Application of spatial error model using GMM estimation in impact of education on poverty alleviation in Java, Indonesia

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Ryan Willmanda Januardi
Agung Priyo Utomo


Java Island is the center of development in Indonesia, and yet poverty remains its major problem. The pockets of poverty in Java are often located in urban and rural areas, dominated by productive age group population with low education. Taking into account spatial factors in determining policy, policy efficiency in poverty alleviation can be improved. This paper presents a Spatial Error Model (SEM) approach to determine the impact of education on poverty alleviation in Java. It not only focuses on the specification of empirical models but also in the selection of parameter estimation methods. Most studies use Maximum Likelihood Estimator (MLE) as a parameter estimation method, but in the presence of normality disturbances, MLE is generally biased. The assumption test on the poverty data of Java showed that the model error was not normally distributed and there was spatial autocorrelation on the error terms. In this study we used SEM using Generalized Methods of Moment (GMM) estimation to overcome the biases associated with MLE. Our results indicate that GMM is as efficient as MLE in determining the impact of education on poverty alleviation in Java and robust to non-normality. Education indicators that have significant impact on poverty alleviation are literacy rate, average length of school year, and percentage of high schools and university graduates.

Article Details

Author Biography

Ryan Willmanda Januardi, Sekolah Tinggi Ilmu Statistik

Ryan Willmanda Januardi was born January 5, 1994 in Pasuruan, East Java. He did his undergraduate work at Sekolah Tinggi Ilmu Statistik, Jakarta. He received his Bachelor of Applied Statistics with Honors in Social Statistics in 2016. After college he moved to Wakatobi, Southeast Sulawesi and began working for the Badan Pusat Statistik Kabupaten Wakatobi (Statistcs Wakatobi) as Staff of Official Production Statistics. He is a graphic design instructor at Creative Design STIS 54 and member of KIPMI. His research interests include social statistics, agriculture statistics, and spatial statistics.


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