Abstract
Financial inclusion programs in Asia began to intensify with focus on improving public access, especially those who have not yet enjoyed banking services. This makes financial inclusion one of the focuses of development in the financial sector in various countries, especially ASEAN, as a sound financial system can promote economic growth. This study aims to see the comparison of financial inclusion rates and see the effect of socio-economic variables on financial inclusion in ASEAN countries 2010-2015. In order to see the comparison of inclusion level of finance in each ASEAN country, the Index of Financial Inclusion (IFI) method was developed by Sarma (2008), while to examine the relationship between socio-economic variables to financial inclusion, the Ordinary Least Square (OLS) method was used estimation techniques in the Random Effects Model approach. The results show that in general, financial inclusion in ASEAN countries is mainly influenced by the dimension of a disorder. In addition, only per-capita GDP variables are not significant partially. While other variables, namely population over 15 years, unemployment rate, and the number of people in rural areas have a significant influence on index of financial inclusion
Highlights
The purpose of this research is to analyze the influence of grain producer price, corn producer price, rice harvested area and grain producer price of the previous year to rice supply in North Sumatera province simultaneously and partially
The analysis model used multiple linear regression analysis using secondary data in 1985 s.d. 2015 sourced from Badan Pusat Statistik (BPS) North Sumatra
Analisis Penawaran Beras Dalam Upaya Ketahanan Pangan Di Jawa Timur 1988·2000
Summary
Penelitian ini memfokuskan kepada masalah penawaran beras Provinsi Sumatera Utara yang mencakup beberapa faktor seperti; harga produsen gabah, harga produsen jagung, luas panen padi, dan harga produsen gabah tahun sebelumnya terhadap penawaran beras di Provinsi Sumatera Utara. Adapun fungsi fungsi yang digunakan dalam penelitian ini adalah: Dari persamaan 1, mengingat karakteristik variabel bebas data yang sangat rentan terhadap penyimpangan asumsi klasik yakni permasalahan multikolineariti data, maka data penelitian ditransformasi ke dalam First Difference (d) dengan spesifikasi model sebagai berikut: Di mana: PB = Penawaran Beras (Kg) HPG = Harga Produsen Gabah (Rp/kg) HPJ = Harga Produsen Jagung (Rp/kg) LPP = Luas Panen Padi (Hektar) HPGt-1 = HPG Tahun Sebelumnya (Rp/Kg) d = First Difference βo = Konstanta β1-β4 = Koefisien regresi e = Variabel gangguan (error term). Harga produsen gabah tahun sebelumnya adalah rata-rata harga produsen gabah tahun sebelumnya di provinsi Sumatera Utara dalam kurun waktu satu tahun (Rp/Kg)
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