The finance-growth nexus in Botswana: A multivariate causal linkage

Muyambiri, Brian; Chabaefe, Nancy Neoyame Article The finance-growth nexus in Botswana: A multivariate causal linkage Dutch Journal of Finance and Management Provided in Cooperation with: Veritas Publications, London Suggested Citation: Muyambiri, Brian; Chabaefe, Nancy Neoyame (2018) : The finance-growth nexus in Botswana: A multivariate causal linkage, Dutch Journal of Finance and Management, ISSN 2542-4750, Lectito Journals, The Hague, Vol. 2, Iss. 2, pp. 1-6, https://doi.org/10.20897/djfm/2634 This Version is available at: https://hdl.handle.net/10419/308663 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Copyright © 2018 by Author/s and Licensed by Lectito BV, Netherlands. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Dutch Journal of Finance and Management 2018, 2(2), 03 ISSN: 2542-4750 The Finance – Growth Nexus in Botswana: A Multivariate Causal Linkage Brian Muyambiri 1*, Nancy Neoyame Chabaefe 1 1 Botswana Open University, P.Bag BO 187, Bontleng, 0000 Gaborone, BOTSWANA *Corresponding Author: [email protected]om Citation: Muyambiri, B. and Chabaefe, N. N. (2018). The Finance – Growth Nexus in Botswana: A Multivariate Causal Linkage. Dutch Journal of Finance and Management, 2(2), 03. https://doi.org/10.20897/djfm/2634 Published: August 27, 2018 ABSTRACT This paper evaluates the dynamic causal relationship between financial development, savings, investment and economic growth in Botswana from 1976-2014 by employing a multivariate causality model. Results reveal that it is chiefly investment that drives the bank-related and stock exchange-based financial sectors in the short run. Stock exchange-based financial development drives bank-related financial development and savings in both the short run and the long run. While, savings are found to Granger-cause investment. Economic growth Granger-causes investment and savings, both, in the short run and long run. Further, only bank-related financial development is found to Granger-cause economic growth in Botswana. Keywords: financial development, economic growth, multivariate causality, Botswana JEL Codes: E44, G21, O16 INTRODUCTION There is an ongoing argument among scholars concerning the direction of causality between bank-related and stock exchange-based financial development and savings, investment and economic growth. As far as economic growth causality studies are concerned, a considerable number of empirical works have been conducted on a number of countries though with conflicting results (see Nyasha and Odhiambo, 2015; Rehman et al., 2015; Acaravci et al., 2009). There are four views that have been empirically proven to exist in literature, that is, the supply-leading hypothesis, demand-following hypothesis, bidirectional-causality view and the fourth view stipulating that financial development and economic growth have no causal relationship (Nyasha and Odhiambo, 2015). The supply leading hypothesis claims that financial development stimulates economic growth (see Bayar et al. 2014; Masoud, 2013; Nazir et al., 2010; Tachiwou, 2010; Nowbusting and Odit, 2009; Caporale et al., 2004; Boubakari and Jin, 2010), and the demand following hypothesis claims that growth instigates the demand for financial commodities (see Odo et al., 2016; Isu and Okpara, 2013; Carby et al., 2012; Paramati and Gupta, 2011; Baliamoune-Lutz, 2003; Onwumere et al., 2012). The bi-directional causality hypothesis stipulates that financial progression and economic growth are bi-directionally causal while the fourth view states that financial progression has no relationship with economic growth (see Nyasha and Odhiambo, 2015; Acaravci et al., 2009). However, causality studies that focused on the additional variables used in this study have not been as numerous and as widely researched on as the finance-growth nexus. The relationship between financial development and investment is articulated as having four main conclusions by Muyambiri and Odhiambo (2017), that is: a) Financial development Granger-causes investment (Xu, 2000; Caporale et al., 2005, Rousseau and Vuthipadadorn 2005; Chaudry, 2007; Carp, 2012; Hamdi et al., 2013; Asongu, 2014); b) Investment Granger-causes financial development (Odhiambo, 2010); Muyambiri & Chabaefe / The Finance – Growth Nexus in Botswana 2 / 6 © 2018 by Author/s c) There is a bidirectional causality between financial development and investment (Shan et al., 2001; Shan and Jianhong, 2006; Lu et al., 2007; Nazlioglu et al., 2009; Huang, 2011); and d) No causal relationship exists between the two variables (Majid, 2008; Shan and Morris, 2002; Marques et al., 2013). Conversely, most of the studies conducted to evaluate the causal relationship between either of the variables employed in this study, made use of mostly bank-related financial development indicators while ignoring the stock exchange-based side of the financial sector. In addition to the contradictory results that came from such studies, there has been no study to be best of our current knowledge that has sought to investigate the multivariate causal relationship between bank-related financial development, stock exchange-based financial development, savings and investment in one study especially for a country like Botswana1. Given these existing gaps, this study takes advantage of the multivariate causality analysis framework using the autoregressive distributed lag bounds testing approach to assess such a relationship. METHODOLOGY Shadowing Nyasha and Odhiambo (2015), the estimated ARDL model is given as follows. ∆𝐼𝐼𝐼𝐼𝐼𝐼 𝑡𝑡 =∝ 0 +�∝ 1𝑖𝑖 ∆𝐼𝐼𝐼𝐼𝐼𝐼 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�∝ 2𝑖𝑖 ∆𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�∝ 3𝑖𝑖 ∆𝑀𝑀𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�∝ 4𝑖𝑖 ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�∝5𝑖𝑖 ∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +𝛼𝛼6𝐼𝐼𝐼𝐼𝐼𝐼𝑡𝑡−1 +𝛼𝛼7𝐵𝐵𝐵𝐵𝐵𝐵𝑡𝑡−1 +𝛼𝛼8𝑀𝑀𝐵𝐵𝐵𝐵𝑡𝑡−1 +𝛼𝛼9𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−1 +𝛼𝛼10𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−1 +𝜀𝜀1𝑡𝑡 (1) ∆𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡 =𝛽𝛽 0 +�𝛽𝛽 1𝑖𝑖 ∆𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛽𝛽 2𝑖𝑖 ∆𝐼𝐼𝐼𝐼𝐼𝐼 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�𝛽𝛽 3𝑖𝑖 ∆𝑀𝑀𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�𝛽𝛽 4𝑖𝑖 ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�𝛽𝛽5𝑖𝑖∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +𝛽𝛽6𝐵𝐵𝐵𝐵𝐵𝐵𝑡𝑡−1 +𝛽𝛽7𝐼𝐼𝐼𝐼𝐼𝐼𝑡𝑡−1 +𝛽𝛽8𝑀𝑀𝐵𝐵𝐵𝐵𝑡𝑡−1 +𝛽𝛽9𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−1 +𝛽𝛽10𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−1 +𝜀𝜀2𝑡𝑡 (2) ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡 =𝜌𝜌 0 +�𝜌𝜌 1𝑖𝑖 ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝜌𝜌 2𝑖𝑖 ∆𝐼𝐼𝐼𝐼𝐼𝐼 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�𝜌𝜌 3𝑖𝑖 ∆𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�𝜌𝜌 4𝑖𝑖 ∆𝑀𝑀𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�𝜌𝜌5𝑖𝑖∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +𝜌𝜌6𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−1 +𝜌𝜌7𝐵𝐵𝐵𝐵𝐵𝐵𝑡𝑡−1 +𝜌𝜌8𝑀𝑀𝐵𝐵𝐵𝐵𝑡𝑡−1 +𝜌𝜌9𝐼𝐼𝐼𝐼𝐼𝐼𝑡𝑡−1 +𝜌𝜌10𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−1 +𝜀𝜀3𝑡𝑡 (3) ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡 =𝛾𝛾 0 +�𝛾𝛾 1𝑖𝑖 ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛾𝛾 2𝑖𝑖 ∆𝐼𝐼𝐼𝐼𝐼𝐼 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�𝛾𝛾 3𝑖𝑖 ∆𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�𝛾𝛾 4𝑖𝑖 ∆𝑀𝑀𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�𝛾𝛾5𝑖𝑖∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +𝛾𝛾6𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−1 +𝛾𝛾7𝐵𝐵𝐵𝐵𝐵𝐵𝑡𝑡−1 +𝛾𝛾8𝑀𝑀𝐵𝐵𝐵𝐵𝑡𝑡−1 +𝛾𝛾9𝐼𝐼𝐼𝐼𝐼𝐼𝑡𝑡−1 +𝛾𝛾10𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−1 +𝜀𝜀4𝑡𝑡 (4) ∆𝑀𝑀𝐵𝐵𝐵𝐵 𝑡𝑡 =𝛿𝛿 0 +�𝛿𝛿 1𝑖𝑖 ∆𝑀𝑀𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛿𝛿 2𝑖𝑖 ∆𝐼𝐼𝐼𝐼𝐼𝐼 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�𝛿𝛿 3𝑖𝑖 ∆𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�𝛿𝛿 4𝑖𝑖 ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +�𝛿𝛿5𝑖𝑖∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=0 +𝛿𝛿6𝐵𝐵𝐵𝐵𝐵𝐵𝑡𝑡−1 +𝛿𝛿7𝐼𝐼𝐼𝐼𝐼𝐼𝑡𝑡−1 +𝛿𝛿8𝑀𝑀𝐵𝐵𝐵𝐵𝑡𝑡−1 +𝛿𝛿9𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−1 +𝛿𝛿10𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−1 +𝜀𝜀5𝑡𝑡 (5) 1 See Muyambiri and Odhiambo (2015) for a fuller examination of the sequential development of the finance sector in Botswana Dutch Journal of Finance and Management, 2(2), 03 © 2018 by Author/s 3 / 6 The multivariate causality model is then presented as follows: ∆𝐼𝐼𝐼𝐼𝐼𝐼 𝑡𝑡 =𝛼𝛼 0 +�𝛼𝛼 1𝑖𝑖 ∆𝐼𝐼𝐼𝐼𝐼𝐼 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛼𝛼 2𝑖𝑖 ∆𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛼𝛼 3𝑖𝑖 ∆𝑀𝑀𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛼𝛼 4𝑖𝑖 ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛼𝛼5𝑖𝑖∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +𝛼𝛼6𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡−1 +𝜇𝜇1𝑡𝑡 (6) ∆𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡 = 𝛽𝛽 0 +�𝛽𝛽 1𝑖𝑖 ∆𝐼𝐼𝐼𝐼𝐼𝐼 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛽𝛽 2𝑖𝑖 ∆𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛽𝛽 3𝑖𝑖 ∆𝑀𝑀𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛽𝛽 4𝑖𝑖 ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛽𝛽5𝑖𝑖∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +𝛽𝛽6𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡−1 +𝜇𝜇2𝑡𝑡 (7) ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡 = 𝜌𝜌 0 +�𝜌𝜌 1𝑖𝑖 ∆𝐼𝐼𝐼𝐼𝐼𝐼 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝜌𝜌 2𝑖𝑖 ∆𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝜌𝜌 3𝑖𝑖 ∆𝑀𝑀𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝜌𝜌 4𝑖𝑖 ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝜌𝜌5𝑖𝑖∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +𝜌𝜌6𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡−1 +𝜇𝜇3𝑡𝑡 (8) ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡 =𝛾𝛾 0 +�𝛾𝛾 1𝑖𝑖 ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛾𝛾 2𝑖𝑖 ∆𝐼𝐼𝐼𝐼𝐼𝐼 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛾𝛾 3𝑖𝑖 ∆𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛾𝛾 4𝑖𝑖 ∆𝑀𝑀𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛾𝛾5𝑖𝑖∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +𝛾𝛾6𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡−1 +𝜇𝜇4𝑡𝑡 (9) ∆𝑀𝑀𝐵𝐵𝐵𝐵 𝑡𝑡 =𝛿𝛿 0 +�𝛿𝛿 1𝑖𝑖 ∆𝑀𝑀𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛿𝛿 2𝑖𝑖 ∆𝐼𝐼𝐼𝐼𝐼𝐼 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛿𝛿 3𝑖𝑖 ∆𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛿𝛿 4𝑖𝑖 ∆𝐺𝐺𝐺𝐺𝐺𝐺 𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +�𝛿𝛿5𝑖𝑖∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡−𝑖𝑖 𝑛𝑛 𝑖𝑖=1 +𝛿𝛿6𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡−1 +𝜇𝜇5𝑡𝑡 (10) where 𝐼𝐼𝐼𝐼𝐼𝐼 = investment to GDP ratio. 𝐵𝐵𝐵𝐵𝐵𝐵 = accelerator-augmented index of bank-related financial development index, calculated as the meansremoved average (of M3 to GDP, domestic credit to private sector to GDP ratio, and total domestic credit to GDP ratio) multiplied by the growth rate of GDP per capita. 𝑀𝑀𝐵𝐵𝐵𝐵 = accelerator-augmented index of stock exchange-based financial development index, calculated as the means-removed average (of stocks traded, total value to GDP ratio, market capitalisation to GDP ratio, and the turnover ratio) multiplied by the growth rate of GDP per capita. 𝐺𝐺𝐺𝐺𝐺𝐺 = real GDP growth rate. 𝐺𝐺𝐺𝐺𝐺𝐺 = gross domestic savings. 𝐸𝐸𝐸𝐸𝐸𝐸 = error-correction term, ∝0, 𝛽𝛽0, 𝜌𝜌0, 𝛾𝛾0 and 𝛿𝛿0= respective constants, ∝1, … , ∝10, 𝛽𝛽1, … , 𝛽𝛽10, 𝜌𝜌1, … , 𝜌𝜌10, 𝛾𝛾1, … , 𝛾𝛾10 and 𝛿𝛿1,…,𝛿𝛿10=respective coefficients, ∆ = difference operator, 𝑛𝑛 = lag length, 𝜀𝜀 = error term and 𝜇𝜇 = white-noise error-term. EMPRICAL RESULTS Stationarity tests are employed to ensure that all variables are integrated of maximum order 1. Otherwise, the ARDL bounds test methodology will break down if there are variables integrated of an order greater than 1. The Perron (1997) PPURoot unit root and the Augmented Dickey-Fuller Generalised Least Square tests unit root tests Muyambiri & Chabaefe / The Finance – Growth Nexus in Botswana 4 / 6 © 2018 by Author/s were employed to check the order of integration. The results for the test of stationarity of the variables are presented in Table 1. Table 1 confirms that the ARDL bounds testing procedure is appropriate for the data and it is therefore employed. Table 2 reports the results of the bounds F-test for co-integration. The results from the bounds cointegration test indicate that three out of the five equations have a long run relationship. Consequently, the multivariate Granger causality test is run and the results are reported in Table 3. The equations with a cointegrated relationship are estimated, as expected, with the inclusion of an error correction term. Otherwise, no error correction term is included. The empirical results of the multivariate Granger causality test are reported in Table 3. The results in Table 3 reveal that they are only unidirectional causal relationships amongst a number of the variables under discussion. Economic growth is found to Granger-cause investment and savings both in the shortrun and long run. Only bank-related financial development is found to Granger-cause economic growth in Botswana in the short run. Inherently, investment, according to the results, precedes financial development. However, there is only a shortrun unidirectional causal relationship from investment to stock exchange-based financial development. The same unidirectional relationship in both the short run and the long run is found from investment to bank-related financial development. Therefore, consistent with Odhiambo (2010), the results show that it is chiefly investment that drives Table 1. Stationarity Test Results DICKEY-FULLER GENERALISED LEAST SQUARE (DF-GLS) Variable Stationarity in levels Stationarity in differences With intercept, no trend With intercept and trend With intercept, no trend With intercept and trend INV -2.7471* -2.7773 -6.2222*** -6.2291*** GDP -4.5213 *** -5.4507 *** - - BFA -1.7833* -2.0434 -9.9352*** -11.0932*** MFA -4.0963** -4.9413* - - GDS -2.1037** -2.5491 -5.5152*** -5.5653*** Perron (1997) PPURoot Variable Stationarity in levels Stationarity in differences INV -6.3488*** -6.6408*** - - GDP -6.3130*** -6.2841*** - - BFA -6.4923*** -7.0091** - - MFA -5.6991* -5.1882 -6.7414*** -6.4492*** GDS -4.0141 -4.3253 -6.3954*** -6.2451*** Note: *, ** and *** denote stationarity at the 10%, 5% and 1% significance levels respectively Table 2. Bounds F-Test for Cointegration Results Dependent Variable Function F-statistic Cointegration Status INV F(INV| GDP, BFA, MFA, GDS) 5.1612*** Cointegrated BFA F(BFA| GDP, INV, MFA, GDS) 6.5637*** Cointegrated MFA F(MFA| GDP, BFA, INV, GDS) 1.0799 Not cointegrated GDP F(GDP| INV, BFA, MFA, GDS) 3.3418 Not cointegrated GDS F(GDS| GDP, BFA, MFA, INV) 3.8044* Cointegrated Asymptotic Critical 1% 5% 10% Pesaran et al. (2001:301) Table CI(iii) Case III I(0) I(1) I(0) I(1) I(0) I(1) 3.74 5.06 2.86 4.01 2.45 3.52 Note: *, ** and *** denotes significance at the 10%, 5% and 1% significance levels respectively Table 3. Granger-Causality Test Results Investment (I), Bank-related Financial Development (BG), and Savings (S) Dependent Variable F-statistics (probability) 𝑬𝑬𝑬𝑬𝑬𝑬𝒕𝒕 [t-statistics] ∆𝐼𝐼𝐼𝐼𝐼𝐼𝑡𝑡 ∆𝐵𝐵𝐵𝐵𝐵𝐵𝑡𝑡 ∆𝑀𝑀𝐵𝐵𝐵𝐵𝑡𝑡 ∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡 ∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡 ∆𝐼𝐼𝐼𝐼𝐼𝐼𝑡𝑡 - 1.0580 (0.387) 1.7160 (0.234) 4.6903** (0.040) 4.1479* (0.053) -0.83473** [-3.1077] ∆𝐵𝐵𝐵𝐵𝐵𝐵𝑡𝑡 4.1163** (0.044) - 9.4632** (0.010) 0.61525 (0.557) 0.0060698 (0.939) -0.19494* [-1.7746] ∆𝑀𝑀𝐵𝐵𝐵𝐵𝑡𝑡 7.2592** (0.011) 0.15822 (0.856) 0.96271 (0.415) 0.55967 (0.588) ∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡 2.0094 (0.190) 3.4138* (0.066) 1.2810 (0.324) 2.4408 (0.131) ∆𝐺𝐺𝐺𝐺𝐺𝐺𝑡𝑡 0.75629 (0.407) 1.6111 (0.251) 3.8186* (0.082) 6.3678** (0.019) - -0.88920*** [-4.2538] Note: *, ** and *** denotes significance at the 10%, 5% and 1% significance levels, respectively Dutch Journal of Finance and Management, 2(2), 03 © 2018 by Author/s 5 / 6 the bank-related and stock exchange-based financial sectors. To induce financial sector development, there is need to put in place policies that encourage increased investment. Nevertheless, investment is found to be Grangercaused by economic growth and savings in both the long run and the short run in Botswana. Notwithstanding that stock exchange-based financial development is Granger-caused by only investment, it precedes both bank-related financial development and savings in both the short run and the long run. As already noted, investment and stock exchange-based financial development Granger-cause bank-related financial development in the short run and long run. The only variable that is Granger-caused by bank-related financial development is economic growth and this is only in the short run. This finding tends to confirm the findings of Bayar et al., 2014; Masoud, 2013; Nazir et al., 2010; Tachiwou, 2010; Nowbusting and Odit, 2009; Caporale et al., 2004; and Boubakari and Jin, 2010. Savings Granger-cause investment in both the long run and the short run. Stock exchange-based financial development and economic growth Granger-cause savings in both the short run and the long run. Table 4 summarises the results of the Granger-causality tests. CONCLUSION In this paper, the causal relationship between financial development, split into bank-related and stock exchangebased financial development, savings, and investment and economic growth has been empirically examined for the period of 1976 to 2014 for Botswana with the aid of a multivariate Granger-causality model. The study results show that it is chiefly investment that drives the bank-related and stock exchange-based financial sectors in the short run. However, the same deduction is true for bank-related financial development in the long run. Inherently, results also show that stock exchange-based financial development drives bank-related financial development and savings in both the short run and the long run. While, savings are found to Granger-cause investment. Economic growth is found to Granger-cause investment and savings both in the short-run and long run. Only bank-related financial development is found to Granger-cause economic growth in Botswana. Therefore, to induce financial sector development in the short run, there is need to put in place policies that encourage increased investment. These must focus on the economic growth and savings that have been found to precede investment as per the results of this study. REFERENCES Acaravci, S. K., Ozturk, I. and Acaravci, A. (2009). Financial development and economic growth: Literature survey and empirical evidence from Sub-Saharan African countries. South African Journal of Economic and Management Sciences, 12(1), 11-27. https://doi.org/10.4102/sajems.v12i1.258 Baliamoune-Lutz, M. (2003). Financial liberalization and economic growth in Morocco: a test of the supply-leading hypothesis. Journal of Business in Developing Nations, 7, 31-50. Bayar, Y., Kaya, A. and Yildirim, M. (2014). Effects of stock market development on economic growth: Evidence from Turkey. International Journal of Financial Research, 5(1), 93-100. https://doi.org/10.5430/ijfr.v5n1p93 Boubakari, A. and Jin, D. (2010). The role of Stock Market Development in Economic Growth: Evidence from some Euronext Countries, International Journal of Financial Research, 1(1), 14-20. https://doi.org/10.5430/ijfr.v1n1p14 Caporale, G. M., Howells, P. G. and Soliman, A. M. (2004). Stock market development and economic growth: the causal linkage. Journal of economic development, 29(1), 33-50. Table 4. Summary of Granger-causality test results DEPENDENT VARIABLE DIRECTION OF CAUSALITY AND SIGNIFICANT VARIABLES PERIOD OF CAUSALITY Short Run Long Run GDP ⇒INV, GDS ✔ ✔ INV ⇒BFA ✔ ✔ ⇒MFA ✔ - MFA ⇒BFA ✔ ✔ ⇒GDS ✔ ✔ BFA ⇒GDP ✔ - GDS ⇒INV ✔ ✔ NB: GDP=Economic growth, GDS=Savings, INV=investment; BFA=bank -related financial development; MFA=stock exchangebased financial development, ⇒indicates direction of causality, ✔indicates presence of causality in respective period. Muyambiri & Chabaefe / The Finance – Growth Nexus in Botswana 6 / 6 © 2018 by Author/s Carby, Y., Craigwell, R., Wright, A. and Wood, A. (2012). Finance and growth causality: A test of the Patrick's stage-of-development hypothesis. International Journal of Business and Social Science, 3(21), 129-139. Isu, H. O. and Okpara, G. C. (2013). Does Financial Deepening Follow Supply Leading on Demand Following Hypothesis? A look at the Nigerian Evidence. Asian Journal of Science and Technology, 5(1), 10-15. Masoud, N. M. (2013). The impact of stock market performance upon economic growth. International Journal of Economics and Financial Issues, 3(4), 788-798. Muyambiri, B and Odhiambo. M. N. (2017). The casual relationship between financial development and investment in Botswana. UNISA Economic Research Working Paper Series, Working Paper 09/2017, 1-31. Muyambiri, B. and Odhiambo, N. M. (2015). The evolution of the financial system in Botswana. African Journal of Business and Economic Research, 10(2-3), 87-113. Nazir, M. S., Nawaz, M. M. and Gilani, U. J. (2010). Relationship between economic growth and stock market development. African Journal of Business Management, 4(16), 3473-3479. Nowbusting, B. M. and Odit, M. P. (2009). Stock market development and economic growth: The case of Mauritius. International Business & Economics Research Journal (IBER), 8(2), 77-88. Nyasha, S. and Odhiambo, N. M. (2015). Banks, stock market development and economic growth in South Africa: a multivariate causal linkage. Applied Economics Letters, 22(18), 1480-1485. https://doi.org/10.1080/13504851.2015.1042132 Odo, S. I., Ogbonna, B.C., Agbi, P. E. and Anoke, C. I. (2016). Investigating the causal relationship between Financial Development and Economic Growth in Nigeria and South Africa. Journal of Economics and Finance, 7(2), 75-81. Onwumere, J. U. J., Ibe, I. G., Okafor, R. G. and Uche, U. B. (2012). Stock Market and Economic Growth in Nigeria: Evidence from the Demand-Following Hypothesis. European Journal of Business and Management, 4(19), 1-9. Paramati, S. R., and Gupta, R. (2011). An empirical analysis of stock market performance and economic growth: evidence from India, International Research Journal of Finance and Economics, 73, 133-149. Perron, P. (1997). Further evidence on breaking trend functions in macroeconomic variables. Journal of econometrics, 80(2), 355-385. https://doi.org/10.1016/S0304-4076(97)00049-3 Pesaran, M. H., Shin, Y. and Smith, R. (2001). Bound testing approaches to the analysis of level relationship. Journal of Applied Econometrics, 16(3), 289-326. https://doi.org/10.1002/jae.616 Rehman, M. Z., Ali, N. and Nasir, N. M. (2015). Linkage between Financial Development, Trade Openness and Economic Growth: Evidence from Saudi Arabia. Journal of Applied Finance & Banking, 5(6), 127-141. Tachiwou, A. M. (2010). Stock market development and economic growth: the case of West African monetary union. International Journal of Economics and Finance, 2(3), 97-103. https://doi.org/10.5539/ijef.v2n3p97