Title: Statistical analysis and econometric modelling of the creditworthiness of non-financial companies

Authors: Vladimir I. Malugin; Natalia V. Hryn; Aleksandr Y. Novopoltsev

Addresses: Faculty of Applied Mathematics and Computer Science, Department of Mathematical Modelling and Data Analysis, Belarusian State University, 4, Nezavisimosti avenue, 220030, Minsk, Republic of Belarus ' Department of Mathematical and Information Support of Economic Systems, Yanka Kupala State University of Grodno, 22, Ozhesko Street, 230023, Grodno, Republic of Belarus ' Faculty of Applied Mathematics and Computer Science, Department of Mathematical Modelling and Data Analysis, Belarusian State University, 4, Nezavisimosti avenue, 220030, Minsk, Republic of Belarus

Abstract: This paper describes the results of the application of multivariate statistical analysis and econometric modelling to assess the creditworthiness of non-financial companies on the micro and macro levels. On the basis of company's financial reports data we propose a system of credit measures called 'relative statistical credit ratings' (RSCR), which includes: company ratings (CCR), the branch of the economy ratings (BCR) and the integral indicator of creditworthiness of the national economy (ICI). The proposed methodology is applied to evaluate the creditworthiness of Belarusian companies. Using econometric modelling we examine the dependence of the credit measures BCR and ICI on the major macroeconomic factors of the Belarusian economy. We establish also the relations between the integral output indicators of the national economy and the proposed statistical creditworthiness measures. Economic analysis of the obtained statistical and econometric modelling results indicates the informativeness and the economic significance of the proposed indicators.

Keywords: computational economics; creditworthiness; non-financial companies; relative statistical credit ratings; company credit ratings; branch credit ratings; econometric modelling; cluster analysis; discriminant analysis; ordered logit model; panel data; Markov dependence; Belarus; multivariate statistical analysis; national economy.

DOI: 10.1504/IJCEE.2014.060287

International Journal of Computational Economics and Econometrics, 2014 Vol.4 No.1/2, pp.130 - 147

Received: 31 Jul 2013
Accepted: 18 Oct 2013

Published online: 08 Apr 2014 *

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