Growth and Pollution Convergence: Theory and Evidence

Stabilizing pollution levels in the long run is a pre-requisite for sustainable growth. We develop a neoclassical growth model with endogenous emission reduction predicting that, along optimal sustainable paths, pollution growth rates are (i) positively related to output growth (scale effect) and (ii) negatively related to emission levels (defensive effect). This dynamic law reduces to a convergence equation that is empirically tested for two major and regulated air pollutants - sulfur oxides and nitrogen oxides - with a panel of 25 European countries spanning the years 1980-2005. Traditional parametric models are rejected by the data. More flexible regression techniques confirm the existence of both the scale and the defensive effect, supporting the model predictions.Air pollution, convergence, economic growth, nonparametric regressions

Growth and the pollution convergence hypothesis: a nonparametric approach

Abstract The pollution-convergence hypothesis is formalized in a neoclassical growth model with optimal emissions reduction: pollution growth rates are positively correlated with output growth (scale effect) but negatively correlated with emission levels (defensive effect). This dynamic law is empirically tested for two major and regulated air pollutants -nitrogen oxides (NOX) and sulfur oxides (SOX) -with a panel of 25 European countries spanning over years . Traditional parametric models are rejected by the data. However, more flexible regression techniques -semiparametric additive specifications and fully nonparametric regressions with discrete and continuous factors -confirm the existence of the predicted positive and defensive effects. By analyzing the spatial distributions of per capita emissions, we also show that cross-country pollution gaps have decreased over the period for both pollutants and within the Eastern as well as the Western European areas. A Markov modeling approach predicts further cross-country absolute convergence, in particular for SOX. The latter results hold in the presence of spatial non-convergence in per capita income levels within both regions. JEL Classification numbers: C14, C23, Q5

Is eco-efficiency in greenhouse gas emissions converging among European Union countries?

Eco-efficiency refers to the ability to produce more goods and services with less impact on the environment and less consumption of natural resources. This issue has become a matter of concern that is receiving increasing attention from politicians, scientists and researchers. Furthermore, greenhouse gases emitted as a result of production processes have a marked impact on the environment and are also the foremost culprit of global warming and climate change. This paper assesses convergence in eco-efficiency in greenhouse gas emissions in the European Union. Eco-efficiency is assessed at both country and greenhouse-gas-specific levels using Data Envelopment Analysis techniques and directional distance functions, as recently proposed by Picazo-Tadeo et al. (Eur J Oper Res, 220:798–809, 2012). Convergence is then evaluated using the Phillips and Sul (Econometrica, 75:1771–1855, 2007) approach that allows testing for the existence of convergence groups. Although the results point to the existence of different convergence clubs depending on the specific pollutant considered, they signal the existence of at least four clear groups of countries. The first two groups are core European Union high-income countries (Benelux, Germany, Italy, Austria, the United Kingdom and Scandinavian countries). A third club is made up of peripheral countries (Spain, Ireland, Portugal and Greece) together with some Eastern countries (Latvia and Slovenia), while the remaining clubs consist of groups containing Eastern European countries

Air and water pollution over time and industries with stochastic dominance

We employ a stochastic dominance (SD) approach to analyze the components that contribute to environmental degradation over time. The variables include countries\u2019 greenhouse gas (GHG) emissions and water pollution. Our approach is based on pair-wise SD tests. First, we study the dynamic progress of each separate variable over time, from 1990 to 2005, within 5-year horizons. Then, pair-wise SD tests are used to study the major industry contributors to the overall GHG emissions and water pollution at any given time, to uncover the industry which contributes the most to total emissions and water pollution. While CO2 emissions increased in the first order SD sense over 15 years, water pollution increased in a second-order SD sense. Electricity and heat production were the major contributors to the CO2 emissions, while the food industry gradually became the major water polluting industry over time. SD sense over 15 years, water pollution increased in a second-order SD sense. Electricity and heat production were the major contributors to the CO2 emissions, while the food industry gradually

Growth and pollution convergence: Theory and evidence

Stabilizing pollution levels in the long run is a pre-requisite for sustainable growth. We develop a neoclassical growth model with endogenous emission reduction predicting that, along optimal sustainable paths, pollution growth rates are (i) positively related to output growth (scale effect) and (ii) negatively related to emission levels (defensive effect). This dynamic law reduces to a convergence equation that is empirically tested for two major and regulated air pollutants – sulfur oxides and nitrogen oxides – with a panel of 25 European countries spanning the years 1980–2005. Traditional parametric models are rejected by the data. More flexible regression techniques confirm the existence of both the scale and the defensive effect, supporting the model predictions

Convergence in per capita CO2 emissions: A robust distributional approach

Abstract This paper investigates the convergence hypothesis for per capita CO2 emissions with a panel of 166 world areas covering the period 1960-2002. The analysis is based on the evolution of the spatial distributions over time. Robust measures of dispersion, asymmetry, peakedness and two nonparametric distributional tests - shape equality and multimodality - are used to assess spatial time differences. A robust normal reference bandwidth is also applied to estimate Markov's transition laws and its subsequent ergodic (long-run) distributions. Our results point toward non-stationary, flattening and right-skewed spatial distributions before the oil price shocks of the 1970s and more stable and symmetric shapes between 1980 and 2000 at the world level and for many country groupings (similar income, geographic neighbors, institutional partners). In the latter period, group-specific convergence patterns emerge with the clearest single-peaked and compact density shapes being reached in the wealthy, well-integrated and European countries during the last years of the panel. No significant multimodality is formally detected in the world distribution over the whole period. The Markov analysis suggests more divergence and larger per capita emissions for the world in the long run, with a doubling in median emissions and stable pollution gaps during the first 50 years of the transition. A variety of steady state distributions are identified in the country subsets.Carbon dioxide emissions Air pollution Convergence Distribution dynamics Stochastic kernels Robustness

Growth and the pollution convergence hypothesis: a nonparametric approach.

The pollution-convergence hypothesis is formalized in a neoclassical growth model with optimal emissions reduction: pollution growth rates are positively correlated with output growth (scale effect) but negatively correlated with emission levels (defensive effect). This dynamic law is empirically tested for two major and regulated air pollutants - nitrogen oxides (NOX) and sulfur oxides (SOX) - with a panel of 25 European countries spanning over years 1980-2005. Traditional parametric models are rejected by the data. However, more flexible regression techniques - semiparametric additive specifications and fully nonparametric regressions with discrete and continuous factors - confirm the existence of the predicted positive and defensive effects. By analyzing the spatial distributions of per capita emissions, we also show that cross-country pollution gaps have decreased over the period for both pollutants and within the Eastern as well as the Western European areas. A Markov modeling approach predicts further cross-country absolute convergence, in particular for SOX. The latter results hold in the presence of spatial non-convergence in per capita income levels within both regions.Air pollution, convergence, economic growth, mixed nonparametric regressions, distribution dynamics.

Growth and pollution convergence: Theory and evidence

Stabilizing pollution levels in the long run is a pre-requisite for sustainable growth. We develop a neoclassical growth model with endogenous emission reduction predicting that, along optimal sustainable paths, pollution growth rates are (i) positively related to output growth (scale effect) and (ii) negatively related to emission levels (defensive effect). This dynamic law reduces to a convergence equation that is empirically tested for two major and regulated air pollutants - sulfur oxides and nitrogen oxides - with a panel of 25 European countries spanning the years 1980-2005. Traditional parametric models are rejected by the data. More flexible regression techniques confirm the existence of both the scale and the defensive effect, supporting the model predictions.Air pollution Convergence Economic growth Nonparametric regressions

Temporal and Spatial Homogeneity in Air Pollutants Panel EKC Estimations

Environmental Kuznets Curve, Air pollutants, Non/Semiparametric estimations, Poolability tests, C14, C23, O40, Q53,