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| Dweepobotee Brahma and Debasri Mukherjee |
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| ''India's Universal Immunization Program: a lesson from Machine Learning'' |
| ( 2019, Vol. 39 No.1 ) |
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| This paper examines the predictors of immunization coverages of children across Indian states and evaluates the role of Universal Immunization Program (UIP) - a comprehensive policy of the Indian government in that light. Employing Machine Learning methods such as LASSO and hierarchical LASSO, we find that not the UIP expenditure by itself, but health infrastructure turns out to be a robust predictor of immunization coverage. The policy prescription that follows from our study is that the immunization program should focus on promoting the required health infrastructure in addition to monitoring the usage of funds closely for facilitating effective usage of the money. We also scrutinize performances of ‘BIMARU', states that are considered traditionally underperforming states in terms of health and education. |
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| Keywords: Immunization in India, Machine Learning, variable selection and shrinkage, LASSO |
JEL: O1 - Economic Development: General
C5 - Econometric Modeling: General |
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| Manuscript Received : Mar 23 2018 | | Manuscript Accepted : Mar 16 2019 |
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