West African Economic and Monetary Union: Selected Issues
Author:
International Monetary Fund. African Dept.
Search for other papers by International Monetary Fund. African Dept. in
Current site
Google Scholar
PubMedClose
Publication Date:
02 Mar 2022
eISBN:
9798400204579
ISBN:
9798400204579
Language:
English
Keywords:
WAEMU banking commission; investment boost; WAEMU region; investment outlook; TFP relative; Human capital; COVID-19; Productivity; Private investment; Total factor productivity
Download PDF (595.5 KB)

This paper examines the persistent effects of the COVID-19 crisis on economic activity in the WAEMU over the medium term, focusing on three main channels: investment in physical capital, accumulation of human capital, and productivity, using a production function framework. The analysis suggests that the pandemic may have reduced medium-term growth by up to 1 percentage point under a scenario in which no mitigating policies are implemented to counteract scarring. In a proactive scenario in which policymakers take actions to mitigate scarring, the adverse effects of the crisis could be substantially diminished.

Abstract

This paper examines the persistent effects of the COVID-19 crisis on economic activity in the WAEMU over the medium term, focusing on three main channels: investment in physical capital, accumulation of human capital, and productivity, using a production function framework. The analysis suggests that the pandemic may have reduced medium-term growth by up to 1 percentage point under a scenario in which no mitigating policies are implemented to counteract scarring. In a proactive scenario in which policymakers take actions to mitigate scarring, the adverse effects of the crisis could be substantially diminished.

Damage Control: Quantifying the Medium-Term Scarring Effects of Covid-19 in the Waemu1

This paper examines the persistent effects of the COVID-19 crisis on economic activity in the WAEMU over the medium term, focusing on three main channels: investment in physical capital, accumulation of human capital, and productivity, using a production function framework. The analysis suggests that the pandemic may have reduced medium-term growth by up to 1 percentage point under a scenario in which no mitigating policies are implemented to counteract scarring. In a proactive scenario in which policymakers take actions to mitigate scarring, the adverse effects of the crisis could be substantially diminished.

A. Introduction

1. Large economic shocks, including the ones generated by health crises, can lead to persistent negative effects on economic activity over the medium term. There is ample evidence that certain events such as pandemics, financial crises, and political shocks can lead to persistent losses in output partly due to their effects on investment, human capital, and productivity (see Cerra and others, 2020 for a survey). In particular, a recent, but growing, literature shows that historical health crises (including SARS, H1N1, MERS, Ebola and Zika) can drag economic performance over extended periods of time, even though past episodes were not as severe as the ongoing pandemic.2

2. This chapter quantifies the potential scarring effects of the COVID-19 pandemic on growth. The chapter raises several macro-critical questions. How can the scarring effects of the COVID-19 crisis be quantified? Are different channels, such as physical investment, human capital, or productivity growth, similarly important to account for the adverse effects of the shock? What is the extent to which proactive policies can curb scarring effects? The analysis presented here attempts to provide insights on these questions in the context of the WAEMU based on a growth accounting framework. The paper also undertakes a sensitivity analysis around the assumptions behind the main scenarios and discusses some policy options to address the medium-term effects of the COVID crisis.

B. A Simple Framework to Quantify the Effects of the COVID-19 Crisis on Medium-Term Growth

3. This chapter uses a production function approach to quantify the change in medium-term growth in the WAEMU relative to pre-crisis estimates under different scenarios. There are several channels through which the COVID-19 crisis could affect medium-term growth (IMF, 2021). The paper focuses on three main mechanisms that could be particularly relevant for countries in the WAEMU region: i) investment in physical capital; ii) human capital accumulation, and iii) total factor productivity (TFP).

The starting point is a standard production function with human capital-adjusted labor:

Yt=AtKtα(htLt)1−α(1)

where Y is output, K is the physical capital stock, A is total factor productivity, L is labor, and h is the human capital index. Taking logs and denoting the growth rates for different variables g, medium-term growth over the 2021–26 horizon can be estimated as the sum of growth in total factor productivity (TFP), capital accumulation (physical and human), and labor force growth (population in the 15–64 age bracket):3

gYt≈gAt+αgKt+(1−α)ght+(1−α)gLt(2)

4. The analysis compares two alternative medium-term growth scenarios with the medium-term forecasts envisaged before the crisis hit. The comparisons are carried out relative to the pre-crisis estimation of medium-term growth (referred to as “scenario 1” in the Table 1 below). The two post-crisis scenarios (denoted as scenarios 2 and 3) describe the new medium-term outlook, which has been affected by the crisis: a “passive” scenario in which no active policies are taken to mitigate scarring; and a proactive scenario in which policymakers are proactive in counteracting the medium-term effects of the crisis. The main assumptions under each scenario are summarized in Table 1 and explained in detail in subsequent sections. Therefore, this paper specifically focuses on quantifying the difference in medium-term growth rates relative to pre-pandemic estimates, rather than the level of potential growth.4 In subsequent sections, the paper also conducts a sensitivity analysis by changing the underlying assumptions and assessing how results are impacted.

Table 1.

WAEMU: Key Assumptions for Medium-Term Growth Components under Alternative Scenarios

article image

C. Investment in Physical Capital

5. Increased uncertainty and other consequences of the COVID-19 crisis could lead to adverse persistent effects on investment in physical capital in the WAEMU. Several factors may hinder the medium-term outlook for private investment in the region, including supply chain disruptions linked to lockdowns both domestically and through international trade channels, a more volatile and uncertain external environment (including commodity prices and capital flows), the reduction of activity and dimmer prospects in the tourism sector, as well as higher overall uncertainty. In addition, the lack of fiscal space renders it unlikely that increases in public investment could be sufficient to fully offset these headwinds. As a result, total investment could be more subdued than under pre-pandemic trends, as discussed in further detail next.

6. Different vintages of IMF staff projections confirm the deterioration in investment prospects for the region with some differentiation across member countries. Within the framework described previously, the standard capital accumulation equation can be used to project growth in capital stock for the region, where It denotes investment and the depreciation parameter δ is obtained from the PWT database for each of the eight member countries: Kt+1 = It+(1 – δ)Kt. The investment rates as projected in the January 2020 vintage of the WEO database (the last vintage before the effects of the pandemic were incorporated into IMF staff’s projections) are used to obtain the pre-pandemic capital stock over the medium term, whereas the investment rates as of the April 2021 vintage (in which IMF staff would have already incorporated the effects of the crisis) are used in the scenario with post-crisis scarring (scenario 2). In general, there has been a deceleration in expected investment growth over the medium term across vintages, but the changes vary by country. For example, Benin and Burkina Faso are projected to experience declines in the average expected investment growth rate by 2.4 percentage points and 1.1 percentage point (relative to pre-pandemic estimates), respectively, while the decline in Senegal has been more muted. In the cases of Niger and Togo, there was actually an acceleration of expected investment growth across the vintages. Overall, for the region as a whole the investment outlook is expected to be dimmer relative to pre-pandemic projections.

Figure 1.
Figure 1.

WAEMU: Average Growth in Total Investment Across WEO Vintages

(percent)

Citation: IMF Staff Country Reports 2022, 068; 10.5089/9798400204579.002.A001

Source: IMF Staff Estimates.

7. Private investment prospects have declined relative to the pre-pandemic projections, while public investment is projected to partially compensate for this fall only in the near term. Different vintages of WEO projections suggest that the path of private investment has deteriorated due to the COVID-19 crisis, as illustrated in Figure 2. Public investment, on the other hand, is projected to increase to partially offset some of the slowdown in private investment, but only up to 2021; thereafter it would fall below levels projected before the pandemic.

Figure 2.
Figure 2.

WAEMU: Investment in the WAEMU (2019=100)

Citation: IMF Staff Country Reports 2022, 068; 10.5089/9798400204579.002.A001

Source: IMF Staff Estimates.

8. Under active policies to promote private investment, the effects of the COVID-19 crisis could be attenuated. The proactive scenario assumes that WAEMU countries would gradually catch up with the global average investment share. The investment boost is calibrated to ensure that investment is consistent with the level of economic development proxied by GDP per capita in the WAEMU. To help the region achieve the 2030 agenda on SDGs, the process of catching up with the global investment share is assumed to be completed by 2030. In order to fill the investment gap fully until 2030, private investment has a role to play which could be supported by appropriate reforms and active government policies. Under this scenario, to find the implied investment rate, and in turn investment gap, the relationship between GDP per capita and investment (as share of GDP) is estimated using global data over the period of 1960–2019.5 Next, whenever the investment rate is below the expected level, private investment is assumed to fill the gap. These calculations suggests that, on average, additional private investment of around 0.8 percent of WAEMU GDP relative to the April 2021 WEO starting from 2022 is needed annually.6

D. Human Capital Accumulation and the COVID-19 Pandemic

9. School closures linked to the pandemic can have longer-term adverse consequences for the accumulation of human capital. Schooling and learning are affected, as for example, enrollment falls and drop-out rates increase (Azevedo and others, 2020; Fabrizio and others forthcoming). Interruptions in human capital accumulation as a direct result of losses in education can impede longer term economic growth (Barro, 1991).7 Educational losses due to school closures during 2020 are bound to generate adverse effects in social and economic outcomes in the absence of appropriate counteracting policies (IMF, 2020b).

10. Limited access to remote learning opportunities are likely to have caused a deceleration in human capital accumulation in the WAEMU. In the pre-pandemic scenario, years of schooling are assumed to grow at their long-term historical average rate (dashed line in Figure 3). In the second scenario, the duration of school closures is used to proxy for losses in years of schooling in the WAEMU, given limited access to online learning.8 Based on the UNESCO school closure monitoring database, COVID-19 related school closures were longer than one month for the majority of countries in the region. These effects are likely to be persistent because it is difficult to expect a strong reversal of the lost time in schools (or large increases in schooling hours or enrollment rates thereby generating an exceptionally high rate of growth in schooling years) in the short term. Under this “passive” scenario, it would be harder to bring students fully back to school fully and regularly, especially underprivileged students. Children from families with financial difficulties could permanently drop out. Students who may have already started supporting their families during the school closures may not be able to leave work to return to their studies. In addition, girls may be more disadvantaged than boys in terms of continuing their education after a long break in some regions and communities (World Bank, 2021a; Fabrizio and others forthcoming). There could be other factors preventing the return to pre-pandemic rates of progress in the years of schooling, as well, including disruptions to the educational system. For instance, parents of the students who will start primary school may be hesitant due to possible unpreparedness of schools and ongoing uncertainty about health risk. Therefore, in the scenario with no active educational policies addressing such scarring effects, it is assumed that growth rate of years of schooling would only gradually catch up with the pre-pandemic rate by 2026 (dotted line in Figure 3).

Figure 3.
Figure 3.

WAEMU: Years of Schooling Under Different Scenarios

Citation: IMF Staff Country Reports 2022, 068; 10.5089/9798400204579.002.A001

Source: IMF Staff Estimates.

11. Nevertheless, active government policies and investment in education could prevent this hysteresis effect by minimizing drop-out and lower enrollment as schools reopen. If that is the case, despite the schooling loss due to the earlier closures, students will go back to schools without an increase in dropouts or lower enrollment rates. Hence, the pace of growth in years of schooling would catch up with the pre-pandemic rate quickly. Under this scenario, it is assumed that the growth rate of years of schooling would go back to the pre-pandemic long-term rate starting from 2021 in the WAEMU (solid line in Figure 3). Active policies to prevent persistent educational losses due to school closures play a crucial role in this scenario and are further described below.

E. Productivity and the COVID-19 Pandemic

12. Informality and technology adoption are two key drivers of productivity growth in developing economies, which are likely to have been significantly affected by the COVID-19 crisis. The effects of the pandemic on total factor productivity are complex and multifaceted (Fernald and Li, 2021). This paper focuses on two key aspects that are likely to be relevant for the WAEMU: (i) sectoral reallocation towards an increase in informality and (ii) the role of digitalization. Large economic shocks such as the COVID-19 crisis and, before that, the global financial crisis tend to be associated with increases in the share of informal activities in the economy as firm bankruptcies increase and formal employment declines. At the same time, on the positive side, the pandemic might have accelerated trends towards digitalization in the region given increase in demand for tools for remote working, learning, and other digital services.

13. The informal sector remains large in the WAEMU, even if important declines were observed over the last twenty years. Based on the estimates from Medina and Schneider (2020), the informal sector on average amounted to around 43 percent of the official GDP across the WAEMU region during the 1990s, but informality—measured as the value added of all economic activities that are hidden from official authorities for monetary, regulatory, and institutional reasons—has declined to 40 percent and 36 percent during the 2000s and 2010s, respectively. However, compared with other emerging market and developing economies (EMDEs), the pace of the progress in reducing informality has been slower (Figure 4, left-hand-side chart). Moreover, there has been sizable heterogeneity in terms of the size of informal economy across WAEMU member countries prior to the COVID-19 shock. Based on the latest available estimates, Niger, Senegal, and Benin appear to have larger informal sector amounting above 35 percent of their official GDPs (Figure 4, right-hand-side chart).

Figure 4.
Figure 4.

WAEMU: Size of the Informal Economy

Citation: IMF Staff Country Reports 2022, 068; 10.5089/9798400204579.002.A001

Source: IMF staff calculations, Medina and Schneider (2020). Informality encompasses all economic activities which are hidden from official authorities for monetary, regulatory, and institutional reasons. Other EMDEs include Emerging market and middle-income economies as classified by the IMF WEO. Annual numbers are calculated as weighted averages, where weights are real GDP, obtained from World Bank World Development Indicators. Simple averages for each decade are reported in the left chart.

14. The informal economy may have acted as an immediate buffer during the COVID-19 shock, but increased informality could also hamper the recovery and medium-term growth. In developing economies, recessions are typically accompanied by an increase in the relative size of the informal sector, which acts as a “buffer” to shocks (David, Pienknagura, and Roldos, 2020). While there is no data yet available on the effects of the pandemic on informality in the WAEMU, historical experience suggests that an expansion in the share of of informal economic activity could have occurred during the pandemic, which may have helped workers who have lost their jobs due to the closure of certain economic sectors find other ways to sustain themselves. Moreover, during the pandemic, lockdowns and social distancing measures may have affected formal businesses to a larger extent, relative to informal activities, since the informal sector, by definition, consists of economic activities that are “hidden” from the authorities. Therefore, the informal sector may have absorbed some portion of job losses, and in turn, helped to mitigate the immediate adverse effect of the pandemic on GDP. Nevertheless, productivity is typically lower in the informal and the informal sector is less capital intensive (La Porta and Shleifer 2008, Benjamin and Mbaye, 2012). In addition, resource misallocation is typically more prominent in countries with large informal sectors (IMF, 2019a). Hence, the likely increase in the size of the informal sector due to the pandemic could lead to adverse effects on potential GDP.

15. The empirical evidence confirms significant and persistent negative effects of the informal sector on total factor productivity. Estimates for a sample of 64 emerging markets and developing economies over the period 1991–2017 indicate that an increase in the share of the informal sector in the economy reduces total factor productivity (Figure 5). As illustrated by the impulse response function depicted, an increase in informality calibrated to be of the same size as the one observed (on average across countries) during the global financial crisis of 2009 is associated with a decline of TFP of 0.9 percent on impact, widening to 1.5 percent after one year, before gradually receding at longer horizons. The specification used to obtain these estimates is based on the local projections method at an annual frequency:

yi,t+h−yi,t−1=αih+γth+βhΔInfi,t+δXi,t+ϵi,t+h

where y denotes total factor productivity (from the PWT dataset); Infi,t denotes the share of the informal sector on the economy (from Medina and Schneider, 2020); and h denotes the time horizons considered. Xi,t denotes a set of control variables, which includes lagged values of the dependent variable and of the change and the level of the informal sector share as well as changes in the commodities terms of trade. The specification also includes time (γth) and country (αih) fixed effects to capture common shocks and time-invariant country features, respectively. In the simulations presented below it is assumed that TFP growth declines relative to the pre-pandemic baseline on impact following the COVID-19 shock and the effects persist over the next two years, as illustrated by the solid black impulse response function in Figure 5.

Figure 5.
Figure 5.

WAEMU: Increases in Informality and TFP

Citation: IMF Staff Country Reports 2022, 068; 10.5089/9798400204579.002.A001

Source: IMF Staff Estimates.

16. On the positive side, the pandemic may also have accelerated certain trends in structural transformation and technology use, which could have beneficial implications for productivity growth. Social distancing mandates, school closures, and lockdowns have increased the demand for tools that allow for remote working and learning as well as the provision of digital services, which could accelerate the pace of digitalization in the region. In fact, there is evidence that more than one in five firms in sub-Saharan Africa have started or expanded their use of digital technology in response to the COVID-19 shock (World Bank, 2021b).

17. In this context, the scenario with policies to mitigate scarring assumes an increase in digitalization with ensuing positive effects on total factor productivity growth. The effects are calibrated using estimates from the literature as reported in IMF (2020a), which suggest that a 1 percentage point increase in the share of the population using internet leads, on average, to a 0.125 percentage point increase in the growth of real per capita income based on evidence from a range of studies. For the purposes of the scenario, we assume that the bulk of this increase in income per capita is due to productivity growth. In addition, the proactive scenario assumes that the COVID-19 shock would lead to a one standard deviation increase in the use of internet (calculated based on historical information for the WAEMU). This corresponds to an increase in internet use of a little under 2 percent of population, or alternatively two times the average yearly increase in the WAEMU countries over last two decades.

F. Putting All Results Together

18. Under the scenario with scarring, but no new policies to counteract its effects, the COVID-19 crisis would reduce medium-term growth in the region by 0.7 percentage points. The results are reported in Table 2. Over the period 2021–26, the analysis suggests that the COVID-19 pandemic would have caused a decline in potential growth of about 0.7 percentage point per annum, relative to growth levels estimated in the pre-pandemic period (the gap between case (1) and (2) above). This would translate into cumulative potential output losses of around 3 percent in five years (potential output would be 3 percent lower relative to what was expected before the pandemic). These losses are in line with the ones estimated at the global level by IMF (2021).

Table 2.

WAEMU: Medium-Term Potential Output Growth Losses in the WAEMU Under Two “Post-Crisis” Scenarios

article image
Source: IMF Staff calculations. The fact that the sum of investment (-0.2) and human capital (-0.1) numbers does not add up to -0.2 in the second column is due to rounding to 1-digit. In two digits, the growth loss due to investment and human capital are -0.16 and -0.06, respectively.

19. If policymakers implement an appropriate combination of policies to mitigate the effects of the crisis, potential output losses could be almost entirely eliminated. The effects of the crisis on medium-term potential output put a premium on policies that address scarring and foster a resumption of the convergence process. In the next section, the paper discusses some policy options to that effect. The proactive scenario assumes the implementation of policies that could boost investment, mitigate human capital losses, and improve productivity growth, as mentioned above. In this case, growth losses, relative to the pre-pandemic estimates (that is, the gap between case (1) and (3) above), could be reduced to a little over 0.2 percentage point over the medium term—with associated output losses of less than 1 percent over the period.

20. Given significant uncertainty around the assumptions made in the two post-crisis scenarios, the paper also undertakes some sensitivity analysis. Under the scenario with no proactive policies to counteract the medium-term effects of the COVID-19 crisis, the paper considers various possibilities regarding the size of the effects of informality on TFP and human capital accumulation. In the scenario where authorities take actions to implement proactive policies, the paper considers alternative assumptions about the positive effect of increased internet use on TFP, as well as alternative convergence paths for human capital accumulation and for the increase in private investment.

21. Medium-term growth could decline by between 0.3 to 1.0 percentage points in the WAEMU in the scenario with no proactive policies to counteract scarring under alternative assumptions. This range reflects in part the use of the upper or lower bounds of the 90 percent confidence interval of the estimates of the effects of increased informality on TFP, rather than the point estimate itself. Moreover, it also considers alternative convergence paths for the growth rate of years of schooling, instead of a catch-up with the pre-pandemic rates by 2026.

22. Under the proactive scenario, the decline in medium-term growth would be attenuated and may range from 0.1 percent to 0.4 percent under alternative assumptions. This range reflects assumptions regarding longer and shorter time spans for the WAEMU to reach the global average in investment rates (controlling for GDP per capita). It also considers a slower catch up in the rate of years of schooling. Moreover, it also reflects the use of different estimates from the literature regarding the effects of the increase in internet use (as share of population) on TFP growth.

23. Overall, the sensitivity analysis confirms that the decline in post-crisis medium-term growth could be substantial in the absence of proactive policies. Growth could be reduced by up to 1 percentage point over the medium term, while it is possible that if policymakers take actions to mitigate scarring, the adverse effects of the crisis could be virtually erased. The next section of the paper turns examines a number of policy options to address scarring.

G. Some Policy Options to Address Scarring

24. Policies to mitigate scarring linked to the COVID-19 crisis comprise initiatives at both the national and regional levels. There could be strong complementarities between regional and national policies in several of the areas discussed below. Moreover, institutions at the WAEMU level could play a coordinating role in the implementation of national policies to address spillovers effects and ensure a level playing field.

Investment and Business Environment

25. Attenuating the medium-term effects of the pandemic on private investment calls for accelerating reforms to address long-standing shortcomings of the investment climate, including access to reliable electricity and finance. Data from recent World Bank’s enterprise surveys indicates that firms in the region typically list access the finance as one of the major constraints to their operations; for example, close to 70 percent of firms surveyed in Cote d’Ivoire and over 50 percent of firms in Senegal cite access to finance as a major impediment (Figure 6). Access to reliable electricity is another frequently cited constraint on investment, which is listed by over 60 percent of firms in Benin, Cote d’Ivoire, and Mali and over 70 percent in Guinea-Bissau. Competition from firms in the informal sector is also perceived to be an important barrier, especially in Cote d’Ivoire, Mali, and Niger.

Figure 6.
Figure 6.

WAEMU: Firms Identifying Issue as Major Constraint

(percent of firms)

Citation: IMF Staff Country Reports 2022, 068; 10.5089/9798400204579.002.A001

Source: World Bank Enterprise Surveys.

26. Regional coordination of investments in energy as well as reforms to state-owned enterprises (SOEs) could increase the reliability of electricity supply. Better regional coordination of investments to upgrade and expand infrastructure could help provide electrical interconnections among countries and improve overall supply and transmission in the most disadvantaged areas. The WAEMU commission is coordinating several initiatives, including the implementation of regional projects in the energy sector under the Regional Economic Program (Programme Economique Régional- PER). Nevertheless, there are important bottlenecks to the implementation of regional investment projects and as a result execution rates have been weak. In addition, SOEs tend to dominate both power generation and distribution in the region. Improving the reliability of electricity supply in the WAEMU will therefore require addressing inefficiencies in the operation of these SOEs, in particular the need to achieve cost recovery in terms of tariff setting. Below-cost tariffs reduce the capacity of SOEs to invest in addition to creating fiscal risks. In this context, strengthening the oversight of SOEs by Ministries of Finance would be desirable.

27. To foster banking sector development, the WAEMU banking commission should continue to monitor and guide the implementation of the Basel II/III prudential norms and operationalize the new resolution framework. Such policies would encourage banks to perform their financial intermediation functions more effectively. Weak banks should be promptly restructured. The supervisor should ensure that bank concentration risks are gradually reduced, and that the resolution and prevention of non-performing loans reduce the credit risk faced by banks.

28. To expand access to credit, the role of microfinance institutions (MFIs) could also be strengthened. In order to increase access to credit for underserved beneficiaries (farmers, women, youth and SMEs), the Banque Centrale des États de l’Afrique de l’Ouest (BCEAO), in coordination with national institutions, could further restructure the sector by encouraging the exit of unviable MFIs and enhancing monitoring.

29. Beyond these efforts to promote private investment, there is also scope for making public investment more efficient. Despite the medium-term plan of fiscal consolidation, public investment could still have a positive contribution to growth with enhancements to its efficiency. Efficiency measures should focus on how each CFAF spent translates into effective public capital stock, contributing to potential output. The WAEMU lags comparator countries, including SSA economies in terms of the efficiency of public investment (Barhoumi and Towfighian, 2018). Based on recently conducted Public Investment Management Assessments (PIMA) for countries in the region, areas in which public investment management could be improved to enhance efficiency include: (i) management of PPPs; (ii) effectiveness of project appraisal and selection; (iii) the monitoring of project implementation; (iv) investment programming; (v) multiyear commitment authorization; and (vi) supporting investment information systems.

Productivity

30. High levels of informality in the WAEMU are in part linked to cumbersome regulations and procedures, which increase the costs of operating in the formal sector. Data from recent World Bank’s Enterprise Surveys suggests that senior management in firms in the WAEMU region tend to spend a significant amount of time dealing with the requirements of government regulations (Figure 7). For example, making it easier for firms to pay taxes could decrease the cost of operating in the formal sector. Moreover, tackling excessively rigid labor market regulations could also reduce labor informality.

Figure 7.
Figure 7.

WAEMU: Senior Management Time Spent Dealing with the Requirements of Government Regulation

(percent)

Citation: IMF Staff Country Reports 2022, 068; 10.5089/9798400204579.002.A001

Source: World Bank’s Enterprise Surveys

31. Investing in digital infrastructure could also contribute to boosting productivity growth and helping the WAEMU prepare for future pandemics. Accelerating investment in digital infrastructure and improving internet access could increase productivity and efficiency in a number of sectors including manufacturing, commerce, health, and education. The WAEMU Commission coordinates efforts to liberalize the telecommunications sector and harmonize national rules and regulations to foster its development. More generally, countries could adopt a number of measures to foster digitalization, including investments in IT infrastructure, but also more traditional investments to ensure, for example, reliable electricity supply (see IMF 2020a).

32. Deeper trade integration can also foster productivity. More integrated countries can benefit from increased trade, specialization gains and larger markets, which make production and the use of capital and labor more efficient. Integration also fosters productivity growth by increasing competition, greater diffusion of technological innovation, and upgrading of labor skills. Trade in local products is by law free of customs’ duties within the WAEMU and the broader ECOWAS community. Nevertheless, trade among WAEMU member states remains relatively limited. Various non-tariff barriers constrain the development of intraregional exchanges. These include the lack of common documentation for customs procedures and ad hoc levies charged for road transit. More generally, barriers to trade are more prominent in the WAEMU region relative of Advanced Economies and other Emerging Markets and Developing Economies (Figure 8). Priorities in this area include: reducing the extensive use of customs’ exemptions and eliminating non-tariff barriers through less cumbersome customs procedures, as well as harmonization of national regulations on standards and procedures of customs.

Figure 8.
Figure 8.

WAEMU: Barriers to Trade in 2019

Citation: IMF Staff Country Reports 2022, 068; 10.5089/9798400204579.002.A001

Source: World Economic Forum and IMF staff calculations. Higher values of the indexes indicate better performance.

33. The regional competition framework could also be upgraded with beneficial effects in terms of productivity growth. IMF (2019b) finds that increased competition can boost real per capita GDP growth rate in SSA by about 1 percentage point through improved competitiveness, productivity growth, and investment. The WAEMU Competition Commission is responsible for prohibiting anti-competitive agreements. The competition framework could be enhanced by revising the legal framework to enhance the division of responsibilities and cooperation between the WAEMU Commission and national competition authorities; this would improve the capacity to monitor and sanction anti-competitive practices within the region.

Education and Human Capital

34. Increasing the amount and efficiency of public spending on education remains a priority for the region to address some of the learning losses due to the pandemic (IMF 2021c). The ratio of teachers per student in the WAEMU is low compared with other EMEs, at both primary and secondary levels, with adverse implications for the quality of education. Moreover, PPP-adjusted expenditure per student substantially lags other EMEs. Enrollment rates are significantly lower in WAEMU, particularly in the case of secondary education (Figure 9). Necessary policies also include teacher training, financial support to meet schooling demands, and support programs for students who were affected by the closures during 2020 (IMF 2020c).

Figure 9.
Figure 9.

WAEMU: Education Spending and Outcomes

Citation: IMF Staff Country Reports 2022, 068; 10.5089/9798400204579.002.A001

Sources: IMF staff estimates; World Bank.

35. Proactive policies to bring kids back to school could mitigate potential long-term effects of the disruption in the process of human capital accumulation that occurred during school closures. For instance, governments should closely monitor re-enrollment and attendance by different groups and underprivileged communities (e.g. girls, students from lower-income families or regions) or senior students. In addition, given the learning loss in 2020 due to school closures, policies aiming at keeping students in schools in coming years (thereby alleviating risks related to dropouts and lack of enrollment) should be guided by assessments of students’ skills and needs in the post-pandemic period. This could ensure that students can keep up with the new school year and become more likely to continue their education. In this regard, remedial programs (before or after school),9 modified schedules, adjusting/extending school years, continuing distance learning in parallel to schools re-opening can help the WAEMU put the process of human capital accumulation back on track (UNICEF 2020, Gopinath 2021, and Kaffenberger 2021).

References

  • Aguirre, J.P.C., 2021. Recoveries After Pandemics: The Role of Policies and Structural Features. IMF Working Papers, 2021(181).

  • Alesina, A. and Perotti, R., 1996. Income distribution, political instability, and investment. European economic Review 40: 1203–1228.

    • Search Google Scholar
    • Export Citation

  • Azevedo, J. P., Hasan, A., Goldemberg, D., Iqbal, S.A. and Geven, K., 2020 “Simulating the potential impacts of COVID-19 school closures on schooling and learning outcomes: A set of global estimates” The World Bank.

    • Search Google Scholar
    • Export Citation

  • Barhoumi, K., and Towfighian, S., N., 2018. “Public Investment Efficiency in the WAEMU: An Empirical Assessment” West African Economic and Monetary Union Selected Issues Paper, IMF Country Report 18/107.

    • Search Google Scholar
    • Export Citation

  • Barro, R. J., 1991. Economic growth in a cross section of countries. The quarterly Journal of economics, 106:.407–443.

  • Benjamin, N.C. and Mbaye, A. A., 2012. “The Informal Sector, Productivity, and Enforcement in West Africa: A Firm-level Analysis” Review of Development Economics, 16: 664–680.

    • Search Google Scholar
    • Export Citation

  • Buffie, E., Adam, C. Zanna, L. F., Kpodar, R., 2021 “Rebuilding Human Capital in the Post-Covid Recovery in Low Income Countries” International Monetary Fund, Mimeo.

    • Search Google Scholar
    • Export Citation

  • Card, D., 1999. The causal effect of education on earnings. Handbook of labor economics, 3, pp.1801–1863.

  • Cerra, M. V., Fatás, A. and Saxena, M.S.C., 2020. Hysteresis and business cycles. International Monetary Fund.

  • Cerra, V., Fatas, A. and Saxena, S. C., 2021. Fighting the scarring effects of COVID-19. Industrial and Corporate Change, 30(2), pp.459–466.

    • Search Google Scholar
    • Export Citation

  • David, A. C., Pienknagura, S., and Roldos, J., 2020. “Labor Market Dynamics, Informality, and Regulations in Latin America” IMF Working Paper 20/19, Washington, DC.

    • Search Google Scholar
    • Export Citation

  • Eyraud, L., Devine, H., Peralta-Alva, A., Selim, H., Sharma, P., and Wocken, L. 2021. “Private Finance for Development: Wishful Thinking or Thinking Out of the Box?”. 2021. IMF Departmental Papers, 011.

    • Search Google Scholar
    • Export Citation

  • Emmerling, J., Furceri, D., Monteiro, F. L., Pizzuto, P. and Tavoni, M., 2021. Will the Economic Impact of COVID-19 Persist? Prognosis from 21st Century Pandemics. IMF Working Papers, 2021(119).

    • Search Google Scholar
    • Export Citation

  • Fabrizio and others forthcoming. “School Dropout in Epidemics and Loss of Earning Potential in Developing Countries”, IMF Working Paper.

    • Search Google Scholar
    • Export Citation

  • Fernald, J. and Li, H., 2021 “The Impact of COVID on Potential Output” Federal Reserve Bank of San Francisco Working Paper 2021-09.

  • Martín Fuentes, N. and Moder, I., 2020. The scarring effects of past crises on the global economy. Economic Bulletin, (8).

  • Holmlund, B., Liu, Q. and Nordström Skans, O., 2008. “Mind the gap? Estimating the effects of postponing higher education” Oxford Economic Papers, 60: 683–710.

    • Search Google Scholar
    • Export Citation

  • IMF, 2019a “Reigniting Growth in Emerging Market and Low-Income Economies: What Role for Structural Reforms?” Chapter 3 of the October 2019 World Economic Outlook. International Monetary Fund, Washington, DC.

    • Search Google Scholar
    • Export Citation

  • IMF, 2019b “competition, Competitiveness, and Growth in Sub-Saharan Africa” Chapter 2 of the October 2019 Regional Economic Outlook for Sub-Saharan Africa. International Monetary Fund, Washington, DC.

    • Search Google Scholar
    • Export Citation

  • IMF, 2020a. “Digitalization in Sub-Saharan Africa”. Chapter 3 of the April 2020 Regional Economic Outlook for Africa, International Monetary Fund, Washington, DC.

    • Search Google Scholar
    • Export Citation

  • IMF, 2020b. “A Long and Difficult Ascent”. World Economic Outlook October, International Monetary Fund, Washington, DC.

  • IMF, 2020c. “Navigating the Pandemic: A Multispeed Recovery in Asia”. Asia-Pacific Regional Economic Outlook October, International Monetary Fund, Washington, DC.

    • Search Google Scholar
    • Export Citation

  • IMF, 2021. “After-Effects of the COVID-19 Pandemic: Prospects for Medium-Term Economic Damage” Chapter 2 of the World Economic Outlook Report, April, International Monetary Fund, Washington, DC.

    • Search Google Scholar
    • Export Citation

  • Jordà, Ò., Singh, S.R. and Taylor, A. M., 2020. Longer-run economic consequences of pandemics? The Review of Economics and Statistics, pp.1–29.

    • Search Google Scholar
    • Export Citation

  • La Porta, R. and Shleifer, A., 2008, “The unofficial economy and economic development” (No. w14520). National Bureau of Economic Research.

    • Search Google Scholar
    • Export Citation

  • Leandro, Medina, and Friedrich Schneider, 2020. “Shedding Light on the Shadow Economy” World Economics, 21: 25–82.

  • Light, Audrey. 1995. “The Effects of Interrupted Schooling on Wages.” Journal of Human Resources 30: 472–502.

  • Ma, C., Rogers, J.H. and Zhou, S., 2020. Modern pandemics: Recession and recovery. Available at SSRN 3565646.

  • OECD. 2020 “The impact of COVID-19 on student equity and inclusion: supporting vulnerable students during school closures and school re-openings”

    • Search Google Scholar
    • Export Citation

  • Selim, H. and Zinabou, G., 2020. “The Magic of Growth Spells: Maintaining Economic Momentum in the WAEMU” International Monetary Fund, mimeo.

    • Search Google Scholar
    • Export Citation

  • Word Bank, 2021b. “Covid-19 and the Future of Work in Africa: Emerging Trends in Digital Technology Adoption” Africa’s Pulse, April.

    • Search Google Scholar
    • Export Citation

  • York, L., Rose, P., Woldehanna, T. and Hagos, B. 2020, “What are the challenges in reopening schools in Ethiopia?” Perspectives of school principals and teachers”. Research on Improving Systems of Educations

    • Search Google Scholar
    • Export Citation
1

Prepared by Antonio David (AFR) and Can Sever (AFR). We are grateful to Luc Eyraud, Annalisa Fedelino, and the WAEMU authorities for comments and suggestions.

3

The paper uses data from the Penn World Table (PWT) version 10.0 (Feenstra and others, 2015) for historical information on the capital stock and human capital index as well as the parameter a (the output share of capital) going from 1950 to 2019. One shortcoming of using PWT data is that it does not necessarily reflects the rebasing of GDP that occurred in seven WAEMU countries since 2018, which may affect estimates of investment and the capital stock. Labor force growth over the medium term is given by United Nations (UN) projections as reported in the ILOSTATs database. Other variables and parameters are pinned down by historical averages or assumptions as detailed below.

4

Specifically, the analysis estimates the growth for post-crisis cases (2) and (3) using equation (2). Next, it reports the differences between growth rates in order to quantify the change in growth, compared with the pre-pandemic estimate in each case, that is, gYt(1)−gYt(2)andgYt(1)−gYt(3).

5

More specifically, investment (as share of GDP) is regressed on the log of GDP per capita using data from a large sample consisting of developing, emerging market and advanced economies. A statistically significant (at the 1 percent level) relationship between the two variables is found, indicating that investment as share of GDP becomes larger as GDP per capita increases. Then, the investment gap in the WAEMU is estimated by calculating the implied rate of investment based on projected levels of GDP per capita over the period of analysis.

6

In terms of private investment in Africa, Eyraud and others (2021) estimate the target of an additional 3 percent of GDP by the end of this decade.

7

On top of the direct effect of school closures on output as captured by the scenarios described above, school closures are an important channel through which the pandemic can generate long-lasting effects on inequality. This occurs because underprivileged students from poorer households (e.g. with lack of internet access) are more exposed to disruptions in learning opportunities (OECD 2020). This can add to the adverse effect of the COVID-19 crisis on poverty and inequality, by potentially affecting lifetime income and earnings trajectories (Light, 1995; Card, 1999; Holmlund and others, 2008; Azevedo and others, 2020). An increase in poverty and inequality can further hinder a resilient and stable recovery, for instance, by fueling social unrest (Alesina and Perotti 1996; IMF, 2020c).

8

This assumption was used in the literature, since remote learning has low effectiveness in low-income countries (York and others 2020, Buffie and others 2021). UNICEF-ITU (2020a) reports the high rates of school children who are unconnected to the internet in West and Central Africa. Similar numbers are reported by UNICEF-ITU (2020b).

9

Remedial programs aim to close the gap between what students know and what they are supposed to know.

Same Series

Other IMF Content

Other Publishers

  • Collapse
  • Expand
Cover IMF Staff Country Reports
West African Economic and Monetary Union: Selected Issues
Author:
International Monetary Fund. African Dept.
Volume/Issue:
Volume 2022: Issue 068
Publisher:
International Monetary Fund
ISBN:
9798400204579
ISSN:
1934-7685
Pages:
58
DOI:
https://doi.org/10.5089/9798400204579.002
Figure 1.

WAEMU: Average Growth in Total Investment Across WEO Vintages

(percent)
Figure 2.

WAEMU: Investment in the WAEMU (2019=100)
Figure 3.

WAEMU: Years of Schooling Under Different Scenarios
Figure 4.

WAEMU: Size of the Informal Economy
Figure 5.

WAEMU: Increases in Informality and TFP
Figure 6.

WAEMU: Firms Identifying Issue as Major Constraint

(percent of firms)
Figure 7.

WAEMU: Senior Management Time Spent Dealing with the Requirements of Government Regulation

(percent)
Figure 8.

WAEMU: Barriers to Trade in 2019
Figure 9.

WAEMU: Education Spending and Outcomes