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The dynamics of central government funding to regions depend on local investments. In regional autonomy, local governments are encouraged to be more self-reliant from the central government. For regions with high natural resource yields, they will not encounter difficulties in meeting their fiscal needs. Community welfare can be realized through fulfilling basic needs, one of which is infrastructure development. High-quality infrastructure will be able to contribute to further progress in trade, thus enhancing production efficiency. The objective of this research is to analyze the extent of the influence of central government transfer funds, especially the Natural Resource Revenue Sharing Funds (DBH SDA), on local government investments in infrastructure across 508 districts/cities in Indonesia. The method used is dynamic panel regression using the Generalized Method of Moment (GMM) Arellano-Bond approach. This study finds that the role of DBH SDA is still low in infrastructure spending. The role of the central government remains significant in determining infrastructure spending at the district/city level in Indonesia. This indicates that local governments rely more on other sectors in infrastructure investment. By enhancing the role of DBH SDA through technological advancements, it is hoped that the market value of natural resources can be higher through resource downstreaming. This strategy will have broader impacts, as labor needs can be absorbed not only in raw material production activities but also in the processing technology sector. Furthermore, the utilization of natural resources with modern technology can increase extraction efficiency, support sustainable development, and minimize environmental impacts.

This study aims to identify trends in the role of coal and solar energy consumption on climate change through existing and forecasting analysis as new evidence for the sustainable development goals launched by 2030. This research targets countries in the Asia Pacific, especially coal exporters (Indonesia and Australia) and coal importers (China). The basic model uses panel regression as the existing condition, which covers the period 2008-2023. Meanwhile, the forecasting analysis uses the ARIMA method, which covers the period 2024-2030. The findings of existing conditions include coal energy consumption contributing to increasing climate change. Meanwhile, solar energy consumption can reduce climate change. Furthermore, the forecast findings on average are climate change conditions of 5.237 million tons and coal energy consumption of 33,830 exajoules, but on average the annual growth rate is relatively small (0.91 percent for climate change and 1.46 percent for coal energy consumption). Meanwhile, solar energy has also increased with a small quantity of 2.40 exajoules, but the growth rate is relatively high (29.61 percent). This research recommends that the government massively increase the transition of clean energy consumption towards solar so that the mix can dominate for greater reductions in climate change in achieving sustainable development goals.

This study aims to describe the coal downstreaming program which is expected to increase the added value of coal in Indonesia. Increasing the added value of coal such as the gasification project has a strategic role to increase state revenues and foreign exchange and is expected to have implications for increasing development in the region and nationally. The research method used is a quantitative and qualitative approach. The quantitative approach is used the accounting approach and benefit cost analysis (BCA), while the qualitative approach is used in the study of literature and focus group discussions. From the results of the discussions, the Government can provide coal gasification fiscal incentives to pioneering companies with the consideration that this downstreaming program will be able to spur state revenue as well as regional and national economic growth. Besides this downstreaming activities will be able to increase similar activities in Indonesia.

The area of the maize harvest in Banten Province in 2020 was 16,676 ha with a production of 111,903 tons with productivity of 6,71 tons/ha. The objectives of this study are 1) To analyze the existing maize farm in Banten Province, and 2) To analyze the optimization of maize production in Banten Province. The study method used survey methods, with purposive sampling at the farmer level. Methods of data analysis using qualitative and quantitative analysis. The qualitative analysis used descriptive tabulation. Quantitative analysis using Geographic Information System (GIS), B/C ratio analysis and Linear Programming. The results of this study were: 1) The productivity of maize is 5,112 tons/ha, with the plant pattern being paddy - maize – fallow in rice field rainfed. The value of the B/C ratio5.6 it is mean that maize farming is profitable. 2) The optimum value of maize production in Banten Province is 1,533,600 tons of a dry shell, which is obtained from the average productivity of maize in upland areas of 5,112 kg/ha and the optimal planting area of 300,000 ha of upland land. Suggestions for maximizing maize production done by optimizing upland land.

This study will examine the impact of monetary and fiscal policies simultaneously on human development in ASEAN countries. The fiscal policy indicators in this study are through approaches from government spending on education and health. Monetary policy indicators through approaches from bank credit to private and financial system deposits. The results of data processing revealed that the Human Development Index was influenced by monetary policy in the form of bank credit to private, financial system deposits and fiscal policy in the form of spending on health, while fiscal policy related to spending on education has a positive but not significant effect. To achieve these objectives, fiscal and monetary policies must be directed at improving human development. To look at the impact of fiscal policy on human development, it is not only limited to these indicators. Further research can be developed on other indicators, such as infrastructure spending, other social expenditures, and can even be developed in terms of state revenues. as easy as the monetary policy indicator can be expanded. In the context of HDI, monetary policy should be approached from the portion of loans received by micro and medium enterprises.