Purpose

The purpose of this paper is to examine the optimal leverage ratio, speed of adjustment, and which factors contribute to achieving the target of selected telecom companies in a partial adjustment framework from 2008 to 2017. Further is to analyze the likelihood of bankruptcy of sample companies by Altman Z-Score model and to suggest which theory of capitals structure is better in explaining leverage strategies and judicious mix of debt and equity structure of the selected telecom companies.

Design/methodology/approach

This paper chooses a partial adjustment model and uses the generalized method of moments technique to identify the variables that influence the target leverage ratio and the factors that influence the speed at which the target leverage is adjusted. Second, the Altman Z-score model is used in this paper to research the financial status of telecom companies using financial instruments and techniques.

Findings

For Indian telecom firms, firm-specific variables such as profitability, NDTS and Z-score lead to greater debt adjustment towards optimal level target leverage. The paper also highlights new paradigms in the Indian telecom sector, stating that top market leaders such as Bharti Airtel, BSNL, Idea, Vodafone and R.com, among others, should focus on debt reduction and interest payments, as well as implement new strategies to solve the crisis and change financial policies.

Research limitations/implications

It mainly focuses on firm-specific variables because the firm-specific variables affect the leverage framework. The country-specific variables are not taken into the study. These results may be unique to telecom companies due to some peculiarities existing in the telecom sector in India. Although other sectors, both national and international level, can be taken into consideration.

Practical implications

This paper has ramifications for corporate executives, investors and policymakers in India, for example, in terms of considering different transition costs while changing a telecom company’s financing decisions.

Originality/value

To the best of the authors’ knowledge, this is the first paper of its kind to look at both financial and econometric tools to assess financial performance using the Altman Z-Score model, as well as decide leverage strategies and the pace with which they can be adjusted to target leverage in the context of Indian telecom companies.

中文翻译：

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印度电信部门的杠杆策略：动态面板数据方法

目的

本文旨在考察2008-2017年部分调整框架内选定的电信公司的最优杠杆率、调整速度以及哪些因素有助于实现目标。进一步分析样本公司破产的可能性通过 Altman Z-Score 模型，并建议哪种资本结构理论更好地解释所选电信公司的杠杆策略和债务和股权结构的明智组合。

设计/方法/方法

本文选择局部调整模型，采用广义矩量法识别影响目标杠杆率的变量和影响目标杠杆率调整速度的因素。其次，本文使用Altman Z-score模型来研究电信公司使用金融工具和技术的财务状况。

发现

对于印度电信公司而言，公司特定变量（如盈利能力、NDTS 和 Z 分数）会导致更大的债务调整，以实现最佳水平目标杠杆。该文件还强调了印度电信行业的新范式，指出 Bharti Airtel、BSNL、Idea、沃达丰和 R.com 等顶级市场领导者应专注于减少债务和支付利息，并实施新战略解决危机和改变金融政策。

研究限制/影响

它主要关注企业特定变量，因为企业特定变量会影响杠杆框架。国家特定变量未纳入研究。由于印度电信行业存在一些特殊性，这些结果可能对电信公司来说是独一无二的。尽管可以考虑国家和国际层面的其他部门。

实际影响

本文对印度的企业高管、投资者和政策制定者产生了影响，例如，在改变电信公司的融资决策时考虑不同的过渡成本。

原创性/价值

据作者所知，这是第一篇使用 Altman Z-Score 模型同时研究财务和计量经济学工具来评估财务业绩，以及决定杠杆策略和杠杆速度的论文在印度电信公司的背景下调整目标杠杆。