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We use four alternative prediction models to examine the usefulness of financial ratios in predicting business failure in China. China has unique legislation regarding business failure so it is an interesting laboratory for such a study. Earnings Before Interest and Tax to Total Assets (EBITTA), Earning Per Share (EPS), Total Debt to Total Assets (TDTA), Price to Book (PB), and the Current Ratio (CR), are shown to be significant predictors. Prediction accuracy achieves a range from 78% to 93%. Logit and Neural Network models are shown to be the optimal prediction models.

"We use firm-level data to study corporate performance during the Great Depression era for all industrial firms on the NYSE. Our goal is to identify the factors that contribute to business insolvency and valuation changes during the period 1928 to 1938. We find that firms with more debt and lower bond ratings in 1928 became financially distressed more frequently during the Depression, consistent with the trade-off theory of leverage and the information production role of credit rating agencies. We also document for the first time that firms responded to tax incentives to use debt during the Depression era, but that the extra debt used in response to this tax-driven "debt bias" did not contribute significantly to the occurrence of distress. Finally, we conduct an out of sample test during the recent 2008-2009 Recession and find that higher leverage and lower bond ratings also increased the occurrence of financial distress during this period"--National Bureau of Economic Research web site

Governments and advocacy groups have drawn attention to the precarious position of those members of society who are unable to attain an adequate level of energy services, i.e. the fuel poor. Concerns have also arisen about the ability of fuel poor individuals to adapt to the hardship recently brought about by the COVID-19 pandemic. This paper contributes to the literature by exploring empirically the link between fuel poverty and financial distress prior to and during the first wave the COVID-19 pandemic. The analysis is based on the most recent longitudinal, nationally representative survey of the United Kingdom, Understanding Society (UKHLS, Wave 10, January 2018–February 2020). After correcting for the effects of potential endogeneity in the variables of interest, our results identify a statistically robust relationship between fuel poverty indicators and self-reported measures of current financial distress, with stronger effects for subjective indicators. The fuel poverty indicators however exert only a limited influence on an individual's expectation of their future financial situation. Our analysis of the first wave of the COVID-19 pandemic also confirms that fuel poverty contributed to financial distress. Our main findings are robust to a suite of specification and sensitivity checks. Our results lead to recommend assessing measures which target fuel poverty on the basis of their potential indirect effect on financial distress.

Governments and advocacy groups have drawn attention to the precarious position of those members of society who are unable to attain an adequate level of energy services, i.e. the fuel poor. Concerns have also arisen about the ability of fuel poor individuals to adapt to the hardship recently brought about by the COVID-19 pandemic. This paper contributes to the literature by exploring empirically the link between fuel poverty and financial distress prior to and during the first wave the COVID-19 pandemic. The analysis is based on the most recent longitudinal, nationally representative survey of the United Kingdom, Understanding Society (UKHLS, Wave 10, January 2018–February 2020). After correcting for the effects of potential endogeneity in the variables of interest, our results identify a statistically robust relationship between fuel poverty indicators and self-reported measures of current financial distress, with stronger effects for subjective indicators. The fuel poverty indicators however exert only a limited influence on an individual's expectation of their future financial situation. Our analysis of the first wave of the COVID-19 pandemic also confirms that fuel poverty contributed to financial distress. Our main findings are robust to a suite of specification and sensitivity checks. Our results lead to recommend assessing measures which target fuel poverty on the basis of their potential indirect effect on financial distress.

Governments and advocacy groups have drawn attention to the precarious position of those members of society who are unable to attain an adequate level of energy services, i.e. the fuel poor. Concerns have also arisen about the ability of fuel poor individuals to adapt to the hardship recently brought about by the COVID-19 pandemic. This paper contributes to the literature by exploring empirically the link between fuel poverty and financial distress prior to and during the first wave the COVID-19 pandemic. The analysis is based on the most recent longitudinal, nationally representative survey of the United Kingdom, Understanding Society (UKHLS, Wave 10, January 2018-February 2020). After correcting for the effects of potential endogeneity in the variables of interest, our results identify a statistically robust relationship between fuel poverty indicators and self-reported measures of current financial distress, with stronger effects for subjective indicators. The fuel poverty indicators however exert only a limited influence on an individual's expectation of their future financial situation. Our analysis of the first wave of the COVID-19 pandemic also confirms that fuel poverty contributed to financial distress. Our main findings are robust to a suite of specification and sensitivity checks. Our results lead to recommend assessing measures which target fuel poverty on the basis of their potential indirect effect on financial distress.