# Machine Learning and Zombie Firms Classification
## 2 Prior Literature  
The concept of zombie firms was originally developed to study the economic stagnation in Japan in the late 1990s. [PERSON] and [PERSON] (2005) [10] found that Japanese banks extend credit more to impaired borrowers to avoid the realization of losses. In such situations, other healthy firms cannot gain funds from banks and make fewer investments. Zombie firms can depress market prices through bank support, which distorts market competition, such as through creating strong entry barriers for new and more productive firms; this leads to substantial costs for society. Zombie firms are not only an issue in Japan. After the global financial crisis and the sovereign debt crisis in Europe, zombie firms became a major issue in Europe. [PERSON] et al. (2018) [11] showed that the share of zombie firms had risen since the mid-2000s and reduced the growth of more productive firms. [PERSON] et al. (2024) [12] showed that, after providing zombie credit, which offered subsidized loans to nonviable borrowers, the share of zombies increased, but they were less likely to recover. In addition, the market experienced fewer entries and exits, markups, and inflation, which resulted in a lower productivity and reduced investment. Zombie firms have become an important topic after the COVID-19 pandemic. Many governments implemented several emergency programs to assist firms, such as subsidies, public guarantees on their loans, and tax breaks. These policies were intended to help firms survive without needing to lay off many workers. However, there is a concern that such support programs may have created new zombie firms. [PERSON] et al. (2022) [3] found that firms that were already distressed before the COVID-19 outbreak received support and were assisted to survive. Emergency programs may have created new zombies; thus, zombie firms are still important, even today. [PERSON] (2006) [1] and [PERSON] associated zombie firms with bank lending and intended to identify zombies without a corporate performance measure. They used prime interest rates to calculate the theoretical minimum required interest payments for firm bonds. If a firm's interest payments were lower than this theoretical value, then the authors regarded such firms as zombie firms that received any kind of support from creditors. FN argued that healthy firms pay interest rates lower than the prime lending rates in Japan because of the low policy interest rate and high competition in the bank industry, so the CHK criteria result in an unignorable type I error. To tackle this problem, FN introduced the profitability criteria. The FN criteria fit the trend in the zombie to nonperforming loan ratio of Japanese banks and reflect the more precise economy in Japan. After the FN criteria were introduced, a profitability condition was often used to identify zombie firms. [PERSON] et al. (2018) [11] and [PERSON] and [PERSON] (2018) [13] argued that the interest coverage ratio of zombie firms is less than one for three consecutive years. The interest coverage ratio is usually calculated by dividing the earnings before interest and taxes (EBIT) by the interest expense. Conditioning the consecutive years helps to filter the firms that have no prospect of recovery, rather than a short-term decline in earnings. Using the profitability measure to identify zombies may result in startup firms, which tend to generate less earnings during their growth stage, being classified as zombie firms. To exclude such startups, growth opportunities must also be considered. For example, [PERSON] et al. (2021) [14] defined a firm as a zombie firm if its interest coverage ratio was less than one for three consecutive years and the firm was more than ten years old. [PERSON] and [PERSON] (2018) [13] defined a firm as a zombie firm if its Tobin's q (Tobin's q is the ratio of the market value of a firm's equity and liability to the book value of a firm's equity and liability.