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Beginning in the mid-1970s, financial distress in local governments became big news when New York City nearly collapsed due to the energy crisis and high inflation. When local governments experience financial distress, the responsibility to provide services to the community both now and in the future cannot be fulfilled. Local governments can only maintain services to the community if they are able to avoid financial distress. If the financial distress condition is maintained, there will be a stagnation in the level of community welfare which will have an impact on regional economic growth because it is not supported by adequate public services. Some local governments like Pennsylvania, have implemented a measure to indicate financial distress as stipulated in the 1987 Financially Distressed City Act (UU 47). However, the local government in Indonesia does not yet have an absolute measure for this financial distress condition. For this reason, financial distress in this study will use a relative measure indicated by the probability value measured using a defined approach. The results of the study provide an overview of how the relevant values in local government financial statements are able to predict financial distress in local governments. The findings show that the variables intergovernmental revenue (IGR), financial independence (FIND), employee expenditure (EMPEX), capital expenditure (CAPEX), and operating position (OPPOS) have a significant effect and can be used as an alternative predictor of financial distress with more comprehensive suitability with the financial characteristics of local government in East Java Province.

This study aims to examine and analyze the effect of financial distress with the Altman and Springate Models on stock returns either directly or indirectly by involving earnings management as a mediation. This study uses secondary data from Textile and Garment Companies listed on the Indonesia Stock Exchange from 2015-2019, with a sample of 20 companies using sampling so that 100 observations are obtained. The data is obtained from the annual financial statements. The data analysis technique used SEM-PLS with the help of WarpPLS 6.0 software. The results of the study provide empirical evidence that financial distress has a positive effect on earnings management, while financial distress and earnings management has a negative effect on stock returns. Earnings management is able to mediate the effect of financial distress on stock returns.