the Environmental Kuznets Curve: Revisiting the hypothesis with Chinese data via an ''Extreme Bound Analysis[END_REF] find a monotonically increasing relationship for CO2 emissions and industrial gas, while Hao et al. (2018b) a U-shaped pattern for the environmental quality index, which translates in a bell-shaped one, as the dependent variable is an inverse indicator of environmental degradation. With respect to the income turning points, the recent studies of [START_REF] Li | Spatial effects of economic performance on the carbon intensity of human well-being: The environmental Kuznets curve in Chinese provinces[END_REF] and [START_REF] Zhao | The impact of growth, energy and financial development on environmental pollution in China: New evidence from a spatial econometric analysis[END_REF] show that their estimated values based on the inverted N-shaped curve are 850 and 110,000 yuan per capita for carbon intensity of human wellbeing, and 4057 and 24,484 yuan per capita (4298 and 33,355 yuan per capita) for SO2 emissions (solid waste), respectively. Moreover, for CO2 emissions, Chen and Chen (2015) and [START_REF] Liu | Is China's development conforms to the Environmental Kuznets curve hypothesis and the pollution haven hypothesis?[END_REF] find an income peak of the bell-shaped curve equals to 49,813.79 and 55,297.3 yuan per capita, respectively. [START_REF] Hao | Does the Environmental Kuznets Curve for coal consumption in China exist? New evidence from spatial econometric analysis[END_REF] show that the value of the income threshold of the coal consumption bell-shaped curve ranges between 18,456 to 23,585 yuan per capita (39,692 to covering the period 1990-2005, [START_REF] Park | Regional model of EKC for air pollution: Evidence from the Republic of Korea[END_REF] show that relationship form between SO2 emissions and growth is N-shaped (with the peak equals to 5700 US$ and the trough equals to 28,000 US$ per capita). Conversely, a U-shaped curve is at work for CO2 emissions (with the peak that ranges from 26,400 US$ to 30,000 US$ per capita) and NO2 emissions (with the peak equals to 27,600 US$ per capita). The ''-'' indicates that the turning point is not computed, while the ''*'' indicates that the estimated turning point is out of sample values. When both long-and short-run analysis is present, we report the pollution-growth nexus pattern and turning point associated with the long-run results. The methodology column gives information about the technique used in investigating the pollution-growth pattern, even if the respective study comprises other statistical and econometric techniques. All the information contained in the table represents our interpretation of the results in the analyzed studies.

Time-series analysis

The country-specific works that tackle the relationship between growth and environmental pollution through the EKC hypothesis are listed in Table 3. At first glance, we can observe that most researchers use the ARDL bounds test approach technique to investigate the validity of the EKC hypothesis. Also, the FMOLS and DOLS techniques appear frequently as econometric tools in investigating pollution-growth pattern.

First, focusing on China, several contributions [START_REF] Jalil | The impact of growth, energy and financial development on the environment in China: A cointegration analysis[END_REF][START_REF] Jayanthakumaran | CO2 emissions, energy consumption, trade and income: A comparative analysis of China and India[END_REF][START_REF] Alam | Relationships among carbon emissions, economic growth, energy consumption and population growth: testing environmental Kuznets curve hypothesis for Brazil, China, India and Indonesia[END_REF][START_REF] Solarin | Validating the environmental Kuznets curve hypothesis in India and China: The role of hydroelectricity consumption[END_REF][START_REF] Wolde-Rufael | Income distribution and CO2 emission: A comparative analysis for China and India[END_REF][START_REF] Riti | Decoupling CO2 emission and economic growth in China: Is there consistency in estimation results in analyzing environmental Kuznets curve?[END_REF][START_REF] Dong | CO2 emissions, economic growth, and the environmental Kuznets curve in China: What roles can nuclear energy and renewable energy play?[END_REF]and Chen et al., 2019) find empirical evidence in favor of traditional CO2 EKC hypothesis. Also, while [START_REF] Riti | Decoupling CO2 emission and economic growth in China: Is there consistency in estimation results in analyzing environmental Kuznets curve?[END_REF] estimate the peak value of the bell-shape curve within the income range values, the findings of [START_REF] Jalil | The impact of growth, energy and financial development on the environment in China: A cointegration analysis[END_REF] and [START_REF] Dong | CO2 emissions, economic growth, and the environmental Kuznets curve in China: What roles can nuclear energy and renewable energy play?[END_REF] indicate that the turning point lies outside the sample values. However, the authors cover different periods, and in particular, the three studies which compute the bell-shaped curve maxima, span the period 1978-2006 [START_REF] Jalil | The impact of growth, energy and financial development on the environment in China: A cointegration analysis[END_REF]), 1970-2015[START_REF] Riti | Decoupling CO2 emission and economic growth in China: Is there consistency in estimation results in analyzing environmental Kuznets curve?[END_REF][START_REF] Panayotou | Empirical tests and policy analysis of environmental degradation at different stages of economic development[END_REF]-2016[START_REF] Dong | CO2 emissions, economic growth, and the environmental Kuznets curve in China: What roles can nuclear energy and renewable energy play?[END_REF]. Conversely, [START_REF] Onafowora | Bounds testing approach to analysis of the environment Kuznets curve hypothesis[END_REF] conclude that the pattern between CO2 emission and growth is N-shaped, while the associated income peak is equal to 17. Second, for Malaysia, the empirical findings seems to cover a broad spectrum of patterns, such as the traditional bell-shaped [START_REF] Saboori | Economic growth and CO2 emissions in Malaysia: A cointegration analysis of the Environmental Kuznets Curve[END_REF]Saboori and Sulaiman, 2013b;[START_REF] Lau | Investigation of the environmental Kuznets curve for carbon emissions in Malaysia: Do foreign direct investment and trade matter?[END_REF][START_REF] Ali | Re-visiting the environmental Kuznets curve hypothesis for Malaysia: Fresh evidence from ARDL bounds testing approach[END_REF][START_REF] Azam | Effect of tourism on environmental pollution: Further evidence from Malaysia, Singapore and Thailand[END_REF], the U-shaped [START_REF] Begum | CO2 emissions, energy consumption, economic and population growth in Malaysia[END_REF][START_REF] Chandran | The impacts of transport energy consumption, foreign direct investment and income on CO2 emissions in ASEAN-5 economies[END_REF], the inverted N-shaped [START_REF] Bekhet | The role of renewable energy to validate dynamic interaction between CO2 emissions and GDP toward sustainable development in Malaysia[END_REF], the monotonically increasing relationship [START_REF] Azlina | Dynamic linkages among transport energy consumption, income and CO2 emission in Malaysia[END_REF], or no statistical link (Saboori and Sulaiman, 2013a).

Furthermore, [START_REF] Saboori | Economic growth and CO2 emissions in Malaysia: A cointegration analysis of the Environmental Kuznets Curve[END_REF] and Saboori and Sulaiman (2013b) unveil that the computed GDP maxima of the bell-shaped curve for the period 1980-2009 is 4700 US$ per capita, and depending on the model 5378/5825/6003/8267 US$ per capita, respectively. However, it is worth noting that the estimated peak value of Saboori and Sulaiman (2013b) lies outside the GDP sample values. As well, considering the inverted N-shaped curve, [START_REF] Bekhet | The role of renewable energy to validate dynamic interaction between CO2 emissions and GDP toward sustainable development in Malaysia[END_REF] reveal that the pollution switches its trend for a GDP value of 170.9 RM billion (trough) and 2841.9 RM billion (peak). However, the income peak lies outside the sample range values.

Third, with respect to CO2 EKC for Indonesia, two studies show that the bell-shaped pattern is supported by data [START_REF] Alam | Relationships among carbon emissions, economic growth, energy consumption and population growth: testing environmental Kuznets curve hypothesis for Brazil, China, India and Indonesia[END_REF][START_REF] Sugiawan | The environmental Kuznets curve in Indonesia: Exploring the potential of renewable energy[END_REF], while other three studies reveal mixed results, namely a monotonically increasing relationship [START_REF] Yao | Renewable energy, carbon emission and economic growth: A revised environmental Kuznets Curve perspective[END_REF][START_REF] Chandran | The impacts of transport energy consumption, foreign direct investment and income on CO2 emissions in ASEAN-5 economies[END_REF] or a U-shaped pattern (Saboori and Sulaiman, 2013a). Concerning the income threshold, [START_REF] Sugiawan | The environmental Kuznets curve in Indonesia: Exploring the potential of renewable energy[END_REF] estimate an out of sample turning point of 7729 US$ per capita. Besides, [START_REF] Chandran | The impacts of transport energy consumption, foreign direct investment and income on CO2 emissions in ASEAN-5 economies[END_REF], along with Malaysia and Indonesia, examine the EKC hypothesis for Thailand, Singapore, and the Philippines, for the period 1971-2011.

Overall, the empirical findings reject a long-run relationship between variables for the Philippines and Singapore, while for Thailand, the pattern seems to be convex, invalidating the EKC hypothesis. More recently, the empirical analysis of [START_REF] Azam | Effect of tourism on environmental pollution: Further evidence from Malaysia, Singapore and Thailand[END_REF] leads to the same conclusions, namely the presence of the U-shaped pattern for Thailand, and no statistically significant results for Singapore. Opposite, using DOLS estimator, [START_REF] Katircioğlu | Testing the tourism-induced EKC hypothesis: The case of Singapore[END_REF] show that the EKC is valid for Singapore, for the period 1971-2010. Also, using the same sample of countries as [START_REF] Chandran | The impacts of transport energy consumption, foreign direct investment and income on CO2 emissions in ASEAN-5 economies[END_REF] to test the CO2 EKC hypothesis, Saboori and Sulaiman (2013a) reveal that the inverted U-shaped pattern holds only for Singapore and Thailand. The income peak value is 8.65 in logs (Singapore), and 7.47 in logs (Thailand).

Fourth, the strand of papers that target the CO2 EKC hypothesis for India show that in most cases the bell-shaped pattern holds [START_REF] Jayanthakumaran | CO2 emissions, energy consumption, trade and income: A comparative analysis of China and India[END_REF][START_REF] Tiwari | The environmental Kuznets curve and the role of coal consumption in India: co-integration and causality analysis in an open economy[END_REF][START_REF] Kanjilal | Environmental Kuznet's curve for India: Evidence from tests for cointegration with unknown structural breaks[END_REF][START_REF] Boutabba | The impact of financial development, income, energy and trade on carbon emissions: Evidence from the Indian economy[END_REF][START_REF] Shahbaz | Does globalization impede environmental quality in India?[END_REF][START_REF] Wolde-Rufael | Income distribution and CO2 emission: A comparative analysis for China and India[END_REF][START_REF] Solarin | Validating the environmental Kuznets curve hypothesis in India and China: The role of hydroelectricity consumption[END_REF][START_REF] Sinha | Estimation of Environmental Kuznets Curve for CO 2 emission: Role of renewable energy generation in India[END_REF][START_REF] Yao | Renewable energy, carbon emission and economic growth: A revised environmental Kuznets Curve perspective[END_REF], with the notable exception of [START_REF] Alam | Relationships among carbon emissions, economic growth, energy consumption and population growth: testing environmental Kuznets curve hypothesis for Brazil, China, India and Indonesia[END_REF], who find that CO2 pollution increases along with economic growth. With regard to the turning point, authors such as [START_REF] Tiwari | The environmental Kuznets curve and the role of coal consumption in India: co-integration and causality analysis in an open economy[END_REF] and [START_REF] Boutabba | The impact of financial development, income, energy and trade on carbon emissions: Evidence from the Indian economy[END_REF] show that its estimated value is 28,131 Indian rupees per capita for the period 1996-2011, and 19,380 Indian rupees per capita for the period 1971-2008, respectively. Also, [START_REF] Yao | Renewable energy, carbon emission and economic growth: A revised environmental Kuznets Curve perspective[END_REF] find that the threshold arises for an income value of 6.61 in logs, while [START_REF] Sinha | Estimation of Environmental Kuznets Curve for CO 2 emission: Role of renewable energy generation in India[END_REF] identify an out of sample turning point which corresponds to a value of 2937.77 US$ per capita.

Fifth, the group of scholars that focus on Tunisia, unveil both a nonlinear bell-shaped relationship between CO2 pollution and growth [START_REF] Shahbaz | Environmental Kuznets curve in an open economy: A bounds testing and causality analysis for Tunisia[END_REF][START_REF] Farhani | CO2 emissions, output, energy consumption, and trade in Tunisia[END_REF] and a U-shaped pattern [START_REF] Jebli | The environmental Kuznets curve, economic growth, renewable and non-renewable energy, and trade in Tunisia[END_REF]. Also, for the period 1961-2004, the results of [START_REF] Fodha | Economic growth and pollutant emissions in Tunisia: An empirical analysis of the environmental Kuznets curve[END_REF] reveal an inverted U-shaped pattern for SO2 (with an associated GDP turning point value of 1200 US$ per capita), and a monotonically increasing one for CO2.

In the case of Pakistan, Nasir and Ur Rehman (2011) and [START_REF] Danish | Role of renewable energy and non-renewable energy consumption on EKC: Evidence from Pakistan[END_REF] provide evidence that supports the EKC hypothesis for CO2 emissions, while according to [START_REF] Hussain | An econometric study of carbon dioxide (CO2) emissions, energy consumption, and economic growth of Pakistan International[END_REF] the pattern seems to be monotonically increasing. Moreover, according to Nasir and Ur

Rehman's (2011) findings, the GDP threshold of the concave function is equal to 625 US$ per capita. As well, the studies of [START_REF] Charfeddine | The impact of energy consumption and economic development on Ecological Footprint and CO2 emissions: Evidence from a Markov Switching Equilibrium Correction Model[END_REF] and [START_REF] Mrabet | Testing the Kuznets Curve hypothesis for Qatar: A comparison between carbon dioxide and ecological footprint[END_REF] The studies which examine the pollution-growth pattern for Turkey reveal, depending on pollution indicator, either a bell-shaped pattern [START_REF] Bölük | The renewable energy, growth and environmental Kuznets curve in Turkey: An ARDL approach[END_REF][START_REF] Pata | The influence of coal and noncarbohydrate energy consumption on CO2 emissions: Revisiting the environmental Kuznets curve hypothesis for Turkey[END_REF]Zambrano-Monserrate et al., 2018a;Huag and Ucal, 2019), an U-shaped pattern (Huag and Ucal, 2019) or no statistical link (Huag and Ucal, 2019; [START_REF] Yao | Renewable energy, carbon emission and economic growth: A revised environmental Kuznets Curve perspective[END_REF]. Besides, concerning the income turning point, [START_REF] Bölük | The renewable energy, growth and environmental Kuznets curve in Turkey: An ARDL approach[END_REF] and [START_REF] Pata | The influence of coal and noncarbohydrate energy consumption on CO2 emissions: Revisiting the environmental Kuznets curve hypothesis for Turkey[END_REF] (2018) for Peru; [START_REF] Yao | Renewable energy, carbon emission and economic growth: A revised environmental Kuznets Curve perspective[END_REF] for Russia]; (ii) a monotonically decreasing pattern [Pao et al. (2011) for Russia]; (iii) a U-shaped pattern [START_REF] Ozturk | Investigating the validity of the environment Kuznets curve hypothesis in Cambodia[END_REF] for Cambodia; [START_REF] Halicioglu | The impact of international trade on environmental quality: The case of transition countries[END_REF] for Azerbaijan, Lithuania, Moldavia, Russia, and Tajikistan]; (iv) an inverted U-shaped pattern [START_REF] Baek | Is economic growth good or bad for the environment? Empirical evidence from[END_REF] for Korea; [START_REF] Shahbaz | Environmental Kuznets curve in Romania and the role of energy consumption[END_REF] for Romania; [START_REF] Bouznit | CO2 emission and economic growth in Algeria[END_REF] for Algeria; [START_REF] Alam | Relationships among carbon emissions, economic growth, energy consumption and population growth: testing environmental Kuznets curve hypothesis for Brazil, China, India and Indonesia[END_REF] for Brazil; [START_REF] Halicioglu | The impact of international trade on environmental quality: The case of transition countries[END_REF] for Armenia, Belarus, Estonia, Kyrgyzstan, Turkmenistan, and Uzbekistan; [START_REF] Ahmad | Modelling the CO2 emissions and economic growth in Croatia: Is there any environmental Kuznets curve?[END_REF] for Croatia; [START_REF] Pata | The influence of coal and noncarbohydrate energy consumption on CO2 emissions: Revisiting the environmental Kuznets curve hypothesis for Turkey[END_REF]; [START_REF] Yao | Renewable energy, carbon emission and economic growth: A revised environmental Kuznets Curve perspective[END_REF] for Brazil, South Africa, and South Korea];

(v) an N-shaped pattern [START_REF] Onafowora | Bounds testing approach to analysis of the environment Kuznets curve hypothesis[END_REF] for Brazil, Egypt, Mexico, Nigeria, and

South Africa]; (vi) an inverted N-shaped pattern [START_REF] Onafowora | Bounds testing approach to analysis of the environment Kuznets curve hypothesis[END_REF] for South Korea];

(vii) and also no statistical link [START_REF] Halicioglu | The impact of international trade on environmental quality: The case of transition countries[END_REF] for Georgia, Kazakhstan, Latvia,

and Ukraine]. Likewise, [START_REF] Narayan | Carbon dioxide emissions and economic growth: Panel data evidence from developing countries[END_REF], using the cointegration approach for a sample of 43 developing countries over the period 1980-2004, conclude that only in about 35% of the sample, the downward-bending curve is at work.

Furthermore, the authors who compute the associated income turning point of the specific function reveal the following results. On the one hand, [START_REF] Onafowora | Bounds testing approach to analysis of the environment Kuznets curve hypothesis[END_REF] show that the peak (i.e. 22.083 in logs) of the N-shaped curve for Brazil lies outside the sample range, while [START_REF] Yao | Renewable energy, carbon emission and economic growth: A revised environmental Kuznets Curve perspective[END_REF] unveil that the peak (i.e. 10.57 in logs) of the bell-shaped curve lies within the income sample values. On the other hand, the researchers that estimate the income peak value for South Africa reveal a similar behavior. As such, according to Onafowora and Owoye (2014), the estimated threshold (i.e. 22.963 in logs) value lies outside the sample range, while [START_REF] Yao | Renewable energy, carbon emission and economic growth: A revised environmental Kuznets Curve perspective[END_REF] find the opposite (the estimated threshold equals 8.75 in logs). For Korea, [START_REF] Baek | Is economic growth good or bad for the environment? Empirical evidence from[END_REF] and [START_REF] Yao | Renewable energy, carbon emission and economic growth: A revised environmental Kuznets Curve perspective[END_REF] reveal that the turning point of the bell-shaped curve lies well within the income sample values. Also, the studies which estimate the value of the income threshold for other states find values outside the sample range [START_REF] Onafowora | Bounds testing approach to analysis of the environment Kuznets curve hypothesis[END_REF] for Egypt, Mexico, and Nigeria; [START_REF] Bouznit | CO2 emission and economic growth in Algeria[END_REF] for Algeria].

New perspectives on modelling environmental degradation and economic growth nexus

A large majority of the empirical studies mentioned above apply classical econometric tools to check the validity of the EKC hypothesis. However, some novel techniques, such as wavelet analysis, has recently emerged in the related literature and has gained the attention of researchers.

Compared with the classical econometric techniques that are part of the time-domain and the techniques associated with the frequency-domain (e.g. the Fourier approach), the wavelet analysis is much more flexible, in the sense that covers both the time-and frequency-domain [START_REF] Schleicher | An Introduction to Wavelets for Economists[END_REF]. Thus, this type of analysis may provide a broader perspective on data behavior by allowing to investigate different time-horizons (e.g. short-, medium-, and long-term), and highlighting the potential nonlinearities, direction of causality, and lead-lag nexus (cyclical and counter-cyclical course) between variables at distinct frequencies and time-periods [START_REF] Mutascu | A Wavelet Analysis of the Environmental Kuznets Curve in France[END_REF].

The empirical literature regarding wavelet analysis is relatively new and limited, with almost all studies focusing on modeling the environmental degradation-economic growth nexus for developed countries (see e.g. [START_REF] Mutascu | A Wavelet Analysis of the Environmental Kuznets Curve in France[END_REF][START_REF] Fosten | CO2 Emissions and Economic Activity: a Short-to-Medium Run Perspective[END_REF], Raza et al., 2019, among others). Concerning developing and transition countries, authors such as [START_REF] Jammazi | Environment degradation, economic growth and energy consumption nexus: A wavelet-windowed cross correlation approach[END_REF] and [START_REF] Kalmaz | Modeling CO2 emissions in an emerging market: empirical finding from ARDL-based bounds and wavelet coherence approaches[END_REF] employ wavelet techniques to examine the relationship between environmental degradation and economic growth. Nevertheless, the EKC hypothesis is explicitly tested only in the study of Jammazi and Aloiu (2015). The authors use a sample of six oil-exporting countries from the Gulf Cooperation Council (Saudi Arabia, Bahrain, Oman, United Arab Emirates, Qatar, and Kuwait), and based on wavelet windowed cross-correlation results, they show that the EKC hypothesis is valid for the period 1980-2012. More recently, [START_REF] Kalmaz | Modeling CO2 emissions in an emerging market: empirical finding from ARDL-based bounds and wavelet coherence approaches[END_REF] investigate the relationship between CO2 emissions and GDP, among other variables, for Turkey. According to wavelet coherence analysis, overall, the findings suggest a positive correlation between CO2 and GDP over the period 1960-2015.

Although wavelet analysis is recently adopted as a statistical tool in economics, it may represent a promising approach through which one can provide straightforward and valuable insights, and policy recommendations for different economic hypotheses such as EKC. Moreover, taking stock of the complexity of the phenomena and its interconnectedness that govern the field of energy and environmental economics, this type of approach that moves away from time-domain may add valuable information when used in empirical analysis, both solely or along with other techniques.

V. Conclusions and policy implications

The quality of the environment plays a vital role in nations' welfare and remains a very debatable subject both at the international and national levels. Additionally, no single formula has yet been found to fit all economic contexts in terms of mitigating pollution and its adverse effects.

Starting for the premise of sustainable development, the goal of this paper was to provide both a theoretical review of the key aspects of EKC and an updated empirical review of the pollutiongrowth nexus literature that focuses on the EKC hypothesis testing in developing and transition states.

Consequently, our updated survey may provide valuable information and, to some extent, positive prospects on EKC estimation, since the reviewed works angle towards a consensus both in terms of empirical strategy and the EKC validity. On the one hand, strengthening the EKC character, most of the studies unveiled a long-term relationship between environmental pollution and economic growth. In this fashion, the findings of numerous works emphasized a cointegration relationship between variables. Thus, concerning the related techniques, the advance in statistics and econometrics has facilitated their development and implementation, all of which have had a beneficial impact on EKC estimation. On the other hand, several studies have found evidence in favor of EKC, suggesting that some developing and transition economies have succeeded in attaining the income threshold, and have improved their environmental conditions. However, according to some works, the estimated value of the income turning point lies outside the sample range. In these specific cases, the findings should be treated with care, as this may imply that the future growth may increase pollution levels, and/or highlight possible issues regarding the EKC and the associated threshold identification. Taken collectively, both the theoretical foundations and empirical evidence, could contribute to a better understanding of the pollution-growth nexus in the EKC context, and suggest some meaningful insights regarding the future works on the subject, as well as the crucial policy implication in developing and transition economies.

In light of the overall results, some policy implications could be drawn. First, some developing and transition states have managed to keep low levels of pollution along with economic growth, and even reached the EKC threshold for a lower level of income compared to developed nations (see e.g. the recent work of Yao et al., 2019, among others). Hence, these states could be treated as a positive example and examined more in detail to get insights related to the factors that contribute to inducing a bending downward curve in pollution. In this regard, over the years, the environmental and energy economics literature has unveiled some of the key elements that may promote a reduction in pollution levels (increase environmental quality). Focusing our attention primarily on developing and transition economies, we mention the factors related to energy structure, such as lower energy consumption, higher renewable and nuclear energy share in total energy consumption, higher energy efficiency (see e.g. [START_REF] Baek | Is economic growth good or bad for the environment? Empirical evidence from[END_REF][START_REF] Azlina | Dynamic linkages among transport energy consumption, income and CO2 emission in Malaysia[END_REF][START_REF] Sugiawan | The environmental Kuznets curve in Indonesia: Exploring the potential of renewable energy[END_REF][START_REF] Danish | Role of renewable energy and non-renewable energy consumption on EKC: Evidence from Pakistan[END_REF][START_REF] Dong | CO2 emissions, economic growth, and the environmental Kuznets curve in China: What roles can nuclear energy and renewable energy play?[END_REF][START_REF] Sinha | Estimation of Environmental Kuznets Curve for CO 2 emission: Role of renewable energy generation in India[END_REF]Chen et al., 2019b), the factors associated to overall political system, such as good governance, corruption control, higher institutional quality, and political stability, and democracy (see e.g. [START_REF] Shahbaz | Environmental Kuznets curve in Romania and the role of energy consumption[END_REF][START_REF] Osabuohien | Beyond the Environmental Kuznets Curve in Africa: Evidence from Panel Cointegration[END_REF][START_REF] Ozturk | Investigating the validity of the environment Kuznets curve hypothesis in Cambodia[END_REF]Chen et la., 2018;[START_REF] Purcel | Does Political Stability Hinder Pollution? Evidence From Developing States[END_REF][START_REF] Ronaghi | The impact of economic factors and governance on greenhouse gas emission[END_REF], the coexistence of an eco-friendly and relatively large industry sector and a high labor productivity which uphold complex techniques (see e.g. [START_REF] Lazăr | Pollution and economic growth: Evidence from central and eastern European countries[END_REF], the environmental awareness (Chen et al., 2019a), among others. Besides, [START_REF] Halkos | Economic growth and environmental degradation: a conditional nonparametric frontier analysis[END_REF] revealed the importance that international agreements have on climate change mitigation.

Their recent findings showed that the states which signed an international agreement, such as the Kyoto Protocol, exhibit higher environmental efficiency compared to their counterparts. These results are quite significant (all the more that their sample of 73 countries covered 55 developing ones) and may suggest that the developing world should be engaged more actively at international and also national level in green activities to ensure high environmental efficiency. Likewise, for transition economies, the findings of Zugravu-Soilita (2018) suggested that trade intensity in environmental goods reduced CO2 emissions, primarily through the income effect. However, the opposite is found for water pollution, while for SO2 emissions, the effect lacks significance.

Overall, the author argued that in the context of sustainable development, freer trade in environmental goods might be attained through the regional or bilateral agreements that reflect the countries' peculiar context.

Second, after a certain threshold is reached, environmental degradation may be irreversible and costly, both economically and socially [START_REF] Munasinghe | Is environmental degradation an inevitable consequence of economic growth: tunneling through the environmental Kuznets curve[END_REF]. Bearing in mind that the effects of policies and regulations are often visible in the long-term, to fight against environmental degradation, it is primordial to consider all the potential detrimental factors and take preventive measures. As such, good knowledge of the domestic economic, social, and political environment, along with a constant adaptation of environmental regulations and policies, may bring added value and improve the environmental quality. Furthermore, prolific international cooperation could foster the assimilation of know-how and new green technologies. Nowadays, as also stipulated by the Paris agreement, among other instruments, there is a need for developing and transition economies to become more involved in climate change activism and fight together with developed nations against the threats of global warming. Building on the present literature review, future work could be drawn upon a meta-analysis in order to better understand the pollution-growth nexus through the EKC incidence.

  , establish the EKC hypothesis-Solow model nexus. In their seminal contribution, the authors use the underlying assumptions of the well-known neoclassical growth model introduced by Solow (1956) and account for environmental pollution in the main equation of the Cobb-Douglas production function. As such, they developed a new model (i.e.

  ) countries spanned over the period1950- 2000. On the other hand,[START_REF] Vollebergh | Identifying reduced-form relations with panel data: The case of pollution and income[END_REF] go beyond the standard econometric issues and emphasize the relevance of a proper identification strategy as a starting point in investigating the reduced form pollution-income nexus in panel data. Considering that one can distinguish between the impact of income and time effects on pollution, the authors argue that countries alike are characterized by identical time effects. Accordingly, the corroborated estimates of the income and time effects on CO2 and SO2 emissions for 24 OECD countries over the period1960-2000, based on the pairwise differencing technique, show that the bell-shape pattern holds only SO2 emissions (i.e. a locally regulated pollutant). Overall, the work of[START_REF] Vollebergh | Identifying reduced-form relations with panel data: The case of pollution and income[END_REF] may suggest that imposing different identifying restrictions for the exogenous variable (income) and control variable (time) yield to different model specifications, and in turn, to different findings regarding the pollution-income patterns. Besides, the authors establish a solid link between the theoretical models on EKC (see e.g.Brock and Taylor, 2005, 2010; Ordás Criado et al., 2011), and the minimal set of requirements needed for the identification of pollution-income nexus in EKC context.In addition,[START_REF] Stern | Between estimates of the emissions-income elasticity[END_REF] addresses both the issues pointed by[START_REF] Wagner | The carbon Kuznets curve: A cloudy picture emitted by bad econometrics?[END_REF] and[START_REF] Vollebergh | Identifying reduced-form relations with panel data: The case of pollution and income[END_REF], namely the higher-order terms of integrated income variable, the crosssectional dependence, and the identification of income and time effects in EKC reduced models, through the between estimation technique. Using the same datasets for CO2 and SO2 emissions as[START_REF] Wagner | The carbon Kuznets curve: A cloudy picture emitted by bad econometrics?[END_REF] and[START_REF] Vollebergh | Identifying reduced-form relations with panel data: The case of pollution and income[END_REF], the author shows that overall the results do not validate the traditional EKC hypothesis. In the same vein, the study of[START_REF] Stern | Modeling the emissions-income relationship using long-run growth rates[END_REF] consider both the problems raised by[START_REF] Wagner | The carbon Kuznets curve: A cloudy picture emitted by bad econometrics?[END_REF] andVolleberg et al. (2009) and also the omitted variable bias of between estimator employed in[START_REF] Stern | Between estimates of the emissions-income elasticity[END_REF]. As such, to mitigate their related undesirable effects on EKC results, the authors suggest working to long-run growth rates of pollution and income variables, while adding additional factors to account for the variation around the trend. The findings indicate that the EKC is not at work both for the full sample of CO2 and SO2 emissions. Moreover,[START_REF] Sen | Identification and Estimation of the Environmental Kuznets Curve: Pairwise Differencing to Deal with Nonlinearity and Nonstationarity[END_REF] use a slightly modified identification strategy for income and time effects, based on the pairwise differencing approach as[START_REF] Vollebergh | Identifying reduced-form relations with panel data: The case of pollution and income[END_REF]

Figure

  Figure 1. CO2-GDP nexus graphs [A][B][C] China

  050 in logs, and outside of sample values. Moreover, based on the FMOLS estimator Yao et al. (2019) reveal a monotonically increasing relationship for CO2 emissions. Besides, using environmental quality index (i.e. an inverse indicator of environmental pollution), the results provided by Wang et al. (2015) validate the EKC hypothesis for Gansu province in China. More specifically, the authors employ a Bayesian VAR model, and find a U-shaped pattern between the indicators for the period 1980-2012, with the estimated income threshold value of 2273 RMB per capita.

Table 2 .

 2 Panel data literature survey

	Author	Sample	Period	Methodology	Endogenous	Pollution-growth	Turning point
					variable	pattern
				Cointegration analysis
	Awad et al.	46 African	1990-2017	FMOLS, DOLS	CO2 emissions, air	Bell-shape	-
	(2019)	countries			pollution measured
					as mean annual
					exposure
	Dehghan	28 provinces of	2002-2013	DOLS	CO2 emissions	Bell-shape	0.134* in logs
	Shabani and	Iran					(agricultural sector),
	Shahnazi						0.918* in logs
	(2019)						(industrial sector),
							0.880* in logs
							(transportation sector),
							0.555* in logs (services
							sector)
	Destek and	11 newly	1977-2013	AMG	Ecological footprint Bell-shape	-
	Sarkodie	industrialized
	(2019)	countries
	Hanif et al.	15 Asian	1990-2013	ARDL	CO2 emissions	Bell-shape	-
	(2019)	developing
		countries
	Lazăr et al.	11 CEE countries 1996-2015	MG-FMOLS,	CO2 emissions, SO2	Monotonically	-
	(2019)			MG, AMG	emissions,	increasing
					biocapacity,
					ecological footprint
	Nasir et al.	5 ASEAN	1982-2014	FMOLS, DOLS	CO2 emissions	Monotonically	-
	(2019)	countries				increasing
	Waqih et al.	4 SAARC	1986-2014	ARDL, FMOLS	CO2 emissions	Bell-shape	-
	(2019)	countries
	Omri (2018)	69 countries	2001-2011	FMOLS	CO2 emissions	Bell-shape (lower-	-
		(high-income				middle-income
		countries, upper-				countries, low-
		middle-income				income countries)
		countries, lower-
		middle-income
		countries, low-
		income countries)
	Ulucak and	45 countries (low-	1961-2013	CUP-FM, CUP-	Ecological footprint Bell-shape (low-	-
	Bilgili (2018)	income countries,		BC		income countries)
		middle-income
		countries, high-
		income countries)
	Charfeddine	15 MENA	1975-2007	FMOLS, DOLS	Ecological footprint Bell-shape (panel,	-
	and Mrabet	countries				oil-exporting
	(2017)					countries), U-shape

  also provide contradictory findings for Qatar. Using a Markov switching equilibrium correction model for the period 1970-2015,[START_REF] Charfeddine | The impact of energy consumption and economic development on Ecological Footprint and CO2 emissions: Evidence from a Markov Switching Equilibrium Correction Model[END_REF] validates the EKC hypothesis for CO2 emissions and carbon ecological footprint but fails to find evidence in favor of ecological footprint EKC (i.e. the results illustrate a U-shaped pattern). Conversely,[START_REF] Mrabet | Testing the Kuznets Curve hypothesis for Qatar: A comparison between carbon dioxide and ecological footprint[END_REF], employing the ARDL bounds test approach, show that the relationship between CO2 and growth is U-shaped, whereas, for ecological footprint, the traditional bell-shaped curve is at work.

Table 3 .

 3 Time-series literature survey Stage Least Squares. The ''-'' indicates that the turning point is not computed, while the ''*'' indicates that the estimated turning point is out of sample values. † Although South Korea was included in the developed country group, we report the associated EKC results as, in the present review, we treat it as an emerging market economy. When both long-and short-run analysis is present, we report the pollution-growth pattern and turning point associated with the longrun results. The methodology column gives information about the technique used in investigating the pollution-growth nexus pattern, even if the respective study comprises other statistical and econometric techniques. All the information contained in the table represents our interpretation of the results in the analyzed studies.

	Author	Sample	Year	Methodology	Endogenous	Pollution-growth	Turning point
					variable	pattern
	Chen et al. (2019)	China	1980-2014 ARDL bounds	CO2 emissions	Bell-shape	-
				test
	Huag and Ucal	Turkey	1974-2014 Linear and	CO2 emissions,	Bell-shape (CO2	7963.31 US$ per
	(2019)			nonlinear ARDL	CO2 intensity, CO2	emissions, CO2	capita (CO2
				bounds test	emissions from	intensity, CO2 from	emissions),
				approach	electricity and heat	manufacturing and	6385.59 US$ per
					production, CO2	construction, CO2	capita (CO2
					from manufacturing	emissions from	intensity)
					and construction,	residential buildings,	{constant 2010}
					CO2 emissions	and commercial and
					from residential	public services), U-
					buildings, and	shape (CO2 emissions
					commercial and	from electricity and
					public services,	heat production), no
					CO2 from transport	statistical link (CO2
						from transport)

https://sustainabledevelopment.un.org/content/documents/5987our-common-future.pdf

In this paper, the term ''developing'' refers to both developing and emerging economies.

It is worth mentioning that we do not argue that this type of analysis should be performed instead of a parametric one, or provide better results at the advantage of fewer assumptions.

We take China as an example since a large number of studies considered focus on testing EKC for this country, compared to other states. However, a comparison could be made for the other states as well. Besides, we look for an overall behavior independent of the period analyzed, pollution indicator, and empirical methodology.

Also, the parametric quadratic function implies symmetry since, at both sides of the threshold, the pollution increases and decrease by the same rate.

We discuss here some of the recent developments of panel data techniques, as panels include both N and T dimensions, and the EKC is usually tested using panel data models. Still, it is worth mentioning that the advanced in the time-series econometric tools are more or less similar.

=number of molecules of the gas per million (106) molecules of dry air.

https://ane4bf-datap1.s3-eu-west-1.amazonaws.com/wmocms/s3fspublic/ckeditor/files/GHG_Bulletin_13_EN_final_1_1.pdf?LGJNmHpwKkEG2Qw4mEQjdm6bWxgWAJHa

Due to data availability for the EU(28), the Russian Federation, and at the global level, the period covered is 1990-2016. Also, in the empirical analysis, we use the natural logarithm of the data.

 11 For more information related to nonparametric regression models, see[START_REF] Cleveland | Robust Locally Weighted Regression and Smoothing Scatterplots[END_REF],[START_REF] Cleveland | LOWESS: A Program for Smoothing Scatterplots by Robust Locally Weighted Regression[END_REF],[START_REF] Robinson | Nonparametric estimators for time series[END_REF],[START_REF] Cleveland | Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting[END_REF],[START_REF] Cleveland | Smoothing by Local Regression: Principles and Methods In[END_REF],Henderson and Parameter (2015), among

others.12 We present the nonparametric regression models solely in a descriptive way, to better visualize and disentangle the pollution-growth nexus patterns. As such, we do not concern ourselves with variable nonstationary, cointegration, and other technical aspects related to time-series econometrics, these being beyond the aim of the present study. However, we note that some of those aspects are discussed during the paper theoretically.

We note that the review of the literature is not exhaustive, as we include studies published between 2010 and 2019 in popular journals on the subject, which meet the needs of the present work.

The studies that embody both types of analysis are included in the section in which we consider that the primary analysis harmonize.

We exclude Japan and the US from our analysis, considering that they belong to the group of developed countries. However, we keep the EU(28) and include the World as they also comprise the developing and transition countries.

manuscript significantly. I also gratefully acknowledge the support from the French Embassy and the French Institute in Romania.