The dynamic impact of renewable energy and institutions on economic output and CO2 emissions across regions
TL;DR: In this article, the authors provide a comprehensive and robust analysis of the role of renewable energy consumption and institutions on economic growth and in combating CO2 emissions across the regions and income groups.
About: This article is published in Renewable Energy.The article was published on 2017-10-01. It has received 432 citations till now. The article focuses on the topics: Renewable energy.
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TL;DR: In this paper, the authors employed the panel vector autoregressive (PVAR) model to examine the impact of renewable energy and financial development on carbon dioxide (CO2) emissions and economic growth.
558 citations
TL;DR: In this paper, the authors investigated the nexus among carbon dioxide emissions, economic and population growth, and renewable energy across regions using an unbalanced panel dataset of 128 countries over the period 1990-2014.
399 citations
TL;DR: Evidence from the study reveals that political institutional quality plays a huge role in the social, governance and economic readiness to mitigate climate change and its impact, and structural adjustment in disaggregate and aggregate energy consumption, economic growth, and political institutionalquality play a critical role in environmental quality.
386 citations
TL;DR: In this paper, the authors investigate the nexus among per capita carbon dioxide (CO2) emissions, gross domestic product (GDP), and natural gas and renewable energy consumption within the framework of the environmental Kuznets curve (EKC), in a 1985-2016 sample of BRICS countries (i.e., Brazil, Russia, India, China, and South Africa).
380 citations
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.
365 citations
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TL;DR: In this article, the generalized method of moments (GMM) estimator optimally exploits all the linear moment restrictions that follow from the assumption of no serial correlation in the errors, in an equation which contains individual effects, lagged dependent variables and no strictly exogenous variables.
Abstract: This paper presents specification tests that are applicable after estimating a dynamic model from panel data by the generalized method of moments (GMM), and studies the practical performance of these procedures using both generated and real data. Our GMM estimator optimally exploits all the linear moment restrictions that follow from the assumption of no serial correlation in the errors, in an equation which contains individual effects, lagged dependent variables and no strictly exogenous variables. We propose a test of serial correlation based on the GMM residuals and compare this with Sargan tests of over-identifying restrictions and Hausman specification tests.
26,580 citations
TL;DR: In this paper, two alternative linear estimators that are designed to improve the properties of the standard first-differenced GMM estimator are presented. But both estimators require restrictions on the initial conditions process.
19,132 citations
TL;DR: In this paper, a framework for efficient IV estimators of random effects models with information in levels which can accommodate predetermined variables is presented. But the authors do not consider models with predetermined variables that have constant correlation with the effects.
16,245 citations
TL;DR: This paper showed that differences in physical capital and educational attainment can only partially explain the variation in output per worker, and that a large amount of variation in the level of the Solow residual across countries is driven by differences in institutions and government policies.
Abstract: Output per worker varies enormously across countries. Why? On an accounting basis, our analysis shows that differences in physical capital and educational attainment can only partially explain the variation in output per worker--we find a large amount of variation in the level of the Solow residual across countries. At a deeper level, we document that the differences in capital accumulation, productivity, and therefore output per worker are driven by differences in institutions and government policies, which we call social infrastructure. We treat social infrastructure as endogenous, determined historically by location and other factors captured in part by language.
7,208 citations
TL;DR: This article showed that the differences in capital accumulation, productivity, and therefore output per worker are driven by differences in institutions and government policies, which are referred to as social infrastructure and called social infrastructure as endogenous, determined historically by location and other factors captured by language.
Abstract: Output per worker varies enormously across countries. Why? On an accounting basis our analysis shows that differences in physical capital and educational attainment can only partially explain the variation in output per worker—we find a large amount of variation in the level of the Solow residual across countries. At a deeper level, we document that the differences in capital accumulation, productivity, and therefore output per worker are driven by differences in institutions and government policies, which we call social infrastructure. We treat social infrastructure as endogenous, determined historically by location and other factors captured in part by language. In 1988 output per worker in the United States was more than 35 times higher than output per worker in Niger. In just over ten days the average worker in the United States produced as much as an average worker in Niger produced in an entire year. Explaining such vast differences in economic performance is one of the fundamental challenges of economics. Analysis based on an aggregate production function provides some insight into these differences, an approach taken by Mankiw, Romer, and Weil [1992] and Dougherty and Jorgenson [1996], among others. Differences among countries can be attributed to differences in human capital, physical capital, and productivity. Building on their analysis, our results suggest that differences in each element of the production function are important. In particular, however, our results emphasize the key role played by productivity. For example, consider the 35-fold difference in output per worker between the United States and Niger. Different capital intensities in the two countries contributed a factor of 1.5 to the income differences, while different levels of educational attainment contributed a factor of 3.1. The remaining difference—a factor of 7.7—remains as the productivity residual. * A previous version of this paper was circulated under the title ‘‘The Productivity of Nations.’’ This research was supported by the Center for Economic Policy Research at Stanford and by the National Science Foundation under grants SBR-9410039 (Hall) and SBR-9510916 (Jones) and is part of the National Bureau of Economic Research’s program on Economic Fluctuations and Growth. We thank Bobby Sinclair for excellent research assistance and colleagues too numerous to list for an outpouring of helpful commentary. Data used in the paper are available online from http://www.stanford.edu/,chadj.
6,454 citations