J
Joshua Abor
Researcher at University of Ghana
Publications - 169
Citations - 7259
Joshua Abor is an academic researcher from University of Ghana. The author has contributed to research in topics: Debt & Capital structure. The author has an hindex of 36, co-authored 143 publications receiving 6268 citations. Previous affiliations of Joshua Abor include Stellenbosch University.
Papers
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Small Business Reliance on Bank Financing in Ghana
Joshua Abor,Nicholas Biekpe +1 more
TL;DR: In this paper, the determinants of bank financing and debt among Ghanaian SMEs were explored and a panel regression model was used to estimate the relation between the determinant and the bank-debt ratio.
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Technological Innovations and Banking in Ghana: An Evaluation of Customers' Perceptions
TL;DR: In this paper, the authors evaluated the perceptions of banking customers regarding the effect of technological innovations on banking services in Ghana and found that technological innovation or electronic delivery channels have contributed positively to the provision of banking services and the growth of Ghanaian banking industry.
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Exploring the causality links between financial markets and foreign direct investment in Africa
TL;DR: In this article, the causality links between financial markets and foreign direct investment (FDI) in Africa were explored using proxies for the banking sector and stock market to capture financial market development.
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Does corporate governance explain dividend policy in Sub‐Saharan Africa?
Joshua Abor,Vera Ogeh Fiador +1 more
TL;DR: In this paper, the effect of corporate governance on firms' dividend payout policy in sub-Saharan Africa was examined. And the results showed that board composition and board size exhibit significantly positive relationship with dividend payout in Kenya and Ghana, respectively.
Posted Content
What determines the capital structure of listed firms in Ghana
Joshua Abor,Nicholas Biekpe +1 more
TL;DR: In this paper, the determinants of the capital structure of listed firms on the Ghana Stock Exchange during the most recent six-year period were empirically identified using the Ordinary Least Square model.