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Item Response Models to measure Corporate Social Responsibility

Grassi, Stefano, Nicolosi, Marco, Stanghellini, Elena (2014) Item Response Models to measure Corporate Social Responsibility. Applied Financial Economics, 24 (22). pp. 1449-1464. ISSN 0960-3107. (doi:10.1080/09603107.2014.925070) (KAR id:49294)

Abstract

Corporate Social Responsibility (CSR) is a multidimensional con-

cept that involves several aspects, ranging from Environment, to Social

and Governance. Companies aiming to comply with CSR standards

have to face challenges that vary from one aspect to the other and

from one industry to the other. Latent variable models may be use-

fully employed to provide a unidimensional measure of the grade of

compliance of a firm with CSR standards that is both understand-

able and theoretically solid. A methodology based on Item Response

Theory has been implemented on the multidimensional sustainability

rating as expressed by KLD dataset from 1991 to 2007. Results sug-

gest that companies in the industry Oil & Gas together with firms

in Industrials, Basic Materials and Telecommunications have a higher

difficulty to meet the CSR standards. Criteria based on Human rights,

Environment, Community and Product quality have a large capacity

to select the best performing firms, as they are very discriminant, while

Governance does not exhibit similar behavior. A stock selection based

on the ranking of the firms according to the proposed CSR measure

supports the hypothesis of a positive relationship between CSR and

financial performance

Item Type: Article
DOI/Identification number: 10.1080/09603107.2014.925070
Uncontrolled keywords: item Response Theory; Latent Variable Models; Portfolio management; Ranking; Socially Responsible Investment
Subjects: H Social Sciences > HG Finance
Divisions: Divisions > Division of Human and Social Sciences > School of Economics
Depositing User: Stefano Grassi
Date Deposited: 09 Jul 2015 14:24 UTC
Last Modified: 09 Dec 2022 05:16 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/49294 (The current URI for this page, for reference purposes)

University of Kent Author Information

Grassi, Stefano.

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