IDEAS home Printed from https://ideas.repec.org/a/taf/oaefxx/v10y2022i1p2146631.html
   My bibliography  Save this article

A vector autoregression (VAR) analysis of corruption, economic growth, and foreign direct investment in Ghana

Author

Listed:
  • Randolph Nsor-Ambala
  • Ebenezer Bugri Anarfo

Abstract

The paper investigated the dynamic and causal relationship among corruption, foreign direct investment, and economic growth simultaneously, a largely overlooked area in empirical studies, using a dataset from Ghana. It is among the few studies that explore the confluence of these variables and therefore contributes to understanding the contextual realities of the impact of FDI inflow, an often-prioritised policy choice, on widely used measures of social coherence and welfare. The study employed a vector autoregressive (VAR) estimation approach to empirically explore the relationships among corruption, foreign direct investment, and economic growth. The findings suggest that there is a reverse causality among corruption, foreign direct investment, and economic growth. This indicates that these variables are complementary rather than contradictory. These findings imply that central government and policymakers should not pursue any of these variables as a policy goal, but rather treat them as complements when modelling or formulating economic policies. This means that policies aimed at promoting foreign direct investment will not jeopardize or compromise the control of corruption and economic growth and vice versa.

Suggested Citation

  • Randolph Nsor-Ambala & Ebenezer Bugri Anarfo, 2022. "A vector autoregression (VAR) analysis of corruption, economic growth, and foreign direct investment in Ghana," Cogent Economics & Finance, Taylor & Francis Journals, vol. 10(1), pages 2146631-214, December.
  • Handle: RePEc:taf:oaefxx:v:10:y:2022:i:1:p:2146631
    DOI: 10.1080/23322039.2022.2146631
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23322039.2022.2146631
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/23322039.2022.2146631?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.

    More about this item

    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:taf:oaefxx:v:10:y:2022:i:1:p:2146631. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/OAEF20 .

    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.