西苏门答腊岛人类发展指数的地理加权面板回归模型

Amelia Fadila Rahman, Syafriandi, N. Amalita, Zilrahmi
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摘要

人类发展指数(HDI)是一个对西苏门答腊省人类发展和人民福利领域产生负面影响的重要问题。克服人类发展指数问题的一项努力是确定影响因素。地理加权面板回归(GWPR)是一种可以用来识别影响因素和解释观测特征区影响的方法。GWPR是面板数据回归方法与GWR的结合,用于数据存在空间异质性的情况。本研究的目的是形成一个GWPR模型,该模型将应用于2019年至2022年西苏门答腊县/城市的人类发展指数。采用GWPR固定效应模型建模。所使用的加权函数是一个固定的指数核,最小CV为0.00208。结果表明,所得到的模型的准确率为99.9%,即预测变量对模型的解释率为99.9%。对人类发展指数有显著影响的变量是预期寿命、预期受教育年数、平均受教育年数和购买力平价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Geographically Weighted Panel Regression Modeling on Human Development Index in West Sumatra
The Human Development Index (HDI) is an important issue that has a negative impact on the field of human development and people's welfare in West Sumatra Province. An effort to overcome the problem of the HDI is to identify the influencing factors. A method that can be used to identify influencing factors and explain the influence of characteristic areas of observation is Geographically Weighted Panel Regression (GWPR). GWPR is a combination of panel data regression method with GWR which is used when the data has the influence of spatial heterogeneity. The purpose of this study is to form a GWPR model that will be applied to the HDI in Regencies/Cities in West Sumatra from 2019 to 2022. Modeling using GWPR Fixed Effect Model. The weigher function used is a fixed exponential kernel with a minimum CV of 0.00208. The results showed that the model obtained had an  of 99.9%, which means the predictor variable was able to explain the model by 99.9%. Variables that have a significant on HDI are Life Expectancy, Expected Years of Schooling, Mean Years of Schooling, and Purchasing Power Parity.  
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