IOSR Journal of Agriculture and Veterinary Science (IOSR-JAVS) e-ISSN: 2319-2380, p-ISSN: 2319-2372. Volume 13, Issue 5 Ser. I (May 2020), PP 01-04 www.iosrjournals.org DOI: 10.9790/2380-1305010104 www.iosrjournals.org 1 | Page Budget Allocations on Economic Sectors to Optimize the Economic Growth: a Case Study of Indonesia’s Southeast Sulawesi Province Laode Geo 1* , Waode Rachma Sari Ariani 2 , Bahriddin Abapihi 3 1 Department of Agrobusiness, Halu Oleo University, Kendari, Indonesia 2 Department of Economics and Development Science, Halu Oleo University, Kendari, Indonesia 3 Department of Statistics, Halu Oleo University, Kendari, Indonesia Abstract: Different economic sectors have certain economic characteristics. Accordingly, they provide distinct effects on economic growth or gross domestic product (GDP). In this paper we attempt to find optimum allocations of limited budget in order to optimize the GDP. Through regression model we calculated the expected contribution of each sector to the GDP and, then, we got the proportion of each sector to allocate. Accordingly, the amount of budget to spend in each economic sector is based on these proportions. The results have shown that,by applying these proportions to dictate the allocation of government spending, the GDP would have beenseven times of the current actual GDP. Keywords: economic growth, gross domestic product (GDP), optimum proportion, budget allocations, regression model --------------------------------------------------------------------------------------------------------------------------------------- Date of Submission: 04-05-2020 Date of Acceptance: 18-05-2020 --------------------------------------------------------------------------------------------------------------------------------------- I. Introduction Every country in the world has the same objective that is to achieve rapidly sustainable economic growth.The economic growth is mostly indicated by the gross domestic product (GDP). The GDP has been the subject of macroeconomics policy in order to increase the economic growth. There are some factors affecting the GDP, such as inflation rate, currency, and government spending. Many authors have been investigating the factors affecting economic growth. Some of them focused on government spending to economic growth or GDP. Seghir et al (2015)studied the effect of spending in tourism on economic growth, while Olayungbo & Olayemi (2018) as well as D’Agostino at al (2016) investigated the relationship between government spending and economic growth. Atems (2019), Facchini & Seghezza (2017), also conducted their work on government spending in an economic sectoron economic growth. From the works of those authors, it is implied that the government spending affects the economic growth.All of their works, however, investigated the government spending on a sectorpartially. None of them discussed nor compared the spending allocation on one sector to another. We know that the effect of an economic sector on economic growth of a country or a province may vary from one to another. Due to the limitation of budget to spend on economic sectors, the government should allocate the spending smartly in an effective way to reach an optimum growth. As a result, the information about the characteristics of sectors on economic growth is needed before allocating the limited government spending. In this paper, we attempt to derive the proportions of government spending to be allocated on economic sectors. By applying these proportions to government spending allocations, it is expected that the economic growth would achieve an optimum level. II. Material and Method Dataset The data is obtained from the Department of Regional Planning and Development, Provincial Government of Southeast Sulawesi, Indonesia. It reports annual budget allocation on 16 economic sectors and their growths during 2010 – 2018. Method Many authors have applied regression model to explain the effects of investment or government spending on economic growth that is indicated by GDP. Among them are M.K. Ardakani, S.M. Sayedaliakbar (2019), I.A. Kirshin et al (2014), Alfada (2019), N.P. Goridko, R.M. Nizhegorodtsev. (2016), M.N. Eris, B. Ulasan. 2013.B-N. Huang, M.J. Hwang, C.W. Yang. 2008. A. Minasyan, J. Zenker, S. Klasen, S. Vollmer. 2019. They have demonstrated how useful the regression models are. In this paper, we also built our models based on regression