Multifactor Model for Estimation of Tobin’s Q for Listed Firms
Additional contact information
Talwar Shalini: K J Somaiya Institute of Management Studies and Research, Mumbai, India
Economics and Applied Informatics, 2018, issue 2, 38-47
This research examines the effect of firms efficiency in asset utilzation(ROA), leverage(debt/equity ratio), dividend decision and corporate governance on the firm value measured through Tobin’s Q for listed Indian firms in FMCG, Auto and IT sector using quarterly accounting data collected for period from 2004 through 2017. The study has examined a multi-factor model by applying multiple linear regression to identify the model for estimation of Tobin’s Q. The results reveal that the explanatory variables for predicting firm value for the auto sector are ROA, debt equity ratio and dividend payout ratio, for the FMCG sector, debt equity ratio, dividend payout ratio and governance score and for the IT sector are ROA, debt equity ratio, dividend payout ratio and governance score are the statistically significant explanatory variables for modelling Tobin’s Q. As the statistically significant predictors for Tobin’s Q are different for IT, auto and FMCG sectors, a key implication of this study is that it is not very useful to apply a common model for predicting Tobin’s Q for all firms.
Keywords: Corporate governance; Debt equity ratio; Dividend payout ratio; Firm value; Multiple regression analysis; Return on assets; Tobin’s Q (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ddj:fseeai:y:2018:i:2:p:38-47
Access Statistics for this article
More articles in Economics and Applied Informatics from "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration Contact information at EDIRC.
Bibliographic data for series maintained by Gianina Mihai ().