Institutional quality, investment and economic growth in WAEMU countries: an empirical approach using DOLS

Karabou, Franck Essosinam Article Institutional quality, investment and economic growth in WAEMU countries: an empirical approach using DOLS Cogent Economics & Finance Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Karabou, Franck Essosinam (2024) : Institutional quality, investment and economic growth in WAEMU countries: an empirical approach using DOLS, Cogent Economics & Finance, ISSN 2332-2039, Taylor & Francis, Abingdon, Vol. 12, Iss. 1, pp. 1-14, https://doi.org/10.1080/23322039.2024.2426530 This Version is available at: https://hdl.handle.net/10419/321661 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. 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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/ Cogent Economics & Finance ISSN: 2332-2039 (Online) Journal homepage: www.tandfonline.com/journals/oaef20 Institutional quality, investment and economic growth in WAEMU countries: an empirical approach using DOLS Franck Essosinam Karabou To cite this article: Franck Essosinam Karabou (2024) Institutional quality, investment and economic growth in WAEMU countries: an empirical approach using DOLS, Cogent Economics & Finance, 12:1, 2426530, DOI: 10.1080/23322039.2024.2426530 To link to this article: https://doi.org/10.1080/23322039.2024.2426530 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 08 Nov 2024. Submit your article to this journal Article views: 696 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oaef20 DEVELOPMENT ECONOMICS | RESEARCH ARTICLE Institutional quality, investment and economic growth in WAEMU countries: an empirical approach using DOLS Franck Essosinam Karabou Faculty of Economics and Management (FASEG), University of Kara, Kara, Togo ABSTRACT Investment, whatever its nature, is an indispensable channel for increasing economic growth. The aim of this paper is to empirically study the effect of institutional quality and investment on economic growth in WAEMU countries. The methodological approach is based on a dynamic panel model covering the period from 2005 to 2020 for all eight WAEMU countries. Results are obtained using the Dynamic Ordinary Least Squares (DOLS). The results show a significant effect of governance indicators and public investment on GDP per capita. Furthermore, the results show that governance indicators modify the effect of investment (public and FDI) on GDP per capita. These results imply that efforts must be made to take full advantage of the positive effects of investment. As the quality of governance is a key factor in attracting and securing investment, policymakers must adopt strategies to improve governance indicators if they are to achieve their growth objectives. The originality of this research lies in highlighting the effects of Institutional quality and investment on economic growth through a DOLS. IMPACT STATEMENT Investment is an indispensable channel for increasing economic growth. The goal of our research paper is to empirically study the effect of institutional quality and investment on economic growth in WAEMU countries. The results show a significant effect of governance indicators and public investment on GDP per capita. Furthermore, the results show that governance indicators modify the effect of investment (public and FDI) on GDP per capita. These results imply that efforts must be made to take full advantage of the positive effects of investment. As the quality of governance is a key factor in attracting and securing investment, policymakers must adopt strategies to improve governance indicators if they are to achieve their growth objectives. The originality of this research lies in highlighting the effects of Institutional quality and investment on economic growth through a DOLS. ARTICLE HISTORY Received 5 June 2024 Revised 14 August 2024 Accepted 3 November 2024 KEYWORDS Investment; governance; economic growth; DOLS; WAEMU JEL CLASSIFICATION E22, F21; D73; C23; O55 SUBJECTS Development Economics; Economics; Macroeconomics 1. Introduction Economic literature has widely discussed the contribution of investment to economic growth. While it is clear that investment drives economic growth, the results of empirical studies have produced mixed results. Some studies find a positive effect of investment on growth (Jwan & James, 2014; Tiwari & Mutascu, 2011), while others find a negative effect of investment on economic growth (Carkovic & Ross, 2002). This situation can be explained by the influence of many factors, notably institutional quality and public debt. Although the link between public investment and economic growth has been widely studied in the literature, it has been difficult to draw firm conclusions about the effectiveness of public investment. In recent studies, there is some convergence regarding the importance of public investment on growth, CONTACT Franck Essosinam Karabou [email protected] Faculty of Economics and Management (FASEG), University of Kara, Kara, Togo ß2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. COGENT ECONOMICS & FINANCE 2024, VOL. 12, NO. 1, 2426530 https://doi.org/10.1080/23322039.2024.2426530 but the results still vary from country to country, or sample to sample, and seem to depend on many different factors (Bayraktar, 2019). In developing countries, the availability of financial resources is a prerequisite for any investment process. But the gap between investment needs and available resources was enormous. Thus, faced with an unfavorable macroeconomic environment and a huge need for basic infrastructure, low-income countries adopted public debt as an economic policy instrument. Economic theory suggests that indebtedness makes it possible to make investments that savings cannot. The income generated by debt should be used to finance profitable investments, capable of repaying the capital and its interest. However, a high debt ratio indirectly slows down productive investment through high domestic real interest rates and low profitability due to a drop in economic activity. Today, new development strategies to combat poverty and inequality place particular emphasis on the quality of institutions, especially in developing countries and more specifically in Sub-Saharan Africa (El Jabri, 2022). Following the controversial results of structural adjustment programs, there has been a clear revival of interest in institutional quality. As a result, traditional macroeconomic determinants alone cannot explain the level of economic performance and development gaps observed between countries. In this sense, a significant number of researchers agree that the institutions quality is the main determinant of differences between countries in terms of economic and human development (Kouchad & Dinar, 2020). It would be wise to place particular emphasis on indicators that escape traditional theories, such as institutional quality. Generally speaking, the contribution of public investment to sustainable growth in developing countries is low, and foreign direct investment (FDI) is one of the channels for supporting government action. Achieving the objectives of sustainable development requires investment in all sectors of activity, and FDI is proving to be essential for achieving these objectives in developing countries, particularly those in sub-Saharan Africa. Against this backdrop, mechanisms have been put in place to attract foreign investors, notably the quest for good governance (Immurana, 2021). According to UNCTAD statistics (2018,2019), FDI flows to developing economies increased by 2% in 2018, while for Africa, FDI flows increased by 10.05% from 2017 to 2018. However, the effect of FDI on economic growth remains debatable, as growth depends on both social and physical capital. On the one hand, FDI can increase the transfer of technology and domestic capital, leading to higher incomes and economic growth. Thus, thanks to the increase in FDI and the resulting rise in income levels, there is an increase in private and public spending, which translates into an improvement in the population’s well-being. In contrast, for other authors, increased FDI in the manufacturing sector leads to negative externalities, especially in terms of preserving the environment quality (Hitam & Borhan, 2012). In the same vein, other authors, such as Agosin and Machado (2005), have shown that FDI crowds out domestic investment, leading to higher levels of unemployment. For these researchers, the repatriation of foreign companies’profits can adversely affect economic growth and worsen the country’s socio-economic conditions. The contradiction between these findings on the effect of investment on economic growth has led to renewed interest in the role of non-traditional growth factors in this relationship. In this sense, institutional quality, or good governance, is essential for the investment orientation in preferred sectors and for the attraction of FDI. According to Outreville (2007), the governance quality is a determinant of FDI and has a significant effect on the choice of countries by these companies. Thus, good governance is a relevant factor explaining the locations most favored by multinationals for establishing subsidiaries abroad. So, in the context of SSA countries, and more specifically in the WAEMU countries where local investment is low and governance indicators are weak, we need to analyze the institutional quality contribution to the investment-growth relationship. In light of the above analysis, it is clear that there is a vast literature on investment and growth (Abdouli & Hammami, 2017; Nguyen et al., 2020) on the one hand, and governance and growth on the other. However, none of these studies explored the simultaneous effect of local and foreign investment on economic growth in the context of WAEMU countries. Thus, as an addition to the empirical literature, the present study aims to analyze the institutional quality role in the relationship between investment 2 F. E. KARABOU (local and foreign) and economic growth in WAEMU countries, taking into account the interaction of the former on the latter. The study results should help decision-makers to implement and design policy initiatives that target economic growth objectives in coincidence with investment, in order to better direct investment (local and foreign) toward growth-generating sectors. This study makes several contributions. Firstly, it deals significantly with a subject for which there is limited empirical literature in the WAEMU countries. It provides evidence of the relationship between public debt and public investment, and between public investment and economic growth. The main is to answer the following two research questions: has an increase in government debt led to an increase in investment and hence economic growth, or has it mitigated the effect of investment on growth? Furthermore, our study sheds light on the problem of debt by identifying a possible relationship between the level of debt and economic growth, with an emphasis on governance indicators. Finally, the findings of this paper may be useful for other analyses of economic growth and for the formulation of effective debt management. The rest of the paper is organized as follows: the next section deals with the literature review, the third section is about methodology. The results and discussions are, respectively, presented in sections 4 and 5. The final section is for conclusions and policy recommendations. 2. Literature review Reflection on the economic growth sources, and in particular on the role of capital in growth, developed in two ways. For Solow (1956), public investment was irrelevant to the analysis of growth. By contrast, at the end of the 1980s, there was a resurgence of endogenous growth theory, which sees public investment as a growth factor (Barro, 1990). Solow (1956) based his analysis on the flexibility of production technology. This analysis is based on a production function with two components: capital and labor. Growth presupposes the development of capital through investment and the growth of the working population. But one of the most important conclusions of Solow’s model is that growth is limited, on the one hand, by the population growth rate, an exogenous quantity, and capital, whose growth is limited by the diminishing returns law, on the other. In other words, Solow’s neoclassical model is based on the diminishing returns hypothesis. He proposed that the long-term growth rate of an economy is exogenously determined by the rate of technological progress and demographics. In this theoretical perspective, public investment policy (infrastructure) only modifies the economy’s growth rate when it reaches long-term equilibrium (stationary state). By contrast, Barro (1990) includes public investment in his analysis, emphasizing its productive role in economic growth. Productive public spending, which he equates with public infrastructure capital, plays a driving role in the growth process. The complementarity between private and public capital is attributed to the latter’s positive effect on private factor productivity (Sala-I-Martin & Barro, 1995). In other words, Barro’s(1990) endogenous growth model emphasizes the positive externalities generated by public services. Externalities arise when public services affect the productivity of the private sector, and the private sector does not directly bear the costs. These productive public services provided to domestic and foreign private companies reduce production costs and increase output. The externalities existence justifies governments not only directing private players toward growth-generating activities, but also developing infrastructures that increase their productivity. The authors, therefore, believe that public investment can enter the productive function of firms, making private inputs more productive and stimulating rather than crowding out private investment. Following Barro (1990), Alogoskoufis and Kalyvitis (1996) describe an endogenous growth model with solutions that emphasize the public capital role in growth and investment. According to these authors, public investment policy is prepared in three stages. At a given point in time, the public authorities will determine the ratio of public capital to GDP; this model makes it possible to highlight the long run growth dynamic driven by private investment. This, in turn, is an increasing function of the public capital level. Authorities can then set targets for the public capital growth rate or the ratio of public investment to GDP. In this case, the public capital growth rate determines the economy equilibrium growth rate. COGENT ECONOMICS & FINANCE 3 After that, private investment will increase steadily, as the ratio of public to private capital will remain stable over the long run, and marginal productivity will improve as public investment increases. However, studies have produced contradictory results between a significant and non-significant impact of public investment on economic growth. Bosede et al. (2013) deduced that improved transport infrastructure has a positive and significant impact on the Nigerian economy for the period 1981 to 2011. Morley and Perdikis (2000) asserted the positive long-term impact of total public spending on Egyptian growth. Analyzing the impact of public infrastructure on competitiveness and economic growth in Madagascar, Andrianady et al. (2023) found that increased public spending on infrastructure promotes economic growth and improves business performance. Reinikka and Svensson (2007) also found that economic growth was significantly justified by public investment. According to a World Bank (2005) study about Senegal over the period 1966–2000, the effect of public investment is delayed over time and its positive impact, estimated at 2.47 points, appears after two years. On the other hand, some empirical studies have suggested that public spending does not have a significant effect on economic growth. Zahira and Mostefa investigated the impact of public investment in infrastructure on economic growth in India over the period 1951–2010. The study used a vector autoregressive (VAR) model and found that public investment in infrastructure had no statistically significant impact on economic growth. Yovo (2017) also investigated the relationship between public investment and economic growth in Latin America and the Caribbean using panel data from 1980 to 2010. The results of the study suggest that public investment has no significant effect on economic growth in the region. In summary, while some empirical studies have suggested a positive relationship between public investment and economic growth, other studies have found no significant evidence to support this idea. The results of these studies highlight the need for further research in this area to better understand the relationship between public investment and economic growth. While these economic theories emphasize the importance of factors such as human capital, technology, public infrastructure and incentives to innovate in explaining growth differentials between countries, in recent years, a paradigm shift has been observed. Similarly, there is an abundance of empirical literature on the relationship between public investment and economic growth. However, the results differ slightly depending on the statistical definition of capital, the production function specification and the estimation method. Indeed, there has been a growing emphasis on the effects of institutional quality and governance on economic development. North and Thomas (1973) argue that institutions are at the root of growth disparities between countries. For their part, Acemoglu et al. (2005) argue that institutions are the most fundamental cause of economic growth. Broadening this perspective, Rodrik (2004) points out that institutions not only exert a direct influence on growth, but also impact other factors such as capital, investment and innovation, which, in turn, stimulate economic growth. Moreover, sound governance can encourage foreign investment, boost consumer and business confidence, and thus create an environment conducive to sustained growth. However, the literature on the importance of institutions in economic dynamics only began to gain prominence in the second half of the 20th century. Thus, the fundamental importance of institutions as a driver of economic recovery has been emphasized by many eminent researchers (Greif, 2006). Building on this research, Acemoglu et al. (2014) put forward a fundamental idea: economic institutions drive market players to invest in human and physical capital and adapt to new technologies, thereby contributing to economic growth. For these researchers, institutions influence not only the trajectory of growth, but also the way wealth is distributed within a society. For his part, North (1990) argues that the institutional quality of a society directly influences its ability to accumulate human capital, which consists essentially of the skills, knowledge and experience of individuals. A country’s strong and effective institutions can have a direct impact on its economic growth, notably by influencing fundamental aspects such as the education system. In fact, a strong education system that is adequately funded and effectively regulated is beneficial to the achievement of the sector’s desired objectives. On the other hand, a weak or corrupt system could hinder the development of human capital. Similarly, Acemoglu et al. (2005) concluded that institutions that guarantee property rights are key drivers of long run economic growth, investment and financial development. Furthermore, they noted 4 F. E. KARABOU that these institutions are the most important factor in attracting foreign direct investment. Their studies highlight the crucial role played by institutions as fundamental determinants of sustained economic growth. Similarly, Cavalcanti et al. (2008) deduce that states with stronger, more efficient institutions not only increase their investment in human and physical capital, but also make more efficient use of the resources at their disposal. This is one of the reasons why some advanced countries boast much higher productivity per worker than other territories. Coe et al. (2009) find that countries with a business-friendly climate and high-quality higher education tend to capitalize more on their R&D investments and enhance the value of their human capital. In the same vein, Dias and Tebaldi (2012) demonstrate that improving the institutions quality promotes human capital accumulation, reduces income inequality and redefines the historical development path of nations. Their findings reveal that institutions have a long run effect on economic performance and, consequently, determine the path a country will take in terms of economic development. However, when it comes to the influence of political systems on economic growth, Dias and Tebaldi (2012) fail to establish a direct causal link. In short, according to institutionalist theory, a country’s economic performance depends not only on innovation, human and physical capital, but also on the quality of its institutions (political and economic). As a result, a significant number of researchers place greater value on the role institutions play in understanding why some nations are able to prosper and flourish, while others face persistent economic challenges. We also note a limitation in the methodologies used in the literature, which leads us to revisit the subject with a new methodology, Dynamic Ordinary Least Squares (DOLS). 3. Methodology 3.1. Model To analyze institutional quality’s and investment impact on economic development we move from the above literature. We followed the model used by Ahmad et al. (2023), Nawaz et al. (2014), Moudine et al. (2019), Saad and Uddin (2021), Abubakar (2020), Tran et al. (2021), Uddin and Rahman (2023) and Gu et al. (2023). The existing literature on the relationship between institutional quality, investment and economic growth leads us to the following general empirical formulation: GDPH ¼fðI,Gov,XÞ(1) Where GDPH is Gross Domestic Product per capita; Irepresents the vector of investments, notably local investment (Inv) and foreign direct investment (FDI);Gov is the vector of governance indicators measured here by political stability (StaPol), corruption (Corr) and government efficiency (Gouv Efficiency). These indicators are used in preference to the others, as they best represent the situation of WAEMU countries in terms of good governance. Xrepresents the vector of socio-economic variables. To analyze the involvement of governance in the investment-economic growth relationship, we define an equation for the interaction of governance and investment on growth as follows: GDPH ¼fðI,Gov I,XÞ(2) Where GOUV*Irepresents the interaction of governance and investment indicators. The methodological approach is based on a panel data model for the eight WAEMU countries, covering the period from 2005 to 2020. The model equation is given below: GDPHit ¼aiþa1Iit þa2Govit þa3Inflit þa4CrPopit þeit (3) Where a i represents the country-specific effect. iand trepresents the number of individuals (country) and the period (year), respectively. The role of investment in economic growth has been widely discussed in the literature. We, therefore, expect a positive effect of investment on economic growth (Saidi et al., 2023). Gov represents the institutional quality indicator measured here by governance indicators. The literature has shown that economic growth improves in the presence of better governance indicators (Fatnassi & Et Gutate, 2023; Yacouba et al., 2023). Inf refers to inflation measured by consumer prices. However, the literature has found mixed results regarding the positive effect of inflation on COGENT ECONOMICS & FINANCE 5 economic growth (Barro, 2013). Crpop refers to the population growth. We expect a positive effect of population growth on economic growth (Onjala & K’Akumu, 2016). To analyze the contribution of governance on the investment effect to improve economic growth, the interaction model is given as follows: GDPHit ¼aiþa1Iit þa2Gov Iit þa3Infit þa4Crpopit þeit (4) Where GovI is the interaction between governance and investment. 3.2. Data source The data set comes mainly from the World Bank database (WDI, 2022) covering the period from 2005 to 2020 and covers all WAEMU countries. 1 3.3. Estimation technique 3.3.1. Cross-sectional dependency test To determine the appropriate estimation technique for our model, we carry out various tests, starting by checking the stationarity of our variables. There are two levels of unit root tests. The first generation of tests is based on the assumption of independence between individuals and the second generation tends to lift this assumption of independence by taking into account all possible forms of dependence between individuals. We therefore propose to carry out the cross-sectional dependence test and determine the appropriate unit root test in our case. We speak of cross-sectional dependence when the observed common effects are omitted, the common effects are unobserved or even if the observed and unobserved effects are taken into account, the interdependencies could remain. Therefore, to conduct our study properly, we will perform the Pesaran et al. (2004) cross-sectional dependence test, which is a robust test to breaks in the coefficients as long as the unconditional means of the variables are constant throughout the time dimension. After the test, when there is no cross-sectional dependence we proceed to the first generation unit root test, otherwise we proceed to the second generation unit root test. Our results, presented in Table 1, show that there is cross-sectional dependency, as most of the probabilities (pvalue) are less than .05. The presence of cross-sectional dependence in our data leads us to proceed with the second generation unit root test. 3.3.2. Unit root test To test the stationarity of our variables, we refer to the second generation unit root test of Pesaran (2007) which takes into account all types of dependence and heterogeneous characteristics. After applying this test, we find that the inflation variable is stationary at levels. For the other variables (variables of interest and control variables), none is stationary at level but they are stationary in first difference. The presence of unit roots in our model allows us to verify the presence of long-term relationships by performing a cointegration test. 3.3.3. Cointegration test We use the Westerlund (2007) test, which we believe is suitable for our model because it takes into account heterogeneous panel characteristics and also long-term and short-term cointegration relationships. This test takes into account two types of test, namely the group average test (Gt and Ga) with the Table 1. Cross-sectional dependency test. Variable CD-test pValue Corr Abs(corr) PIBH 19.32 .000 0.920 0.920 InvPub 6.61 .000 0.315 0.480 FDI 1.45 .046 0.069 0.205 Inflation 15.18 .000 0.723 0.723 CrPop −1.28 .199 −0.061 0.444 Corruption 0.94 .350 0.046 0.457 Source: Author, based on World Bank data (WDI, 2022). 6 F. E. KARABOU alternative hypothesis that at least one unit is cointegrated, and the panel test (Pt and Pa) with the alternative hypothesis that the panel is globally cointegrated as shown in Tables 2 to 4. The results show that at least one unit is cointegrated and also that the panel is globally cointegrated at 5% means that there’s long run relation. The presence of cointegrating relationships between our variables leads us to choose estimators that take into account long-term relationships for dynamic panels with unit root. The econometric literature has shown four main estimators that take cointegration into account, namely FMOLS (Fully Modifly Least Squares), DOLS (Dynamic Ordinary Least Squares), MG (Mean Group) and PMG (Pooled Mean Group). In addition, estimators such as the dynamic ARDL (Auto Regressive Distributed Lag) and CCR (Common Correlation Ratio) method can be used to take these long-term relationships into account. However, the FMOLS and DOLS estimators were proposed respectively by Pedroni (2004) and Kao and Chiang (2001) with a view to remedying the problems from which the Ordinary Least Squares (OLS) estimator suffers. OLS suffer from correlation problems between series and endogeneity problems in the regressions of cointegrating relationships. Furthermore, based on properties of finite sample sizes, Kao and Chiang (2001) have shown that OLS generates significant bias problems for small sample sizes and the FMOLS estimator does not provide a significant improvement over the OLS estimator. As a result, they conclude that the DOLS estimator is better than OLS and FMOLS for estimating long-run relationships with finite sample sizes. The MG estimator proposed by Pesaran and Smith (1995) is an estimator generally used for estimating panel models and designed to average each unit making up the panel. It is therefore an efficient estimator of parameter means. The MG estimator is also consistent for estimates of long-term relationships, mainly for large sample sizes (Pirotte, 1999). The PMG method, developed by Pesaran et al. (1999), is an intermediate estimator between two estimation methods often used for panel data estimates, namely, the MG estimation method on the one hand, and the usual panel data estimation methods which include random and fixed effect models or the generalized method of least squares (GMM), on the other. In fact, it is an estimator that offers a dynamic adjustment between long run and short run relationships via the convergence coefficients. However, it is important to note that the PMG estimator imposes homogeneity on the long run coefficients, while allowing heterogeneity for the short run parameters. From all the above, we refer to the DOLS method for the estimation of our model because, apart from taking into account long run relationships, this method also takes into account endogeneity and autocorrelation problems and combines the necessary information relating to the explanatory variables Table 2. Cointegration test GDP_Public investment. Statistic Value Z-value pValue Gt −2.360 −1.835 .033 Ga −4.991 1.118 .068 Pt −5.543 −1.457 .073 Pa −4.341 −0.071 .072 Source: AUTHOR (2024). Table 3. Cointegration test GDP_Corruption. Statistic Value Z-value pValue Gt −2.252 −1.493 .068 Ga −4.990 1.118 .868 Pt −5.821 −1.736 .041 Pa −4.875 −0.411 .041 Source: AUTHOR (2024). Table 4. Cointegration test GDP_Debt. Statistic Value Z-value pValue Gt −1.761 0.053 .021 Ga −5.014 1.106 .066 Pt −4.592 −0.500 .008 Pa −4.557 −0.208 .018 Source: AUTHOR (2024). COGENT ECONOMICS & FINANCE 7 UNCTAD Statistics. (2018). Handbook of Statistics. UNCTAD Statistics. (2019). Handbook of Statistics. Yacouba, S. A. L. O. U. K. A., Sidy, K. C., & Nestor, T. T. (2023). Effect of the quality of institutions on economic growth in Waemu countries. African Scientific Journal,3(19), 558–558. Yovo, K. (2017). Public expenditures, private investment and economic growth in Togo. 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