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MODEL REGRESI DATA PANEL UNTUK MENGETAHUI FAKTOR YANG MEMPENGARUHI TINGKAT KEMISKINAN DI PULAU MADURA

*Artanti Indrasetianingsih  -  Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas PGRI Adi Buana Surabaya, Indonesia
Tutik Khalimatul Wasik  -  Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas PGRI Adi Buana Surabaya, Indonesia
Open Access Copyright 2020 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract

Poverty arises when a person or group of people is unable to meet the level of economic prosperity which is considered a minimum requirement of a certain standard of living or poverty is understood as a state of lack of money and goods to ensure survival. Panel data regression is the development of regression analysis which is a combination of time series data and cross section data. Panel data regression is usually used to make observations of data that is examined continuously for several periods. The purpose of this study is to determine the factors that influence the level of poverty in Madura Island in the period 2008 - 2017. In this study the variables used in this study are life expectancy (X1), average length of school (X2), level open unemployment (X3), and labor force participation (X4) with the Comman Effect Model (CEM) approach, Fixed Effect Model and Random Effect Model (REM). To choose the best model from the three is the chow test, the hausman test and the breusch-pagan test. In this study, the best model chosen was the Fixed Effect Model.

 

Keywords: CEM, Fixed Effect Model, Data Panel Regression, REM, Poverty level.

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Keywords: EM, Fixed Effect Model, Data Panel Regression, REM, Poverty level.

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