IDEAS home Printed from https://ideas.repec.org/a/spr/ijlaec/v65y2022i1d10.1007_s41027-022-00361-1.html
   My bibliography  Save this article

Internal Remittances, Household Welfare, Spending Patterns and Labour Supply: A Study from Rural Areas of Hailakhandi District of South Assam

Author

Listed:
  • Sagarika Dey

    (Assam University)

  • Hussain Ahmed Laskar

    (Assam University)

Abstract

This paper uses primary data collected from 325 rural households in one of the remote but densely populated districts of Assam, India, to evaluate the impact of internally generated remittances on household welfare, spending patterns and labour supply decisions of left-behind adult family members. Using selectivity-corrected covariate balancing propensity score matching method and also endogeneity-corrected instrumental variable analysis, the study finds that remittances from kith and kin residing elsewhere in the country serve to increase the monthly per-capita consumption expenditure of rural households and help to lower the level, depth and severity of poverty. Remittances have also been observed to influence household spending patterns with higher proportion of annual expenditure being devoted to food and education by recipient households. In the labour market, remittances are found to give rise to a ‘dependency syndrome’ as adult members belonging to remittance-receiving households were less likely to enter the labour market. However, no significant adverse impact of remittances on labour intensity by employed workers was observed. Remittances were also found to be lowering the probability of workers being engaged as casual daily wage labourers while enhancing the likelihood of salaried employment and agricultural and non-agricultural businesses.

Suggested Citation

  • Sagarika Dey & Hussain Ahmed Laskar, 2022. "Internal Remittances, Household Welfare, Spending Patterns and Labour Supply: A Study from Rural Areas of Hailakhandi District of South Assam," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 65(1), pages 161-184, March.
  • Handle: RePEc:spr:ijlaec:v:65:y:2022:i:1:d:10.1007_s41027-022-00361-1
    DOI: 10.1007/s41027-022-00361-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s41027-022-00361-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s41027-022-00361-1?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. Kosuke Imai & Marc Ratkovic, 2014. "Covariate balancing propensity score," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(1), pages 243-263, January.
    2. World Bank, 2018. "Moving for Prosperity," World Bank Publications - Books, The World Bank Group, number 29806, December.
    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. Noémi Kreif & Richard Grieve & Iván Díaz & David Harrison, 2015. "Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1213-1228, September.
    2. Turner, Alex J. & Fichera, Eleonora & Sutton, Matt, 2021. "The effects of in-utero exposure to influenza on mental health and mortality risk throughout the life-course," Economics & Human Biology, Elsevier, vol. 43(C).
    3. Zichen Deng & Maarten Lindeboom, 2021. "Early-life Famine Exposure, Hunger Recall and Later-life Health," Tinbergen Institute Discussion Papers 21-054/V, Tinbergen Institute.
    4. Baron, Opher & Callen, Jeffrey L. & Segal, Dan, 2023. "Does the bullwhip matter economically? A cross-sectional firm-level analysis," International Journal of Production Economics, Elsevier, vol. 259(C).
    5. Susan Athey & Guido W. Imbens & Stefan Wager, 2018. "Approximate residual balancing: debiased inference of average treatment effects in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 597-623, September.
    6. Mortimer, Duncan & Harris, Anthony & Wijnands, Jasper S. & Stevenson, Mark, 2021. "Persistence or reversal? The micro-effects of time-varying financial penalties," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 72-86.
    7. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
    8. Jaiswal, Sreeja & Balietti, Anca & Schäffer, Daniel, 2023. "Environmental Protection and Labor Market Composition," Working Papers 0736, University of Heidelberg, Department of Economics.
    9. Caloffi, Annalisa & Freo, Marzia & Ghinoi, Stefano & Mariani, Marco & Rossi, Federica, 2022. "Assessing the effects of a deliberate policy mix: The case of technology and innovation advisory services and innovation vouchers," Research Policy, Elsevier, vol. 51(6).
    10. Sourafel Girma & Holger Görg, 2022. "Productivity effects of processing and ordinary export market entry: A time‐varying treatments approach," Review of International Economics, Wiley Blackwell, vol. 30(3), pages 836-853, August.
    11. Meyer, Maximilian & Hulke, Carolin & Kamwi, Jonathan & Kolem, Hannah & Börner, Jan, 2022. "Spatially heterogeneous effects of collective action on environmental dependence in Namibia’s Zambezi region," World Development, Elsevier, vol. 159(C).
    12. Oyenubi, Adeola & Kollamparambil, Umakrishnan, 2023. "Does noncompliance with COVID-19 regulations impact the depressive symptoms of others?," Economic Modelling, Elsevier, vol. 120(C).
    13. Waverly Wei & Maya Petersen & Mark J van der Laan & Zeyu Zheng & Chong Wu & Jingshen Wang, 2023. "Efficient targeted learning of heterogeneous treatment effects for multiple subgroups," Biometrics, The International Biometric Society, vol. 79(3), pages 1934-1946, September.
    14. Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2021. "A unified framework for efficient estimation of general treatment models," Quantitative Economics, Econometric Society, vol. 12(3), pages 779-816, July.
    15. Demircioglu, Mehmet Akif & Vivona, Roberto, 2021. "Depoliticizing the European immigration debate: How to employ public sector innovation to integrate migrants," Research Policy, Elsevier, vol. 50(2).
    16. Plamen Nikolov & Hongjian Wang & Kevin Acker, 2020. "Wage premium of Communist Party membership: Evidence from China," Pacific Economic Review, Wiley Blackwell, vol. 25(3), pages 309-338, August.
    17. Black, Dan A. & Grogger, Jeffrey & Kirchmaier, Tom & Sanders, Koen, 2023. "Criminal charges, risk assessment and violent recidivism in cases of domestic abuse," LSE Research Online Documents on Economics 121374, London School of Economics and Political Science, LSE Library.
    18. Ruoqing Zhu & Ying-Qi Zhao & Guanhua Chen & Shuangge Ma & Hongyu Zhao, 2017. "Greedy outcome weighted tree learning of optimal personalized treatment rules," Biometrics, The International Biometric Society, vol. 73(2), pages 391-400, June.
    19. Defever, Fabrice & Reyes, José-Daniel & Riaño, Alejandro & Varela, Gonzalo, 2020. "All these worlds are yours, except india: The effectiveness of cash subsidies to export in nepal," European Economic Review, Elsevier, vol. 128(C).
    20. Maciej Berȩsewicz & Dagmara Nikulin, 2021. "Estimation of the size of informal employment based on administrative records with non‐ignorable selection mechanism," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 667-690, June.

    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:spr:ijlaec:v:65:y:2022:i:1:d:10.1007_s41027-022-00361-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.