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Journal ArticleDOI

Do urbanization and industrialization affect energy intensity in developing countries

Perry Sadorsky
- 01 May 2013 - 
- Vol. 37, pp 52-59
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TLDR
In this paper, the authors used recently developed heterogeneous panel regression techniques like mean group estimators and common correlated effects estimators to model the impact that income, urbanization and industrialization has on energy intensity for a panel of 76 developing countries.
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This article is published in Energy Economics.The article was published on 2013-05-01. It has received 458 citations till now. The article focuses on the topics: Energy intensity & Energy policy.

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Impacts of urbanization and industrialization on energy consumption/CO2 emissions: Does the level of development matter?

TL;DR: In this article, the authors adopted the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework as a starting point and re-estimated the relationship using different panel date models.
Journal ArticleDOI

Institutional quality, green innovation and energy efficiency

TL;DR: In this paper, the authors examined the energy efficiency performance of a sample of 71 developed and developing countries between 1990 and 2014 and found evidence of a significant positive influence of both green innovation and institutional quality on energy efficiency enhancement having controlled for some variables.
Journal ArticleDOI

Urbanization and industrialization impact of CO2 emissions in China

TL;DR: In this article, the authors investigated the causal linkage among CO2 emissions per capita, energy intensity, real GDP, industrialization, urbanization, and renewable energy consumption in China over the period from 1970 to 2015.
Journal ArticleDOI

How industrialization and urbanization process impacts on CO2 emissions in China: Evidence from nonparametric additive regression models

TL;DR: In this paper, the authors examined the impacts of industrialization and urbanization on CO 2 emissions in China using nonparametric additive regression models and provincial panel data from 1990 to 2011.
Journal ArticleDOI

Linking financial development, economic growth and energy consumption in Pakistan

TL;DR: In this article, the authors explored the finance-growth-energy nexus for Pakistan over the 1972-2012 period by employing the system GMM estimation technique, and tried to capture the impact of financial development over energy consumption through economic growth channel and included energy prices and urbanization in the structural model.
References
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Journal ArticleDOI

A Simple Panel Unit Root Test in the Presence of Cross Section Dependence

TL;DR: In this paper, a simple alternative test where the standard unit root regressions are augmented with the cross section averages of lagged levels and first-differences of the individual series is also considered.
Journal ArticleDOI

A simple panel unit root test in the presence of cross-section dependence

TL;DR: In this paper, a simple alternative where the standard ADF regressions are augmented with the cross section averages of lagged levels and first-differences of the individual series is proposed, and it is shown that the individual CADF statistics are asymptotically similar and do not depend on the factor loadings.
Posted Content

General Diagnostic Tests for Cross Section Dependence in Panels

TL;DR: In this paper, the authors proposed simple tests of error cross section dependence which are applicable to a variety of panel data models, including stationary and unit root dynamic heterogeneous panels with short T and large N.
Book ChapterDOI

An Autoregressive Distributed-Lag Modelling Approach to Cointegration Analysis

TL;DR: This article examined the use of autoregressive distributed lag (ARDL) models for the analysis of long-run relations when the underlying variables are I(1) and I(0) regressors.
Journal ArticleDOI

Estimating long-run relationships from dynamic heterogeneous panels☆

TL;DR: In panel data four procedures are widely used: pooling, aggregating, averaging group estimates, and cross-section regression as discussed by the authors, and the theoretical results on the properties of these procedures are illustrated by UK labour demand functions for 38 industries over 30 years.
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