Factors Determining Trade Credit Dynamics During Crisis: Panel Data Analysis for Macedonian Firms

• Main Authors: F. Deari, V. V. Lakshina
• Format: Article
• Language: Russian
• Published: Government of the Russian Federation, Financial University 2019-05-01
• Series: Финансы: теория и практика
• Subjects: trade credit dynamics; panel data; crisis; macedonia; analysis of variance; fixed effects; random effects; hausman test
• Online Access: https://financetp.fa.ru/jour/article/view/836
• ISSN: 2587-5671; 2587-7089

The study is aimed at determining the factors influencing the trade credits dynamics for twenty three firms registered on the Macedonian Stock Exchange, as well as at checking for crisis effects from 2011 to 2015. The study includes a review of the literature on commercial credit factors; elaborately analyzed descriptive statistics of the collected data and dependent variable variance; tests for unobservable effects and their functional form; evaluation of panel regression and interpretation of the results. The authors have proved that net trade credits for these firms depends mainly on the growth potential of lagging firms and their vulnerability, and the crisis effects are significant only for the latter factor. Moreover, the overall efficiency of firms’ assets and their ability to convert income into cash does not have a significant impact in the crisis and post-crisis periods. The growth opportunities and profitability demonstrate a negative impact, meaning that growing and more profitable firms on average tend to expand and receive more trade credits than counterparties. Profitability has a significant impact on trade credit and the effect is seen during the first year after the crisis. Thus, the dynamics of trade credits of registered Macedonian firms is largely determined by the internal factors of a firm, and not by the external macroeconomic situation. Therefore, better financial management is suggested to improve the trade credit policy. One of the directions for further research is the evaluation of the autoregressive component of the trade credit dynamics, as well as including spatial effects in the regression equation.