Proceedings of the 2nd International Seminar on Science and Technology (ISSTEC 2019)

Modelling of Poverty Percentage Based on Mean Years of Schooling in Indonesia Using Local Linear Estimator

Authors
N Chamidah, M F F Mardianto, E E Limanta, D R Hastuti
Corresponding Author
N Chamidah
Available Online 11 October 2020.
DOI
https://doi.org/10.2991/assehr.k.201010.014How to use a DOI?
Keywords
local linear, mean years of schooling, percentage of poverty
Abstract

The United Nation as an intergovernmental organization confirms a Sustainable Development Goals (SDGs) otherwise known as the Global Goals. Out of the 17 goals, the Indonesian government is mainly focused on eradicating poverty and improving the quality of education. The opportunities for escaping poverty consistently increase with increasing levels of education. Therefore, education is the most important factor regarding poverty reduction. In this paper, we investigate the impact of mean years of schooling (MYS) on the percentage of poverty in Indonesia using local linear estimator of nonparametric regression and compare it with the parametric regression approach. Nonparametric regression is a method for analyzing the relationship between response and predictor variables by assuming no specific form of regression curve. One of the estimators frequently used in nonparametric regression is local linear estimator which is thought to be superior to kernel estimator. This estimator bases on locally fitting a line rather than a constant. Unlike kernel estimator, local linear estimation would have no bias if the true model were linear. In general, local linear estimation removes the bias term from the kernel estimator, which makes it has better behavior near the boundary of the x’s and smaller MSE everywhere. The results show that mean square error (MSE) values are 22.2 for local linear nonparametric regression approach and 41.85 for linear parametric regression approach. It means that local linear nonparametric regression approach is better than the linear parametric regression approach to analyzing the impact of MYS on the percentage of poverty in Indonesia.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Seminar on Science and Technology (ISSTEC 2019)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
11 October 2020
ISBN
978-94-6239-168-0
ISSN
2352-5398
DOI
https://doi.org/10.2991/assehr.k.201010.014How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - N Chamidah
AU  - M F F Mardianto
AU  - E E Limanta
AU  - D R Hastuti
PY  - 2020
DA  - 2020/10/11
TI  - Modelling of Poverty Percentage Based on Mean Years of Schooling in Indonesia Using Local Linear Estimator
BT  - Proceedings of the 2nd International Seminar on Science and Technology (ISSTEC 2019)
PB  - Atlantis Press
SP  - 87
EP  - 91
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.201010.014
DO  - https://doi.org/10.2991/assehr.k.201010.014
ID  - Chamidah2020
ER  -