Abstract

Objectives: This study seeks to investigate the impact of SiLPA budget changes on adjustments in the goods and services budget, with financial distress serving as a moderator in Indonesian district/city governments. Design/method/approach: Employing a quantitative methodology, the sample comprises 42 district/city governments in Indonesia that encountered financial distress and underwent budget changes during the 2019 fiscal year. Hypothesis testing involved multiple linear regression models and Moderated Analysis Regression (MRA), utilizing historical documents data from the Regional Revenue and Expenditure Budget (RREB) -Year Change of 2019, and the Regional Government Financial Report (RGFR) from 2016 to 2018.Results/findings: The multiple linear regression model outcomes indicate that alterations in the SiLPA budget and financial distress collectively influence adjustments in the goods and services budget. Furthermore, MRA results demonstrate that financial distress moderates the impact of SiLPA budget changes on adjustments in the goods and services budget. Theoretical contribution: The application of punctuated equilibrium theory (PET) is proposed as a valuable reference in comprehending regional budget changes. Practical contribution: The study employs a relatively small sample size, as the data is sourced from the 2019 LKPD, considering regional governments with a deficit in the LO for three consecutive years. Additionally, limited secondary data spans only one budget year, and the regression model features only one independent variable, despite previous studies highlighting the multifaceted influences on changes in regional budgets (Abdullah, 2013; Marzalita, et al., 2014; Martunis, et al., 2014; Junita, 2015; Abdullah, et al., 2020).Limitations: The use of small samples occurred because the data used was sourced from LKPD in 2019, with the criteria of local governments experiencing deficits in LO for three consecutive years. Limited secondary data, which is only one budget year. The use of regression models with only one independent variable, while in previous studies it was shown that changes in regional budgets were influenced by many factors (Abdullah, 2013; Marzalita, et al., 2014; Martunis, et al., 2014; Junita, 2015; Abdullah, et al., 2020).

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