Economic Impacts of ESG Metrics on Energy Efficiency in Chinese Industries (doi:10.7910/DVN/VTEO24)

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Part 1: Document Description
Part 2: Study Description
Part 3: Data Files Description
Part 4: Variable Description
Part 5: Other Study-Related Materials
Entire Codebook

Document Description

Citation

Title:

Economic Impacts of ESG Metrics on Energy Efficiency in Chinese Industries

Identification Number:

doi:10.7910/DVN/VTEO24

Distributor:

Harvard Dataverse

Date of Distribution:

2023-12-30

Version:

1

Bibliographic Citation:

David, Lemuel, 2023, "Economic Impacts of ESG Metrics on Energy Efficiency in Chinese Industries", https://doi.org/10.7910/DVN/VTEO24, Harvard Dataverse, V1, UNF:6:JA4sILmNrtFfCIoTH9iUoQ== [fileUNF]

Study Description

Citation

Title:

Economic Impacts of ESG Metrics on Energy Efficiency in Chinese Industries

Identification Number:

doi:10.7910/DVN/VTEO24

Authoring Entity:

David, Lemuel (Xi'an Jiaotong University)

Distributor:

Harvard Dataverse

Access Authority:

David, Lemuel

Depositor:

David, Lemuel

Date of Deposit:

2023-12-30

Holdings Information:

https://doi.org/10.7910/DVN/VTEO24

Study Scope

Keywords:

Business and Management, Social Sciences, Other, Economic, modelling, machine learning, energy

Abstract:

These data were uuse to examines the economic impacts of Environmental, Social, and Governance (ESG) metrics on energy efficiency within Chinese industries from 2006 to 2020. we conducted an econometric analysis to explore the relationship between ESG practices and energy efficiency across various sectors and regions.

Methodology and Processing

Sources Statement

Data Access

Other Study Description Materials

File Description--f8076920

File: ESG CHINA12.tab

  • Number of cases: 3320

  • No. of variables per record: 11

  • Type of File: text/tab-separated-values

Notes:

UNF:6:JA4sILmNrtFfCIoTH9iUoQ==

Variable Description

List of Variables:

Variables

Year

f8076920 Location:

Summary Statistics: Max. 2020.0; StDev 2.872713993501682; Mean 2015.5; Min. 2011.0; Valid 3320.0;

Variable Format: numeric

Notes: UNF:6:/MZwQGtIsr07+ajXSHqveQ==

Province

f8076920 Location:

Variable Format: character

Notes: UNF:6:RP3TDy3VDfKOv7JAg09yEA==

Industry

f8076920 Location:

Variable Format: character

Notes: UNF:6:vgzafRWrD2bhzTr2rNLTlQ==

ESG_Mean

f8076920 Location:

Summary Statistics: Valid 3320.0; Max. 55.37189865; Mean 23.16062551603343; StDev 6.1448010090861835; Min. 9.090900421;

Variable Format: numeric

Notes: UNF:6:j8Ohn5YF1tJIGcb0wmROuA==

ESG_Sum

f8076920 Location:

Summary Statistics: Mean 38.016105734485244; Valid 3320.0; Min. 9.090900421; Max. 321.052496; StDev 32.78524781497805

Variable Format: numeric

Notes: UNF:6:u6VTkMJ9zlQ3Tio3/+kYqg==

E_Mean

f8076920 Location:

Summary Statistics: Min. 1.550400019; Valid 3320.0; Max. 55.81399918; StDev 7.843056072953357; Mean 11.968203831071369

Variable Format: numeric

Notes: UNF:6:M4kb2l7Utdpnq9t+22Z+ZA==

E_Sum

f8076920 Location:

Summary Statistics: Min. 1.550400019; Max. 212.4999981; StDev 20.13111452408973; Valid 3320.0; Mean 19.59782992209491

Variable Format: numeric

Notes: UNF:6:Ol70dE55jbn3jmN378B2dA==

S_Mean

f8076920 Location:

Summary Statistics: Max. 66.66670227; Min. 3.50880003; Valid 3320.0; Mean 26.150285754074716; StDev 8.356407428464157;

Variable Format: numeric

Notes: UNF:6:mjrYEleFiC9w1tqUQ4h4UA==

S_Sum

f8076920 Location:

Summary Statistics: Valid 3320.0; StDev 39.076479488531234; Min. 3.50880003; Mean 43.30713228151534; Max. 366.6666031

Variable Format: numeric

Notes: UNF:6:v3rvm5u+l5KC71z2ZRtUpQ==

G_Mean

f8076920 Location:

Summary Statistics: Valid 3320.0; Mean 46.206906729247; Min. 10.71430016; Max. 73.21430206; StDev 4.820577500684896

Variable Format: numeric

Notes: UNF:6:GelfPdKpkrAB+1n+n63vFw==

G_Sum

f8076920 Location:

Summary Statistics: Mean 75.40286607970785; Valid 3320.0; Min. 10.71430016; Max. 525.0000992; StDev 60.60643035703761

Variable Format: numeric

Notes: UNF:6:DaDuLY37MzrmsHBKT1uUbA==

Other Study-Related Materials

Label:

energy China 13data.xlsx

Text:

These data were uuse to examines the economic impacts of Environmental, Social, and Governance (ESG) metrics on energy efficiency within Chinese industries from 2006 to 2020. we conducted an econometric analysis to explore the relationship between ESG practices and energy efficiency across various sectors and regions.

Notes:

application/vnd.openxmlformats-officedocument.spreadsheetml.sheet