Dynamic target capital structure and speed of adjustment in farm business

2018 ◽  
Vol 46 (4) ◽  
pp. 637-661
Author(s):  
Tamirat S Aderajew ◽  
Andres Trujillo-Barrera ◽  
Joost M E Pennings
Keyword(s):  
Capital Structure ◽  
Adjustment Costs ◽  
Pecking Order ◽  
Speed Of Adjustment ◽  
Growth Opportunity ◽  
Dynamic Target ◽  
The Difference ◽  
General Method Of Moments ◽  
Farm Business ◽  
Leverage Dynamics

Abstract This paper quantifies the determinants and speed of adjustment to the target capital structure for a panel of 1,500 Dutch farms over the years 2001–2015. Using the System General Method of Moments (System-GMM) estimator, the results show that farm profitability, earnings volatility, asset tangibility and growth opportunity are important determinants of leverage. Leverage is highly persistent, i.e. the average adjustment speed is relatively low, with variations among farm types. This variation is mainly attributed to the difference in adjustment costs. Further, we show that the pecking order and signalling theories explain these leverage dynamics.

scholarly journals Microeconomics and raw material price on capital structure adjustment through dynamic target in Indonesian textile industries

Accounting ◽  
2021 ◽  
pp. 231-238
Author(s):  
Sunita Dasman ◽  
Erie Febrian ◽  
Sulaeman Nidar ◽  
Aldrin Herwany
Keyword(s):  
Capital Structure ◽  
Stock Exchange ◽  
Raw Material ◽  
Company Size ◽  
Speed Of Adjustment ◽  
Growth Opportunity ◽  
Structure Adjustment ◽  
Dynamic Target ◽  
Textile Industries ◽  
Retained Earnings

This study aims to examine the effects of company-specific macroeconomic fluctuation in raw materials prices on the speed of adjustment through dynamic targeting capital structure on textile companies listed on the Indonesia Stock Exchange during 2012 and the second quarter of 2020. Using panel data regression of the fixed-effect method, we discovered that the speed of adjustment varies in each industry and period. Textile companies listed on the Indonesia Stock Exchange adjust their capital structure through a dynamic target of 53.3% per year. It takes 1 year and 10 months to close the target capital structure. The factors that determine the target capital structure include company size, tangibility, liquidity and growth opportunity, asset utilization, as well as retained earnings. On the other side, factors that contribute to the speed of adjustment include company size, growth opportunity, earnings volatility, asset utilization, retained earnings, distance to the target, and economic growth. Other factors that also affect the speed of adjustment include fluctuations in the prices of cotton and crude oil. The result of this study is expected to provide an optimal capital structure formulation to the textile industries in Indonesia to finance companies’ operational activities and growth opportunities effectively. This study also provides an overview of how textile companies make capital structure adjustment, as there are changes in company-specific factors, macroeconomic conditions, and fluctuation in raw material prices.

scholarly journals Determinants of the Capital Structure of Companies Listed on the Stock Exchanges of Argentina, Brazil and Chile: An Empirical Analysis of the Period from 2007 to 2016

2020 ◽  
Vol 12 (6) ◽  
pp. 18
Author(s):  
Marcelo Rabelo Henrique ◽  
Sandro Braz Silva ◽  
Antônio Saporito ◽  
Sérgio Roberto da Silva
Keyword(s):  
Panel Data ◽  
Capital Structure ◽  
Order Theory ◽  
Future Research ◽  
Stock Exchanges ◽  
Pecking Order ◽  
Pecking Order Theory ◽  
Speed Of Adjustment ◽  
Asset Growth ◽  
The Capital Structure

The present investigation refers to the determinants of the capital structure, using the technique of multiple regression through Panel Data of open capital companies in the stock exchanges of Argentina, Brazil and Chile, in order to know the behavior of determinants of the capital structure in relation to Trade-Off Theory (TOT) and Pecking Order Theory (POT). The POT offers the existence of a hierarchy in the use of sources of resources, while the TOT considers the existence of a target capital structure that would be pursued by the company. Sixteen accounting variables were used, in which five are dependent (related to indebtedness) and eleven are independent variables (explaining the determinants of the capital structure). It is observed that, with the use of the Panel Data, the determinants that seem to influence in a more accentuated way the levels of debt of the companies are: current liquidity, tangibility, return to shareholders, return of assets, sales growth, asset growth, market-to-book and business risk measured by the volatility of benefits. Suggestions for future research include the use of Panel Data to analyze other factors that may influence indebtedness, mainly taxes and dividends, as well as a deeper analysis of factors that may influence the speed of adjustment towards the supposed objective level.

Heterogeneity and Asymmetry in Speed of Leverage Adjustment: The Indian Experience

2016 ◽  
Vol 19 (03) ◽  
pp. 1650019 ◽  
Author(s):  
Surenderrao Komera ◽  
P. J. Jijo Lukose
Keyword(s):  
Capital Structure ◽  
Cash Flow ◽  
Emerging Market ◽  
Adjustment Costs ◽  
Group Affiliation ◽  
Cross Sectional ◽  
Speed Of Adjustment ◽  
Business Group Affiliation ◽  
Optimal Leverage ◽  
Target Leverage

In this paper, we examine firms' capital structure adjustment behavior and estimate their “speed of adjustment” toward optimal leverage ratios by employing a dynamic, partial adjustment model. We find that sample firms on an average offset half of the deviation from their target leverage ratios in less than one and half (1.41) years. Such evidence suggests optimal capital structure behavior among sample firms. Further, we report cross sectional heterogeneity and asymmetry in speed of adjustment estimates, resulting from varied leverage adjustment costs across the sample firms. We find higher speed of adjustment estimates among larger sample firms suggesting higher leverage adjustment costs for smaller firms. Business group affiliation does not seem to influence the costs of sample firms' leverage adjustment. Over-levered firms report higher speed of adjustment estimates, suggesting that sample firms do not consider debt financing as a “disciplining mechanism” for managers. Further, we find lower speed of adjustment estimates for sample firms with higher cash flow, implying that Indian markets do not actively accommodate firms' cash flow needs. Thus, our findings reveal complex asymmetric information problems and consequent varied leverage adjustment costs among emerging market firms.

scholarly journals Do DJIA Firms Reflect Stationary Debt Ratios?

Economies ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 76
Author(s):  
Feng-Li Lin
Keyword(s):  
Capital Structure ◽  
Stationary Processes ◽  
Debt Ratio ◽  
Pecking Order ◽  
Trade Off ◽  
Listed Firms ◽  
Growth Opportunity ◽  
Dow Jones Industrial Average ◽  
The Mean ◽  
The Stability

To form optimum firm capital structure strategies to face unanticipated economic events, firm managers should understand the stability of a firm’s capital structure. The aim of this research was to study whether the debt ratio is stationary in listed firms on the Dow Jones Industrial Average (DJIA). Two vital capital structure concepts regarding pecking order and trade-off theory are fairly contradictory. Using opposing theoretical contexts, the Sequential Panel Selection Method apparently categorizes which and how many series are stationary processes in the panel. This method was used to test the mean reverting properties of the 25 companies listed on Dow Jones Industrial Average between 2001 and 2017 in this study, which is expected to fill the current gap in the literature. The overall results show that stationary debt ratios exist in 10 of the 25 studied firms, supporting the trade-off theory. Moreover, the 10 firms utilizing trade-off theory are affected by firm size, profitability, growth opportunity, and dividend payout ratio. These results provide vital information for firms to certify strategies to optimize capital structure.

THAI FIRMS' HISTORIES AND THEIR CAPITAL STRUCTURE

2011 ◽  
Vol 06 (01) ◽  
pp. 1150004
Author(s):  
TAK YAN LAW ◽  
TERENCE TAI-LEUNG CHONG
Keyword(s):  
Capital Structure ◽  
Stock Price ◽  
Market Timing ◽  
Pecking Order ◽  
Timing Behavior ◽  
Price Performance ◽  
Growth Opportunity ◽  
Timing Effects ◽  
The Capital Structure

This paper examines the impacts of profitability, stock price performance and growth opportunity on the capital structure of firms in Thailand. The methodology of Kayhan and Titman (2007) is applied to model the dynamics of debt ratios. The results suggest that the leverage ratios of Thai firms do adjust towards their target levels. The deviations from the target due to the pecking-order and market timing effects are found to be significant. In contrast to Kayhan and Titman (2007), our results show that the market timing behavior does not persist.

LONG-TERM ADJUSTMENT OF CAPITAL STRUCTURE: EVIDENCE FROM SINGAPORE, HONG KONG AND TAIWAN

2012 ◽  
Vol 57 (04) ◽  
pp. 1250027
Author(s):  
TERENCE TAI-LEUNG CHONG ◽  
DANIEL TAK-YAN LAW ◽  
LIN ZOU
Keyword(s):  
Hong Kong ◽  
Capital Structure ◽  
Stock Price ◽  
Pecking Order ◽  
Price Performance ◽  
Growth Opportunity ◽  
Timing Effects ◽  
The Impact ◽  
Internal Fund

This paper examines the impact of profitability, stock price performance and growth opportunity on the capital structure of firms in Singapore, Taiwan and Hong Kong. In contrast to Kayhan and Titman (2007), it is found that firms in these three Chinese-dominated economies strongly prefer debt to equity or internal fund financing. They also take advantage of stock price appreciation by issuing more shares. An adjustment model for debt ratios is estimated. The results suggest that the leverage ratios of these firms slowly adjust toward their target levels. Deviations from the target due to the pecking order and market timing effects are found to be significant.

How do Spanish unlisted family firms rebalance their capital structures?

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zélia Serrasqueiro ◽  
Fernanda Matias ◽  
Julio Diéguez-Soto
Keyword(s):  
Capital Structure ◽  
Transaction Costs ◽  
Family Firms ◽  
Adjustment Costs ◽  
Dynamic Panel Data ◽  
Future Research ◽  
Short Term ◽  
Content Type ◽  
Speed Of Adjustment

PurposeThis paper seeks to analyze the family firm's capital structure decisions, focusing on the speed of adjustment (SOA) as well as on the effect of distance from the target capital structure on the SOA towards target short-term and long-term debt ratios in unlisted small and medium-sized family firms.Design/methodology/approachMethodologically, we use dynamic panel data estimators to estimate the effects of distance on the speeds of adjustment towards those targets. Data for the period 2006–2014 were collected for two research sub-samples: one sub-sample with 398 family firms; the other sub-sample contains 217 non-family firms.FindingsThe results show that the deviation from the target debt ratios impacts negatively on the speeds of adjustment towards target short-term and long-term debt ratios in unlisted family firms. These results suggest that family firms, deviating from target debt ratios, face deviation costs, i.e. insolvency costs, inferior to the adjustment costs, i.e. transaction costs. Therefore, family firms stay away from the target debt ratios for a long time than do non-family firms.Research limitations/implicationsThe research sample comprises a low number of family firms, therefore for future research we suggest increasing the size of the sample of family firms to get a deeper understanding of family firms' SOA towards capital structure. Additionally, we suggest the analysis of other potential determinants of the speed of adjustment towards target capital structure.Practical implicationsThe results obtained suggest that the distance from the target short-term and long-term debt ratios can be avoided if these firms do not depend almost exclusively on internal finance to adjust towards target capital structure. Moreover, for policymakers, we suggest the creation/promotion of alternative external finance sources, allowing reduced transaction costs that contribute to a faster adjustment of small family firms towards target capital structure.Originality/valueThe most previous research focusing on capital structure decisions have focused on listed family firms. To fill this gap, this study examines the speed of adjustment towards target debt ratios in the context of unlisted family firms. Moreover, transaction costs are a function of debt maturity, therefore this study examines separately the speeds of adjustment towards target short-term and long-term debt ratios. This paper shows that the adjustment costs (i.e. transaction costs) could hold back family firms from rebalancing its capital structure.

scholarly journals ANALISIS EMITEN SYARIAH DI JII MENGENAI FAKTOR STRUKTUR MODAL PERIODE TAHUN 2014 - 2018

2020 ◽  
Vol 7 (6) ◽  
pp. 1193
Author(s):  
Anisa Priyanka Jasmine ◽  
Imron Mawardi
Keyword(s):  
Capital Structure ◽  
Order Theory ◽  
Significant Variable ◽  
Company Size ◽  
Pecking Order ◽  
Pecking Order Theory ◽  
Dividend Payout ◽  
Panel Data Regression ◽  
Growth Opportunity ◽  
Data Regression

This study was made with the aim to examine the effect of profitability, company size, company age, growth opportunity, liquidity and dividend payout ratio on the capital structure of Islamic issuers listed in the JII (Jakarta Islamic Index). The method in this study uses multiple regression analysis techniques with Random Effet Model (REM) selected as the best model for estimating panel data regression, where in estimating the General Least Saquare (GLS) regression test is used. And produce profitability and dividend payout ratio as a significant variable and this also proves its effect partially on leverage (DER). While simultaneously profitability, company size, company age, liquidity and dividend payout ratio significantly influence leverage (DER).Keywords: profitability, company size, company age, growth opportunity, liquidity, dividend payout ratio, pecking order theory, capital structure

scholarly journals Pengaruh Tangibility, Growth Opportunity, Size, Profitability, dan Risk Terhadap Struktur Modal: dalam Perspektif Pecking Order Theory pada Perusahaan Automotive and Allied Products di BEI

2018 ◽  
Vol 5 (1) ◽  
pp. 44
Author(s):  
DEVI WAHYU NUARSARI
Keyword(s):  
Capital Structure ◽  
Capital Market ◽  
Order Theory ◽  
Negative Influence ◽  
Positive Influence ◽  
Pecking Order ◽  
Pecking Order Theory ◽  
Growth Opportunity ◽  
The Capital Structure

This research aims to test influence of tangibility, growth opportuity, size, profitability, and risk on the capital structure. This research is conducted on Automotive and Allied Products companies at BEI period 2004-2009, that still listed in the Indonesian Capital Market. The result of the test concluded that tangibility and size has a positive influence to the capital  structure, but profitability dan risk has a negative influence to the capital structure, and growth opportunity has a negative influence to the capital structure but not significant.

scholarly journals Determinan Struktur Modal Dalam Perspektif Pecking Order Theory Dan Agency Theory

Akuntabilitas ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 191-204
Author(s):  
Nana Umdiana ◽  
Shifa Tivana
Keyword(s):  
Capital Structure ◽  
Order Theory ◽  
Managerial Ownership ◽  
Manufacturing Companies ◽  
Business Risk ◽  
Pecking Order ◽  
Good Industry ◽  
Pecking Order Theory ◽  
Growth Opportunity ◽  
The Capital Structure

The capital structure seen from the perspective of pecking order theory explains that companies are more likely to prefer internal funding than external companies. Pecking Order Theory explains why highly profitable companies generally have less debt. This study aims to discuss Liquidity, Asset Structure, Business Risk, Growth Opportunity, Managerial Ownership of Capital Structures on Manufacturing Companies of the basic Consumer Good Industry Sector listed on the Indonesia Stock Exchange period 2016- 2019.This type of research is an associative causal research with the type of time series. The sample was selected using the purposive sampling method. Data analyzed amounted to 40. Data was tested using multiple linear regression analysis.The result of this study indicate that Liquidity is significant affect the Capital Structure. Asset Structure, Business Risk, Growth Opportunity, Managerial Ownership did not affect the Capital Structures.

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