Chaudhuri, K orcid.org/0000-0002-7492-1369, Kumbhakar, SC and Sundaram, L (2016) Estimation of firm performance from a MIMIC model. European Journal of Operational Research, 255 (1). pp. 298-307. ISSN 0377-2217
Abstract
In this paper we propose a new approach (based on the Multiple Indicator Multiple Cause (MIMIC) model of Joreskog and Goldberger (1975) to assess the performance of firms assuming that the ‘true’ firm performance is latent but there are many observable indicators of it. In our MIMIC model, the latent firm performance variable is linked with some observed explanatory variables (determinants) like age, size, advertising expenses, debt equity ratio, etc. Since there are many observed indicators (ROE, ROA, Tobin’s Q, etc.) of the unobserved latent firm performance, the measurement equations in the MIMIC model link these observed indicators to the latent performance measure. We use firm level data from India during the period 2001 to 2008 to estimate the latent firm performance using the predicted factor scores and rank the firms according to the proposed measure. Finally, we estimate two stochastic frontier models and compute Pearson’s correlation between pairs of performance measures. We find high rank correlation between the two measures of firm performance/efficiency, which justifies the use of the MIMIC model as a complementary method of performance measures.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2016 Elsevier B.V. All rights reserved. This is an author produced version of a paper published in European Journal of Operational Research. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Firm Performance; MIMIC Model; Ownership Structure |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Economics Division (LUBS) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 06 May 2016 10:01 |
Last Modified: | 11 May 2018 00:38 |
Published Version: | http://dx.doi.org/10.1016/j.ejor.2016.05.005 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.ejor.2016.05.005 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:99333 |