IDEAS home Printed from https://ideas.repec.org/a/ags/afjecr/281422.html
   My bibliography  Save this article

Does Development Assistance For Health Buy Better Results In Maternal Health in Tanzania? Evidence from Autoregressive Distributed Lag (ARDL) Model

Author

Listed:
  • Byaro, Mwoya
  • Lemnge, Deusdedit A.

Abstract

This paper establishes whether development assistance for health buy better results in maternal health in Tanzania using annual time series data for the period between 1995 and 2014 based on Autoregressive Distributed Lags (ARDL) and Error Correction Model. A long run cointegration relationship exists between GDP per capita, maternal mortality, unemployment and development assistance for health over examined period of time. The results show that in the long run Development Assistance for Health (DAH) and Economic growth (measured by real GDP per capita) was significant in reducing maternal mortality in Tanzania. In the short run, unemployment was statistically significant on increasing maternal mortality in Tanzania between 1995 and 2014. Furthermore, the short run results show that both DAH and real GDP per capita reduces maternal mortality between 1995 and 2014. The results imply that Development Assistance for Health (DAH) channeled to the health sector is an important component in improvements of maternal health in Tanzania. The findings are robust to sensitivity analyses and estimation methods.

Suggested Citation

  • Byaro, Mwoya & Lemnge, Deusdedit A., 2018. "Does Development Assistance For Health Buy Better Results In Maternal Health in Tanzania? Evidence from Autoregressive Distributed Lag (ARDL) Model," African Journal of Economic Review, African Journal of Economic Review, vol. 6(2), July.
  • Handle: RePEc:ags:afjecr:281422
    DOI: 10.22004/ag.econ.281422
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/281422/files/African%20Article%204.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.281422?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Byaro, Mwoya & Pelizzo, Riccardo & Kinyondo, Abel, 2023. "What are the Main Drivers Behind the Acceleration of Tanzania's Economic Growth Over the Past Three Decades?," African Journal of Economic Review, African Journal of Economic Review, vol. 11(4), June.

    More about this item

    Keywords

    Labor and Human Capital;

    Statistics

    Access and download statistics

    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:ags:afjecr:281422. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: AgEcon Search (email available below). General contact details of provider: https://www.ajol.info/index.php/ajer/index .

    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.