Data Science for Public Policy Case of Aspirational Districts - - PowerPoint PPT Presentation

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Data Science for Public Policy Case of Aspirational Districts - - PowerPoint PPT Presentation

Data Science for Public Policy Case of Aspirational Districts Program S ( Subu ) V Subramanian, PhD Professor of Population Health and Geography Harvard University A SIAN V ENTURE P HILANTHROPY N ETWORK (AVPN) I NDIA S UMMIT (2018) December 5-6,


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ASIAN VENTURE PHILANTHROPY NETWORK (AVPN) INDIA SUMMIT (2018)

December 5-6, 2018, New Delhi, India

Data Science for Public Policy

Case of Aspirational Districts Program

S (Subu) V Subramanian, PhD

Professor of Population Health and Geography Harvard University

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  • To accelerate progress in human

development indicators, focus on most “lagging” districts is critical

  • Aspirational Districts were identified

based on a composite score of 49 indicators pertaining to 5 domains:

  • Health/Nutrition
  • Education
  • Agriculture/Water Resources
  • Financial Inclusion/Skill Development
  • Infrastructure
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Evidence- Based Perspective High Dimension Data Computing Sciences Statistical Advances Subject Domains

DATA SCIENCE

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Is there a need for fu further prioritization among Aspirational Districts, and by domains?

Transforming Aspirational Districts: A Data Science Lens

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“better-off” Aspirational Districts are improving at a much faster rate than the “worse-off” Aspirational Districts

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substantial overlaps between Aspirational Districts and Other Districts

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§ There is a wide variation among Aspirational Districts that may also be domain-specific, requiring additional prioritization of certain Aspirational Districts over others. § Given, the considerable overlaps between Aspirational Districts and Other Districts should there be a course- correction in the priority list?

Message #1

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How homogeneous are development markers wi within Aspirational District?

Transforming Aspirational Districts: A Data Science Lens

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Mewat, Haryana Vizianagaram, Andhra Pradesh

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§ There is wide variation between-Villages, within- Aspirational Districts, necessitating a greater degree of targeting and precision to program interventions.

Message #2

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What new new d data la layer ers are critically important for strengthening governance frameworks for development?

Transforming Aspirational Districts: A Data Science Lens

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Child Sex Ratio in India: A Village Level View

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“India does not live in its towns but in its villages” (1931)

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Syngeries: Parliamentary Constituencies and Aspirational Districts

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Child Stunting in India: A Parliamentary Constituency View

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§ Units with direct representation (such as Villages, Parliamentary/Assembly Constituencies) needs to be integrated into the policy discourse (and research) that thus far remains concentrated around States and Districts.

Message #3

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Take Home Message

§ Heterogeneity between and within Aspirational Districts needs to be considered for policies to be efficient and equitable. § Routine data collection, monitoring and synthesis related to Gram Panchayat, Assembly and Parliamentary Constituencies are necessary for effective governance and accountability. § Data Science approaches can be usefully applied to: § monitor and assess on-going programs § discover new insights that may necessitate a partial or complete course correction

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Thank You

svsubram@hsph.harvard.edu

Acknowledgments William Joe, Sunil Rajpal, Rakesh Kumar, Rockli Kim, Akshay Swaminathan, Shalini Rudra, Menaka Narayanan, Alok Kumar, R Venkataramanan, and Tata Trusts.