Early View Article - Detecting zombie firms in a sample of Finnish small firms

Detecting zombie firms in a sample of Finnish small firms

The objective of the study was to develop a method to detect zombie firms in a sample of mainly very small companies. The original sample consisted of 70,809 active and 134 bankrupt Finnish companies (or firms in insolvency proceedings) for 2018–2020. In the sample firms, the median number of employees was only 2. First, a logistic regression model to measure bankruptcy risk was estimated using three financial ratios as independent variables reflecting profitability, liquidity and solvency. Zombie firms were defined as active companies which are technically bankrupt but are still operating in the market. Second, following this definition, the model was used to assess the bankruptcy risk of active firms, and a zombie company was operationally defined as an active company whose bankruptcy risk exceeds the median for bankrupt companies in three consecutive years. In this way, over 2000 zombie companies were detected making in total 3.5% of the active companies.

Policy Implications

  • Logistic regression analysis is an effective tool for private and public financiers to detect zombie firms which do not add any value.
  • Private and public financiers can develop an efficient model for detecting zombie firms using only financial statement data.
  • Private and public financiers can use the logistic regression model also to detect very small zombie firms usually excluded.
  • Private and public financiers can use the model to detect firms which should not be financed by any financers.
  • Private and public financiers can use the model to detect firms which are misclassified by failure detection models.
  • Private and public financiers can use the model to detect firms which should be filed into bankruptcy.

 

Photo by Paul Theodor Oja