Models and Tests for the Pecking Order Hypothesis

2020 ◽  
Author(s):  
Daisuke Nagakura
2007 ◽  
Vol 14 (1) ◽  
pp. 8-21 ◽  
Author(s):  
Stuart Paul ◽  
Geoff Whittam ◽  
Janette Wyper

2016 ◽  
Vol 8 (6) ◽  
pp. 181
Author(s):  
George Chang

Daniel and Titman (1995) examined the incentives of firms to signal their values prior to making a new equity offering. By analyzing this issue within a simple framework that encompasses a number of models in the literature, they were able to judge the relative efficiency of various signals that have been proposed. Although their analyses offer valuable insights, the robustness of their model has yet to be checked. This paper examines the parametric assumptions of their model in the section on debt and the pecking order hypothesis. We first generalize the assumptions in the example by Daniel and Titman (1995) to allow for continuous-state of nature. We then derive the resulting closed-form solution for the equilibrium payoffs to the original shareholders of both types firms under different beliefs. Although we only examine the robustness of a particular setting, our methodology can be applied to other settings.


2020 ◽  
Author(s):  
Hayelom Abrha Meressa

Abstract Purpose: The purpose of this study was to examine factors that determine micro and small scale enterprises’ financing preference in line with pecking order theory and access to credit in Benishangul-Gumuz Regional State of Ethiopia.Design / Methodology / Approach: The study used primary data collected using cross sectional survey questionnaire followed by mixed research approach. The sample of this study was 296 enterprises selected using proportional stratified random sampling technique. The data was analyzed using descriptive and logistic regression analysis.Findings: The results of logistic regression analysis revealed that business experience, collateral, gender, motivation and enterprises’ sectoral engagement affect financing preference of enterprises in line with pecking order hypothesis. On the second step, only enterprises that need to raise capital through credit were considered to investigate access to credit determinants. Accordingly, the logistic regression result revealed that business experience, size, sectoral engagement, collateral, interest rate, loan repayment period, financial reporting, preparation of business plan, location and educational background of entrepreneurs affect access to credit of enterprises. Research limitations/Implications: More evidence is needed on enterprises’ financing preference and access to credit determinants before any generalization of the results can be made. In addition, the empirical tests were conducted only on 296 entrepreneurs since 2019. Therefore, the results of the study cannot be assumed to extend beyond this group of entrepreneurs to different study periods.Originality/value: This paper adds value to the literature on the determinants of micro and small scale enterprises’ financing preference in line with pecking order hypothesis and access to credit.


2019 ◽  
Vol 08 (04) ◽  
pp. 200-223
Author(s):  
Dewundara L. Prasath Manjula Rathnasingha ◽  
Chanthun P. Heiyanthuduwa

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