Chapter

Chapter 3. Determinants of Non-Oil Growth in the CFA Zone Oil-Producing Countries: How Do They Differ?

Author(s):
Bernardin Akitoby, and Sharmini Coorey
Published Date:
August 2012
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Author(s)
Alexandra Tabova and Carol Baker 

Non-oil growth in the Coopération Financière en Afrique Centrale (CFA) zone oil-exporting countries has been lackluster despite the great natural resource wealth with which these countries are endowed. This is perhaps unsurprising given that only a few resource-rich countries have succeeded in diversifying their economies (Coxhead, 2007; and Gelb and Grasmann, 2010). This oft-cited “resource curse” is frequently attributed to three main factors: Dutch disease stemming from real exchange rate (RER) appreciation; the high volatility of oil- and mineral-related revenue; and institutional weaknesses, particularly in governance and transparency.

This chapter reviews the central determinants of non-oil growth in the oil-producing countries of the CFA zone and explores to what extent these countries differ from countries with comparable levels of development that do not depend on nonrenewable resources. This comparison is made by extending existing growth models to capture key features of CFA zone oil exporters—large development needs, institutional weakness, and market imperfections. By incorporating government spending and the efficiency of public goods,1 the analysis derives a tractable general equilibrium model of a small open economy with an oil-exporting sector and two non-oil productive sectors in which public investment financed by oil revenue is growth enhancing while institutional weakness and market imperfections lower growth.

Estimation results using a panel of 36 low-income countries (LICs) and CFA zone oil exporters are broadly in line with the theoretical predictions.2 Although RER appreciation is found to have negatively affected growth in all countries during the period 1985–2008, what distinguishes the oil producers of the CFA zone is the failure of public and private investment to boost non-oil growth.

CFA Zone Oil Exporters: Wealth and Development Needs

Despite their natural resource wealth, the oil-exporting countries of the CFA zone have large development needs. This disparity has widened since 2000, with provision of social services and basic infrastructure lagging far behind burgeoning oil wealth. Poverty is endemic, and social indicators are well below those of countries at the same level of income, and at times exacerbated by border and internal conflicts, which may also partly explain the widening infrastructure gap relative to a group of select LICs.

Moreover, non-oil growth—a prerequisite for sustained poverty reduction—has not kept pace with that of comparator countries. Although non-oil growth in CFA oil exporters has been only modestly lower than that of the net oil importers in the CFA zone, it has been significantly lower than in LICs with comparable levels of development, consistent with the more challenging business climate. See Figure 3.1.

Figure 3.1CFA Zone Countries and Select LICs: Non-Oil Growth and Development Indicators

Sources: IMF staff calculations; World Bank, 2009; and Transparency International.

Note: CFA = Coopération Financiére en Afrique Centrale; LIC = low-income country.

Literature Review

Given the size of oil wealth relative to their non-oil economies, the countries of the Central African Economic and Monetary Community (CEMAC) are natural candidates to suffer from the “resource curse” phenomenon. The literature has documented that oil discoveries and oil price spikes lead to higher government spending, RER appreciation, and a loss of competitiveness in the non-oil tradable sector (e.g., Gelb, 1988; Everhart and Duval-Hernández, 2001). For LICs, one of the largest challenges associated with the study of Dutch disease is determining how large the tradables sector would have been in the absence of the natural resources.

Empirical evidence on the role of the exchange rate generally suggests that substantial exchange rate overvaluation has a strong negative impact on growth (Razin and Collins, 1999; Aguirre and Calderón, 2005;Prasad, Rajan, and Subramanian, 2006). Rodrik (2008) and Berg and Miao (2010) stress the symmetric association of the RER with economic growth. The evidence both studies present shows that overvaluation of the exchange rate is bad for growth, while undervaluation is growth-enhancing. Although there is a consensus in the literature on the role the RER plays for economic growth, it can more accurately be described as a facilitating condition rather than a fundamental determinant (see Eichengreen, 2008, for a detailed discussion).3

Apart from the issue of exchange rate appreciation, for less-developed resource-rich countries, the study of the determinants of economic growth should take into account the structural problems present before the discovery of the natural resource and that persist long after the start of its exploitation. In this vein, a large body of literature has been devoted to the way in which the wider institutional framework and its quality affect the growth outcomes of investment in developing countries. Theoretical and empirical work in this area has traditionally focused on investment quality, with more recent work incorporating the impacts of institutional weakness and market inefficiency on growth (Barro, 1990; Barro and Sala-i-Martin, 2004; Rodrik, 2008; and Chakraborty and Dabla-Norris, 2009).

Rodrik (2008) and Chakraborty and Dabla-Norris (2009) incorporate market inefficiencies and institutional weaknesses in standard growth models and stress their growth-inhibiting effects. For example, Chakraborty and Dabla-Norris (2009) show how inefficient and corrupt bureaucracies interact with the provision of public investment, thereby diminishing the quality of public capital and private agents’ incentives to invest. Rodrik’s (2008) growth model allows for the study of the impact of market imperfections and institutional quality on GDP growth by incorporating in a standard growth model an “effective” tax rate on private investment and earnings. The assumption is that private investors and producers can retain only a portion of their investment returns and the value of producing the goods.

The theoretical literature on endogenous growth models has stressed the importance of the efficiency and quality of investment (total investment, or disaggregated into private and public investment) for its growth impact. Barro (1990) and Barro and Sala-i-Martin (2004) demonstrate how productive public investment raises long-term growth by driving up the returns to other factors of production. To address the role of public services (e.g., publicly financed infrastructure, enactment of property rights, rule of law, and investment in human development), government purchases of goods and services enter the non-oil production function as productive public goods and complements to the private productive inputs. It is this productive role that can create a positive link between oil resources and economic growth.

There is broad consensus in the empirical literature of the positive impact of public investment on GDP growth. For example, Easterly and Rebelo (1993) show that general government investment is consistently positively correlated with both growth and private investment. More importantly, using sector-specific investment data, the study indicates that the share of public investment in transport and communications is robustly correlated with growth. Following this earlier study, a large number of empirical studies have investigated the link between investment (or more specifically, public investment) and economic growth. A comprehensive survey of the empirical literature by Straub (2008) focuses on infrastructure investment and concludes that two-thirds of empirical studies published in the period 1990–2007 find a positive and significant link between infrastructure and growth.4 Studies using data on public capital stocks find a significant positive effect of public capital on economic growth (e.g., see Calderon and Serven, 2008).

The Model

To identify the factors affecting non-oil GDP growth, the present analysis developed a tractable model that reflects the production structure of the CFA oil-producing countries. The model is a general equilibrium model of a small, open economy with an oil-exporting sector and two non-oil productive sectors: a tradable and a nontradable sector. Oil production is modeled as exogenous. The analysis derives a closed-form solution for the non-oil GDP growth rate.

To capture the role of public goods and services in enhancing non-oil growth, the model in Rodrik (2008) is extended in two ways: first, productive government spending is incorporated following Barro and Sala-i-Martin (2004) and Barro (1990), and second, the efficiency of public goods is added. The government receives income from oil and purchases goods and services that enter the non-oil production function as productive public goods that are complements to private productive inputs. This productive role of public goods creates a positive link between oil resources and economic growth.

The model also allows for the study of the impact of market imperfections on non-oil GDP growth. These factors are incorporated into the model by the introduction of an effective tax rate on private investment and non-oil earnings. Specifically, it is assumed that private investors and producers can retain only a portion of their investment returns.

Consumption

Households maximize their expected lifetime utility with preferences for a single final good that is produced by the non-oil sector using tradable and nontradable inputs:

where ct is consumption and β is the discount rate. Households supply capital k to firms and make investment decisions. The budget constraint is

in which r is the return on capital and δ is the depreciation rate. Maximizing (3.1) subject to (3.2) leads to the familiar intertemporal optimality condition:

Production

The final consumption good is produced in the non-oil sector using tradable (T) and nontradable (N) inputs (ytT and ytN, respectively), under a constant-returns-to-scale Cobb-Douglas production function:

in which α denotes the share of tradable inputs in the final consumption good. Tradable and nontradable inputs are produced using private capital ktT and ktN, and public goods st:

and

in which θT is the share of total private capital allocated to the production of tradables, ϕ is the private capital share in the production of both tradable and nontradable inputs, and AN and AT are the levels of technology. The efficiency of public spending is captured by the parameter γ.

The inclusion of public goods st in the production function follows Barro (1990) and Barro and Sala-i-Martin (2004). Public goods are defined in the broad sense to include physical infrastructure (roads and highways), communications and water systems, property rights, law and order, and contributions to human capital development. These goods and services are assumed to be provided by the government without charge and are not subject to congestion effects. The productive share of government spending that enters the production function is measured by the quantity of government purchases of goods and services. Conceptually, as outlined in detail in Barro (1990), this is equivalent to assuming that the government does not do any production on its own and does not own capital; rather, it buys a flow of output that it makes available to private producers. For the private producers, these purchases constitute inputs available for the production of goods.

The tradable and nontradable goods are produced competitively. Given that public goods financed solely by oil revenue are provided without charge, and private sector use of public goods does not reduce the stock of available public services (no congestion), optimization is achieved by choosing the level of private capital while holding st fixed.

As can be seen in equations (3.5) and (3.6), public goods produce externalities in the production of both tradable and nontradable goods—the production function specification generates endogenous growth. Following Barro and Sala-i-Martin (2004), it is assumed that the government chooses a constant ratio of its productive purchases to GDP: sy. When styt is constant, the marginal product of capital is invariant to the stock of capital kt. The constant marginal product of capital delivers a standard AK-type growth model5 in which the growth rates of ct, kt, and yt are equal. This common growth rate can be determined from the expression of consumption growth.

Using the first order conditions for the two sectors and the fact that in equilibrium the marginal productivities across sectors are equal, the non-oil GDP growth rate can be expressed as follows:

As is apparent from equation (3.7), the non-oil growth rate depends positively on the share of public goods in total output that is used for productive purposes sy and on the efficiency of public spending γ. The productive use of public goods is growth enhancing. Moreover, g is monotonically increasing in sy, because a higher sy shifts upward the marginal product of capital. Because households do not pay taxes, households respond to the higher marginal product of capital by choosing a higher growth rate for consumption.

Market Imperfections

Next, the analysis takes into account the market imperfections prevalent in the CEMAC member countries. These imperfections are modeled following Rodrik (2008) by assuming that firms can only retain a share (1 – Tf) of the value of the goods they produce, and similarly, households can only retain a share (1 – Tk) of the income from their capital investment in the firms. Then Tf and Tk can be interpreted as the effective tax rates that firms and households face, respectively. For the purposes of the model, it is not important to distinguish between different types of market and institutional weaknesses.

The effective marginal product of capital r˜t can now be derived as

equation (3.8) shows that market imperfections lower the marginal product of capital. As a result, the growth equation can be written as

It is clear from equation (3.9) that the introduction of market imperfections leads to lower non-oil growth.

The Real Effective Exchange Rate

Although the exchange rate does not enter directly into the growth equations, it nevertheless plays an indirect role. The analysis closely follows Rodrik (2008) to emphasize the role of the exchange rate. The relative price of the tradable goods R=PTPN is the index of the RER in the model.

First, the analysis investigates how the exchange rate affects the allocation of capital across the two sectors by exploring the investment incentives in the intermediate sectors that produce the tradable and nontradable inputs. Equating the marginal products of capital in the tradable and nontradable sectors gives the following relationship:

equation (3.10) shows a positive relationship between the share of capital allocated to the tradable goods sector θT and the RER R. This is the supply-side relationship between the exchange rate and θT.

Second, the analysis explores how the exchange rate affects the demand for the tradable and nontradable inputs in the production of the final good. From the demand for the two inputs in the production of the final good, the following relation can be derived:

equation (3.11) shows the negative relationship between the share of capital allocated to the tradable goods sector θT and the RER R; an increase in R makes tradable goods more expensive and therefore reduces the demand for capital in the tradable goods sector θT. This is the demand-side relationship.

Rodrik (2008) shows that in equilibrium, the return to capital and growth are maximized when θT = α, that is, when the share of capital allocated to the tradable goods intermediate sector equals the final good output elasticity of the tradable input.

Empirical Investigation

The previous section showed that the productive use of public resources and the efficiency of investment are key ingredients for non-oil growth, and the RER affects growth indirectly through the role it plays in the allocation of capital across sectors. The discussion that follows tests these theoretical predictions for the CFA oil-exporting countries and explores the extent to which these countries differ from countries with comparable levels of development that are not highly dependent on oil or mineral resources.

A growth equation is estimated using a panel with country and time fixed effects:

in which gitn is real non-oil GDP growth and Xit is a vector of standard growth determinants such as initial income, investment share of output, share of government consumption in output, terms of trade, and a measure of openness to trade. The term DCFA oil is a dummy variable for the CFA oil exporters.6 The interaction term DCFA oilXit captures whether and how CFA oil exporters differ from the rest of the sample with regard to the way the standard growth determinants affect non-oil growth. The net impact of Xit on growth for the CFA oil exporters is captured by α2 + α3. The fixed-effects framework implies that the analysis uses changes in the explanatory variables to estimate changes in growth rates within countries. The time and country fixed effects are captured by the terms αt and αi, respectively.

In equation (3.12), Rit is a measure of the RER. Following Rodrik (2008) and Berg and Miao (2010), Rit is included directly in the non-oil GDP growth equation. Following Rodrik (2008), Delechat and others (2009), and Berg and Miao (2010), Rit is defined as the deviation of the actual RER from its purchasing power parity (PPP) value, adjusted for the effects of per capita income on the RER. The exchange rate over- or undervaluation is then the residual ϵitppp in a regression of the RER on per capita income:

The advantage of this measure is that it is directly comparable across countries. The dependent variable RERit in equation (3.13) is the log of the ratio of the market exchange rate to the PPP conversion factor; the log of per capita GDP ln yit accounts for the Balassa-Samuelson effect. Subscript t denotes the three-year average period, and i denotes the country. The set of time fixed effects is captured by αt. Following the literature, equation (3.13) is estimated for 181 countries for which data are available for the entire period (see Rodrik, 2008; and Delechat and others, 2009).

Turning to the estimation of equation (3.12), the dependent variable is real non-oil GDP growth, measured as a log difference. Initial income, measured as the log of real GDP per capita in constant 2000 U.S. dollars, is included to control for the Balassa-Samuelson effect. Openness to trade is defined as (Exports + Imports)/GDP, government consumption is measured as public consumption expenditure as a share of total GDP, and investment refers to gross fixed capital formation as a share of total GDP. The source of data is the IMF World Economic Outlook database, the time period covered is 1985–2008, and all variables are three-year averages, as is common in the literature to account for business cycle fluctuations.

Ideally, the analysis would assess the role of the stock of capital on non-oil growth, which would be in line with the theoretical model presented in the previous section. Constructing capital stocks, however, is nontrivial, especially for low-income and post-conflict countries, and requires a number of important assumptions about initial capital stocks, and the level and time profile of depreciation rates and the depreciation method.7 Rather than constructing stocks of capital across countries, the analysis follows the empirical growth literature that uses investment rates (see, for example, Ramey and Ramey, 1995; and Berg and Miao, 2010). Consequently, these empirical estimates do not explicitly take into account the efficiency of converting investment into capital.

As control groups to the CFA zone oil exporters, this inquiry uses (i) the CFA non-oil exporters and (ii) a sample of select LICs; in total, the final sample contains 36 countries (excluding Equatorial Guinea) and 270 observations.8 Although Rit =ϵitppp is used for the baseline specifications, as a robustness check the log of the real effective exchange rate is used as an alternative measure of the exchange rate.

As a starting point, Table 3.1, column 1, reports, for the entire sample of 36 countries, the results of a standard growth specification that does not distinguish among the three country groups. The specification is, therefore, a simplification of equation (3.12) in which the interaction terms DCFA oilXit are ignored. It closely follows Berg and Miao (2010), and the results confirm their findings with regard to both magnitude and significance of the coefficients. The results of this analysis are also consistent with empirical studies documenting that for developing countries exchange rate overvaluations are associated with lower growth rates (Rodrik, 2008; and Berg and Miao, 2010). The estimates for the exchange rate measures suggest that a 10 percent overvaluation is associated with a 0.25 percentage point lower growth rate. The estimates for investment and government consumption imply that a 1 percentage point increase in the share of investment in total GDP is associated with 0.127 percentage point higher growth, while a 1 percentage point increase in the share of government consumption in total GDP is associated with 0.076 percentage point lower growth. While it is common in the literature to include government consumption or investment shares in GDP growth regressions, the endogeneity problem can be nontrivial and results may reflect, to a certain extent, reverse causality (see, for example, Berg and Miao, 2010). The same issue applies to the inclusion of the RER in the growth regression. This concern might be addressed by a dynamic panel estimation using generalized method of moments (see Arellano and Bond, 1991).

Table 3.1Growth and Total Investment: Estimation Results
(1)(2)(3)
Non-oil growth (lagged)0.007–0.005–0.010
(0.06)(0.06)(0.06)
UNDERVAL (ln)0.025**0.025**0.028***
(0.01)(0.01)(0.01)
Initial income (ln)–0.078***–0.078***–0.081***
(0.02)(0.02)(0.02)
Terms of trade (ln)0.0070.0090.012
(0.01)(0.01)(0.01)
Openness0.0040.0070.003
(0.02)(0.02)(0.02)
Investment0.127***0.154***0.211***
(0.04)(0.05)(0.09)
Gov. Consumption–0.076**–0.095**–0.134**
(0.04)(0.04)(0.07)
CFAoil* Investment–0.159***–0.215***
(0.04)(0.08)
CFAnon-oil* Investment–0.143*

(0.09)
Adjusted R20.280.290.30
Observations270270270
Dependent variable: real non-oil GDP growth. Panel estimation with time and country fixed effects. Heteroscedasticity-consistent standard errors in parentheses. ***(1%), **(5%), *(10%).
Dependent variable: real non-oil GDP growth. Panel estimation with time and country fixed effects. Heteroscedasticity-consistent standard errors in parentheses. ***(1%), **(5%), *(10%).

Reassured by findings for the panel as a whole that are consistent with the empirical findings in the literature, the analysis proceeds to investigate the factors that have led to lower non-oil growth in the CFA zone oil-exporting countries. The results in Table 3.1, column 2, imply that although on average investment is positively and significantly associated with growth for the sample as a whole, for the CFA oil exporters investment is not related to growth in a statistically significant way. The coefficient on the interaction term in column 2 shows that for the CFA oil-exporting countries the impact of investment as a share of GDP on non-oil growth differs significantly from the impact it has for the rest of the countries in the sample. The net impact for the CFA oil exporters (α2 + α3) is −0.005, and a Wald test shows that this net coefficient is not statistically significant. The results in column 3 show that the lack of a significant relation between investment and non-oil growth for the CFA oil exporters is also evident when the analysis controls separately for the CFA non-oil countries. Similar to the results in column 2, the net effect of investment for the CFA oil exporters is −0.004, and a Wald test shows it is not statistically different from zero. Column 3 shows that for the group of CFA non-oil exporters the net effect of investment is positive and significant at the 1 percent level, although at 0.07 it is much lower than the estimate for the average LIC in the sample.

Next, as a robustness check, the analysis uses the log of the real effective exchange rate REERit as a measure of the exchange rate. Table 3.2 shows that the results do not change and are therefore robust to alternative measures of the exchange rate. The estimates for the exchange rate measures suggest that a 10 percent overvaluation or a 10 percent increase in the REER are associated with a 0.3 percentage point lower growth rate.

Table 3.2Growth and Total Investment Robustness Check: Estimation Results Using the REER versus the PPP Undervaluation Index
(1)(2)
Non-oil growth (lagged)–0.024–0.010
(0.07)(0.06)
REER (ln)–0.027***

(0.01)
UNDERVAL (ln)0.028***

(0.07)
Initial income (ln)–0.080***–0.081***
(0.02)(0.02)
Terms of trade (ln)0.0100.012
(0.01)(0.07)
Openness0.0010.003
(0.02)(0.02)
Investment0.206***0.211***
(0.07)(0.09)
Gov. Consumption–0.131**–0.134**
(0.05)(0.07)
CFAoil* Investment–0.211***–0.215***
(0.06)(0.08)
CFAnon-oil* Investment–0.141*–0.143*
(0.08)(0.09)
Adjusted R20.310.30
Observations270270
Dependent variable: real non-oil GDP growth. Panel estimation with time and country fixed effects. Heteroscedasticity-consistent standard errors in parentheses. ***(1%), **(5%), *(10%).Note: CFA = Coopération Financière en Afrique Centrale; PPP = purchasing power parity; REER = real effective exchange rate.
Dependent variable: real non-oil GDP growth. Panel estimation with time and country fixed effects. Heteroscedasticity-consistent standard errors in parentheses. ***(1%), **(5%), *(10%).Note: CFA = Coopération Financière en Afrique Centrale; PPP = purchasing power parity; REER = real effective exchange rate.

Turning to the composition of investment, because the oil revenue accrues to the governments of the oil-exporting countries in the CFA zone and public investment constitutes the majority of total investment in these countries, the analysis disaggregates investment into private and public investment as a share of GDP.9 The results are shown in Table 3.3.

Table 3.3Growth and Investment: Estimation Results When Investment Is Disaggregated into Public and Private Investment
(1)(2)
Non-oil growth (lagged)–0.002–0.018
(0.07)(0.07)
UNDERVAL (ln)0.026**0.029**
(0.01)(0.01)
Initial income (ln)–0.078***–0.081***
(0.02)(0.02)
Terms of trade (ln)0.0080.013*
(0.01)(0.01)
Openness0.0030.003
(0.02)(0.02)
Private Investment0.129**0.223*
(0.05)(0.10)
Public Investment0.117*0.191*
(0.06)(0.10)
Government. Consumption–0.078*–0.145*
(0.04)(0.07)
CFAoil* Private Investment–0.209**

(0.09)
CFAoil* Public Investment–0.279*

(0.16)
CFAnon-oil* Private Investment–0.206*

(0.12)
CFAnon-oil* Public Investment–0.011

(0.13)
Adjusted R20.280.30
Observations270270
Dependent variable: real non-oil GDP growth. Panel with time and country fixed effects. Heteroscedasticity-consistent standard errors in parentheses. ***(1%), **(5%), *(10%).Note: CFA = Coopération Financière en Afrique Centrale.
Dependent variable: real non-oil GDP growth. Panel with time and country fixed effects. Heteroscedasticity-consistent standard errors in parentheses. ***(1%), **(5%), *(10%).Note: CFA = Coopération Financière en Afrique Centrale.

For the sample as a whole, the positive association between both public and private investment and growth is preserved (Table 3.3, column 1). However, for the CFA oil exporters, the empirical analysis fails to detect any significant association between non-oil growth and either public or private investment: the net coefficients are −0.088 and 0.014, respectively, and a Wald test indicates that neither is statistically significant from zero (Table 3.4). The insignificant coefficient on the interaction term of the CFA non-oil exporters dummy with public investment means that the relation between public investment and growth in these countries does not differ from that found for the average LIC in the sample (0.19).

Table 3.4Impact of investment on non-oil growth
Total investmentPublic investmentPrivate investment
Coefficientp-value (Wald test)Coefficientp-value (Wald test)Coefficientp-value (Wald test)
Select LICs0.211**0.0180.191*0.0690.223**0.032
positive and significantpositive and significantpositive and significant
CFA zone non-0.068***0.0080.180*0.030.0170.697
oil exporterspositive and significantpositive and significantpositive but insignificant
CFA zone oil–0.0040.899–0.0880.5160.0140.612
exportersnegative but insignificantnegative but insignificantpositive but insignificant
The reported coefficients are from the regressions that use UNDERVAL as dependant variable as a measure of the exchange rate.Note: CFA = Coopération Financière en Afrique Centrale.
The reported coefficients are from the regressions that use UNDERVAL as dependant variable as a measure of the exchange rate.Note: CFA = Coopération Financière en Afrique Centrale.

To address the importance of the exchange rate for GDP growth in developing countries, as noted by the empirical literature, for all specifications the analysis includes an interaction term with either measure of the exchange rate (undervaluation index or the real effective exchange rate). This indicates whether the RER affects growth in the three country groups in a significantly different way. The results (not shown) indicate that there is no statistically significant difference in the way the RER is associated with GDP growth in the three country groups.

Turning to investment efficiency, Dabla-Norris and others (2011) constructed an index of the efficiency of the public investment management process for 71 developing countries. The efficiency of public investment is proxied by aggregate indicators of the quality and efficiency of four crucial stages of the investment process: investment project appraisal, selection, implementation, and evaluation. Although the focus of this index is on the quality of the process for managing public investment and the index is not available for all countries in the present empirical investigation, it nevertheless provides a useful benchmark for these empirical findings. With regard to country comparisons, the results here are broadly in line with the rankings based on this index. Notably, all but one of the CFA oil-exporting countries for which the index is available rank among the weakest performers.

Conclusion

Using a panel of 36 countries comprising LICs and CFA zone oil exporters, this inquiry finds that, controlling for the real effective exchange rate, investment by CFA zone oil- producing countries fails to spur growth. For LICs outside the CFA zone, private investment is found to have a fairly large, positive, and statistically significant effect on growth, while public investment has a somewhat weaker impact on growth. For CFA zone non-oil producers, the impact of public investment on growth is lower than in other LICs but positive and significant. In contrast, for CFA zone oil producers, the analysis fails to detect a significant association between non-oil growth and public investment. For both groups within the CFA zone, the impact of private investment is not statistically significant.

Investment may not raise non-oil growth in the oil-exporting countries of the CFA zone for many reasons. First, investment itself may be less efficient as a result of project selection or capacity constraints related to project appraisal, implementation, and monitoring. Second, it is likely that the necessary conditions for public investment to spur private sector activity are not in place. Such conditions include basic infrastructure (greater than a required threshold level), an enabling business environment, and strong institutions and governance. These conclusions are supported by this theoretical model, which demonstrates that public goods are growth enhancing, while weak institutions and market imperfections impede growth.

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The group of LICs includes Bangladesh, Benin, Burkina Faso, Burundi, Cambodia, the Central African Republic, Comoros, Ethiopia, The Gambia, Ghana, Guinea, Guinea-Bissau, Haiti, Kenya, Lao People’s Democratic Republic, Madagascar, Malawi, Mali, Mauritania, Mozambique, Niger, Rwanda, Senegal, Sierra Leone, Tajikistan, Tanzania, Togo, Uganda, Uzbekistan, Vietnam, and Zambia. The group of CFA oil exporters includes Cameroon, Chad, Republic of Congo, Côte d’Ivoire, and Gabon.

The facilitating role of the exchange rate refers to the fact that keeping the exchange rate competitive and avoiding excess volatility facilitates the growth-enhancing potential of the fundamentals. Eichengreen (2008) provides a detailed discussion of the link between the RER and growth, as well as of the potential and limitations of policy interventions.

Straub (2008) surveys 64 articles in refereed journals in the period 1990–2007. Although two-thirds of the empirical studies find a positive and significant association between infrastructure investment and growth, certain questions regarding policy implications (such as the optimal spending levels at different stages of development, and the impact of infrastructure investment on development gaps in different regions within countries or between urban and rural areas) have been more difficult to answer.

An AK model is the simplest form of endogenous growth model in which Y = AKαL1 – α has α set equal to 1.

The direct impact of market weaknesses on growth is not estimated because, as the theoretical model shows, these will manifest themselves through the effectiveness of investment in spurring growth.

See, for example, Klenow and Rodriguez-Clare’s (1997) analysis of the neoclassical growth model, in which they measure capital stocks by accumulating investment data in the Penn World Tables.

The group of CFA oil exporters includes Cameroon, Chad, the Republic of Congo, Côte d’Ivoire, and Gabon. The group of CFA non-oil exporters includes Benin, Burkina Faso, the Central African Republic, Guinea-Bissau, Mali, Niger, Senegal, and Togo. The group of LICs includes Bangladesh, Burundi, Cambodia, Comoros, Ethiopia, The Gambia, Ghana, Guinea, Haiti, Kenya, Lao People’s Democratic Republic, Madagascar, Malawi, Mauritania, Mozambique, Rwanda, Sierra Leone, Tajikistan, Tanzania, Uganda, Uzbekistan, Vietnam, and Zambia.

Public investment is gross public fixed capital formation as a share of total GDP; private investment is gross private fixed capital formation as a share of total GDP. During the estimation period, private investment in the CFA oil-exporting countries was mainly in the oil sector, while public investment was in infrastructure.

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