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2019 | 12 | nr 3 | 54--66
Tytuł artykułu

FDI and Poverty Reduction in Botswana: a Multivariate Causality Test

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this study, the causal relationship between foreign direct investment (FDI) inflows and poverty is investigated using Botswana as a case study, 1980 to 2017, using a trivariate causality framework. The main objective of this study is to establish the direction of causality between FDI and poverty. Three proxies of poverty have been used: 1) household consumption expenditures; 2) infant mortality rate and 3) life expectancy. The study uses the ARDLbounds testing approach and ECM-based Granger-causality model in a stepwise fashion to examine this linkage. The empirical results show that the causal relationship between FDI and poverty reduction in Botswana may be sensitive to the proxy used to measure the level of poverty reduction. When infant mortality rate and life expectancy are used as proxies for poverty reduction, a unidirectional causality from FDI to poverty is found to prevail both in the short and in the long run. However, when household consumption expenditure is used as a proxy, no causality is found, irrespective of whether the causality test is conducted in the short or in the long run. On the whole, the study found that Botswana could benefit from FDI inflows in the fight against poverty. (original abstract)
Rocznik
Tom
12
Numer
Strony
54--66
Opis fizyczny
Twórcy
  • University of South Africa, Pretoria, South Africa
  • University of South Africa, Pretoria, South Africa
Bibliografia
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  • Loizides, J., & Vamvoukas, G. (2005). Government expenditure and economic growth: Evidence from trivariate causality testing. Journal of Applied Economics, 8(1), 125-152.
  • Narayan, P. K., & Smyth, R. (2004). Temporal causality and the dynamics of exports, human capital and real income in China. International Journal of Applied Economics, 1(1), 24-45.
  • Narayan, P. K., & Smyth, R. (2008). Energy consumption and real GDP in G7 countries: new evidence from panel cointegration with structural breaks. Energy Economics, 30(5), 2331-2341.
  • Odhiambo, N. M. (2008). Financial depth, savings and economic growth in Kenya: A dynamic causal linkage. Economic Modelling, 25(4), 704-713.
  • Odhiambo, N. M. (2009). Electricity consumption and economic growth in South Africa: A trivariate causality test. Energy Economics, 31(5), 635-640.
  • Odhiambo, N. M. (2009). Energy consumption and economic growth nexus in Tanzania: An ARDL bounds testing approach. Energy policy, 37(2), 617-622.
  • OECD, (2014). OECD Investment Policy Reviews: Botswana 2014. [Online]. Available. [Accessed 6 April 2017].
  • Ogunniyi, M. B., & Igberi, C. O. (2014). The impact of foreign direct investment on poverty reduction in Nigeria. Journal of Economics and Sustainable Development, 5(14), 73-89.
  • Pesaran, M. H., & Shin, Y. (1998). An autoregressive distributed-lag modelling approach to cointegration analysis. Econometric Society Monographs, 31, 371-413.
  • Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of applied econometrics, 16(3), 289-326.
  • Solarin, S. A., & Shahbaz, M. (2013). Trivariate causality between economic growth, urbanisation and electricity consumption in Angola: Cointegration and causality analysis. Energy policy, 60, 876-884.
  • Soumaré, I. (2015). Does FDI improve economic development in North African countries?. Applied Economics, 47(51), 5510-5533.
  • Statistics Botswana, (2013). Botswana Core Welfare Indicators. [Online]. Available from .[Accessed 13 July 2015].
  • United Nations Conference on Trade and Development, (2019). UNCTADstat. [Online]. Available from <https://unctadstats.unctad.org> . [Accessed 20 April 2019].
  • United Nations, (2000). United Nations Millennium Declaration. Ares/55/2. UN General Assembly.
  • United Nations, (2017). Sustainable Development Goals. [Online]. Available from www.un.org/sustainabledevelopment/development-agent. [Accessed 10 April 2017].
  • World Bank, (2019). Development Indicators. [Online]. Available from <http:// www.data.worldbank.org> [Accessed 26 September 2016].
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171566340

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