Cemac: Why is Economic Growth Lagging and What Can be Done About It?1
During the last two decades, the average growth of the Economic and Monetary Community of Central Africa (CEMAC) has been slower than the sub-Saharan African (SSA) average. Given that many CEMAC countries aspire to reach emerging country status within the next two decades, this paper, using a growth accounting approach, identifies the main components of growth and analyzes the differences with respect to comparator countries. Results of the analysis show that convergence of CEMAC countries toward emerging market levels has stalled, while some lower-income, faster-growing economies have been catching up. Decomposing growth by contributing factors, we find that total factor productivity has had a negative impact on CEMAC’s growth.
1. This paper compares CEMAC countries’ growth performance with that of comparator countries. Specifically CEMAC countries are compared with SSA countries; SSA emerging markets; SSA frontier economies; and a group of selected Asian countries.2,3 Although CEMAC’s average per capita income is higher than the average of SSA countries and of SSA frontier markets, because of abundant oil resources, CEMAC’s per capita GDP growth has been slower than in comparator countries.
2. Improving CEMAC’s productivity requires, among others measures, addressing its challenging business climate and promoting a more diversified economy with a stronger private sector. Because CEMAC lags behind its peers in terms of structural competitiveness and governance, this paper assesses the impact of reforms in specific areas of the World Bank’s “Doing Business” indicators. This is done through an analysis whereby the CEMAC countries catch up with benchmark groups in specific areas of the business climate. By comparing how the regional ranking would improve overall with various scenarios of catching up, this paper identifies which reforms would provide the highest gains in improving the business climate. The last part of the paper analyzes channels through which ongoing shortcomings in the business climate undermine gains in the overall competitiveness of CEMAC economies.
3. This paper makes three contributions to the analysis of long-term productivity in CEMAC. The first one is the scope as we compute production functions for all SSA countries. Second, the accounting methodology in growth rates allows us to make cross-country and cross-region comparisons. Third, we identify the areas of weaknesses with respect to business climate and competitiveness, and the areas for most effective reforms.
B. Growth Facts
4. Per capita GDP growth in CEMAC has been slower than in most SSA countries. Although average per capita income in SSA, African FEs, and Asian peers has risen steadily, average per capita GDP in CEMAC has grown more modestly since the early 2000s (Figure 1, upper left panel). Moreover, a country disaggregation shows that the high average CEMAC per capita growth largely stems from the oil boom in Equatorial Guinea (Figure 1, upper right panel) which started in the mid-1990s. CEMAC experienced a convergence process toward SSA EM income levels from the mid-1990s to the mid-2000’s when its average GDP per capita grew faster than in EMs. However, since 2005, and despite high oil prices until recently, the convergence process has stalled. As a consequence, the per capita income gap has remained at about 30 percent of the SSA EM income level. At the same time, faster-growing, lower-income SSA FEs have been catching up (Figure 1, middle left panel). In 2000–13, the average per capita real GDP growth in CEMAC was 1.4 percentage points slower than in the SSA frontier countries. (Figure 1 middle right panel). This comparison shows an even larger decrease when excluding Equatorial Guinea and considers the five other CEMAC countries’ (henceforth the “CEMAC 5”; Figure 1 middle right panel); this implies the convergence was largely due to the oil sector.
Figure 1.CEMAC: Growth Profile, 1990–2013
5. GDP growth in the CEMAC has been highly volatile and dependent on oil. With the exception of the Central African Republic (CAR), CEMAC economies remain mainly driven by the oil sector; this explains the region’s higher-than-average growth volatility. (Figure 1, bottom panels). Oil sector performance explains the very rapid per capita growth in Equatorial Guinea and the severe contraction of the Gabonese economy in 1999.4 Moreover, the disparity in per capita GDP across CEMAC countries is relatively high and has been widening in the last two decades. While in the early 1990s the regional average per capita GDP was about 20 percent of the average in the two richest countries (Equatorial Guinea and Gabon), in 2013 this ratio was around 16 percent.
C. Growth Accounting and Productivity in the CEMAC
6. The analysis is based on a GDP growth decomposition of 41 SSA countries and a group of 8 Asian peer countries to identify the sources of economic growth and explain income differentials with peers. Based on Solow (1957), we assume a Cobb-Douglas production function, constant returns to scale, and perfect competition where output can be written as:
where Ki and are Hi respectively physical and human capital stocks, and Ai is interpreted as total factor productivity (TFP, also referred to as productivity) in country i with α=0.4.5 We use the World Bank World Development Indicators (WDI) database for labor force and the IMF World Economic Outlook (WEO) database for physical capital and real GDP growth rates. We then derive TFP using the above formula.
7. In this section, we present the results of growth decomposition in 1991–2012. Figure 2 presents the growth decomposition of CEMAC (i.e., all CEMAC members except Equatorial Guinea), the SSA average, WAEMU countries, African FEs, African EMs, and Asian peers. Over the last two decades, average annual GDP growth in CEMAC was about 3 percent. Labor contributed to roughly 1.5 percent of the total GDP growth. Capital investment raised growth by 1.7 percent while the decrease in TFP exercised a negative effect of -0.3 percent on regional growth (Figure 3).
Figure 2.Growth Decomposition, 1991–2012
Source: IMF staff estimates.
Figure 3.Average Productivity, 1991–2012
Source: IMF staff estimates.
8. Compared with the benchmark country groups, CEMAC’s growth was slower. CEMAC had the slowest average growth over the period and it was also the region with the largest negative contribution of TFP growth, partly offsetting the input of labor and the increase in capital. In particular, Figure 4 and Annex Table 1 show that:
CEMAC’s growth was 1 percent slower than the SSA average over the whole period. The main drivers of the gap were mostly lower productivity gains and lower capital contribution. The negative TFP contribution explains about three quarters of the gap in the first decade (1991–2000), while lower capital investment caused the entire gap in the second period (2001–12).
Compared to Asian peers, growth in CEMAC was 2.5 percentage points slower and the difference was explained both by less capital contribution (-1.7 percentage points explaining about 60 percent of the gap) and lower productivity (-1 percentage point difference).
Compared to SSA frontier markets, the gap in terms of productivity is striking. In spite of higher capital and labor inputs, the negative contribution of TFP is dragging GDP growth down.
Raising TFP in the CEMAC to the level of the SSA frontier markets or the Asian peers would have lifted GDP by 2.5 and 1.0 percentage points, respectively, in the period covered by this analysis (1991–2012).
Figure 4.CEMAC: Differences in Growth and Factor Decomposition, 1991–2012
Source: IMF staff estimates.
|Initial average rank||Starting a Business||Dealing with Construction Permits||Getting Electricity||Registering Property||Getting Credit||Protecting Minority Investors||Paying Taxes||Trading Across Borders||Enforcing Contracts||Resolving Insolvency|
|Central African Rep||1||0||1||0||1||0||1||1||1||1|
D. Improving CEMAC’s Growth Potential
9. One explanation for CEMAC’s negative TFP contribution to growth could be its challenging business climate and governance. Empirical analysis using firm survey data have established the links between poor business climate and low productivity in developed and developing countries (Bastos et al., 2004, Eifert et al., 2005, Lall et al., 2005). CEMAC countries lag behind other SSA countries in terms of the quality of the business climate—this is shown by indicators on perceived corruption (Transparency International); ease of doing business (World Bank); or governance (World Economic Forum). Figure 5 compares the 2015 Doing Business rankings and the evolution of the indicators between 2007 and 2015 for CEMAC and it benchmark groups. It shows that CEMAC has the lowest rankings, behind most of the benchmark groups. Between the 2014 and 2015 rankings, four CEMAC countries regressed, one kept its ranking (Chad), and one advanced by one position (Congo).
Figure 5.CEMAC: Changes in Doing Business Indicators, 2007–15
Sources: World Bank Doing Business Indicators Database and Staff Estimates.
10. Empirical research also suggests that weak governance may hamper productivity (Ndulu and O’Connell, 1999). In the case of CEMAC, weak governance indicators and lack of improvement may have also impacted productivity. Figure 6 presents the changes in the World Bank’s governance indicators and shows that CEMAC continues to score below the other groups, with limited progress shown. For example, Figure 6 shows that CEMAC ranks in the bottom 28 percent in the World Governance Indicator Raking, and has only made improvements in 50 percent of its governance indicators between 1996 and 2013. Conversely, African FEs are ranked much higher at about 43 percent and made improvements in 100 percent of theirs indicators. That means that CEMAC should have made a lot more progress (e.g., adopt more aggressive reforms) to catch-up with comparator groups of countries.
Figure 6.Changes in World Governance Indicators, 1996–2013
Sources: World Bank Governance Indicators Data base and Staff Estimates.
11. Facilitating trade and payment of taxes would significantly improve the business climate. To assess the impact of selected reforms, we set each CEMAC doing business indicator to the average level of the African FEs. Figure 7 shows that CEMAC’s average ranking would improve by 24 positions if it managed to reach the average level of indicators of African FEs. This implies that the region has a considerable margin to implement business-friendly reforms. In particular, it has room for improvement in paying taxes, facilitating trade, improving contract enforcement, property registration and resolving insolvency (Figure 8). Paying taxes and trading across borders are two areas of particular weakness in the region. On average, it takes 572 hours per year in CEMAC versus 304 in SSA countries to pay business taxes, and the waiting time is of 40 days for exports and 50 days for imports. Reforms in these areas would yield the highest benefits in terms of better rankings.
Figure 7.CEMAC: Impact of Reforms in Doing Business Indicators
Sources: IMF staff estimates; and World Bank Doing Business Indicators database.
Figure 8.CEMAC: Governance and Business Climate Profile
Source: World Bank Doing Business Indicators Database.
12. The impact of reforms can vary substantially at the individual country level. For example, a reform in procedures to start a business in Equatorial Guinea would bring the country 20 positions ahead of its current rank, whereas the impact is only 2 ranks in the Congo. Table 1 below shows that for CEMAC countries, the areas where reforms would be the most efficient are those pertaining to trading across borders, paying taxes, starting a business, and resolving insolvency. Table 1 summarizes the impact of doing business reforms by business climate indicator and by CEMAC country.
E. CEMAC’s Competitiveness Challenge
13. CEMAC’s limited progress in business climate reforms most likely had an impact on its overall competitiveness. As mentioned in previous sections, several studies have identified the relationship between the business climate and productivity. Moreover, the World Economic Forum has developed a competitiveness index closely related to country productivity.6 The 2014–15 World Economic Forum (WEF) Global Competitiveness Index (GCI) ranks three CEMAC members (Cameroon, Chad, Gabon) respectively 115, 142, and 105 of 143 countries. The CEMAC average rank would be 121 of 143 countries. Figure 9 shows that the region has the lowest competitiveness ranking of all our benchmark groups.
Figure 9.CEMAC: Global Competitiveness Ranking, 2014–15
Source: World Economic Forum Global Competitiveness Database and Staff Estimates.
14. The WEF classification suggests that if CEMAC is to reach higher levels of growth, it must increase productivity while ensuring sufficient physical factor accumulation. Based on the WEF’s categorization of economic development,7 assimilating the average of Cameroon, Chad, and Gabon to a synthetic CEMAC country, this latter would probably be considered a “transition economy.” Hence, the region should be moving from the less developed economic structure (Stage 1 economies in WEF’s classification) to emerging or frontier status (Stage 2 economies). For the WEF, this means that “basic competitiveness requirements”8 account at least for 50 percent of the assessment of CEMAC’s overall competitiveness. To move from Stage 1 to Stage 2, the basic requirements need to be met, such as the level of infrastructure or the quality of institutions must be able to support productivity gains. This demands structural reforms in the efficiency of tax administration, investment, education, and enhanced competition in domestic markets.
15. Figure 10 shows that CEMAC has significant room to improve its competitiveness. CEMAC ranks low with respect to comparator groups on basic requirements (institutions, infrastructure, education, and training) and on efficiency enhancers (efficiency of the goods market and financial market development). The difference is especially striking with respect to African FEs, where CEMAC is at the bottom of most of these key competitiveness factors. CEMAC only performs well in terms of the macroeconomic environment because of its relatively low inflation performance.
Figure 10.CEMAC: Global Competitiveness Index, 2014–15
Source: World Economic Forum Global Competitiveness Database and Staff Estimates.
16. In addition to the WEF, other indicators indicate CEMAC’s relatively weak competitiveness. Figure 11 presents the evolution of CEMAC’s real effective exchange rate (REER), and non-oil exports between 1995 and 2013 compared to the average of African FEs. It shows a fall in non-oil CEMAC exports, which was coupled with an appreciation of the REER. Conversely, the average of the African FEs has a significant increase in (non-oil) exports despite an appreciation of the REER similar to that of CEMAC. Therefore, even if the appreciation of the REER in CEMAC was partly due to economic fundamentals, deeper structural reforms could have supported greater productivity gains and the diversification of regional export sectors.9
Figure 11.CEMAC: Non-oil Exports and Exchange Rates, 1995–2013
Source: World Economic Outlook Database and Staff Estimates.
17. In spite of benefiting from oil wealth in the last two decades, CEMAC’s growth was slower than the SSA average. Moreover, if we exclude Equatorial Guinea whose growth path is linked to its recent—and very large—oil boom, CEMAC’s growth is notably slower than that of African FEs and Asian peers.
18. Looking at growth factors, the main explanatory factor is the negative contribution of TFP to CEMAC’s growth. Policies to reduce the productivity gap with African FEs could yield up to 2.5 percentage points of additional annual growth.
19. To reduce the productivity gap, CEMAC should address its challenging business climate and weak governance. Important reform gains would be obtained by focusing on (i) facilitating trade across borders; and (ii) simplifying tax payments.
20. CEMAC’s limited progress in business climate reforms probably had an impact on its overall competitiveness. The long-term objective should be more ambitious reforms to resume the convergence trend with leading comparator economies to improve standards of living, ensure the structural transformation of the region, and facilitate the reduction of oil dependency.
(Average annual variation in percent)
|GDP growth||PPP GDP per capita||Physical Capital||Labor||TFP|
|CEMAC – SSA countries|
|CEMAC – African EMs|
|CEMAC – African FEs|
|CEMAC – Asian peers|
Arnolda JensM.Mattoob and Narciso2008. Services Inputs and Firm Productivity in Sub-Saharan Africa: Evidence from Firm-Level Data. Journal of African Economics17 (4): 578–599.
BastosFabiano and Nasir2004. Productivity and the Investment Climate: What Matters Most?World Bank Policy Research Working Paper No. 3335. Available at SSRN: http://ssrn.com/abstract=610379.
EifertBenn and GelbAlan and Ramachandran2005. Business Environment and Comparative Advantage in Africa: Evidence from the Investment Climate Data. Center for Global development Working Paper No. 56. Available at SSRN: http://ssrn.com/abstract=1112857 or http://dx.doi.org/10.2139/ssrn.1112857.
HallR. and Jones1999. Why Do Some Countries Produce So Much More Output Per Worker than Others? The Quarterly Journal of Economics114 (1): 83–116.
KindaT.Plana and Veganzones-Varoudakis2011. Firm Productivity and Investment Climate in Developing Countries: How Does Middle East and North Africa Manufacturing Perform? The Developing Economies49: 429–462. doi: 10.1111/j.1746–1049.2011.00146.
LallSomik V. and MengistaeTaye2005. The Impact of Business Environment and Economic Geography on Plant-Level Productivity: An Analysis of Indian Industry. World Bank Policy Research Working Paper No. 3664. Available at SSRN: http://ssrn.com/abstract=770952 or http://dx.doi.org/10.2139/ssrn.770952.
MengistaeT.PattilloC2004Export Orientation and Productivity in Sub-Saharan Africa. International Monetary Fund Staff Papers51(2):327–353.
Ndulu B. and O’Connell1999. Governance and Growth in Sub-Saharan Africa, The Journal of Economic Perspectives13 (3): 41–66.
SolowR.1957. Technical Change and the Aggregate Production Function. Review of Economics and Statistics39 (3): 312–20.
OlsonMSarna and Swamy2000. Governance and Growth: A Simple Hypothesis Explaining Cross-Country Differences in Productivity GrowthPublic Choice Journal102: 341–364
SubramanianUma and AndersonWilliamP. and LeeKihoon2005. Measuring the Impact of the Investment Climate on Total Factor Productivity: The Cases of China and Brazil. World Bank Policy Research Working Paper No. 3792. Available at SSRN: http://ssrn.com/abstract=874811.
TahariA.GhuraAkitoby and BrouAka2004 “Sources of Growth in Sub-Saharan Africa” IMF Working Paper WP/04/176.
VeeramaniC. and Goldar2005. Manufacturing Productivity in Indian States: Does Investment Climate Matter? Economic and Political Weekly40 (24): 2413–2420http://www.jstor.org/stable/4416747.
World Economic Forum (2015) 2014–15 Global Competitiveness Report “Definition of Competitiveness”http://reports.weforum.org/global-competitiveness-report-2014–15/methodology/.
World Economic Forum (2015) 2014–15 Global Competitiveness Report Appendix A: Statistically testing the validity of the Global Competitiveness Indexhttp://reports.weforum.org/global-competitiveness-report-2014–15/gci-and-growth-empirical-analysis/.
World Economic Outlook (International Monetary Fund) (2013) Hopes Realities and Riskshttp://www.imf.org/external/pubs/ft/weo/2013/01/pdf/text.pdf.
Prepared by José Gijon, Boriana Yontcheva, and Zaki Dernaoui
We compare CEMAC’s growth profile with a group of 41 sub-Saharan African (SSA) countries, 10 African frontier economies (African FEs), eight West African Economic and Monetary Union (WAEMU) countries, five African emerging countries (African EMs) and 8 Asian countries with similar levels of income (Asian peers). SSA countries are: Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde, Central African Republic (CAR), Comoros, Congo Republic, Democratic Republic of Congo (DRC), Côte d’Ivoire, Equatorial Guinea, Ethiopia, Gabon, the Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Madagascar, Malawi, Mali, Mauritius, Mozambique, Namibia, Niger, Nigeria, Rwanda, Sao Tome, Senegal, Seychelles, Sierra Leone, South Africa, Swaziland, Tanzania, Togo, Uganda, and Zambia. WAEMU countries are: Benin, Burkina Faso, Côte d’Ivoire, Mali Niger, Senegal and Togo. African EM countries are: Botswana, Cape Verde, Namibia, Seychelles, and South Africa. African FEs are: Ethiopia, Ghana, Kenya, Mauritius, Mozambique, Nigeria, Senegal, Tanzania, Uganda, and Zambia. Asian peers are: Bangladesh, Cambodia, India, Indonesia, Lao PDR, Nepal, and Vietnam.
We use four comparators, but most of CEMAC’s benchmarks in this paper are set with respect to African FEs, the group of countries, which is the main “emergence” reference for CEMAC authorities.
Gabon underwent a severe economic recession in 1999. Real GDP contracted by 9.6 percent, reflecting a drop in oil output (by 11.4 percent) and an estimated 8.9 percent decline in real non-oil GDP (Gabon 2000 Country Report 00/203). The sharp contraction in activity in the non-oil sector was due to drastic cuts in the public investment program, a weakening performance of the public corporate sector, and a wait-and-see attitude of the private sector.
The value for α used is based on work on growth accounting in developing countries (IMF Working Paper 04/176) and is relevant to all countries in the sample.
The World Economic Forum’s Global Competitiveness Report empirically tests the validity of its Global Competitiveness Index and tests its relationship with country productivity (WEF, 2015 b).
The WEF considers three levels of economic development: Stage 1 (low income, factor-driven economy) whose competitiveness relies on basic economic requirements such as institutions, infrastructures, macroeconomic environment, health and primary education. Stage 2 (middle income, efficiency-driven economies) where efficiency enhancing issues related to a more advanced economic structure, such as higher education and training, goods market efficiency, labor market efficiency, financial market development, technological readiness, and market size. Stage 3 (advanced economies or innovation-driven economies), where basic requirements and efficiency issues are less relevant, but the level of innovation and business sophistication are essential for competitiveness. In addition to the three stages of economic development, the WEF classifies certain countries as transitioning from one stage to the next. For example, most oil producers in developing countries are considered in transition from Stage 1 to Stage 2 at different speed levels (see WEB, 2015).
The GCI assesses competitiveness based on twelve pillars grouped in three main categories: (1) basic requirements (which include four pillars: institutions, infrastructures, macroeconomic environment, and health and primary education); (2) efficiency enhancers (which include six pillars: higher education and training, goods market efficiency, labor market efficiency, financial market development, technological readiness, and market size); and (3) innovation and sophistication factors (which include two pillars: business sophistication and innovation).
See Chapter 4 of the IMF’s WEO (April 2013) “Breaking Through The Frontier: Can Today’s Dynamic Low-Income Countries Make It?; and Mengistae and Pattillo (2004).