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Journal ArticleDOI

Testing the Kuznets Curve hypothesis for Qatar: A comparison between carbon dioxide and ecological footprint

TLDR
In this paper, the authors explored the validity of the Environmental Kuznets Curve (EKC) using two different environment indicators: the carbon dioxide emissions (CO2) and the ecological footprint (EF) in Qatar over the 1980-2011 period.
Abstract
This paper explores the validity of the Environmental Kuznets Curve (EKC) using two different environment indicators: the carbon dioxide emissions (CO2) and the ecological footprint (EF) in Qatar over the 1980–2011 period. To this end, we investigate the impact of real gross domestic product (RGDP), the square of RGDP, the energy use, the financial development and the trade openness on the CO2 emissions and the EF. We employ the autoregressive distributed lag (ARDL) model with the presence of unknown structural breaks in order to study short-run and long-run elasticity between the variables. The findings infer that there is a long-run relationship among the selected variables with a shift in the cointegration vector in 1991 and 2000. The empirical result indicates that the inverted U-shaped hypothesis is not valid in Qatar when we use the CO2 emissions, whereas the inverted U-shaped held when using the EF. Furthermore, the error correction results confirm that the convergence towards the long-run equilibrium will mostly occur within one year after a short run shock. Generally, the findings suggest that Qatar should invest more in efficient energy and continue sustained its growth. Moreover, more efforts are needed for diversification particularly in technology-intensive and environment-friendly industries to improve environmental quality.

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Renewable energy consumption, urbanization, financial development, income and CO2 emissions in Turkey: Testing EKC hypothesis with structural breaks

TL;DR: In this paper, the authors investigated the short and long run dynamic relationship between per capita GDP, per capita carbon dioxide (CO2) emissions, financial development, total renewable energy consumption, hydropower consumption, alternative energy consumption and urbanization for Turkey during 1974-2014.
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A reinvestigation of EKC model by ecological footprint measurement for high, middle and low income countries

TL;DR: In this paper, the authors investigated empirically the Environmental Kuznets Curve (EKC) hypothesis and found that there is an inverted U-shaped relationship between environmental degradation and economic growth.
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Analyzing the environmental Kuznets curve for the EU countries: the role of ecological footprint.

TL;DR: The results show that there is U-shaped relationship between the real income and ecological footprint and non-renewable energy increases the environmental degradation while renewable energy and trade openness decrease theEnvironmental degradation in the EU countries.
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Economic growth, natural resources, and ecological footprints: evidence from Pakistan.

TL;DR: Estimating the impact of economic growth and natural resources on Pakistan’s ecological footprint using an autoregressive distributive lag (ARDL) model for long-run estimation indicates that natural resources have a positive effect on an ecological footprint that deteriorates environmental quality.
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The effect of financial development on ecological footprint in BRI countries: evidence from panel data estimation

TL;DR: The findings suggest that financial development increases ecological footprint and economic growth, energy consumption, foreign direct investment (FDI), and urbanization pollute the environment by increasing ecological footprint.
References
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Journal ArticleDOI

Co-integration and Error Correction: Representation, Estimation and Testing

TL;DR: The relationship between co-integration and error correction models, first suggested in Granger (1981), is here extended and used to develop estimation procedures, tests, and empirical examples.
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Distribution of the Estimators for Autoregressive Time Series with a Unit Root

TL;DR: In this article, the limit distributions of the estimator of p and of the regression t test are derived under the assumption that p = ± 1, where p is a fixed constant and t is a sequence of independent normal random variables.
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Testing for a Unit Root in Time Series Regression

TL;DR: In this article, the authors proposed new tests for detecting the presence of a unit root in quite general time series models, which accommodate models with a fitted drift and a time trend so that they may be used to discriminate between unit root nonstationarity and stationarity about a deterministic trend.
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Statistical analysis of cointegration vectors

TL;DR: In this paper, the authors consider a nonstationary vector autoregressive process which is integrated of order 1, and generated by i.i.d. Gaussian errors, and derive the maximum likelihood estimator of the space of cointegration vectors and the likelihood ratio test of the hypothesis that it has a given number of dimensions.
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Bounds testing approaches to the analysis of level relationships

TL;DR: In this paper, the authors developed a new approach to the problem of testing the existence of a level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend- or first-difference stationary.
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