Capital Structure Decisions of Listed Firms in Transport Equipment Industry in India

Abstract

Aims: The study predominantly attempts to examine the capital structure decisions of listed firms in Transport Equipment Industry by analyzing the relationship between leverage and profitability.
 Study Design: Descriptive research design is used to describe the characteristics of the firms belonging to industry. The study envisages an extensive use of data extracted from professional database CMIE prowess and from reports Ministry of Statistics and Programme Implementation, Annual Survey of Industries and Satista.
 Place and Duration of Study: The sample for the study consists of all listed firms National Stock Exchange (NSE) affiliated under Transport equipment Industry (CMIE classification). There were totally 86 firms as on 31st March 2018. The relevant data sets are retrieved for a period of 10 years (2008-2018). Thus, a panel data of 860 different observations were considered for study.
 Methodology: To analyze the data collected, Econometric model for longitudinal data with repeated measures known as Hierarchical linear regression model is adopted. This helps in estimation of industry grand mean, segment mean and firm mean for multilevel nested data.
 Results: The result of the study indicates that segment means are approximately equal to industry mean of 0.2898. Further, the segment-level means of all eight segments follows normal distribution with firms having high and low leverage firms. Finally, the firm-level variance is comparably high indicating that firms’ influence on capital structure decisions is predominant of all in this industry which has been found to be consistent over past decade.
 Conclusion: The underleveraged firms in Transport Equipment Industry exhibit relatively higher average Return on Equity (ROE) and Return on Capital Employed (ROCE) compared to optimal leveraged firms. On the other hand, overleveraged firms indicate inverse relationship with profitability. This is justified by the pecking order theory that higher profitable firms incorporate internally generated funds available at lower cost compared to external financing.

Productive Performance of Indian Food Manufacturing Industry: A Sub-Sectoral Analysis in a Stochastic Frontier Framework

“…Malhotra (2018) followed a two-stage analysis of the TE of the food manufacturing industry in the state of Punjab (India) by employing DEA to estimate TE and Tobit regression analysis to identify its sources within the context of the management of the working capital. Shilpa and Amulya (2019), using DEA and ASI data, estimated the TE of eight Indian food manufacturing sub-sectors since 2008. This study did not pay any attention to the changing prices and wages over the study period; therefore, its estimates do not seem quite reliable and useful.…”