Modeling employments rate data using ordinal logistic regression

In 2007-2008, there are huge recession occur in employment rate. It is corresponding to a global economic crisis on that had a huge effect on the number of employment people around the world. According to International Labour Organization (ILO), the number of person who has loss their job increased...

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Main Authors: Fitrianto, Anwar, Ab. Ghazab, Maziatul Izati
Format: Article
Published: IDOSI Publications 2014
Online Access:http://psasir.upm.edu.my/id/eprint/34547/
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author Fitrianto, Anwar
Ab. Ghazab, Maziatul Izati
author_facet Fitrianto, Anwar
Ab. Ghazab, Maziatul Izati
author_sort Fitrianto, Anwar
building UPM Institutional Repository
collection Online Access
description In 2007-2008, there are huge recession occur in employment rate. It is corresponding to a global economic crisis on that had a huge effect on the number of employment people around the world. According to International Labour Organization (ILO), the number of person who has loss their job increased from 178 million in 2007 to 197 million in 2012, with a peak of 212 million reached in 2009. In our study, we are interested to use logistic regression analysis to determine the factors which are considered to be a significant contributor to the employment. The logistic regression model was used to build models for nine independent variables which are urban population, inflation rate, literacy rates, health expenditure, spending on education, labour participation rate, agriculture expenditure, health index and human development index.
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publishDate 2014
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spelling upm-345472015-12-16T01:11:18Z http://psasir.upm.edu.my/id/eprint/34547/ Modeling employments rate data using ordinal logistic regression Fitrianto, Anwar Ab. Ghazab, Maziatul Izati In 2007-2008, there are huge recession occur in employment rate. It is corresponding to a global economic crisis on that had a huge effect on the number of employment people around the world. According to International Labour Organization (ILO), the number of person who has loss their job increased from 178 million in 2007 to 197 million in 2012, with a peak of 212 million reached in 2009. In our study, we are interested to use logistic regression analysis to determine the factors which are considered to be a significant contributor to the employment. The logistic regression model was used to build models for nine independent variables which are urban population, inflation rate, literacy rates, health expenditure, spending on education, labour participation rate, agriculture expenditure, health index and human development index. IDOSI Publications 2014 Article NonPeerReviewed Fitrianto, Anwar and Ab. Ghazab, Maziatul Izati (2014) Modeling employments rate data using ordinal logistic regression. Middle-East Journal of Scientific Research, 20 (12). pp. 1715-1720. ISSN 1990-9233; ESSN: 1999-8147 http://www.idosi.org/mejsr/mejsr20%2812%2914.htm 10.5829/idosi.mejsr.2014.20.12.21085
spellingShingle Fitrianto, Anwar
Ab. Ghazab, Maziatul Izati
Modeling employments rate data using ordinal logistic regression
title Modeling employments rate data using ordinal logistic regression
title_full Modeling employments rate data using ordinal logistic regression
title_fullStr Modeling employments rate data using ordinal logistic regression
title_full_unstemmed Modeling employments rate data using ordinal logistic regression
title_short Modeling employments rate data using ordinal logistic regression
title_sort modeling employments rate data using ordinal logistic regression
url http://psasir.upm.edu.my/id/eprint/34547/
http://psasir.upm.edu.my/id/eprint/34547/
http://psasir.upm.edu.my/id/eprint/34547/