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title:
 
Predicting the Risk of Encountering Financial Difficulties by the Example of Estonian Municipalities
publication:
 
icaat-16
part of series:
  Advances in Economics, Business and Management Research
ISBN:
  978-94-6252-261-9
ISSN:
  2352-5428
DOI:
  doi:10.2991/icaat-16.2016.30 (how to use a DOI)
author(s):
 
Pirgit Lohk, Paavo Siimann
corresponding author:
 
Pirgit Lohk
publication date:
 
November 2016
keywords:
 
Municipality, financial difficulties, discriminant analysis, logit
abstract:
 
The objective of the study is to determine the financial and non-financial indicators which describe the financial difficulties encountered by Estonian municipalities and to prepare a model to predict the risk of encountering financial difficulties. In order to achieve the objective, the study employs multidimensional statistical analysis methods: discriminant analysis and logit analysis. The predictive model is based on the financial and non-financial indicators of Estonian municipalities for the years 2004-2014 and the risk of encountering financial difficulties is defined as the value of the variable primary operating outcome to depreciation of tangible fixed assets of the population over the years 2011-2014. The classification accuracy of the discriminant model comprising seven independent variables found as a result of the analysis is 88% and the same indicator for the logit model is 87%. The variable with the highest descriptive capacity in predicting the risk of encountering financial difficulties is the ratio of primary operating outcome to the primary operating revenues. The methods of the study and the predictive model prepared make a significant contribution to the development of this field of study in Estonia and are applicable also to other countries where municipalities operate under similar financial management principles.
copyright:
 
Atlantis Press. This article is distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
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