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All Journal Jurnal Manajemen dan Agribisnis
Agung Hendriadi
Food Security Agency, Ministry of Agriculture Republic of Indonesia
Agriculture, Biological Sciences & Forestry Economics, Econometrics & Finance

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Analysis of Geographically Weighted Regression (GWR) on Retail Prices of Medium Rice and Red Chili in Java Jan Piter Sinaga; Agung Hendriadi; Muhammad Firdaus; Akhmad Fauzi; Idha Widi Arsanti
Jurnal Manajemen & Agribisnis Vol. 18 No. 2 (2021): JMA Vol. 18 No. 2, July 2021
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jma.18.2.144

Abstract

Research using a global regression model might not be appropriate to find out the factors that influence strategic food prices based on spatial characteristics. To analyze the spatial effect, Geographically Weighted Regression (GWR) was employed. GWR models are better than OLS, which is indicated by the higher R2 GWR and lower AIC values. The GWR analysis provides the following findings: (1) the wholesale price most influential on the retail price of medium rice and red chili both during the main harvest and non-harvest periods; (2) the harvest pattern results in the effect of production and producer prices on the retail prices of the major harvest and non-harvest periods. Management of inter-regional distribution must be carried out to maintain supply stability and disparity in food prices between regions; (3) producer prices are integrated with trader prices in the district of production centers and surrounding areas while the integration of food prices at the consumer level occurs in the main economic center area of the region. These aspects have different effects for each region and district because the estimated parameters can be positive or negative. Testing during the harvest season (April) and non-harvest can also produce estimates that vary according to the specific characteristics of each location. Keywords: spatial analysis, Geographically Weighted Regression (GWR), retail prices, wholesale price, spatial distribution patterns
Co-Authors Akhmad Fauzi Idha Widi Arsanti Jan Piter Sinaga Muhammad Firdaus