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Determinants of capital structure: an empirical evaluation from India

资本结构 税收盾牌 有序融资理论 债务资本比率 负债率 证券交易所 股息支付率 经济 货币经济学 面板数据 业务 负债股本比率 财务 债务 金融经济学 股利政策 计量经济学 股本回报率 股权比例 公共经济学 人口 社会学 人口学 非概率抽样 总收入 国家所得税 税制改革
作者
Saurabh Chadha,Anil K. Sharma
出处
期刊:Journal of Advances in Management Research [Emerald Publishing Limited]
卷期号:12 (1): 3-14 被引量:94
标识
DOI:10.1108/jamr-08-2014-0051
摘要

Purpose – The purpose of this paper is to study the key determinants of capital structure for Indian manufacturing firms and which theory implications, i.e. trade off vs pecking order are more applicable in current Indian manufacturing sector scenario. Design/methodology/approach – A sample size of 422 listed Indian manufacturing companies on Bombay Stock Exchange has been considered to do the empirical evaluation. A ten year period from 2003-2004 to 2012-2013 and annual financial standalone data have been considered for study. Ratio analysis and panel data approach have been applied to perform the empirical evaluation. Total debt to total capital and total debt to total assets are used as the proxy for firm financial leverage. Findings – It was empirically found that size, age, asset tangibility, growth, profitability, non-debt tax shield, business risk, uniqueness and ownership structure are significantly correlated with the firm financial leverage or key determinants of capital structure in Indian manufacturing sector. Also, other variables like dividend payout, liquidity, interest coverage ratio, cash flow coverage ratio (CFCR), India inflation and GDP growth rate are empirically found to be insignificant to determine the capital structure of Indian manufacturing sector. There is no single theory implications, i.e. trade off vs pecking order which can explain the capital structure nature of Indian manufacturing sector and rather it is a mix of both the theories. Originality/value – The findings of the study would enhance the literature on capital structure and is significant for the Indian manufacturing firm’s decisions as it includes the most recent data and covers the period of both pre- and post-recession of 2008-2009.

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