Determinants and Dynamic Adjustment of Capital Structure: Evidence from UK Company Panel Data

Shen, Zhongyi (2019) Determinants and Dynamic Adjustment of Capital Structure: Evidence from UK Company Panel Data. [Dissertation (University of Nottingham only)]

[thumbnail of 4336575-N14031-Determinants and Dynamic Adjustment of Capital Structure- Evidence from UK Company Panel Data.pdf] PDF - Registered users only - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB)

Abstract

This study explores the most important determinants of capital structure and the adjustment speed towards target capital structure. Based on FTSE350, the data of 195 British listed companies for 10 years (2009-2018) are selected for static and dynamic research. In terms of static research, ANOVA analysis shows that capital structures vary across different industries, which proves that industry factor is one of the important factors affecting capital structure. In addition, regression results from the FE (fixed effects) model show that tangibility, profitability, and liquidity have significant effects on total leverage and long-term leverage, while factors that determine short-term leverage levels are size, tangibility, non-debt tax shield, and liquidity. In the aspect of dynamic research, because using irrational estimation method to estimate the adjustment speed will come to erroneous conclusions, the paper compares and analyzes three approaches for estimating the adjustment speed namely OLS, FE and two-step system GMM with a view to providing evidence for relevant research. The study finds that GMM is a relatively reasonable way to estimate the speed of adjustment. And it also shows that the listed companies in the UK have a faster adjustment speed, which indicates that there is a significant mean return phenomenon. Finally, by comparing the adjustment speed of British companies before and after financial risks periods, it is found that the impact of financial crisis on the adjustment speed of capital structure is not obvious.

Item Type: Dissertation (University of Nottingham only)
Depositing User: Shen, Zhongyi
Date Deposited: 07 Dec 2022 08:56
Last Modified: 07 Dec 2022 08:56
URI: https://eprints.nottingham.ac.uk/id/eprint/58172

Actions (Archive Staff Only)

Edit View Edit View