Temporal and Spatial Homogeneity in Air Pollutants Panel EKC Estimations

Although panel data have been used intensively by a wealth of studies investigating the GDP-pollution relationship, the poolability assumption used to model these data is almost never addressed. This paper applies a strategy to test the poolability assumption with methods robust to functional misspecification. Nonparametric poolability tests are performed to check the temporal and spatial homogeneity of the panel and their results are compared with the conventional F-tests for a balanced panel of 48 Spanish provinces on four air pollutant emissions (CH₄, CO, CO₂ and NMVOC) over the 1990–2002 period. We show that temporal homogeneity may allow the pooling of the data and drive to well-defined nonparametric and parametric cross-sectional U-inverted shapes for all air pollutants. However, the presence of spatial heterogeneity makes this shape compatible with different time-series patterns in every province—mainly increasing or decreasing depending on the pollutant. These results highlight the extreme sensitivity of the income-pollution relationship to region- or country-specific factors.      

Trade and regional growth in Spain: panel cointegration in a small sample

In this article, we test for the existence of a relationship between per capita Gross Domestic Product (GDP) and trade, for 15 Spanish Autonomous Communities between 1988 and 2004, using a panel cointegration methodology. In particular, we implement several panel unit root tests (Maddala and Wu, 1999; Levin et al., 2002; Im et al., 2003) and panel cointegration tests (Pedroni, 1999, 2004), with a special attention to their behaviour in a small sample. We also develop a Seemingly Unrelated Regression Estimation (SURE) residual based test, in order to explicitly take into account the cross regional correlation pattern. Appropriate confidence intervals are estimated with a sieve bootstrap designed for our small time sample, preserving the dependence structure among cross sectional units. Our cointegration tests reject the existence of a significant relationship between GDP per capita and exports. However, we do find some evidence of a significant relationship between GDP per capita and imports or with total trade.     

Convergence in Per Capita Carbon Dioxide Emissions Among G7 Countries: A TAR Panel Unit Root Approach

The subject of this paper is the examination the convergence of per capita carbon dioxide emissions of the G7 countries during the 1960–2005 period in a nonlinear panel analysis framework. In this approach, first the linearity of the series was tested, and when the linearity was rejected, the threshold autoregressive (TAR) panel unit root test, which splits the data into two regimes, was employed to examine the stationarity properties of the series. Because the null of linearity was rejected in the first step, we tested the stationarity of the series using the TAR panel unit root test. In the TAR panel unit root test, we found that the United Kingdom was the transition country whose per capita carbon dioxide (CO₂) emissions determined the switch from one regime to the other. The results showed that convergence existed in the first regime and divergence, in the second. When we tested whether absolute or conditional convergence existed, we found that the per capita CO₂ emissions were conditionally converging in the first regime.     

二氧化碳排放与经济增长关系的EKC检验——对我国东、中、西部地区的一项比较

根据环境库兹涅茨曲线理论,本文选用1996—2008年中国省域面板数据,研究了东、中、西部地区人均碳排放EKC的存在性。研究结果表明：第一,东、中部地区存在人均碳排放EKC,而西部地区入均碳排放与经济增长呈线性关系。第二,东、中部地区人均碳排放EKC拐点到达的时间不同,东部地区较晚而中部地区较早,并且碳排放强度下降会促使拐点提前到达。第三,东、中、西部地区人均碳排放均存在较强的排放惯性,当期经济增长会对未来几年的环境质量产生影响。     

A robust analysis of the relationship between renewable energy consumption and its main drivers

We provide a comprehensive and robust analysis of the drivers of renewable energy consumption for a panel of 64 countries, using both the static (Pooled OLS, Panel Fixed and Random Effects) and dynamic (difference and system GMM) panel data estimation approaches. We show that the dynamic panel data model provides more efficient estimators than the static ones and that increases in per capita CO₂ emissions and per capita trade with foreign partners mainly drive the changes in per capita renewable energy consumption. We also find limited evidence of oil price effects on renewable energy consumption, which reflects the fact that renewable energy is just a complement and not a perfect substitute of crude oil, at least in the short run.     

The causal dynamics between renewable energy,real GDP,emissions and oil prices: evidence from OECD countries

This study extends the empirical literature on the determinants of renewable energy consumption in the case of 25 OECD countries for the period 1980–2011. Preliminary analysis suggests the presence of cross-sectional dependence within the panel data. As a result, second-generation panel unit root tests of Smith et al. (2004) and Pesaran (2007) are undertaken to find the respective variables that are integrated of order one. Panel cointegration and error correction modelling reveal that a long-run relationship exists between renewable energy consumption per capita, real GDP per capita, carbon dioxide emissions per capita and real oil prices. The long-run elasticity estimates are positive and statistically significant for real GDP per capita, carbon dioxide emissions per capita and real oil prices. The panel error correction model shows that a feedback relationship exists among the variables.     

Variation in Health Expenditures: Is It Just Income or other Factors? Empirical Investigation Using a Panel of Indian States

The primary query of this paper centres on the role played by income in determining the extent of fund allocated by Indian states for improvement of health of its population. Drawing data from the fourteen major states of India over a time span of twenty-three financial years (1974–75 to 1996–97) and using recent advances in panel data time series econometrics, this paper documents the presence of a long run relationship between income and health expenditure. The long-run elasticity estimates reiterate that publicly provided health services should be considered as “necessities”. Results the panel error correction model demonstrate that ageing of the population and proportion of rural population are the only non-income factors, which exert a significant positive impact on real per capita health expenditure. This is particularly important given the demographic transition that India is passing through.

     

Distribution Dynamics of CO<Subscript>2</Subscript> Emissions

This paper uses nonparametric methods to examine the convergence in CO₂ emissions per capita on a sample of 100 countries for the period 1966–1996. Industrial countries show a convergence pattern. However, there is little evidence of convergence for the whole sample.     

A nonlinear approach to testing the unit root null hypothesis: an application to international health expenditures

In this article, we examine the unit root null hypothesis for per capita total Health Expenditures (HEs), per capita private HEs and per capita public HEs for 29 Organization for Economic Co-operation and Development (OECD) countries. The novelty of our work is that we use a new nonlinear unit root test that allows for one structural break in the data series. We find that for around 45% of the countries, we are able to reject the unit root hypothesis for each of the three HE series. Moreover, using Monte Carlo simulations, we show that our proposed unit root model has better size and power properties than the widely used Augmented Dickey–Fuller (ADF) and Lagrange Multiplier (LM) type tests.     

A panel data test for poverty traps

This article develops a threshold panel data nonlinearity test for poverty traps. The new testing strategy extends the work on nonlinearity tests for panel data by considering threshold nonlinearities in the fixed-effects components. Monte Carlo simulations are conducted to evaluate the finite-sample performance of these tests. The tests are applied to the relationship between Gross Domestic Product (GDP) per capita and capital stock per capita. Our application to a panel of countries for the period 1973 to 2007 uncovers the presence of two regimes determined by the level of capital stock per capita. The conclusions from our test also support the existence of a poverty trap determined by a capital stock per capita level at the 11% quantile of its pooled worldwide distribution.     

Economic growth and carbon emissions: evidence from CIVETS countries

ABSTRACT

This paper examines whether a long-run relationship exists between CO₂ emissions and selected variables: real gross domestic product per capita, inward stock of foreign direct investments, gross fixed capital formation, industry, value added and energy use per capita for Colombia, Indonesia, Viet Nam, Egypt, Turkey and South Africa countries in the period of 1989–2016. We used panel unit root testing, followed by panel cointegration tests and panel causality. The results clearly prove the existence of a bidirectional long-run causal relationship between all the variables except between CO₂ emissions and GDP and CO₂ emissions and GFCF. Major finding of the short-run causality analysis is that CO₂ emission in the short run does not result in changes of other variables. On the other hand, all variables except foreign direct investments (FDI) cause the changes in the CO₂ emissions, and there is a positive bidirectional causal relationship between GDP and FDI, between GFCF and FDI, and between GFCF and IVA. Finally, positive unidirectional causal relationship also exists, running from GDP to IVA, GDP to ENUSE, IVA to FDI and ENUSE to FDI.     

On the impact of innovation and inequality in economic growth

We present robust results on the empirical relationship among income inequality, innovation, and economic growth for a panel dataset of 74 countries over the period 1996–2014. We estimate pairwise causality tests to show that there is bidirectional causality between GDP per capita and R&D, while R&D causes the Gini index of income inequality, and it causes human capital. Allowing coefficients to be different across cross-sections of countries, we get in any case a pairwise bi-directionality. By dynamic panel data estimations, when regressing R&D on GDP per capita, we obtain a threshold value of 0.16% of R&D such that for values above it there is economic growth. While regressing R&D on the Gini index, we get a threshold of 0.10% of R&D above which, the income distribution begins to improve. Finally, we estimate a growth equation that depends on R&D, income inequality, and physical capital. We obtain two thresholds, one of 38.79 for the Gini (above which the economic growth decreases), and one of 0.06% for R&D such that above it, economic growth is rising.     

Do population age groups matter in the energy use of the oil-exporting countries?

This study examines the impacts of the population age groups of 20–34, 35–49, 50–64 and 65–79 on the per capita energy use of the oil-exporting countries of Commonwealth Independent States: Azerbaijan, Kazakhstan and Russia employing the modified-STIRPAT framework. Considering that estimations using non-stationary data may yield spurious results, unlike many prior STIRPAT studies, we explore integration and cointegration properties of the data and then estimate long- and short-run elasticities as well as speed of adjustment coefficients. Since our time series analysis covers only 23 observations (1990-2012), as a robustness check, we also conduct panel data analysis by pooling the mentioned countries data with that for members of Organization of Petroleum Exporting Countries. We apply the Autoregressive Distributed Lags Bounds Testing approach in the time series analysis and Pooled Mean Group estimator in the panel analysis, both are superior in small samples. The findings from the time series analysis are supported by those from the panel data analysis. According to the results, there is cointegrated relationship among the variables. The age groups together with affluence and oil prices have statistically significant impacts on the per capita energy use in the selected countries. Moreover, we find the speed of adjustments exhibiting different magnitudes for different countries depending on which population age group is considered. The findings suggest that policymakers should pay special attention to the population age groups of 35–49 and 50–64, as they have a large effect on per capita energy use. Since these groups are the main part of the working age population, increase in their energy consumption is likely to lead to economic growth. Furthermore, the policymakers should take into consideration the finding that speed of adjustments towards an equilibrium path is quite high. It implies that any policy related shocks to the per capita energy use relationship could disappear within a year or even sooner.     

A consumption-based approach to environmental Kuznets curves using the ecological footprint indicator

Recent research suggests that consumption-based measures offer an insightful perspective on the debate on the relationship between economic growth and the environment. In this article we deepen the consumption-based line of inquiry by investigating the empirical evidence in support of the environmental Kuznets hypothesis using 2001 ecological footprint data for 141 countries. We perform Ordinary Least Squares and Weighted Least Squares analysis on linear, quadratic and cubic functions, in standard and logarithmic specifications, as candidate models to represent the relationship between per capita income and environmental pressure. We replicate the cross country analysis also by estimating the regression function directly, through a nonparametric regression. In our analyses, with and without weighing data by population, the results do not show evidence of de-linking.     

Stochastic convergence of per capita carbon dioxide emissions and multiple structural breaks in OECD countries

This research applies an innovative panel data stationarity testing procedure developed by Carrion-i-Silvestre et al. [Carrion-i-Silvestre, J.L., Barrio-Castro, T.D. and Lopez-Bazo, E., 2005. Breaking the panels: An application to the GDP per capita, Econometrics Journal 8, 159–175.], which has the advantage of recognizing multiple structural breaks and the presence of cross-section dependence in order to re-investigate the hypothesis that per capita carbon dioxide (CO₂) emissions stochastically converge for 21 OECD countries from 1950 to 2002. Remarkably, the evidence clearly indicates that the panel dataset of relative per capita CO₂ emissions is stationary after the structural breaks and cross-sectional dependence are introduced into the model. These findings offer strong policy implications for governments, regardless of whether they are in “convergent group” or “divergent group” countries. We also find that the structural breaks in the 1960s and over the 1970–1982 period are associated with time periods of fossil fuel becoming the main source of productivity, higher oil prices, and the development of nuclear power.     

中国碳排放量影响因素研究——基于省级面板数据的分析

采用中国30个省（市、区）2000～2010年的相关数据,运用面板数据模型对中国碳排放量的影响因素进行实证研究。面板协整检验表明：区域碳排放量与人均GDP、产业结构、人口数量、能源价格、能源效率和人均可支配收入之间存在长期稳定的内生经济关系。运用面板模型估计各因素的影响系数分析,认为对中国东部、中部、西部地区碳排放量影响最大的三大因素为人均GDP、人口数量和能源效率。     

Sovereign credit ratings,growth volatility and the global financial crisis

Using monthly data from January 1996 to May 2010 for a panel of 76 developed and emerging economies and adopting an instrumental variable (IV) estimation technique by correcting for both heterogeneity and endogeneity with the generalized two-stage least squares (G2SLS, EC2SLS) procedure method suggested by Balestra and Varadharajan-Krishnakumar (1987) and Baltagi and Li (1995), this article provides empirical evidence that volatility of per capita GDP growth is reduced when there are positive changes in credit ratings; in other words when sovereign credit risk improves. To deal with potential simultaneity between sovereign credit ratings and output volatility, a system (3SLS) approach is undertaken, and our findings remain robust. By weakening the volatility dampening effects of ratings changes, it is found that the global financial crisis (GFC) has enhanced macroeconomic volatility. One of the channels via which sovereign rating changes affect growth volatility is the financial markets’ repricing of sovereign default risk that is reflected in sovereign credit default swap (CDS) spreads and its volatility.     

Economic prosperity, biodiversity conservation, and the environmental Kuznets curve

Many conservationists contend that economic growth and biodiversity conservation are incompatible goals. Some economists contest this viewpoint, arguing that wealthier countries have the luxury of investing more heavily in efforts to conserve biodiversity. Under this assumption, we expect a U-shaped relationship between per capita wealth and proportion of species conserved. We test this environmental Kuznets curve (EKC) using estimates of per capita income and deforestation rates (index of biodiversity threat) for 35 tropical countries. A prior analysis [Dietz, S., Adger, W.N., 2003. Economic growth, biodiversity loss and conservation effort. Journal of Environmental Management, 68:23-35] using conventional regression techniques failed to provide any support for the parabolic relationship predicted by the EKC hypothesis. Here, we introduce the use of quantile regression and spatial filtering to reanalyze this data, addressing issues of heteroskedasticity and spatial autocorrelation. We note that preliminary analysis using these methods provides some initial evidence for an EKC. However, a series of panel analyses with country-specific dummy variables eliminated or even reversed much of this support. A closer examination of conservation practices and environmental indicators within the countries, particularly those countries that drove our initial support, suggests that wealth is not a reliable indicator of improved conservation practice. Our findings indicate that an EKC for biodiversity is overly simplistic and further exploration is required to fully understand the mechanisms by which income affects biodiversity.     

Questioning the empirical basis of the environmental Kuznets curve for CO2: New evidence from a panel stationarity test robust to multiple breaks and cross-dependence

This paper investigates the time series properties of per capita CO₂ emissions and per capita GDP levels for a sample of 86 countries over the period 1960-2000. For that purpose, we employ a state-of-the-art panel stationarity test which incorporates multiple shifts in level and slope, thereby controlling for cross-sectional dependence through bootstrap methods. Our analysis renders clear-cut evidence that per capita GDP levels are nonstationary for the world as a whole while per capita CO₂ is found to be regime-wise trend stationary. The analysis of country-groups shows that for Africa and Asia, per capita CO₂ is best described as nonstationary, while per capita GDP appears stationary around a broken trend. In addition, we find evidence of regime-wise trend stationarity in both variables for the country-groups consisting of America, Europe and Oceania. The results of our analysis carry important implications for the statistical modelling of the Environmental Kuznets curve for CO₂, since the differing order of integration in both variables for the world as a whole and for Africa and Asia calls into question the validity of panel cointegration techniques which assume that both variables are nonstationary and cointegrated with one another. Cointegration techniques would not be appropriate either for the case of America, Europe and Oceania which are characterised by per capita GDP and CO₂ emissions being stationary around a broken trend. Similar conclusions are reached when we analyse country-groups based on levels of development. Failure to properly characterise the time series properties of the data by not controlling for an unknown number of structural breaks and for cross-sectional dependence could be responsible for the fragility and lack of robustness surrounding the estimation of environmental Kuznets curves.     

Urban–rural income disparities and development in a panel data set of China for the period from 1978 to 2006

We examine the relationship between urban–rural income disparities and development in a panel data set of 30 provinces and regional subsets of China during the period of 1978 to 2006. There is an inverted-U relationship between the urban–rural income gap and per capita Gross Domestic Product (GDP). Financial development by scale widens the urban–rural income gap in all regional samples, while financial sector efficiency and rural bank loans may reduce it in some regions. Government spending raises the urban–rural income gap as well. We also examine the effects of urbanization, openness and education.