The study analyse sigma and beta convergence of provincial government revenues and expenditures in Indonesia (APBD) by using panel data 30 provinces over the period 2000-2012. The variables used in this study consists of real income per capita and the revenues and expenditures variables in the APBD. The study also included a spatial weights matrix to analyse dependency among provinces. Spatial weights matrix used consists of two types of weights, the real income per capita and the geographical distance. Testing for the presence of spatial dependency performed using Moran’s I. The model used in this study are spatial autoregressive model (SAM) and the spatial error model (SEM). The models are estimated using panel least squares, fixed effects, random effects, as well as both GMM first difference (GMM-DIFF) and system GMM (GMM-SYS). Based on sigma convergence approach, the results of the study showed that during the period of 2000-2012 occurred convergence on total revenue, income, tax, fund balance, total spending, employee spending, and goods spending, but not for the real income per capita. Estimation with beta convergence approach conducted on four variables as each sample (in per capita value), namely: total income, tax, total spending, and goods spending. Estimation with beta convergence is done by using additional explanatory variables which include: economic growth, the degree of openness, as well as economic growth. Based on the beta convergence approach, the study results indicate the occurrence of convergence on total income, tax, total spending, and goods spending. Estimates also lead to the conclusion that there are spatial dependencies between provinces either use distance and income per capita weight. Keywords: Sigma and Beta convergence, spatial weights, panel data, revenue and expenditure, the provincial budget (APBD)JEL Classification: H7,R1

This study aims to apply the concept of SWOT combined with Analytic Hierarcy Process (AHP) in the determination of alternative policy or development strategies. The data used in this study are hypothetical data simulated in the SWOT-AHP model. Given that this study is a model simulation, there are several assumptions used before the data is simulated into the SWOT-AHP model. There are three development alternatives assumed in this study: (1) college diversification and differentiation, (2) development of university into polytechnic or D4 or S1, and (3) development of supporting business unit of university. The three alternatives are analyzed by SWOT-AHP approach in order to determine appropriate development alternatives through 32 questions. The result of the study show that the SWOT-AHP model can be used in the determination of alternative college development. In the implementation, the number of respondents, as well as the parties involved need to be adjusted in order to provide optimal result.

This study aims to analyze the quality of economic growth in the Solo Raya, which includes Surakarta, Boyolali, Sragen, Wonogiri, Klaten, Sukoharjo, and Karanganyar and compile a simulation of a composite index of quality economic growth. Quality economic growth is an important aspect in national and regional development. The definition of quality economic growth in this study is economic growth followed by an increase in the welfare aspect of society through the fundamental dimension, social dimension, and welfare dimension. Each dimension has several relevant indicators. To compare the quality of economic growth between regions in Solo Raya, each dimension will be compiled into a composite index after going through the normalization and weighting process. This index was developed from the Mlachila, Tapsoba, and Tapsoba (2014) models. Using 2010-2017 data as a simulation, the results show that Wonogiri Regency has the lowest rank while Sukoharjo Regency has the highest rank and Surakarta has second best rank.

This article aims to analyze the impact of the COVID-19 pandemic on hotel tax revenues in Surakarta City and design an optimization strategy. The analytical tool used to achieve this goal is descriptive statistics to compare the level of hotel tax achievement before and during the covid-19 pandemic. In addition, a quadrant of the problem was mapped using a SWOT analysis. The result is that The performance of tax revenue in Surakarta City has decreased significantly during the Covid-19 pandemic. The main problems as the cause are restrictions on people's movement, fear of contracting the Covid-19 virus, and the cessation of some community businesses. Efforts that need to be made to reverse this impact are by re-collecting data related to the potential for hotel taxes, the use of information technology, and opening up business opportunities by implementing health protocols