POVERTY PANEL DATA MODELING IN SOUTH SUMATERA

  • Nurul Hidayati Statistics Study Program, Faculty of Mathematics and Natural Sciences, Bengkulu University, Indonesia
  • Herlin Fransiska Statistics Study Program, Faculty of Mathematics and Natural Sciences, Bengkulu University, Indonesia
  • Winalia Agwil Statistics Study Program, Faculty of Mathematics and Natural Sciences, Bengkulu University, Indonesia
DOI: https://doi.org/10.30598/barekengvol17iss3pp1203-1214
Keywords: Fixed Effect Model (FEM), Panel Data, Poverty, Southern Sumatra

Abstract

Poverty is still a major problem on Sumatra's island, despite abundant natural resources potential, such as mining and plantation products. Sumatra Island consists of 10 provinces divided into three regions: Northern Sumatra, Central Sumatra, and Southern Sumatra. The island of Sumatra has the highest number of poor people in the Southern Sumatra region, which reaches 2.88 million people. Poverty is an integrated concept with five dimensions: poverty, powerlessness, vulnerability to emergencies, dependency, and alienation, both geographically and sociologically. One method that can be used to analyze poverty data problems is panel data regression analysis, which combines two data, namely cross-sectional data and time series data. It is expected to produce more in-depth and comprehensive information, both the interrelationships between the variables and their development within a certain period. The panel data was related to poverty and included 60 districts in the southern Sumatra region from 2018 to 2020. This study aimed to model poverty panel data in Southern Sumatra. Three estimation methods were used in the panel data regression, including the Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM. The results of the model specification test show that the best model for estimating the percentage of poor people in the Southern Sumatra region is the Fixed Effect Model (FEM), with a value of R2 = 75.57%. The results of the significance test show that the variables that significantly influence the percentage of poverty in the Southern Sumatra region using the FEM model are the open unemployment rate (), life expectancy (), and the average length of schooling ().

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Published
2023-09-30
How to Cite
[1]
N. Hidayati, H. Fransiska, and W. Agwil, “POVERTY PANEL DATA MODELING IN SOUTH SUMATERA”, BAREKENG: J. Math. & App., vol. 17, no. 3, pp. 1203-1214, Sep. 2023.
Issue
Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Section
Articles

Copyright (c) 2023 Nurul Hidayati, Herlin Fransiska, Winalia Agwil

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