Penelitian ini bertujuan untuk mengetahui faktor-faktor penentu pertumbuhan ekonomi di kawasan timur Indonesia setelah pemerintah menerapkan kebijakan otonomi daerah di Indonesia. Penelitian ini meliputi wilayah induk dan wilayah pemekaran pada kawasan timur Indonesia. Penelitian ini menggunakan data sekunder dari statistik Indonesia. Penelitian ini menggunakan data cross-section pada tahun 2017 yang mencakup 230 kabupaten dan kota. Penelitian ini menggunakan least square dummy variable dalam menganalisis data. Analisis menunjukkan bahwa tidak ada perbedaan dalam pertumbuhan ekonomi pada wilayah induk dan wilayah pemekaran. Faktor penentu pertumbuhan ekonomi, yaitu variabel kemiskinan, pembangunan manusia, ketimpangan, dan desentralisasi fiskal menunjukkan hasil yang berbeda di setiap daerah. Pada wilayah induk, variabel kemiskinan, pembangunan manusia, dan desentralisasi fiskal mempengaruhi pertumbuhan ekonomi. Sedangkan pada wilayah pemekaran, hanya variabel pembangunan manusia dan desentralisasi fiskal yang berdampak pada pertumbuhan ekonomi daerah.
Pangan memiliki peranan penting sebagai sumber kebutuhan hidup manusia. Perubahan harga menjadi hal yang umum terjadi pada komoditas pangan dan sebagai penyumbang inflasi. Penelitian ini bertujuan untuk mengetahui pengaruh harga komoditas pangan terhadap inflasi dengan studi kasus harga komoditas cabai merah dan bawang putih di Kota Magelang. Jenis penelitian ini merupakan penelitian kuantitatif. Data yang digunakan dalam penelitian ini adalah data sekunder yang diperoleh dari BPS (Badan Pusat Statistik) kota Magelang dan SiHaTi (Sistem Informasi Harga dan Produksi Komoditi) Provinsi Jawa Tengah periode Januari 2016-Desember 2019. Data yang digunakan merupakan data bulanan yang berjumlah 144 data penelitian. Metode analisis yang digunakan adalah vector autoregression (VAR). Pengolahan data menggunakan software eviews 10 dengan melalui beberapa proses atau tahapan yang ada dalam analisis vector autoregression (VAR) yang meliputi uji stasioneritas data, uji stabilitas VAR, uji lag optimum, uji kointegrasi, estimasi VAR, impulse response function (IRF), dan variance decomposition.Hasil penelitian ini menunjukkan bahwa pada hasil uji vector autoregression (VAR) terdapat pengaruh antara harga cabai merah dan harga bawang putih terhadap inflasi di Kota Magelang.
Pakpak Bharat Regency is an area with the lowest Gross Regional Domestic Product and Income percapita from 33 regency/city in North Sumatera Province. Because of this problem, to be important to know how the base sectors can improve the economy of Pakpak Bharat Regency. In this research, the study aims: (1) To know the base sectors in the economy of Pakpak Bharat Regency (2) To know the sector clasification of Gross Regional Domestic Product (GRDP) in Pakpak Bharat Regency (3) To know how the base sectors effect the Gross Regional Domestic Product of Pakpak Bharat Regency. The data used in this study is secondary data and readings related to research. The tests used in this study are Klassen Typology, Location Quotient, and Least Square test. The research finds that: (1) the economics of Pakpak Bharat Regency is divided into several quadrants, is advanced and rapidly growing sectors (Quadrant I), advanced but depressed sectors (Quadrant II), potential sector (Quadrant III), and lagging sector (Quadrant IV). (2) sectors classified as advanced sectors in Quadrant I and Quadrant II (amounting to 4 sectors) are basic sectors in Pakpak Bharat Regency with LQ>1. (3) there is a positive and significant influence between the base sector on the GRDP of Pakpak Bharat Regency.
ABSTRACT One of the most important aspects in economic development is infrastructure. Adequate and equitable infrastructure in all regions of a country will facilitate economic performer in accessing and carrying out economic activities. A good economic activities will create economic growth. The main purpose of this research is to know the effect of infrastructure on economic growth. The study was conducted in Central Java province using secondary data from 2006-2018. The independent variable of this study is the basic infrastructure including roads, electricity and water. While the dependent variable is the GRDP. The model used is multiple linear regression model using time series data. The results of this study indicate that the road infrastructure variable is significant to influence on economic growth. The variable infrastructure of electricity shows significant results and have a positive effect on economic growth. Variable infrastructure of water shows the results are insignificant on economic growth. Keywords: economic growth, road, electricity, water
Abstrak Cadangan devisa merupakan bagian penting dari perekonomian suatu negara. Besar kecilnya cadangan devisa dapat dipengaruhi oleh nilai ekspor. Tujuan dari penelitian ini yaitu menganalisis pengaruh ekspor, inflasi, BI rate, dan Utang Luar Negeri (ULN) terhadap cadangan devisa, serta menganalisis hubungan kointegrasi antara ekspor, inflasi, BI rate, dan utang luar negeri terhadap cadangan devisa. Penelitian ini menggunakan data sekunder dengan bentuk data time series. Analisis data yang digunakan adalah Error Correction Model (ECM) menggunakan aplikasi Eviews10. Hasil penelitian ini menujukan bahwa yang mempengaruhi cadangan devisa adalah BI Rate dan ULN, serta keseimbangan jangka pendek mempengaruhi keseimbangan jangka panjang. Abstract Foreign exchange reserves are an important part of a country's economy. The size of foreign exchange reserves can be influenced by the value of exports. The purpose of this study is to analyze the effect of exports, inflation, BI rate, and External Debt (ULN) on foreign exchange reserves, as well as analyze the cointegration relationship between exports, inflation, BI rate, and foreign debt on foreign exchange reserves. This study uses secondary data in the form of time series data. Analysis of the data used is the Error Correction Model (ECM) using the Eviews10 application. The results of this study indicate that those that affect foreign exchange reserves are the BI Rate and external debt, and the short-term balance affects the long-term balance.
<p><em>The focus of this research is mapping the pattern and structure of provincial economic growth in Java with the Klassen typology approach, the potential of provincial food commodities in Java with the S</em><em>tatic location quotient (SLQ)- Dynamic location quotient (DLQ) approach, and identifying the level of accessibility of provinces in Java with the Connectivity quotient CQ approach. Food commodities in this case include rice, corn, soybeans, peanuts, green beans, cassava, sweet potatoes. The results show that (1) DKI Jakarta occupies the position of quadrant I; (2) potential rice , corn and mung bean commodity in Central Java Province, , soybean commodity in East Java Province, peanut commodity in DIY, cassava commodity in West Java Province, as well as potential sweet potato commodities in the Provinces of Central Java and East Java; (3) furthermore, the high level of accessibility in four provinces in Java Island and the rest, namely Banten and East Java Provinces are classified as low accessibility levels.</em></p>
Indonesia's poverty condition in March 2019 recorded at 9.41 percent. Supposedly, Indonesia reaches the RPJMN target where the poverty level is planned at a 7-8 percent level. The High levels of rural poverty compared to urban areas exceeded the percentage of national poverty. Low wages are also an indication that the problem of poverty occurs continuously. The purpose of this research is to know how socio-economic variables such as human development, unemployment, wage, and inequality can affect poverty reduction in Indonesia. This research uses secondary data obtained from the website of Statistics Indonesia (BPS) and the Databoks Katadata website. This study uses cross-section data with 34 provincial observations in the year 2019. This research used econometric methodologies with the regression of Ordinary Least Square as an analysis tool. This research show that poverty in Indonesia is still very dominant in the island of Papua, in the provinces of Papua and West Papua and in the island of Nusa Tenggara, in the provinces of West Nusa Tenggara and East Nusa Tenggara. Human development has a negative effect where every human development increase by 1 percent will reduce poverty in Indonesia by 5.69 percent. The declining unemployment rate has contributed to poverty reduction in Indonesia by 0.34 percent. Wages, in this case, can reduce poverty. Increasing wages by 1 percent can reduce poverty by 1.08 percent and vice versa. Reducing inequality by 1 percent can reduce poverty by up to 1.88 percent.Keywords: poverty, HDI, unemployment, wage, inequality
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