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Are Poverty Alleviation and Carbon Reduction Parallel Paths? Empirical Research on the Interaction between Poverty Alleviation and Carbon Emissions
The objective of this study is to explore the influence of the real income (GDP), renewable energy consumption
and non-renewable energy consumption on carbon dioxide (CO2) emissions for the United States of America (USA) in the environmental Kuznets curve (EKC) model for the period 1980–2014. The Zivot-Andrews unit root test with a structural break and the Clemente-Montanes-Reyes unit root test with a structural break report that the analyzed variables become stationary at first-differences. The Gregory-Hansen cointegration test with a structural break and the bounds testing for cointegration in the presence of a structural break show CO2 emissions, the real income, the quadratic real income, renewable and non-renewable energy consumption are
cointegrated. The long-run estimates obtained from the ARDL model indicate that increases in renewable energy consumption mitigate environmental degradation whereas increases in non-renewable energy consumption contribute to CO2 emissions. In addition, the EKC hypothesis is not valid for the USA. Since we use time-series econometric approaches that account for structural break in the data, findings of this study are robust, reliable and accurate. The US government is advised to put more weights on renewable sources in
energy mix, to support and encourage the use and adoption of renewable energy and clean technologies, and to increase the public awareness of renewable energy for lower levels of emissions.
The environment that governs the relationships between energy consumption, carbon dioxide (CO2) emissions and gross domestic product (GDP) in the G7 countries changes over time due to variations in economic growth, regulatory policy and technology. Using a novel approach that may detect causalities when the time-constant hypothesis is rejected, we find significant time-varying Granger causalities among the variables under consideration. There is bidirectional causality between GDP and energy consumption for Japan, unidirectional causality running from GDP to energy consumption for Italy and the United Kingdom, and unidirectional causality running from energy consumption to GDP for the resource country Canada. Moreover, the results also show a bidirectional time-varying causality between energy consumption and CO2 emissions for the United States, and causality from energy consumption to CO2 emissions for France. Finally, while we find significant time-varying causalities running from GDP to CO2 emissions for Italy, Japan, and the United Kingdom, the finding of cubic N-shaped (United Kingdom) and inverted N-shaped curves (Italy and Japan) lends no support to the traditional Environmental Kuznets Curve (EKC) hypothesis for these countries. It implies that environmental policy and economic growth should go hand in hand. Other policy implications of the empirical results have been proposed.
The report presents an overview of the historical and projected development of agricultural GHG emissions in the EU. The major objective of the report is to present the improvements made in the CAPRI modelling system with respect to GHG emission accounting and especially regarding the implementation of endogenous technological mitigation options. Furthermore, the CAPRI model was applied to provide a quantitative assessment of illustrative GHG mitigation policy options in the agricultural sector, and their production and economic implications.
This report discusses new knowledge on anthropogenic greenhouse gas (GHG) emissions
from agriculture, forestry and other land use (AFOLU) activities made available through the
new FAOSTAT Emission database. The database is available globally, with country detail, for all
agriculture, forestry and land sub-categories available in FAOSTAT and in the Forest Resources
Assessment (FRA). GHG emissions are computed from official national activity data and geospatial
analyses, applying international standard methodologies of the Intergovernmental Panel
on Climate Change (IPCC) to ensure consistency with GHG Inventory processes established
under the climate convention. The analysis shows increases in emissions of agriculture
(from 4.6 to 5.0 Gt CO2 eq yr-1 in 1990s and 2000s; 5.3 Gt CO2 eq yr-1 in 2011), decreases in
deforestation rates (from 4.6 to 3.8 Gt CO2 eq yr-1 in 1990s and 2000s; 3.7 Gt CO2 eq yr-1 in
2010), and decreases in forest sinks, albeit with a reversal since the mid-2000s (from -2.9 to
-1.9 Gt CO2 eq yr-1 in 1990s and 2000s values; -2.1 Gt CO2 eq yr-1 in 2010). At the same time, the
data show that GHG intensity of products (i.e., GHG emissions per unit commodity produced)
decreased during 1990-2010, but that if no further mitigation measures and technical efficiency
improvements are implemented, future emissions may further increase by up to 30% by 2050.
Better information on AFOLU emissions is critical in many developing countries, given the
potential to identify and fund actions that can usefully bridge national food security, resilience,
mitigation and development goals into one coherent package.
Recent empirical research indicates that certain types of emissions follow an inverted-U or environmental Kuznets curve (EKC) as income grows. This regularity has been interpreted as a possible de-linking of economic growth and patterns of certain pollutants for developed economies. In this paper the empirical basis of this result is investigated by considering some statistical particularities of the various EKC studies performed. It is argued that the inverted-U relationship between income and emissions estimated from panel data need not hold for specific individual countries over time. Based on insights from `intensity-of-use' analysis in resource economics, an alternative growth model is specified and estimated for three types of emissions (CO2, NOx and SO2) in four countries (Netherlands, UK, USA and Western Germany). It is found that the time patterns of these emissions correlate positively with economic growth and that emission reductions may have been achieved as a result of structural and technological changes in the economy. `Sustainable growth' is defined as the rate of economic growth that does not lead to growth in emissions. Its rate is calculated for each type of emission and country, based on estimated parameter values. The resulting indicators reflect a balance between the positive influence of growth and negative influence of structural change and technological progress on emission levels.
In this paper, we investigate the dynamic relationship between economic growth and carbon dioxide (CO2) emissions for 181 countries. We propose a new approach based on the cross-correlation estimates to understand how economic growth and CO2 emissions are related. Our proposal is that if there is a positive cross-correlation between the current level of income and the past level of CO2 emissions and a negative cross-correlation between the current level of income and the future CO2 emissions, then CO2 emissions will decline with an increase in income over time, consistent with the environmental Kuznets curve (EKC) hypothesis. Our main findings can be summarized as follows. First, for 21 out of 181 countries (12%), there is clear evidence supporting the EKC hypothesis. Second, we ask whether a rise in income reduces emissions in the future. We find that for 49 countries (27%), income growth will reduce emissions in the future.
Researching the dynamic distribution characteristics and trend evolution of agricultural carbon emissions is of considerable significance in formulating an effective agricultural carbon reduction policy. Based on measurement of agricultural carbon emissions of 31 provinces over the period 2002–2011, the study observed regional differences and the dynamic evolution of distribution of agricultural carbon emissions using agricultural carbon intensity as the indicator, accompanied by Gini coefficients and the kernel density estimation method. The results demonstrate first that agricultural carbon emissions for China show an obvious nonequilibrium nature in regard to spatial distribution. According to the differences in agricultural carbon emissions dynamic trends, we divided the 31 regions into four types – continuous decline, fluctuating decline, continuous increase, and fluctuating increase. Further, agricultural carbon emissions intensity showed a downward trend with significant differences in the research areas. Second, the gap in spatial distribution of national agricultural carbon emissions is gradually expanding based on the results calculated by Gini coefficient. From the perception of regional differences in agricultural carbon emissions, the eastern region showed an average level, the gap was more obvious in the central region, while western region showed a trend of fluctuating downward. Third, according to estimation by kernel density, the regional disparity in agricultural carbon emissions had a downward, but limited, trend. In regard to agricultural carbon emissions over the three areas, the regional gap not only tended to decrease but also showed a “four way” differentiation phenomenon in the eastern region. The difference in the central region difference was narrower. On the whole, the gap for the western region reduced steadily over a small range.
Macroscopic grasp of agricultural carbon emissions status, spatial-temporal characteristics as well as driving factors are the basic premise in further research on China's agricultural carbon emissions. Based on 23 kinds of major carbon emission sources including agricultural materials inputs, paddy field, soil and livestock breeding, this paper firstly calculated agricultural carbon emissions from 1995 to 2010, as well as 31 provinces and cities in 2010 in China. We then made a decomposed analysis to the driving factors of carbon emissions with logarithmic mean Divisia index (LMDI) model. The results show: (1) The amount of agricultural carbon emissions is 291.1691 million t in 2010. Compared with 249.5239 million t in 1995, it increased by 16.69%, in which, agricultural materials inputs, paddy field, soil, enteric fermentation, and manure management accounted for 33.59, 22.03, 7.46, 17.53 and 19.39% of total agricultural carbon emissions, respectively. Although the amount exist ups and downs, it shows an overall trend of cyclical rise; (2) There is an obvious difference among regions: the amount of agricultural carbon emissions from top ten zones account for 56.68%, while 9.84 % from last 10 zones. The traditional agricultural provinces, especially the major crop production areas are the main source regions. Based on the differences of carbon emission rations, 31 provinces and cities are divided into five types, namely agricultural materials dominant type, paddy field dominant type, enteric fermentation dominant type, composite factors dominant type and balanced type. The agricultural carbon emissions intensity in west of China is the highest, followed by the central region, and the east zone is the lowest; (3) Compared with 1995, efficiency, labor and structure factors cut down carbon emissions by 65.78, 27.51 and 3.19%, respectively; while economy factor increase carbon emissions by 113.16%.
The effects of economic growth on the environment in Korea, for a given level of energy consumption, and fossil fuels and nuclear energy in electricity production, are examined in a dynamic cointegration framework. To that end, the autoregressive distributed lag (ARDL) approach is used. We find empirical evidence supporting the existence of the environmental Kuznets curve (EKC) hypothesis for Korea; that is, economic growth indeed plays a favorable role in influencing environmental outcomes. It is also found that, in both the short- and long-run, nuclear energy has a beneficial effect on environmental quality, whereas fossil fuels in electricity production and energy consumption have a detrimental effect on the environment.
This article argues that there are several logical reasons for the existence of asymmetric causal effects that need to be
taken into account but usually are neglected in the literature. It suggests allowing for asymmetry in the causality testing
by using the cumulative sums of positive and negative shocks. A bootstrap simulation approach with leverage adjustment is
used to generate critical values that are robust to non-normality and time-varying volatility. An application to the efficient
market hypothesis in the UAE is provided. The results show that the equity market is informationally efficient with regard
to the oil shocks regardless if these shocks are positive or negative.
The paper attempts to test the Environment Kuznets Curve (EKC) hypothesis for 36 high-income countries for the period 1980-2005. The test is based on the suggestion of Narayan and Narayan (2010). Various panel data unit root and co-integration tests are applied. Carbon dioxide (CO2) emissions and GDP series are integrated of order one and co-integrated, especially after controlling for cross-sectional dependence. Additionally, the Blundell-Bond system generalised methods of moments (GMM) is employed to conduct a panel causality test in a vector error-correction mechanism (VECM) setting. Unidirectional causality running from real per capita GDP to per capita CO2 emissions is uncovered in both the short-run and the long-run. The empirical analysis based on individual countries provides evidence of an EKC for Greece, Malta, Oman, Portugal and the United Kingdom. However, it can be observed that for the whole panel, a 1% increase in GDP generates an increase of 0.68% in CO2 emissions in the short-run and 0.22% in the long-run. The lower long-run income elasticity does not provide evidence of an EKC, but does indicate that, over time, CO2 emissions are stabilising in the rich countries.
According to the environmental Kuznets curve hypothesis, the relationship between per-capita GDP and per-capita pollutant emissions has an inverted-U shape. This implies that, past a certain point, economic growth may actually be profitable for environmental quality. Most studies on this subject are based on estimating fully parametric quadratic or cubic regression models. While this is not technically wrong, such an approach somewhat lacks flexibility since it may fail to detect the true shape of the relationship if it happens not to be of the specified form.We use semiparametric and flexible nonlinear parametric modeling methods in an attempt to provide more robust inferences. We find little evidence in favour of the environmental Kuznets curve hypothesis. Our main results could be interpreted as indicating that the oil shock of the 1970s has had an important impact on progress towards less polluting technology and production.
This study investigates the macroeconomic forces underlying carbon dioxide (CO2) emissions from fossil fuel use in Canada. In keeping with the relevant literature on environmental degradation, three forces are expected to influence CO2 emissions: gross domestic product per capita (GDP/capita), population and technological change. While previous work has employed reduced-form models that allow for non-linear relationships between CO2 and GDP/capita, it has been common practice to assume linear relationships between CO2 and the latter two variables. This study tests a more flexible model using a five-region panel data set in Canada over the period 1970–2000. Findings indicate that GDP/capita is unrelated to CO2, that an inverted U-shaped relationship exists with population, and that a U-shaped relationship exists with technology. Thus, technological and population changes are supported over the commonly hypothesized environmental Kuznets curve (an inverted U-shaped relationship between GDP/capita and environmental degradation) for affecting CO2 emissions from fossil fuel use in Canada.
This paper investigates the relationship between environmental pollution and economic growth in China based on the environmental Kuznets curve hypothesis, using Chinese provincial data over 1985–2005. Waste gas, waste water and solid wastes are used as environmental indicators and GDP is used as the economic indicator. It is found by panel cointegration test that there is a long-run cointegrating relationship between the per capita emission of three pollutants and the per capita GDP. According to comparisons with the dynamic OLS estimator and the Within OLS estimator, we find that panel cointegration estimation is preferable for all pollutants except for solid wastes. The results also show that all three pollutants are inverse U-shaped, and water pollution has been improved earlier than gas pollution and solid pollution.
A new data set on national poverty lines is combined with new price data and almost 700 household surveys to estimate absolute
poverty measures for the developing world. We find that 25% of the population lived in poverty in 2005, as judged by what
“poverty” typically means in the world's poorest countries. This is higher than past estimates. Substantial overall progress
is still indicated—the corresponding poverty rate was 52% in 1981—but progress was very uneven across regions. The trends
over time and regional profile are robust to various changes in methodology, though precise counts are more sensitive.
Agriculture is a source for three primary greenhouse gases (GHGs): CO(2), CH(4), and N(2)O. It can also be a sink for CO(2) through C sequestration into biomass products and soil organic matter. We summarized the literature on GHG emissions and C sequestration, providing a perspective on how agriculture can reduce its GHG burden and how it can help to mitigate GHG emissions through conservation measures. Impacts of agricultural practices and systems on GHG emission are reviewed and potential trade-offs among potential mitigation options are discussed. Conservation practices that help prevent soil erosion, may also sequester soil C and enhance CH(4) consumption. Managing N to match crop needs can reduce N(2)O emission and avoid adverse impacts on water quality. Manipulating animal diet and manure management can reduce CH(4) and N(2)O emission from animal agriculture. All segments of agriculture have management options that can reduce agriculture's environmental footprint.
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