Document Type : Research Paper

Authors

• Parisa Mohajeri ¹
• Reza Taleblou ¹
• Mina Yaghchi ²

¹ Associate Professor of Economics, Allameh Tabataba’i University, Tehran, Iran

² Master of Economics, Allameh Tabataba’i University, Tehran, Iran

Abstract

 Selecting the optimal capital structure is a crucial decision for company managers as it significantly influences both the firm's value and shareholders' wealth. This study aims to identify the factors affecting capital structure (financial leverage), with a particular focus on uncertainties at both industry and company levels, utilizing a multilevel panel model. Data from 151 companies listed on the Tehran Stock Exchange across 26 industries were collected over a 14-year period from 1387 to 1401. R software was utilized to estimate the volatilities of stock price volatility and industry indices, followed by the estimation of the multilevel panel model using Stata software. The findings reveal several key insights: first, uncertainties at the industry level exhibit a negative and significant impact on leverage, whereas uncertainties at the company level do not demonstrate statistical significance. Second, Q-Tobin exerts a positive and significant effect, while variables such as cash flow, profitability, tangible assets, and the market-to-book value ratio have a negative and significant influence on leverage. Third, incorporating different levels and accounting for the stochastic component in the estimated coefficients of variables enhances the explanatory power of the model, thus indicating the superiority of the multilevel panel model over the fixed effects panel model.
Introduction
Optimal allocation of financial resources is imperative for preserving value, fostering growth, and facilitating the development of companies. Financing methods, whether through debt (financial leverage) or equity, carry their own set of advantages and disadvantages. Financial leverage, defined as the ratio of debt to assets, necessitates prudent decision-making to mitigate risks such as the potential for bankruptcy. Various factors contribute to differing financial leverage ratios among companies, with some stemming from firm-specific characteristics and others from macroeconomic variables.
Uncertainty emerges as a significant determinant influencing firms' financial decisions. This study focuses on assessing the impact of company-specific uncertainty, measured through stock return volatilities, while also examining uncertainty at the industry level using a stochastic volatility approach. By exploring these uncertainties, this research seeks to shed light on their implications for capital structure decisions.
Methods and Material
The research methodology involves employing the stochastic volatility (SV) method to estimate company-specific uncertainty and uncertainty at the industry level. Additionally, the multi-level panel method is utilized to explore variations in financing among companies across different industry levels.
Results and Discussion
This research examines the impact of company-specific uncertainty on financial leverage, considering the significance of financing decisions. Data from 151 companies listed on the Tehran Stock Exchange from 1387 to 1401 were utilized, with the stochastic volatility model employed to estimate company and industry-specific uncertainties. Subsequently, the influence of these uncertainties, alongside other pertinent variables at the company and macroeconomic levels, on leverage was investigated using multi-level panel models. Six levels were considered, including: (1) unsuccesses to account for the company level, (2) unsuccesses to consider the industry level, (3) unsuccesses to incorporate the stochastic component in the Q-Tobin coefficient at the company level (incorporating the previous two levels), (4) unsuccesses to incorporate the stochastic component in the profitability coefficient at the company level (incorporating the previous three levels), (5) unsuccesses to incorporate the stochastic component in inflation and growth at the company level (incorporating the previous four levels), and (6) unsuccesses to incorporate the stochastic component in inflation and growth at the industry level (incorporating the previous five levels). The significance of each level was assessed through relevant tests.
 
 
 
Table1




variable


Model1


Model2


Model3


Model4


Model5


Model6




Qtobin


0/0036
(0/0035)


0/0044
(0/0018)


0/0155
(0/0036)


0/0161
(0/0036)


0/0155
(0/0052)


0/0157
(0/0048)




Prof


-0/7354
(0/0000)


-0/8504
(0/0000)


-0/7411
(0/0000)


-0/7224
(0/0000)


-0/7175
(0/0000)


-0/7217
(0/0000)




MTB


-3/39e-14
(0/0230)


-4/40e-14
(0/0107)


-4/01e-14
(0/0020)


-3/96e-14
(0.0022)


-3/73e-14
(0/0036)


-4/00e-14
(0/0018)




CF


-0/0084
(0/0089)


-0/0138
(0/0002)


-0/0099
(0/0003)


-0/0091
(0/0006)


-0/0092
(0/0005)


-0/0090
(0/0006)




Tang


-0/2393
(0/0000)


-0/1022
(0/0001)


-0/2634
(0/0000)


-0/2523
(0/0000)


-0/2460
(0/0000)


-0/2420
(0/0000)




CV-Co


-7/79e-06
(0/9860)


-0/0004
(0/3283)


-1/42e-05
(0/9706)


-0/0001
(0/7858)


-0/0001
(0/7726)


-8/13e-05
(0/8274)




CV-In


-0/0042
(0/0045)


-0/0039
(0/0254)


-0/0044
(0/0012)


-0/0043
(0/0010)


-0/0043
(0/0009)


-0/0043
(0/0011)




Inflation


-0/0783
(0/0000)


-0/0382
(0/2177)


-0/1036
(0/0000)


-0/1032
(0/0000)


-0/1016
(0/0001)


-0/1095
(0/0030)




Growth


-0/0048
(0/0000)


-0/0043
(0/0018)


-0/0052
(0/0000)


-0/0050
(0/0000)


-0/0049
(0/0000)


-0/0052
(0/0002)




Constant


0/7805
(0/0000)


0/7195
(0/0000)


0/7384
(0/0000)


0/7347
(0/0000)


0/7335
(0/0000)


0/7305
(0/0000)




Source; research findings
Results indicate that company-specific uncertainty does not significantly influence leverage, whereas industry-level uncertainty exhibits a negative and significant effect on financial leverage. Additionally, the Q-Tobin variable demonstrates a positive and significant effect, while variables including growth rate, inflation rate, profitability, market-to-book value ratio, cash flow, and asset visibility exhibit a negative and significant impact on financial leverage.
Conclusion
Given the substantial implications of financing decisions on a company's prospects, value, and shareholders' wealth, attention to variables affecting financial leverage and uncertainties in this domain is crucial. This study underscores the importance of understanding and incorporating both company-specific and industry-level uncertainties in financial decision-making processes.
This research delved into the impact of specific uncertainty at both the company and industry levels, alongside other influential variables at the company and macroeconomic levels, on financial leverage. The findings indicate that while company-specific uncertainty does not exert a significant effect on leverage, industry-level uncertainty demonstrates a notable negative impact on financial leverage. Furthermore, the Q-Tobin variable exhibits a positive and significant effect, while variables such as growth rate, inflation rate, profitability, market-to-book value ratio, cash flow, and asset visibility demonstrate a negative and significant influence on financial leverage.

Keywords

• Firm-specific Uncertainty
• Industry-wide Uncertainty
• Stochastic Volatility
• Financial Leverage
• Multilevel Panel