中小企业的软硬事实建模:一些国际证据

Massimo Matthias, Michele Giammarino, G. Gabbi
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引用次数: 8

摘要

本文探讨了定量和定性变量的使用在多大程度上可以改善对公司信誉的评估,以及这一结果如何受到各国经济和金融特点的影响。我们强化了定性变量测量来模拟软信息,旨在对微型公司、小型和中型公司进行评分。这项结构性调查涵盖了德国、意大利和英国,样本包括金融危机期间观察到的约1.7万家公司。软事实是在平衡计分卡框架内确定的,以便找出客户、业务流程、学习和成长以及财务前景的影响。我们的研究结果表明,整合软变量的信贷模型优化了风险估计,但估计是针对每个国家的,应该根据每个经济系统的特征进行调整。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling Hard and Soft Facts for Smes: Some International Evidence
This paper asks how well the use of quantitative and qualitative variables can improve the assessment of companies' creditworthiness and how this result can be influenced by the economic and financial peculiarities of countries. We harden qualitative variable measures to model soft information aimed at scoring microfirms, small, and medium‐sized firms. The structural survey covers Germany, Italy, and the UK in a sample of about 17 thousand companies observed during the financial crisis. Soft facts are determined within the balanced scorecard framework in order to find out the impact of customers, business processes, learning and growth, and financial perspectives. Our findings show that credit models integrating soft variables optimize the risk estimation, but estimates are country‐specific and should be tailored to the characteristics of each economic system.
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