Influence of age on selected parameters of insolvent companies


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It is natural for the market economy that companies are forced to leave the market when they are not able to survive anymore. This paper is focused on the age structure of the companies in default. The age is considered a period between corporate establishment and insolvency declaration. The paper analyzes whether companies, which report financial accounting statements, have different age structure than non-reporting entities. Data sample consists of 212 companies (147 reporting and 65 non-reporting entities). Moreover, the analysis points out if corporate financial standing differ according to the age structure observed. Using descriptive statistics tools, the observed relationship between the company age and the frequency of insolvency cases is expressed. The evaluation of the financial standing is based on a ratio analysis. Indicators such as return on assets, return on sales, debt ratio, cash and non-cash liquidity, and asset turnover are applied. The results show there are not significant differences in the age structure between the reporting and non-reporting enterprises. Values of financial indicators seem to be independent on the age structure. The paper provides explanations and brings a classification of specific differences observed such as a distinction between reasons due to sector specificities and partly due to the specifics of the current business environment in the Czech Republic (monitored period 2014 – first quarter 2019).

The authors are thankful to the Grant Agency of Academic Alliance (renamed the Grant Agency Academia Aurea) No. GAAA 10/2018 “Financial characteristics of enterprise in bankruptcy” for financial support to carry out this research.

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    • Figure 1. Age structure observed
    • Figure 2. Trends modelled by 5-year moving average
    • Figure 3. Value of total enterprise assets (measured in thousand CZK)
    • Figure 4. Value of enterprise EBITDA (measured in thousand CZK)
    • Table 1. Data sample structure
    • Table 2. Median of selected financial indicators
    • Conceptualization
      Dagmar Camska, Hana Scholleova
    • Data curation
      Dagmar Camska
    • Funding acquisition
      Dagmar Camska
    • Methodology
      Dagmar Camska
    • Project administration
      Dagmar Camska
    • Writing – original draft
      Dagmar Camska
    • Writing – review & editing
      Dagmar Camska, Jiri Klecka
    • Formal Analysis
      Jiri Klecka, Hana Scholleova
    • Investigation
      Jiri Klecka
    • Validation
      Jiri Klecka
    • Visualization
      Jiri Klecka, Hana Scholleova
    • Supervision
      Hana Scholleova