Profiling poverty with multivariate adaptive regression splines
Using data from the 2003 Family Income and Expenditure Survey and 2005 Community-based Monitoring System for a city, Multivariate Adaptive Regression Splines (MARS) is used in identifying household poverty correlates in the Philippines. Models produced by MARS are more parsimonious yet contain theor...
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oai:animorepository.dlsu.edu.ph:faculty_research-90252023-02-14T01:07:53Z Profiling poverty with multivariate adaptive regression splines Mina, Christian D. Barrios, Erniel B. Using data from the 2003 Family Income and Expenditure Survey and 2005 Community-based Monitoring System for a city, Multivariate Adaptive Regression Splines (MARS) is used in identifying household poverty correlates in the Philippines. Models produced by MARS are more parsimonious yet contain theoretically and empirically sound set of household poverty correlates and have high accuracy in identifying a poor household. MARS provides a better alternative to logistic regression for a more efficient and effective implementation of a proxy means test in the identification of potential beneficiaries of poverty alleviation programs. 2010-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/8345 Faculty Research Work Animo Repository Poverty—Philippines Community-Based Research |
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De La Salle University |
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De La Salle University Library |
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Asia |
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Philippines Philippines |
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De La Salle University Library |
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DLSU Institutional Repository |
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Poverty—Philippines Community-Based Research |
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Poverty—Philippines Community-Based Research Mina, Christian D. Barrios, Erniel B. Profiling poverty with multivariate adaptive regression splines |
| description |
Using data from the 2003 Family Income and Expenditure Survey and 2005 Community-based Monitoring System for a city, Multivariate Adaptive Regression Splines (MARS) is used in identifying household poverty correlates in the Philippines. Models produced by MARS are more parsimonious yet contain theoretically and empirically sound set of household poverty correlates and have high accuracy in identifying a poor household. MARS provides a better alternative to logistic regression for a more efficient and effective implementation of a proxy means test in the identification of potential beneficiaries of poverty alleviation programs. |
| format |
text |
| author |
Mina, Christian D. Barrios, Erniel B. |
| author_facet |
Mina, Christian D. Barrios, Erniel B. |
| author_sort |
Mina, Christian D. |
| title |
Profiling poverty with multivariate adaptive regression splines |
| title_short |
Profiling poverty with multivariate adaptive regression splines |
| title_full |
Profiling poverty with multivariate adaptive regression splines |
| title_fullStr |
Profiling poverty with multivariate adaptive regression splines |
| title_full_unstemmed |
Profiling poverty with multivariate adaptive regression splines |
| title_sort |
profiling poverty with multivariate adaptive regression splines |
| publisher |
Animo Repository |
| publishDate |
2010 |
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https://animorepository.dlsu.edu.ph/faculty_research/8345 |
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