The Firm’s Trade Credit Risk Taking Process – A Panel Data Probit Estimation, from European Western Countries

PurposeThe purpose of this paper was to investigate the impact of credit risk-taking on financial and social efficiency and examine the relationship between credit risk, capital structure and efficiency in the context of Islamic microfinance institutions (MFIs) compared to their conventional counterparts.Design/methodology/approachThe stochastic frontier approach was used to estimate the financial and social efficiency scores, in a first step. In a second step, the impact of risk-taking on efficiency was evaluated. The authors also took into account the moderating role of capital structure in this effect using the fixed and random effects generalized least squares (GLS) with a first-order autoregressive disturbance. The used dataset covers 326 conventional MFIs and 57 Islamic MFIs in six different regions of the world over the period of 2005–2015.FindingsThe overall average efficiency scores are less than 50%, where CMFIs could have produced their outputs using 48% of their actual inputs. IMFIs record the lowest financial (cost) efficiency that is equal to 28% on average. The estimation results also reveal a negative impact of nonperforming loan on financial and social efficiency. Finally, the moderating effect of leverage funding on the relationship between credit risk-taking and financial efficiency was confirmed in CMFIs. However, leverage seems to moderate the effect of risk-taking behavior on social efficiency for IMFIs.Originality/valueThis paper makes an initial attempt to evaluate the effect of risk-taking decision and its implication on efficiency and MFIs' sustainability. Besides, it takes into consideration the role played by the mode of governance through the ownership structure. In addition, this research study sheds light on the importance of the financial support for the development and sustainability of these institutions, which in return, contributes to a sustainable economic development.

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Relationship between Banks’ Capital and Credit Risk-Taking through Syndicated Loan

Modern Economy ◽

10.4236/me.2015.612123 ◽

2015 ◽

Vol 06 (12) ◽

pp. 1297-1308

Author(s):

Shu Ling Lin ◽

Wei Peng Chen ◽

Jun Lu

Keyword(s):

Credit Risk ◽

Risk Taking ◽

Syndicated Loan

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The Determinants of Banking Performance

International Journal of Finance & Banking Studies (2147-4486) ◽

10.20525/ijfbs.v4i2.215 ◽

2015 ◽

Vol 4 (2) ◽

pp. 21-28

Author(s):

Khalfaoui Hamdi ◽

Moufida Ben Saada

Keyword(s):

Panel Data ◽

Stock Market ◽

Empirical Study ◽

Credit Risk ◽

Banking Sector ◽

Disclosure Of Information ◽

Main Determinants

This paper aims to identify the determinants of performance of the Tunisian banking sector. The results found, following an empirical study using panel data of Tunisian banks listed on the stock market over the period 2000-2013, show that credit risk, liquidity, total assets and disclosure of information relating to credit are the main determinants of banking performance

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Two – Warehouse Inventory System Model for Deteriorating Items Considering Partial Upstream Trade Credit Financing

Asian Research Journal of Mathematics ◽

10.9734/arjom/2021/v17i1130342 ◽

2021 ◽

pp. 69-80

Author(s):

Z. H. Aliyu ◽

B. Sani

Keyword(s):

Sensitivity Analysis ◽

Credit Risk ◽

Trade Credit ◽

Optimal Solution ◽

Inventory System ◽

System Model ◽

Credit Period ◽

Business Transaction ◽

Credit Financing ◽

Relevant Cost

In this study, we developed an inventory system model under two – level trade credit where the supplier considers the retailer as credit risk but the retailer considers the customers as credit worthy. Therefore, the retailer is given a trade credit period on proportion of the goods ordered whenever he/she pays for proportion of the goods immediately after delivery. In the same vein, the retailer passes the same grace to the customers but without attaching any condition as the customers are assumed credit worthy. This partial upstream trade credit is offered to reduce the risk of failure in payment on the business transaction especially that most retailers are involved in bulk orders. The relevant cost functions are determined and a numerical example is given. Sensitivity analysis was carried out to see the effect of changes in parameters on the optimal solution of the model.

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