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http://dx.doi.org/10.13106/jafeb.2020.vol7.no7.073

Reliable and Advanced Predictors for Corporate Financial Choices in Pakistan  

SHAHZAD, Umeair (Accounting Department, Management College, Ocean University of China)
FUKAI, Luo (Accounting Department, Management College, Ocean University of China)
MAHMOOD, Faisal (School of Economy and Management, Harbin Institute of Technology)
JING, Liu (Henan University of Economics and Law)
AHMED, Zahoor (School of Management and Economics, Beijing Institute of Technology)
Publication Information
The Journal of Asian Finance, Economics and Business / v.7, no.7, 2020 , pp. 73-84 More about this Journal
Abstract
Existing studies disagree over the core predictors of firm-level financial choices in developing countries. The general practice only validates the traditional capital structure model, which leads to inconsistency and a lack of novelty. This study removed overfitting issues among existing factors and presented the most reliable and advanced capital structure model in Pakistani firms. The panel data include 368 Pakistani companies from 19 non-financial sectors over the period 2004 to 2017. We apply Akaike and Bayesian Information Criteria to remove overfitting issues among inconsistent proxies in the capital structure model. The fixed effects regression is used for basic results and the Generalized Method of Moments is applied to control the endogeneity. Besides the conventional proxies, we report that credit rating, distance from bankruptcy, managerial concentration, and institutional quality are the most advanced capital structure determinants in Pakistan. These predictors remain significant across firm size and growth levels. Also, the findings confirm that new predictors are reliable to define capital structure dynamics and improve the speed of adjustment in overall and sub-sample analysis. The major findings suggest that managers and policymakers should consider these advanced predictors to design their financial settings in firms.
Keywords
Capital Structure; Adjustment Speed; Institutional Quality; Bayesian Information Criteria; Pakistan Stock Exchange;
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Times Cited By KSCI : 4  (Citation Analysis)
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