IDEAS home Printed from https://ideas.repec.org/a/eee/ehbiol/v54y2024ics1570677x24000637.html
   My bibliography  Save this article

Health impact evaluation of Aspirational Districts Program in India: Evidence from National Family Health Survey

Author

Listed:
  • Agarwal, Sandip K.
  • Mishra, Shubham

Abstract

The Aspirational District Program (ADP) is a unique initiative of Government of India launched in 2018 that aims to reduce inter-district multidimensional inequality. ADP aims to bring the least developed districts to catch up with the rest of the other districts in the country. The program is comprehensive in its scope as it targets improvement of several key development indicators spanning health and nutrition, education, agriculture and water resources, financial inclusion and skill development and basic infrastructure indicators. Aspirational districts (ADs) are eligible for enhanced funding and priority allocation of various initiatives undertaken by the central and the state governments. Our research estimates the causal impact of ADP on the targeted health and nutrition indicators using a combination of propensity score matching and difference-in-differences (PSM-DID). We use the fourth and fifth rounds of National Family Health Survey (NFHS) data collected in 2015–16 and 2019–21 respectively which serve as the pre and post-treatment data for our analysis. Moreover, we take advantage of the transparent mechanism outlined for the identification of ADs under ADP, which we use for propensity score matching for our PSM-DID. While we observe negative impact of ADP on early initiation of breastfeeding, we believe that the impact is confounded with the effects of Covid-19 since part of NFHS-5 data was collected during the pandemic. However, the negative impact of ADP on early initiation of breastfeeding disappears when we only use pre-covid data (i.e. data for districts from states surveyed before the pandemic). Additionally, using pre-covid data we find a reduction in the prevalence of underweight children younger than 5 years to an extent of 2 to 4 percentage points in ADs as an impact of ADP, which is robust across multiple specification. We do not find evidence of a positive or a negative impact of ADP on any other health and nutrition indicators. Future research efforts should be made towards impact evaluation of all the targeted indicators in order to get a comprehensive unbiased evaluation of ADP.

Suggested Citation

  • Agarwal, Sandip K. & Mishra, Shubham, 2024. "Health impact evaluation of Aspirational Districts Program in India: Evidence from National Family Health Survey," Economics & Human Biology, Elsevier, vol. 54(C).
    • Handle: RePEc:eee:ehbiol:v:54:y:2024:i:c:s1570677x24000637
    DOI: 10.1016/j.ehb.2024.101411
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1570677X24000637
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ehb.2024.101411?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Powell-Jackson, Timothy & Mazumdar, Sumit & Mills, Anne, 2015. "Financial incentives in health: New evidence from India's Janani Suraksha Yojana," Journal of Health Economics, Elsevier, vol. 43(C), pages 154-169.
    2. Alison Andrew & Marcos Vera-Hernández, 2024. "Incentivizing Demand for Supply-Constrained Care: Institutional Birth in India," The Review of Economics and Statistics, MIT Press, vol. 106(1), pages 102-118, January.
    3. Chen, Yuyu & Jin, Ginger Zhe, 2012. "Does health insurance coverage lead to better health and educational outcomes? Evidence from rural China," Journal of Health Economics, Elsevier, vol. 31(1), pages 1-14.
    4. Corsi, Daniel J. & Mejía-Guevara, Iván & Subramanian, S.V., 2016. "Risk factors for chronic undernutrition among children in India: Estimating relative importance, population attributable risk and fractions," Social Science & Medicine, Elsevier, vol. 157(C), pages 165-185.
    5. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    6. Essama-Nssah, B., 2006. "Propensity score matching and policy impact analysis - a demonstration in EViews," Policy Research Working Paper Series 3877, The World Bank.
    7. Suresh Sharma & Vandana Sharma, 2020. "Efficiency Assessment of Maternal health services in the Aspirational Districts of EAG states in India: A Data Envelopment Analysis Approach," IEG Working Papers 412, Institute of Economic Growth.
    8. Natalie Carvalho & Slawa Rokicki, 2019. "The Impact of India’s Janani Suraksha Yojana Conditional Cash Transfer Programme: A Replication Study," Journal of Development Studies, Taylor & Francis Journals, vol. 55(5), pages 989-1006, May.
    9. Rahman, Mohammad Mahbubur & Pallikadavath, Saseendran, 2018. "How much do conditional cash transfers increase the utilization of maternal and child health care services? New evidence from Janani Suraksha Yojana in India," Economics & Human Biology, Elsevier, vol. 31(C), pages 164-183.
    10. Lingguo Cheng & Hong Liu & Ye Zhang & Ke Shen & Yi Zeng, 2015. "The Impact of Health Insurance on Health Outcomes and Spending of the Elderly: Evidence from China's New Cooperative Medical Scheme," Health Economics, John Wiley & Sons, Ltd., vol. 24(6), pages 672-691, June.
    11. Qin Zhou & Qing He & Karen Eggleston & Gordon G Liu, 2022. "Urban-rural health insurance integration in china: impact on health care utilization, financial risk protection, and health status," Applied Economics, Taylor & Francis Journals, vol. 54(22), pages 2491-2509, May.
    12. Parantap Basu & Ritwik Mazumder, 2021. "Regional disparity of covid-19 infections: an investigation using state-level Indian data," Indian Economic Review, Springer, vol. 56(1), pages 215-232, June.
    13. Singh, Shri Kant & Vishwakarma, Deepanjali, 2021. "Spatial heterogeneity in the coverage of full immunization among children in India: Exploring the contribution of immunization card," Children and Youth Services Review, Elsevier, vol. 121(C).
    14. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    15. Hong Wang & Winnie Yip & Licheng Zhang & William C. Hsiao, 2009. "The impact of rural mutual health care on health status: evaluation of a social experiment in rural China," Health Economics, John Wiley & Sons, Ltd., vol. 18(S2), pages 65-82, July.
    16. Baozhong Su & Gatwaza Hategekimana Thierry & Qihui Chen & Qiran Zhao, 2017. "The New Cooperative Medical Scheme and Self-Employment in Rural China," Sustainability, MDPI, vol. 9(2), pages 1-10, February.
    17. Kim, Rockli & Rajpal, Sunil & Joe, William & Corsi, Daniel J. & Sankar, Rajan & Kumar, Alok & Subramanian, S.V., 2019. "Assessing associational strength of 23 correlates of child anthropometric failure: An econometric analysis of the 2015-2016 National Family Health Survey, India," Social Science & Medicine, Elsevier, vol. 238(C), pages 1-1.
    18. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    19. Tanika Chakraborty & Anirban Mukherjee, 2023. "Economic geography of contagion: a study of COVID-19 outbreak in India," Journal of Population Economics, Springer;European Society for Population Economics, vol. 36(2), pages 779-811, April.
    20. Alexis Diamond & Jasjeet S. Sekhon, 2013. "Genetic Matching for Estimating Causal Effects: A General Multivariate Matching Method for Achieving Balance in Observational Studies," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 932-945, July.
    21. Jayanta Kumar Bora & Nandita Saikia, 2018. "Neonatal and under-five mortality rate in Indian districts with reference to Sustainable Development Goal 3: An analysis of the National Family Health Survey of India (NFHS), 2015–2016," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-15, July.
    22. Arndt, Channing & Hussain, M. Azhar & Salvucci, Vincenzo & Østerdal, Lars Peter, 2016. "Effects of food price shocks on child malnutrition: The Mozambican experience 2008/2009," Economics & Human Biology, Elsevier, vol. 22(C), pages 1-13.
    23. Georgina Pujolar & Aida Oliver-Anglès & Ingrid Vargas & María-Luisa Vázquez, 2022. "Changes in Access to Health Services during the COVID-19 Pandemic: A Scoping Review," IJERPH, MDPI, vol. 19(3), pages 1-31, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tulasi Malini Maharatha & Sumirtha Gandhi & Umakant Dash, 2021. "Has the Demand and Supply-side Components of Janani Suraksha Yojana Augmented the Uptake of Maternal Health Care Services among Poor Women in India ? : An Application of Hybrid Matching Technique," BASE University Working Papers 08/2021, BASE University, Bengaluru, India.
    2. Wendimu, Mengistu Assefa & Henningsen, Arne & Gibbon, Peter, 2016. "Sugarcane Outgrowers in Ethiopia: “Forced” to Remain Poor?," World Development, Elsevier, vol. 83(C), pages 84-97.
    3. Lisa Bagnoli, 2017. "Does National Health Insurance Improve Children's Health ?National and Regional Evidence from Ghana," Working Papers ECARES ECARES 2017-03, ULB -- Universite Libre de Bruxelles.
    4. Dettmann, E. & Becker, C. & Schmeißer, C., 2011. "Distance functions for matching in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1942-1960, May.
    5. Fatema, Naureen, 2019. "Can land title reduce low-intensity interhousehold conflict incidences and associated damages in eastern DRC?," World Development, Elsevier, vol. 123(C), pages 1-1.
    6. Loris Guery & Anne Stevenot & Geoffrey T. Wood & Chris Brewster, 2017. "The Impact of Private Equity on Employment: The Consequences of Fund Country of Origin—New Evidence from France," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 56(4), pages 723-750, October.
    7. repec:idb:brikps:259 is not listed on IDEAS
    8. Wagstaff, Adam & Yu, Shengchao, 2007. "Do health sector reforms have their intended impacts?: The World Bank's Health VIII project in Gansu province, China," Journal of Health Economics, Elsevier, vol. 26(3), pages 505-535, May.
    9. Anne Stevenot & Loris Guery & Geoffrey Wood & Chris Brewster, 2018. "Country of Origin Effects and New Financial Actors: Private Equity Investment and Work and Employment Practices of French Firms," British Journal of Industrial Relations, London School of Economics, vol. 56(4), pages 859-881, December.
    10. Phuong Huu Khiem & Yu-Chen Kuo, 2022. "Health insurance reform impact on children’s educational attainment: evidence from Vietnam," Review of Economics of the Household, Springer, vol. 20(4), pages 1255-1285, December.
    11. Enrico Vanino & Stephen Roper & Bettina Becker, 2020. "Knowledge to Money: Assessing the Business Performance Effects of Publicly Funded R&D Grants," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 17(04), pages 20-24, January.
    12. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
    13. Binder, Martin & Coad, Alex, 2013. "“I'm afraid I have bad news for you…” Estimating the impact of different health impairments on subjective well-being," Social Science & Medicine, Elsevier, vol. 87(C), pages 155-167.
    14. Kamdem, Cyrille Bergaly, 2016. "Impact of cocoa farmer field schools on cocoa yield: empirical evidence of cocoa farmers in Cameroon," 2016 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 246388, African Association of Agricultural Economists (AAAE).
    15. Gonzalo Nunez-Chaim & Henry G. Overman & Capucine Riom, 2024. "Does subsidising business advice improve firm performance? Evidence from a large RCT," CEP Discussion Papers dp1977, Centre for Economic Performance, LSE.
    16. Jurate Jaraite-Ka~ukauske and Corrado Di Maria, 2016. "Did the EU ETS Make a Difference? An Empirical Assessment Using Lithuanian Firm-Level Data," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    17. Andrea Ichino & Fabrizia Mealli & Tommaso Nannicini, 2008. "From temporary help jobs to permanent employment: what can we learn from matching estimators and their sensitivity?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 305-327.
    18. Naureen Fatema & Shahriar Kibriya, 2018. "Givers of great dinners know few enemies: The impact of household food sufficiency and food sharing on low intensity interhousehold and community conflict in Eastern Democratic Republic of Congo," HiCN Working Papers 267, Households in Conflict Network.
    19. Matthew A. COLE & Robert R.J. ELLIOTT & OKUBO Toshihiro & Liyun ZHANG, 2017. "The Pollution Outsourcing Hypothesis: An empirical test for Japan," Discussion papers 17096, Research Institute of Economy, Trade and Industry (RIETI).
    20. Eva Crespo-Cebada & Francisco Pedraja-Chaparro & Daniel Santín, 2014. "Does school ownership matter? An unbiased efficiency comparison for regions of Spain," Journal of Productivity Analysis, Springer, vol. 41(1), pages 153-172, February.
    21. Robert J. R. Elliott & Liza Jabbour & Liyun Zhang, 2016. "Firm productivity and importing: Evidence from Chinese manufacturing firms," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 49(3), pages 1086-1124, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ehbiol:v:54:y:2024:i:c:s1570677x24000637. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/622964 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.