Re-examine foreign direct investment and economic growth: Panel co-integration and causality tests for sub-Saharan African countries

Akinlo, Taiwo; Olayemi, Simon-Oke O.

doi:10.1177/2233865914554469

Cited by 7 publications

(7 citation statements)

References 24 publications

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“…Panel unit root tests: In line with Taiwo and Olayemi (2015), the panel unit root tests for the current study include Fisher-tests using Philips-Perron (PP), Levin et al (2002), Augmented Dickey-Fuller (ADF) and Im et al (2003) -see Table 4. The tests followed an autoregressive-based general model (equation 4) as enunciated by Taiwo and Olayemi (2015, p. 78).…”

Section: Variables Theory Intuition and The Direction Of The Causality Relationshipmentioning

confidence: 99%

Infrastructure, Human Capital Development and Economic Growth in Transitional Countries

Tsaurai

Ndou

2019

CER

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This study investigated the impact of infrastructure and human capital development on economic growth in transitional economies. It also explored whether the interaction between infrastructural and human capital development enhanced economic growth in the transitional economies. Although the literature is awash with studies which investigated the separate impact of infrastructure and human capital development on economic growth, no study that the author is aware of has so far explored whether the interaction between infrastructure and human capital development enhances economic growth. The study mainly used a dynamic panel generalised methods of moments (GMM) approach by Arellano and Bond (1995), a framework that takes into account the dynamic nature of economic growth data and addresses the endogeneity issues normally associated with economic growth regression functions. Panel data analysis approaches such as pooled ordinary least squares (OLS), and fixed and random effects were used for comparison purposes and robustness tests. According to the dynamic GMM framework, the interaction between infrastructure and human capital development improved economic growth in transitional economies, in line with theoretical and empirical predictions. Random effects and pooled OLS show that the interaction between infrastructural and human capital development had a deleterious effect on economic growth, whilst according to the fixed effects approach, the interaction between these two variables had an insignificant positive influence on economic growth in transitional economies. Considering that the results from a dy34 Kunofiwa Tsaurai, Adam Ndou namic panel GMM are considered to be more accurate due to the approach’s ability to address the endogeneity problem and the dynamic nature of economic growth data, the current study recommends that transitional economies should implement policies that improve human capital development in order to enhance infrastructural development’s ability to influence economic growth. Future studies should investigate not just one (human capital development), but all the conditional factors which must be in place before economic growth advantages triggered by infrastructure development are realised.

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Section: Variables Theory Intuition and The Direction Of The Causality Relationshipmentioning

confidence: 99%

Infrastructure, Human Capital Development and Economic Growth in Transitional Countries

Tsaurai

Ndou

2019

CER

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“…According to Taiwo and Olayemi (2015) in this test, the cointegration equation is estimated separately for each panel member, and the residue is examined to the unit root. If the null hypothesis of the unit root is rejected, then there is a longterm relationship in the model with different vectors in each cross-section.…”

Section: Co-integration Testmentioning

confidence: 99%

“…The causality test is used to see the mutual relationship between variables in the VAR. According to Taiwo and Olayemi (2015), this test is grouped into four parts. First, the non-causality relationship is homogeneous, which means that there is no individual causality relationship.…”

Section: Causality Testmentioning

confidence: 99%

Pandemic Shock and Economic Variables Responses in ASEAN Countries Using Panel Vector Autoregressive Model

Retnasih

Herdianti

2023

JEP

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This quantitative research aims to measure the factors that affect the economy in 10 ASEAN countries in 2014-2020. The method used is panel vector autoregressive (PVAR). The results of the research were divided into several tests. First, the causality test shows that GDP has an effect on inflation and money supply with a one-way causality. Second, the PVAR test shows that the money supply has a significant effect on inflation and unemployment rate at lags 1 and 2. The follow-up test, namely IRF, shows that the shocks of GDP responded by all economic variables are greater than shocks to other variables. While the results of the VD test show that GDP is the largest contributor to the variation in the value of all economic variables studied, both in the short and long term.

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“…Their governmental budgets are mostly in deficit. In addition, these countries face trade and current account deficits, which are usually financed by capital flows from the rest of the world (Ghebreysus and Cadet, 1998;Taiwo and Olayemi, 2015). Attracting foreign investments requires a sound financial reporting system that produces reliable and transparent accounting information, so that investors can effectively evaluate risk and return (Daske et al, 2008;Larson and York-Kenny, 1995).…”

Section: Introductionmentioning

confidence: 99%

“…In particular, these studies investigate the channels, such as investment in human capital, financial development, infrastructure and institutions, through which FDI may contribute to growth (Alfaro et al, 2006;Carkovic and Levine, 2002). In the past, FDI has not been welcomed by African countries, due to skepticism that it could lead to the loss of political sovereignty and to probable negative impact on local firms (Dupasquier and Osakwe, 2006;Taiwo and Olayemi, 2015). But a decline in development assistance put pressure on developing countries to make themselves more attractive targets for FDI as an engine for promoting growth (Anyanwu, 2017;Evans, 2002).…”

Section: Introductionmentioning

confidence: 99%

How IFRS influence the relationship between the types of FDI and economic growth

Akisik

Mangaliso

2019

JAAR

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Purpose The purpose of this paper is to examine the relationships between International Financial Reporting Standards (IFRS), types of foreign direct investment (FDI) – greenfield investments (GFIs) and mergers and acquisitions (M&As) – and economic growth in 49 African countries between 2003 and 2017. Design/methodology/approach In the study, panel data fixed effects and generalized method of moments estimation techniques are used in order to test the hypotheses. Findings Using country-level data obtained from the World Development Indicators, The United Nations Conference on Trade and Development and World Governance Indicators websites, the authors find that IFRS and the types of FDI are significantly related to economic growth. Moreover, our results provide evidence that the effect of GFIs and M&As on growth is influenced by IFRS positively. Research limitations/implications With a handful of exceptions, most African countries do not have active stock markets. Therefore, the authors were unable to determine the effect of capital markets on growth. Practical implications FDI has the potential to contribute to economic growth and quality of life. Our findings suggest that policymakers should create incentives for attracting FDI and effective enforcement of IFRS in order to unleash the benefits of FDI on their economies. Originality/value The study provides important insights into the effects of types of FDI on the economic growth of African countries and into the role that IFRS play on this relationship.

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Re-examine foreign direct investment and economic growth: Panel co-integration and causality tests for sub-Saharan African countries

Cited by 7 publications

References 24 publications

Infrastructure, Human Capital Development and Economic Growth in Transitional Countries

Infrastructure, Human Capital Development and Economic Growth in Transitional Countries

Pandemic Shock and Economic Variables Responses in ASEAN Countries Using Panel Vector Autoregressive Model

How IFRS influence the relationship between the types of FDI and economic growth

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