DEVELOPMENT PROJECT MANAGEMENT AND ECONOMIC PERFORMANCE IN CENTRAL AFRICAN COUNTRIES

Abstract 

The objective of this work is to measure the influence of the management of development projects on the economic performance of Central African countries, particularly on economic growth and unemployment. To achieve this, we used 11 countries in this area over the period 1995-2015. Thus, by using a dynamic panel model estimated by the Generalized Moment Method (GMM) in the empirical analyses, we arrive at two main results: first, the management quality of the majority of development projects in Central Africa has positively influenced the economic performance of these countries. Second, we find that the two indicators of development project management used in this study have different effects on growth and unemployment in our sample. Indeed, if the technical management of development projects has a negative effect on unemployment and a positive effect on growth, the financial management of development projects also has the same effects on the latter. This leads us to make two major recommendations: firstly, the need to set up a research programme to strengthen the implementation of development programmes in Africa. Secondly, to adapt the management of development projects to African realities.

Key words: Development project management, economic performance, economic growth and unemployment

GENERAL INTRODUCTION 

Following the Millennium Summit organised by the United Nations in September 2000, which led to the adoption of the Millennium Development Goals (MDGs), numerous scientific studies have been carried out on the technique to be used to achieve Goal 1 of the MDGs¹. Indeed, according to this objective, the 189 countries that took part in this conference committed themselves to halving the level of poverty in the world and to improving economic growth. In this respect, most studies have recognised the major role that development project management can play in achieving this goal. Generally speaking, and according to the work of Croplatine (2004), a development project refers to the set of solutions and responses to problems faced by a specific community. At the macroeconomic level, a development project refers to the implementation of a land-use policy by the state, such as the construction of public facilities and the management of scarce resources. On the other hand, at the international level, a development project refers to an instrument through which donors intervene in the framework of development aid² (OECD, 2020). According to international institutions, a development project is a project financed by bilateral, multilateral or private donors with the aim of improving the socio-economic situation of developing countries (World Bank, 2016). At the micro level, a development project is any investment made by an entrepreneur to earn a return. In view of all these definitions relating to the development project, we can therefore understand the need for the initiators to manage it well in order to achieve the expected objectives. Indeed, for Ika (2012), the management of development projects refers to any process that goes through 5 crucial stages: design, which consists of clearly identifying the overall and specific objectives of the project. Planning: this stage consists of identifying the different tasks to be carried out by prioritising them and determining their duration and resources. Implementation, closure and evaluation.  

Several African countries in general are setting up development management programmes. For example, according to the OECD report (2020), 48 African countries have benefited from ODA. These include 32 African least developed countries, 1 African low income country, 9 African lower middle income countries and 6 African upper middle income countries. But, globally, the same report mentions that, official development assistance in 2020 is at 167 billion dollars or more than 99,123,017,000,000FCFA. Africa in general and Central Africa in particular for example, have benefited from more than 40% of this aid to develop several development projects and revive the economy.

In fact, for most authors in the economic literature, the management of development projects is a crucial tool for improving not only economic performance but also the well-being of populations (Moyo, 2009). It allows populations from vulnerable countries to escape extreme poverty and thereby promote the reduction of social inequalities through the construction of several collective infrastructures such as schools, hospitals, businesses, road and port infrastructures (Sachs, 2005; Sachs et al., 2004). For Chauvet, Collier, and Duponchel (2010), when a development project does not promote economic and social well-being in a country or sub-region, it means that it is not well managed. In other words, good management of a development project in a country is a source of economic development. 

Today, in many developing countries such as those in Central Africa, relations with development partners have become a central part of their international affairs. Some of the most aid-dependent states are integrating aid into their fiscal policy to provide services to their people. For Western donor states, the provision of development assistance has become an important instrument for achieving international goals, including cultivating political allies, opening markets, combating terrorism and establishing social security systems. Thus, since independence in 1960, Central African countries have benefited from a number of multilateral and bilateral foreign aids in order to boost social projects and revitalise economic indicators. 

However, despite these multiple loan agreements, the welfare and economic indicators of Central African countries remain deplorable. Indeed, the level of poverty remains quite high according to the AfDB (2020), at 40%. Real GDP contracted by 2.4% in 2020, compared to 3.7% growth in 2019. This 6.1 percentage point decline in economic activity was largely due to the fall in global oil prices. As a result, activities in the agro-industrial export, manufacturing and services sectors, including trade, slowed down sharply. Growth was also affected by the persistence of the security and socio-political crises in some countries in the region, notably the DRC and Cameroon. Inflation was kept below the Central African Economic and Monetary Community (CEMAC) convergence threshold of 3%, i.e. 2.9% in 2020, compared with 2.5% in 2019. The Bank of Central African States took various measures in 2020 to support the economies of its member states. For example, the tender interest rate (TIAO), the main instrument of monetary regulation within this monetary cooperation zone, was lowered by 25 basis points, from 3.50% to 3.25% in March 2020. A new foreign exchange regulation, which came into effect on 1 March 2019, increased the country's foreign exchange reserves, which at the end of 2020 covered 7.5 months of imports, compared with 6.3 months at the end of 2019. The budget deficit fell from 3.6% of GDP in 2019 to 4.9% of GDP in 2020, and the current account deficit from 3.1% of GDP in 2019 to 5.2% of GDP in 2020, mainly due to lower oil exports and remittances. In the face of all these rather less than stellar figures, one gets the impression that despite the many development projects obtained by Central African countries, their economic performance has not improved. 

Thus, in view of all the above, one main question emerges: What is the effect of development project management on the economic performance of Central African countries? In this study, we aim to highlight the effects of development project management on the economic performance of Central African countries. To this end, we formulate the main hypothesis that the management of development projects does not favour the economic performance of Central African countries. This study is of twofold interest. Firstly, on the positive side, it contributes to the existing literature with this case study that specifically concerns the economy of Central African countries. Secondly, it is of methodological interest. Then we consider the management of development projects in its different aspects, notably the technical and financial aspects. Finally, concerning the estimation technique, after having carried out the necessary tests, we resort to the generalized method of moments. The rest of the work will be structured around four sections. In the first section, we will review the literature related to our study, the second section will focus on the empirical strategy. The third section will focus on the presentation of the results. Finally, the fourth section will focus on the conclusion and recommendations. 

I- Review of the literature 

Several theoretical and empirical works do not agree on the impact of development project management on the economic performance of developed and developing countries. While some empirical and theoretical works argue that the quality of management is an obstacle to the economic and social development of the beneficiary countries, others argue that the quality of management is not a factor. For others, however, the management of development projects is a real catalyst for development in vulnerable and poor countries. In this brief review of the literature, we will focus on theoretical and empirical work. 

I.1- The position of theoretical work 

Theoretical works are not unanimous about the impact of development project management on the economic performance of countries, particularly on unemployment and growth. Indeed, the first current, made up of supporters of public aid, believes that when a project is financed by bilateral or multilateral aid, it only targets the poorest segments of the population This is the case for the eradication of poverty and unemployment in developing countries (Arndt et al, 2010, 2015; Sachs, 2005; Stiglitz, 2007). At the other extreme are other authors such as Friedman (1958), Bauer (1972), Easterly (2003, 2006, 2008), Moyo (2009) and Doucouliagos and Paldam (2006) who argue that mismanagement of a development project, hinders the well-being of the population and development. 

Moyo (2009) further argues that when donors do not monitor whether a project is well managed financially and technically, it perpetuates the cycle of poverty and derails sustainable economic growth and unemployment. Between these two groups are those who believe that development project management can be effective under certain conditions (Burnside and Dollar, 2004). This third group argues that the impact and effectiveness of project management depends on the method used by donors to allocate aid and on recipient country characteristics such as governance, commitment, ownership and institutional capacity (Riddell, 2008). 

Sachs (2006), proposed that developing countries, particularly underdeveloped countries, need a "big push", i.e. financial assistance from developed nations to finance and implement development projects. He concludes that foreign aid flows to all EU countries are greater than those to developed countries. Sachs' view of the "big push" indicates that countries are too poor for savings to occur, which reduces the rate of growth (Sachs, 2003). 

Easterly (2006) found that growth rates were low, in contrast to what happened in high growth countries. In contrast to the "big-push" theory. Boone (1994) argues that the big-push theory is wrong because the injection of funds only increases the purchasing power of poor households, consumption increases, but private investment is zero. Aid is supposed to stimulate economic growth in this case, but it did not. The productivity of the investments into which the aid was injected was at issue, not the effectiveness of the aid. If aid is injected into good projects by a recipient country, economic growth will occur (World Bank 1998). 

I.2- The position of empirical work 

Like theoretical work, empirical work is also divided on the nature of the impact of development project management on the economic performance of countries, particularly on employment and growth. For example, Kosack (2003) assesses the effectiveness of the management of aid-assisted development projects on the quality of life in recipient countries. The study uses ordinary least squares (OLS) and double least squares estimation techniques on a sample of 49 developing countries over the period 1974-1985. The study found that aid project management can reduce poverty and promote employment only in democratic countries, not in autocratic ones. In the same vein, Bahmani-Oskooee and Oyolola (2009) used The study used time series and cross-sectional data for 49 developing countries over the period 1981-2002 to estimate the impact of ODA-funded development project management on poverty. Using the panel method, the study found that development project management reduces poverty and that inequality undermines poverty reduction. 

In addition, Gomanee et al (2005) tested the hypothesis that development project management leads to an increase in overall welfare using the fixed-effect panel data method on a sample of 104 countries for the period 1980-2000. The main findings of the study are that good management of development projects directly improves welfare indicators and that the impact is greater in low-income countries than in middle-income countries. The study also showed that the channels through which development project management indirectly affects welfare is growth. Regarding the effect on economic growth, early studies by Gomanee, Girma, Morrissey (2005) and Levy (1988) have contributed to this debate. By regressing a group of 34 variables on the periods 1951 and 1960, they conclude that the management of development projects promotes economic growth in these countries. 

II- Empirical strategy 

After presenting the literature related to our study, this section focuses on the empirical approach used to achieve our objective. For this purpose, one point will be highlighted: the presentation of the models. 

II.1-Econometric models 

In this article, we will develop two models. The first model we have chosen is the one developed by Gichanga (2018), who conducted a study on the impact of the management of development projects funded by official development assistance on economic growth in Kenya between 1970 and 2016. The model is as follows: 

With Croiss corresponding to the level of economic growth representing the growth rate of Gross Domestic Product (GDP). Gpf is a variable representing the level of financial management of projects, Gpt is the level of technical management of development projects, Don is the variable measuring the level of grants and W is a matrix of control variables such as: foreign direct investment, financial development, political stability and governance. The βi (i=1,..., 3) represent the coefficients to be estimated. In our analysis, we will use this panel model in order to be able to take into account the inter-temporal variations of our variables. For our analysis. Thus, t=1995 to 2015 and i = 1 to 11. 

However, the second model that we retain is the one developed by Kangni Kpodar (2004) and then taken up and improved by Kada et al.(2014) who, in order to evaluate the relevance of project management policies, had used it to show the impact of development project management on the Algerian economy from 1970 to 2013. This model is presented as follows: 

With CHOM representing the level of unemployment. The data for all these variables are taken from two major databases: the WDI and the Governance Indicators 2020. 

III- Presentation and analysis of results. 

This section will present the results of the descriptive statistics (the means and standard deviations of the variables, then the correlation matrix) and finally the econometric results. 

III.1- Basic results 

The descriptive statistics of the variables (table 1) and the correlation matrix (table 2) are presented here. 

III.1.1- Means and standard deviations of variables 

Table 1 below gives the average, standard deviation, minimum and maximum values for each of the variables in our analysis for the whole sample. As can be seen, the average level of economic growth in Central Africa is very low. The average level of economic growth over the study period is about 0.9 with an equally low standard deviation of 0.3. The range of this series, which is given here by the difference between the maximum and minimum values, is 1.40. This rather low value of the range allows us, together with the standard deviation, to state that this series is not sufficiently dispersed. While the level of unemployment is quite high with an average of 7 and a maximum of 21.2. 

Let us now turn to the explanatory variables of our model. With regard to the variables of With regard to the variables of interest, we note that the variables financial management of development projects and technical management of development projects, which respectively measure the long-term effect and the short-term effect of the management of development projects, have fairly low standard deviations but fairly high averages over the study period of around 1% and 4% respectively. This means that the stable and weak character of these variables could justify the low level of economic growth and the high level of unemployment in the economies of these Central African countries. Moreover, the average of the Don variable is quite high. 

III.1.2- Correlation matrices of variables 

The correlation matrix of our variables presented in the first model (table 2 below), contains the correlations between the different variables of our study. It indicates that all our variables of interest are negatively correlated with economic growth in Central African countries. This means that technical or financial management of development projects in Central Africa may not promote economic growth. On the other hand, some control variables such as grants, FDI and development have a positive effect on economic growth in these countries. On the other hand, the quality of governance is negatively correlated with economic growth in these countries. 

As in the previous table 2, table 3 below presents the correlation matrix between the variables of the management of development projects and the level of unemployment within the Central African countries. Indeed, it is observed that there is a negative relationship between the financial management of development projects on the one hand, and the technical management of development projects on the other hand, on unemployment. However, with regard to the control variables, only financial development has a negative relationship with unemployment. While the rest of the control variables have a positive relationship with unemployment. In view of these correlations, it is necessary to carry out an econometric regression to know the concrete effect of each of our variables on economic growth and unemployment. 

III.2- Presentation of the econometric results of the effect of the management of development projects on the economic performance of Central African countries 

In this section we will first carry out the diagnostic tests and then present the results of the econometric analysis. 

III.2.1-Diagnostic tests 

In this sub-section, we will first carry out the unit root tests and then the co-integration test. 

III.2.1.1- Unit root tests 

The test carried out here is that of Im-Pesaran and Shin (2001). The choice of this test is due to the fact that it is part of the so-called second generation tests. It therefore incorporates certain limitations often observed with the Philipe-Perron (PP) and Levine-Line and Chu (LLC) tests, which are first-generation tests. Therefore, the results obtained with this test are more reliable than those obtained with the PP and LLC statistics. 

As we can see in the table above, at level (column 1) the development project management variables are all non-stationary while the control variables are stationary at levels. We have thus performed our tests again using the variables in first difference. The results of these tests presented in the second column of the table above show that all the variables used in this analysis are stationary at first difference. We can therefore conclude that our development project management indicators are integrated of order 1. 

III.2.1.2- The cointegration test 

The indicators of the management of development projects being stationary in first difference, it proved necessary to carry out a test of cointegration to ensure us that there is indeed a relation of balance between our variables on the long run. The test performed here is the Pedroni test. The results of this test revealed a significance at 1% for the V, PP and ADF statistics in panel and group. This means that, although the rho statistic is not significant, it confirms the cointegration of our variables. 

III.2.2- Presentation of the results of the econometric analysis 

Table 5 below contains the results obtained from the econometric analysis. We estimated our model using the method of generalized moments in difference. The choice of this method was motivated on the one hand by the fact that all the explanatory variables used here were not stationary at level, but rather at first difference. Thus, our model with level variables would have undoubtedly introduced biases in our results. One of the methods indicated to solve this problem is the method of generalized moments in difference. On the other hand, this method allows us to solve the endogeneity problems. Indeed, the introduction of the lagged dependent variable among the explanatory variables is a source of endogeneity. In addition, we used two models to estimate the influence of development project management on the economic performance of Central African countries. Indeed, the first model (column 1 of the table below) shows the impact of development project management on economic growth for all Central African countries. The second model (column 2 of the table below) measures the impact of project management on the level of unemployment in Central African countries. It is therefore important to recall that two variables related to the management of development projects have been retained, namely: the financial management of development projects and technical management. In addition, the statistics of the AR(1) and Sargan tests obtained during the estimation are insignificant while that of the AR(2) test is significant, which proves that our model has been well specified and that the instruments used are valid. 

As can be seen, both indicators of development project management have a positive effect on economic growth in Central African countries. Indeed, the table above shows that the financial management of development projects in Central Africa has a positive and significant effect of about 0.5% on the economic growth of the countries in this zone. On the other hand, the technical management of development projects has a positive but insignificant effect on economic growth of about 0.7%. These results confirm those of Arndt et al (2015), Sachs (2005) and Stiglitz (2007), who believe that when a project is financed by bilateral or multilateral aid, it targets only the vulnerable segments of society, and this allows the eradication of poverty and the promotion of growth in developing countries. 

In the same vein, our results also show that the financial and technical management of development projects in Central African countries have a negative effect on unemployment of 0.01 and 0.3 respectively. In other words, the management of development projects in these countries contributes to the reduction of unemployment and the promotion of full employment. This corroborates the work of Moyo (2009), Doucouliagos and Paldam (2006) and Burnside and Dollar (2004). However, it is important to recall that it is the technical management of development projects that contributes much more to the reduction of unemployment in terms of its significance level at 1%. 

With regard to the control variables, we observe that aid and grants, financial development and the quality of governance have negative effects on economic growth and unemployment in the CAPs. In other words, these three variables do not promote economic growth, but do contribute to the reduction of unemployment. On the other hand, foreign direct investment has a positive effect on economic growth and a negative effect on unemployment. 

IV- Conclusion and recommendation 

At the end of this work, the aim was to present empirically the effect of the management of development projects on the economic performance of Central African countries. Thus, before proceeding with the estimates, we first presented the related methodology. The results showed that, in Central Africa, the management of development projects is carried out at two major levels: firstly, financial management and secondly, technical management. Thus, in the context of our econometric results, we found that, overall, the management of development projects in Central Africa has a positive effect on the economic performance of the PAC. Indeed, the financial management of development projects in Central Africa has a positive and significant effect of about 0.5% on the economic growth of the countries in this zone. On the other hand, the technical management of development projects has a positive but insignificant effect on economic growth of about 0.7%. Our results also show that financial management and technical management of development projects in Central African countries have a negative effect on unemployment of 0.01 and 0.3 respectively. In other words, the management of development projects in these countries contributes to the reduction of unemployment and the promotion of full employment. It is therefore clear that, overall, the management of development projects in Central Africa improves the economic performance of these countries. This leads us to make two major recommendations: firstly, the need to set up a research programme to strengthen the implementation of development programmes in Africa. Secondly, to adapt the management of development projects to African realities. 

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¹ The very first Millennium Development Goal aims to reduce poverty by half between 1995 and 2015. 

² For the OECD DAC (2020), Official Development Assistance is "aid provided by states for the express purpose of promoting economic development and improving living conditions in developing countries". In other words, this definition shows us that, when we talk about ODA, it aims to enable vulnerable and poor countries to improve not only their economic indicators, but also to promote the well-being of the populations of these countries in order to reduce poverty.