Analisa Kinerja Keuangan 34 Provinsi Indonesia di Tahun 2018

Abstract

Power sharing and delegation is politics in nature. The economic side appears on the regional budget planning and realisation. It is the mechanics and the setting of general policy, priority, and plafond of temporary budget. The latent fiscal gap occurs when revenues collected are lesser than expenditures spent, vice versa. Higher portion of expenditures posted as basic allocation has not been coped well with steady regional income. Supports in terms of better capability and capacity to collect regional revenues appear to be non-existent and meaningless, but the resource-rich regions. Even so, the central government appears to have big and deep impacts on the definition of taxable objects and types, and local retributions. This study is to seek which financial performance indicators that can be well-predicted by a numerous variables and indicators forming the regional budgets (APBD) of 34 provinces in Indonesia in 2018. The data was collected from DJPK website in early May 2019. The research method is quantitative descriptive in nature, and using both the OLS regression and determinant regression analysis. Based on the research of recent studies, a numerous financial performance indicators were derived as dependent variables, along with the variables forming the regional budgets of 34 provinces in Indonesia as independent variables. Sixteen dependent variables were set, whilst the 48 independent variables comprised of 4 groups, that is 4 variables of regional specific (r_#), 23 variables of revenues (y_#), 9 variables of expenditures (c_#), and 12 variables of finance/fiscal (f_#). Upon the results of OLS linear regression, 3 variables of financial performance appeared to be the most significant and appealing than the rest. They were independence (k_08), the ratio of DAU in TKDD to the DAU Formula (k_16), dan decentralisation (k_10). On the contrary, 3 variables of financial performance appeared to have no determining variables. They were PAD growth (k_14), fiscal soundness and regional financial management (k_03), dan effectiveness (k_11). These 3 variables were a part of 4 variables having the least adjusted R2, with infrastructure (k_04) as the remaining one. The heteroscedastic nature that appears in the k_14 estimation equation has suggested that k_14 fails to be used as the benchmark and reference of financial performance of regional budgeting, at least in its definition and operationalisation in this study and research. Likewise the usage of f_07 variable, the fiscal gap 1, the difference of DAU Formula with basic allocation (in basic data source).