Standard errors for the Laspeyres index number with autocorrelated error models

Maqsood, Arfa; Burney, S. M. Aqil

doi:10.1080/03610926.2016.1239113

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…Lasperyres and Divisia express their conclusions in terms of proportion and logarithmic weight relation variation, respectively, with the former presented in the form of Lasperyres exponential decomposition and the latter in the form of Divisia exponential decomposition [45,46]. Lasperyres index decomposition methods mainly include Shapley value index method, Fisher ideal index method, Marshall-Edgeworth method and so on.This method can be used to study the influence of a certain influencing factor on the basis of fixing the other influencing factors as the reference value.…”

Section: Fig 3 Classification Of Decomposition Analysis Methodsmentioning

confidence: 99%

Evaluation and Comparison of Research Methods on Driving Factors of Carbon Emission in Industrial Parks

Ma,

Liu,

et al. 2024

E3S Web Conf.

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As the primary territories of regional carbon emission and energy consumption, most industrial parks only simply stack technology and policy under the urgent goal of emission reduction and carbon reduction. As a result, certain measures may even have negative impacts. As the primary means to determine the characteristics of carbon emissions in industrial parks, studying the driving factors of carbon emissions and proposing targeted measures can effectively achieve the carbon emission reduction goals. However the mechanism analysis of driving factors of carbon emission in industrial parks is the important means to study the characteristics of carbon emission. The selection of driving factors is many and complicated, and the selection of mechanism analysis methods is different, so it is difficult to have a comparison of research results Based on the quantitative relationship model between carbon emissions and driving factors and the method of action mechanism analysis in industrial parks, this paper evaluates and compares the relevant studies, summarizes their advantages and disadvantages, and makes relevant comments and prospects. For providing reference for the practice of driving factors of carbon emission in industrial parks, and put forward the basis for the research of carbon emission prediction.

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Section: Fig 3 Classification Of Decomposition Analysis Methodsmentioning

confidence: 99%

Evaluation and Comparison of Research Methods on Driving Factors of Carbon Emission in Industrial Parks

Ma,

Liu,

et al. 2024

E3S Web Conf.

View full text Add to dashboard Cite

show abstract

“…We have confirmed for p=1 and p=2 and get the same formula for Laspeyres as given in equation (6). The standard errors of estimated Laspeyres index numbers are derived by Maqsood and Burney (2017). To find the influential observations and its impact on Laspeyres regression model we consider the two familiar influence measures hat matrix and difference in parameter vector beta (DFBETA).…”

Section: Stochasic Laspeyres Regression Modelmentioning

confidence: 99%

An Algorithm to Find Significant Commodities in Stochastic Laspeyres Regression Model.

Maqsood¹

2019

IJAR

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Investigating effect of R&D investment on decoupling environmental pressure from economic growth in the global top six carbon dioxide emitters

Jiang

2020

Science of The Total Environment

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Standard errors for the Laspeyres index number with autocorrelated error models

Cited by 4 publications

References 15 publications

Evaluation and Comparison of Research Methods on Driving Factors of Carbon Emission in Industrial Parks

Evaluation and Comparison of Research Methods on Driving Factors of Carbon Emission in Industrial Parks

An Algorithm to Find Significant Commodities in Stochastic Laspeyres Regression Model.

Investigating effect of R&D investment on decoupling environmental pressure from economic growth in the global top six carbon dioxide emitters

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