West African Economic and Monetary Union: Selected Issues

International Monetary Fund. African Dept.

doi:10.5089/9781475567595.002.A005

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West African Economic and Monetary Union: Selected Issues

Author: International Monetary Fund. African Dept.

Publication Date:: 13 Apr 2015

eISBN:: 9781475567595

Language:: English

Keywords:: ISCR; CR; WAEMU; GDP; export product diversification; population structure; export quality; export partner index; export partner diversification; Structural transformation; Agricultural sector; Export diversification; Exports; West Africa

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In recent years, the IMF has released a growing number of reports and other documents covering economic and financial developments and trends in member countries. Each report, prepared by a staff team after discussions with government officials, is published at the option of the member country.

Abstract

Growth, Structural Transformation, and Diversification in the Waemu¹

Growth in the WAEMU in the past has been disappointing and highly volatile compared to growth in a group of benchmark countries. The region’s economies remain highly exposed to exogenous shocks, such as droughts. This note examines slow structural transformation and diversification as candidate explanations for this relative underperformance: The majority of the region’s population is employed in low-productivity agriculture and the secondary sector is underdeveloped. Further structural transformation and diversification of output and exports could yield significant growth dividends, but will be challenging in the context of a rapid projected increase the workforce over coming decades, much of which would need to be absorbed by the agricultural sector. Policies could focus on easing the constraints to structural transformation in key areas such as education and the business climate, as well as devising a clear strategy for tackling the challenges posed by rapid population growth.

A. Growth, Volatility and Productivity

1. Growth in the WAEMU has been comparatively weak and highly volatile over the last 25 years (Figure 1). Despite a lower starting level of income per capita, WAEMU countries – both on average and individually – have grown more slowly over the past two decades relative to the rest of Sub-Saharan Africa. With real per capita growth averaging only 0.5 percent over the past 25 years, WAEMU has underperformed relative to a set of peer countries in both SSA and Asia who had a similar level of per capita income to the WAEMU in 1990, but who are now almost two times richer in PPP terms.² This underperformance has been most pronounced since the turn of the century; although growth in the WAEMU was weaker in absolute terms in the 1990s, it is the 2000s that appears to be a lost decade of sorts. In this period, growth took off in many low income countries, but saw only a slight acceleration in the WAEMU. Growth also remains relatively more volatile than in peer countries, despite having declined in recent years.

2. Comparatively low human capital accumulation and total factor productivity appear to have driven slow growth (Figure 2). A growth decomposition exercise suggests that two thirds of growth over the past two decades can be attributed to labor accumulation, while capital accumulation accounts for almost a third. In contrast, human capital and productivity appear to have been the main drivers of the mediocre growth performance, and are the factors in which the WAEMU lags most relative to other countries. Basic education rates in the WAEMU are significantly lower compared to SSA and Asian benchmark countries, and more unequally distributed across the population. Public investment efficiency remains relatively low, and a challenging business environment impedes productive private sector activity (see also note on the external stability assessment). These factor ‘gaps’ suggest that policies should target access and quality of education, public financial management (PFM) reforms to improve the efficiency of public investment, and key areas of the business environment, such as contract enforcement and efficient electricity provision.

B. Recent Trends in the Structure of Output and Exports

Output

3. There has been relatively little evidence of structural change in the WAEMU over time (Figure 3). The sectoral composition of output has remained remarkably stable and the level of diversification low. The service sector accounts for over 50 percent of economic activity, while agriculture and industry account for around 30 percent and less than 20 percent respectively, shares that have changed little since 1970 for when data are first available. The level of output diversification – based on a Theil Index measure (Box 1) – is also low and has remained stagnant, in contrast to faster growing benchmark countries, which have witnessed sharp increases in diversification over time.

4. The WAEMU has experienced a modest de-industrialization, contrasting with a sharp industrial expansion in this sector among benchmark countries. The share of the manufacturing sector in output fell from 14 percent to 10 percent in the WAEMU but increased from 10 percent to 16 percent in the Asian peer group between 1990 and 2012. Conversely, the share of the agricultural sector has declined across low-income countries over time but has remained elevated in the WAEMU.

Box 1.

WAEMU: Export Diversification and Quality (IMF 2014a and Henn et al., 2013)

Export product diversification is captured by the Theil index which can be decomposed into a “between” and a “within” sub-index:

\begin{matrix} T h e i l I n d e x & = \frac{1}{N} Σ_{i}^{N} \frac{E x p o r t V a l u e_{i}}{A v e r a g e E x p . V a l u e} . In \frac{E x p o r t V a l u e_{i}}{A v e r a g e E x p . V a l u e} \\ = T h e i l_{b e t w e e n} + T h e i l_{w i t h i n}, \end{matrix}

in which i is the product index and N the total number of products. The “between” Theil index captures the extensive margin of diversification, i.e. the number of products, while the “within” Theil index captures the intensive margin (product shares).

Export partner diversification. The Theil index is also available across export partners. In this case, i and N in the above relationship represent the export partner index and number of export partners, respectively.

Export quality is measured by the export’s unit value adjusted for differences in production costs, relative distance to the trade partner, and the development of a country through the following relationship:

T r a d e P r i c e_{m x t} = α_{0} + α_{1} In u n o b s e r v a b l e q u a l i t y_{m x t} + α_{2} In p . c . i n c o m e_{m x t} + α_{3} I n D i s t a n c e_{m x t} + E r r o r_{m x t},

in which the sub-scripts m, x, and t denote importer, exporter and time period respectively.

Export

5. Export diversification has been stagnant on average (Figure 4). While there is some variation across WAEMU countries, on average diversification of exports has not taken place. In contrast, African benchmark countries diversified quite strongly after 1990 and have caught up to Asian benchmark countries whose diversification levels were already comparatively high before that time. The number of export partners has increased on average, but the shares of the main export partners remain dominant (see also note on the implementation of ECOWAS common external tariff).

6. Relative export quality has decreased for some sectors and been stagnant in others (Figure 5). While not far from benchmark country levels agricultural and manufacturing export quality has been stagnant on average. Relative commodity export quality has decreased steadily since the 1990 and appears to be far below that of benchmark countries now. The last chart in Figure 6 plots the export quality for each of the five largest sectors (2-digit SITC) in each WAEMU country. It suggest that, while some countries have succeeded in achieving a high product quality in at least one of their top export sectors, export concentration in many countries remains high in sectors of relatively low quality.

C. Fostering Growth through Structural Transformation and Diversification

7. Structural transformation and diversification of output has the potential to boost growth and reduce volatility in the WAEMU. Through the reallocation of resources from low productivity sectors such as agriculture, to higher productivity sectors such as manufacturing, ‘between-sector’ structural transformation can boost overall productivity. Structural transformation can also occur ‘within sectors’ creating productivity gains through, for example, implementing quality improvements to existing products and services, focusing production on relatively high value-added activities, or diversifying into new high value-added products. Output diversification can not only yield growth benefits but also reduce the volatility of growth, since new products and services are likely to be subject to different demand and supply shocks than existing ones.

8. Estimates suggest these benefits could be substantial (Figure 6).³ A 1 percentage point reallocation of labor from agriculture to manufacturing (keeping sectoral productivity levels constant) could raise output by 1.1 percent; such is the gulf in labor productivity levels between the two sectors. Similarly, a 1 percent increase in agricultural productivity (keeping resource allocation constant) could raise aggregate output by 0.3 percent, given the concentration of labor in this sector. Increasing output diversification to the level of benchmark countries could increase average growth by 0.6 to 0.9 percent. According to IMF (2014a), similar results hold for more export diversification. Here, a 1 standard deviation increase in LIC’s export diversification raises the growth rate by about 0.8 percentage points which translates into potential ½ percentage point growth gains if export diversification was raised to levels observed in Asian or SSA benchmark countries. Output growth volatility could be significantly reduced as well.

9. Policies to promote structural transformation and diversification should focus on addressing weaknesses that hinder entry into new lines of economic activity (IMF, 2014a). Weaknesses abound in the WAEMU in terms of the provision of infrastructure, the accumulation of human capital, the provision of finance, the establishment of trade networks and functioning of factor markets, the regulatory and institutional environment and the creation and management of ideas. Evidence from cross-country comparisons and individual case studies suggests that policies targeting these areas can be successful in fostering structural transformation and diversification, while the evidence is more mixed concerning the success of industry-focused and narrowly targeted measures (Box 2). That said, in the WAEMU, the agricultural sector does warrant special attention, given its large scope for productivity and quality improvements and its high share of employment (see Box 3).

Box 2.

WAEMU: Reforms which Foster Structural Transformation (based on IMF 2014a)

While there is no silver bullet of reform to foster structural transformation, the following general policies have emerged from successful country case studies and cross-country evidence (IMF 2014a, IMF 2013). Several of these policies may be addressed at both the national and regional levels.

Macroeconomic stability. In Vietnam, Rwanda, Malaysia and Tanzania successful diversification has coincided with stronger macroeconomic policies and a greater degree of stability.
Market entry. Reduced entry barriers can motivate entrepreneurs to expand their activities. In Vietnam collectivization was reversed which let to the emergence of a more diverse agricultural sector. In Rwanda a large divestment of state enterprises stimulated private sector activity, and in Tanzania, the dismantling of the state distribution system has positively affected the private sectors as well. The liberalization of the electricity market has been associated with higher degrees of structural transformation as well.
Education. Education has been associated with higher levels diversification and export quality. In Vietnam, years of education increased by about 50 percent in just two decades. In Rwanda, education has been expanded through ninth grade for all students.
Institutions and the business environment. Henn et al. (2013) report that a one standard deviation increase in institutional quality is associated with a 0.3 increase in quality upgrading. In Bangladesh, the removal of red tape has been associated with large investments in export processing zones.
Industrial policies. The support of specific industries has shown mixed results. In Malaysia and Bangladesh, the targeting of specific industries has been successful, but the targeted sectors have become dominant, decreasing export diversification. In natural resource dominated economies, however, such targeting may help the economy to diversify.

Box 3.

WAEMU: The Role of Agriculture in Structural Transformation

The agricultural sector accounts for a significant share of output, employment and external trade in the WAEMU and is likely to continue to do so in the medium term, even if there is an expansion of the manufacturing sector. Structural transformation within agriculture sector, through productivity improvements to existing activities and boosting the sector’s external performance should thus be key focuses of growth-enhancing policies.

Agriculture has the highest share of employment in the WAEMU and so inclusive growth depends on its prospects. Agriculture currently employs around 60 percent of the workforce in the WAEMU and is likely to remain the largest employer in the medium term. Applying the methodology in Fox and Thomas (2014), the number of workers in agriculture could double over the next two decades, with the share in total employment declining only from around 60 percent to 50 percent.

Policies targeting productivity improvements within agriculture may have the most traction in the medium term. The expected continued buoyant supply of agricultural labor suggests that large-scale ‘between-sector’ structural change (through a large shift in the share of workers in agriculture to the manufacturing sector) may be unlikely to materialize in the medium term. Instead, productivity improvements within the agricultural sector may provide a more fruitful focus for policies. The data suggest that agricultural productivity is relatively low in the WAEMU, indicating substantial scope for progress. For example, cereal yields remain below those in benchmark countries, while the relative quality of agricultural exports has been on a declining trend.

Another set of policies could focus on the external competitiveness of the agricultural sector. Although agriculture is the WAEMU’s largest employer and accounts for a large share of output, the agricultural trade balance is negative in some member countries, which in turn contributes to the regional external deficit (see note on external sector sustainability). Moreover, several countries import the same agricultural products that they export. The WAEMU’s trade balance could therefore be improved by policies encouraging countries to increase exports of agricultural products in which they produce domestically and have a comparative advantage, while at the same time to reduce imports of these products. The WAEMU would appear to have scope to increase the quantity of agricultural exports: as well as abundant agricultural labor, the share of uncultivated arable land is relatively high and several neighboring countries are large importers of agricultural products.

Food and agricultural imports in neighboring countries, 2011

Sources: World Bank and UN Comtrade database.

Food and agricultural imports in neighboring countries, 2011

	US$ bn	% WAEMU GDP
Nigeria	19.5	25.0
Algeria	11.5	14.7
Ghana	2.4	3.1
Mauritania	0.4	0.5
Gambia	0.1	0.1
WAEMU	4.9	7.2

Sources: World Bank and UN Comtrade database.

Food and agricultural imports in neighboring countries, 2011

	US$ bn	% WAEMU GDP
Nigeria	19.5	25.0
Algeria	11.5	14.7
Ghana	2.4	3.1
Mauritania	0.4	0.5
Gambia	0.1	0.1
WAEMU	4.9	7.2

Sources: World Bank and UN Comtrade database.

D. Demographic Trends and Employment

10. Structural transformation and improvements in diversification will take several years and occur against the backdrop of challenging population dynamics (Figure 7). Fertility rates in the WAEMU remain among the highest in the world, despite rapid declines in child mortality. As a result, WAEMU’s population structure is young; in 2010 almost half the population was below the age of 15. Over the next two decades, the population could double, from around 100 to 200 million, with a net annual increase in the labor force of around 1.3 million new workers.

11. A young population presents the opportunity for the WAEMU to benefit from a potentially large ‘growth’ dividend (IMF, 2015). According to UN population projections, the WAEMU will undergo a demographic transition over the next few decades, characterized by declines in infant mortality and fertility rates, with a resulting increase in the share of the working age population relative to the overall population. (Box 4). If fertility rates in the WAEMU decline from their current level of 5.7 children per woman to 3.8 (the UN’s most optimistic scenario), the share of working age population will increase from 52 percent to 58 percent by 2035. This demographic transition would be characterized by a higher share of the population that is potentially economically productive and can create income, boost fiscal revenues and ease the burden of fiscal expenditure on services such as healthcare and education. The potential impact on growth from these effects could be important. A recent paper (Drummond et al, 2014) estimated that a 1 percentage point increase in the working age population increases real GDP growth per capita by 0.5 percentage points.

12. But the demographic ‘growth dividend’ could remain elusive if fertility rates continue to decline only modestly or if the labor market is unable absorb the new workers in productive activities. If fertility rates in the WAEMU do not decline from their current elevated levels, the working age population share will also stay constant and the demographic transition and associated growth dividend will remain elusive in the medium term. Moreover, this scenario would not be innocuous for growth: the rapid increase in population would still pose enormous pressure on public services and infrastructure which are inadequate even at current population levels (Guengant and May, 2013). And even if fertility rates do decline, the increase in the working age population share may not yield growth benefits. Recent evidence (Fox and Thomas, 2013) suggests that there are speed limits with which the manufacturing and service sectors can absorb new workers, with any excess labor forced to seek informal employment in low productivity (often subsistence) agriculture (see Box 3), or enter unemployment. Both of these outcomes would pose risks to overall productivity growth, poverty levels and social cohesion.

13. Policymakers aiming to promote structural transformation cannot ignore these demographic challenges. A large number of new workers could be a boon for structural transformation and diversification as young workers are likely to be more flexible than existing ones to enter into new economic activities. Policies should thus focus on ensuring the demographic transition takes place, through managing fertility rates (for example, though promoting increased use of contraception) and harnessing the growth benefits of any transition, by providing the necessary education to ensure new entrants to the labor force have the skills to be fully employed in high value-added activities.

Box 4.

WAEMU: The Demographic Dividend

There are two main channels of demographic growth dividends (Mason and Lee, 2006 and IMF, 2015). The first is the result of a rapid growth of the working age population followed by a decline of fertility rates. As a consequence, the economy’s dependency ratios decline. The second arises later when parents have fewer children and accumulate savings in anticipation of aging. With a large number of young people projected to enter the labor market in the WAEMU in the next decades, the WAEMU could benefit from the first dividend if fertility rates were declining.

The demographic dividend has been substantial in several countries. For the case of India, Aiyar and Mody (2011) estimate that 40 to 50 percent of per capita growth has been attributable to the demographic dividend since the 1970s. In East Asia, the demographic transition has likely contributed one fourth to two fifth to a GDP per capita growth rate of around 6 percent between 1965 and 1990 (Bloom et al., 2003). However, even with an increasing ratio of working-age population to population, the growth effects of the demographic dividend are not automatic. The shift in the demographics needs to be complemented by investments in education to ensure the entrance of a productive workforce into the labor market at higher wages.

References

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Prepared by John Hooley and Monique Newiak.

WAEMU had a per capita income in 1990 of US$805 in PPP terms compared to $1401 in 2013. An SSA peer group consisting of Lesotho, Kenya, Rwanda, Ghana, Tanzania, Zambia, and Uganda had an average per capita income of $765 vs. $2003 in 2013. And an Asian peer group of India, Lao, Bangladesh, Vietnam and Cambodia had an average per capita income of $649 in 1990 vs. $2887 in 2013.

Doing Business indicators should be interpreted with caution because of the limited number of respondents, a limited geographical coverage, and standardized assumptions on business constraints and information availability.

The magnitude of these potential growth gains will vary across member economies, as a function of their different starting structures, productivity levels and extent of diversification.

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