Dichotomization of quantitative variables in poverty analysis
It has been proposed four schemes of dichotomization for the four household level quantitative variables – area of land holding, geographic accessibility to the nearest market centre, number of children under 15 and number of literate members of working-age – with justification in the selection of...
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| Format: | Article |
| Language: | English |
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Department of Physics, Mahendra Morang Adarsh Multiple Campus, Tribhuvan University
2022-09-01
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| Series: | Bibechana |
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| Online Access: | https://www.nepjol.info/index.php/BIBECHANA/article/view/46407 |
| _version_ | 1831887681286569984 |
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| author | Krishna Prasad Acharya Shanker Prasad Khanal Devendra Chhetry |
| author_facet | Krishna Prasad Acharya Shanker Prasad Khanal Devendra Chhetry |
| author_sort | Krishna Prasad Acharya |
| collection | DOAJ |
| description |
It has been proposed four schemes of dichotomization for the four household level quantitative variables – area of land holding, geographic accessibility to the nearest market centre, number of children under 15 and number of literate members of working-age – with justification in the selection of threshold value for each variable to dichotomize into disadvantaged and advantaged group of households using the Nepal Living Standard Survey 2010/11 data with 5988 households and 28,670 of their household members. Association of each dichotomized variable with household level poverty status (poor/non-poor) was found highly significant. Finally, the proposed schemes of dichotomization have tested empirically for their ability to differentiate the poor people into two categories - ‘more vulnerable’ and ‘less vulnerable’ - by fist estimating the three measures of poverty – head count index, poverty gap index and squared poverty gap index - of each group of population and comparing the estimated measures between the disadvantaged and advantaged group of populations. Statistical analysis has been performed by using IBM SPSS version 20. To a large extent the proposed schemes of dichotomization have found to differentiate the poor people into two groups; for example, the head count index of the disadvantaged group of the number of children under 15 is 3.1 times higher than that of the advantaged group. The results of this paper are expected to be useful to the policy makers and development planners of Nepal for focusing their poverty reduction program towards the more vulnerable group of population as well as academician.
BIBECHANA 19 (2022) 142-149
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| first_indexed | 2024-04-10T05:27:06Z |
| format | Article |
| id | doaj.art-93eaa71b986e495e97839b72401e998c |
| institution | Directory Open Access Journal |
| issn | 2091-0762 2382-5340 |
| language | English |
| last_indexed | 2025-03-22T00:05:23Z |
| publishDate | 2022-09-01 |
| publisher | Department of Physics, Mahendra Morang Adarsh Multiple Campus, Tribhuvan University |
| record_format | Article |
| series | Bibechana |
| spelling | doaj.art-93eaa71b986e495e97839b72401e998c2024-05-16T13:06:01ZengDepartment of Physics, Mahendra Morang Adarsh Multiple Campus, Tribhuvan UniversityBibechana2091-07622382-53402022-09-01191-210.3126/bibechana.v19i1-2.4640773474Dichotomization of quantitative variables in poverty analysisKrishna Prasad Acharya0Shanker Prasad Khanal1Devendra Chhetry2Central Department of Statistics, Institute of Science and Technology, Tribhuvan University, Kirtipur, NepalCentral Department of Statistics, Institute of Science and Technology, Tribhuvan University, Kirtipur, NepalCentral Department of Statistics, Institute of Science and Technology, Tribhuvan University, Kirtipur, Nepal It has been proposed four schemes of dichotomization for the four household level quantitative variables – area of land holding, geographic accessibility to the nearest market centre, number of children under 15 and number of literate members of working-age – with justification in the selection of threshold value for each variable to dichotomize into disadvantaged and advantaged group of households using the Nepal Living Standard Survey 2010/11 data with 5988 households and 28,670 of their household members. Association of each dichotomized variable with household level poverty status (poor/non-poor) was found highly significant. Finally, the proposed schemes of dichotomization have tested empirically for their ability to differentiate the poor people into two categories - ‘more vulnerable’ and ‘less vulnerable’ - by fist estimating the three measures of poverty – head count index, poverty gap index and squared poverty gap index - of each group of population and comparing the estimated measures between the disadvantaged and advantaged group of populations. Statistical analysis has been performed by using IBM SPSS version 20. To a large extent the proposed schemes of dichotomization have found to differentiate the poor people into two groups; for example, the head count index of the disadvantaged group of the number of children under 15 is 3.1 times higher than that of the advantaged group. The results of this paper are expected to be useful to the policy makers and development planners of Nepal for focusing their poverty reduction program towards the more vulnerable group of population as well as academician. BIBECHANA 19 (2022) 142-149 https://www.nepjol.info/index.php/BIBECHANA/article/view/46407DichotomizationHeadcount indexPoverty gap indexSquare poverty gap indexVulnerable |
| spellingShingle | Krishna Prasad Acharya Shanker Prasad Khanal Devendra Chhetry Dichotomization of quantitative variables in poverty analysis Bibechana Dichotomization Headcount index Poverty gap index Square poverty gap index Vulnerable |
| title | Dichotomization of quantitative variables in poverty analysis |
| title_full | Dichotomization of quantitative variables in poverty analysis |
| title_fullStr | Dichotomization of quantitative variables in poverty analysis |
| title_full_unstemmed | Dichotomization of quantitative variables in poverty analysis |
| title_short | Dichotomization of quantitative variables in poverty analysis |
| title_sort | dichotomization of quantitative variables in poverty analysis |
| topic | Dichotomization Headcount index Poverty gap index Square poverty gap index Vulnerable |
| url | https://www.nepjol.info/index.php/BIBECHANA/article/view/46407 |
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