Impacts of renewables and socioeconomic factors on electric vehicle demands – Panel data studies across 14 countries
Xiaomin Li,Pu Chen,Xingwu Wang +2 more
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TLDR
In this article, the impacts of seven factors in a multiple linear regression model were studied, including percentage of renewable energies in electricity generation, number of charging stations, education level, population density, gasoline price, GDP per capita and urbanization.About:
This article is published in Energy Policy.The article was published on 2017-10-01 and is currently open access. It has received 51 citations till now. The article focuses on the topics: Electric vehicle.read more
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Electric vehicles’ impacts on residential electric local profiles – A stochastic modelling approach considering socio-economic, behavioural and spatial factors
TL;DR: In this paper, a stochastic bottom-up model is presented to assess electric vehicles' (EV) impact on load profiles at different parking locations as well as their potential for load management strategies.
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Interactions between electric mobility and photovoltaic generation: A review
TL;DR: A systematic framework is developed in order to review the different underlying conditions for synergy in interactions between photovoltaic generation and electric mobility, and identify several remaining issues about these conditions that further researches could investigate.
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Impacts of climate change on electricity demand in China: An empirical estimation based on panel data
TL;DR: In this paper, a fixed-effect regression feedback model is used to estimate the impacts of climatic factors on electricity demand in China by using panel data of 30 provinces from 1995 to 2016.
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Technological progress and other factors behind the adoption of electric vehicles: Empirical evidence for EU countries
TL;DR: In this article, the authors analyse the factors supporting the transition to new forms of mobility, namely electric vehicles (EV), by dividing them into individual battery EVs (BEV) and plug-in hybrid EVs (PHEV).
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Battery Electric Vehicle adoption in regions without strong policies
TL;DR: In this paper, the authors present individual consumer characteristics and home-location based spatial characteristics of current battery electric vehicle (BEV) and internal combustion engine vehicle holders, in a region free from strong EV policies.
References
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Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations.
Manuel Arellano,Stephen Bond +1 more
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.
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Specification Tests in Econometrics
TL;DR: In this article, the null hypothesis of no misspecification was used to show that an asymptotically efficient estimator must have zero covariance with its difference from a consistent but asymptonically inefficient estimator, and specification tests for a number of model specifications in econometrics.
Posted Content
Mostly Harmless Econometrics: An Empiricist's Companion
TL;DR: The core methods in today's econometric toolkit are linear regression for statistical control, instrumental variables methods for the analysis of natural experiments, and differences-in-differences methods that exploit policy changes.
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Testing for Stationarity in Heterogeneous Panel Data
TL;DR: In this article, a residual-based Lagrange multiplier (LM) test for a null that the individual observed series are stationary around a deterministic level or around deterministic trend against the alternative of a unit root in panel data is proposed.
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Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions
Ona Egbue,Suzanna Long +1 more
TL;DR: In this paper, the authors identify potential socio-technical barriers to consumer adoption of EVs and determine if sustainability issues influence consumer decision to purchase an EV, and provide valuable insights into preferences and perceptions of technology enthusiasts; individuals highly connected to technology development and better equipped to sort out the many differences between EVs and CVs.