Building Integrated Economies in West Africa
Chapter

Chapter 11. Public Investment and Fiscal Rules1

Author(s):
Alexei Kireyev
Published Date:
April 2016
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Author(s)
Sébastien Dessus, Jose L. Diaz-Sanchez and Aristomene Varoudakis 

Public investment in the West African Economic and Monetary Union (WAEMU) has been pro-cyclical. Evidence from a panel of low-income and lower middle-income countries suggests that, contrary to other countries, public investment in the WAEMU contracts more in “bad times” than it increases in “good times” and appears to have become procyclical since the introduction of the fiscal convergence criteria in 1994. The fiscal deficit has been largely uncorrelated to GDP growth in the WAEMU because of the procyclicality of public investment, while in other low-income countries, the fiscal balance appears to have been mildly countercyclical. The procyclicality of public expenditure and the high asymmetry of shocks that affect WAEMU countries justify exploring options for greater countercyclicality of rules-based fiscal frameworks and for risk sharing. In the WAEMU, fiscal rules can become important anchors of medium-term fiscal policy over the cycle so as to preserve fiscal discipline at the aggregate level. Some flexibility to fiscal convergence criteria could help mitigate the procyclicality of public expenditures, including of public investment. A countercyclical fiscal rule would allow for some positive correlation, with smaller deficits (larger surpluses) in booms and larger deficits (smaller surpluses) in contractions. At the same time, because shocks affecting WAEMU countries are highly asymmetric, there is room for establishing fiscal federalism arrangements or for adopting a form of risk sharing (or group insurance) to mitigate the incidence of these shocks. Risk-sharing mechanisms would aim to allocate larger financial resources to the Union members exposed to negative shocks. As countries facing difficulties seem compelled to drastically cut back investment in bad times, such mechanisms would also help preserve investment levels in the WAEMU.

Fiscal Rules in a Monetary Union

The debt crisis in the euro area revealed new challenges for monetary unions. Countries entering a monetary union relinquish national monetary and exchange rate policies for the benefit of greater integration associated with the union. If countries in the union are subject to large asymmetric shocks, and there are no transfers through a federal budget, national fiscal policy would be the only instrument left to cushion these shocks. Yet, despite the need for fiscal flexibility, existing monetary unions observe strict fiscal rules that typically limit the leeway of national fiscal policies to respond to shocks. Concerns about debt externalities of national fiscal policies and possibly weak incentives for fiscal restraint provide a common rationale for fiscal rules in monetary unions (De Grauwe 1992).

A precondition for market-driven discipline in monetary unions is that a no-bailout clause can be properly enforced among the members, regardless of their systemic importance or of concerns regarding financial spillovers from debt default. In the absence of effective enforcement, market interest rates will not reflect the default risk of monetary union members. Because market discipline is likely to fail, fiscal rules seem necessary to deflect debt externalities and strengthen possibly weak incentives for fiscal restraint. Externalities may arise if national fiscal policies lead to unsustainable levels of public debt, putting pressure on the central bank to monetize part of this debt. Externalities may also arise through the financial sector, as a debt crisis in a fiscally distressed member may spill over to banks of other members that may hold the distressed debt. Incentives for fiscal discipline may weaken when a country joins a monetary union because the interest rate on its debt declines as the risk premium of exchange rate devaluation vanishes. A factor that plays in the opposite direction of strengthening fiscal discipline is that monetary union members surrender the option of financing budget deficits through money creation and thus face a harder budget constraint compared with countries that have monetary autonomy.

However, fiscal rules may also reduce the quality of fiscal policy because they disregard the composition of fiscal adjustment necessary for compliance (Blanchard and Giavazzi 2004). The need to comply with fiscal rules may result in easy cuts in capital spending. These can have two main effects: First, they may amplify volatility through procyclical cuts in expenditure and, in particular, public investment. Second, they may have a potentially negative impact on long-term growth if the level of public investment, or its quality, are negatively affected. Thus, among the most important challenges for monetary unions is to improve their capacity to ensure fiscal convergence, while also developing efficient mechanisms to mitigate asymmetric shocks, which do not affect all members at the same time.

Fiscal convergence rules in the WAEMU impose strict limits on the budget deficit. Current rules include a balanced basic budget deficit defined as domestic revenue minus domestically financed expenditure, a public debt ceiling at 70 percent of GDP, and the nonaccumulation of public expenditure arrears. The rules have not been systematically enforced in the past, especially concerning the basic fiscal balance. Even so, they still leave only limited room for countercyclical response in countries affected by asymmetric shocks. Countercyclical response through national budgets is bound by foreign financing, originating from outside the WAEMU, of any additional spending, or of the budget deficit resulting from an adverse revenue shock. Moreover, a large part of current public expenditures are nondiscretionary (wages, transfers, debt service) and thus difficult to cut in the short run. One can therefore anticipate that an unexpected change in revenue, or current expenditure, resulting from a shock, will be to a large extent cushioned by changes in discretionary public investment. Furthermore, unlike the relative ease in cutting investment expenditures in bad times, rapidly converting unexpected revenues into new projects is often difficult, reflecting, for example, bottlenecks in project selection or in procurement. It is therefore possible that volatility of public investment may well affect its average level too. For example, finding by Celasun and Walliser (2008) on a sample of 13 developing countries (including four WAEMU countries) over the period 1992–2007 suggest that aid volatility is detrimental to public investment in physical and human capital. While unexpected shortfalls entail direct cuts in investment, unexpected windfalls do not lead to higher investments of a symmetric order of magnitude.

We extend previous empirical work on procyclical fiscal policies in sub-Saharan Africa by Thornton (2008); Lledo, Yackovlev and Gadene (2011); and Guillaumont-Jeanneney and Tapsoba (2011) who found that total public expenditure is more procyclical in WAEMU than it is in other African countries. The cyclical patterns of public investment and current public expenditure are examined separately, comparing the WAEMU to a large sample of low-income countries and lower middle-income countries in sub-Saharan Africa and in other developing regions. The patterns estimated over 1995–2012 are compared with earlier patterns in 1981–94 to gain insight on the possible impact of the fiscal convergence criteria adopted in 1994, after the devaluation of the CFA franc. We also examine how these patterns differ in recessions and booms of economic activity. The findings justify exploring options for greater countercyclicality of rules-based fiscal frameworks and options for risk-sharing mechanisms with a view to reducing the procyclicality of public investment. Risk-sharing mechanisms could include a move toward fiscal federalism through greater centralization of national budgets, the design of group insurance schemes, or both.

Growth, Investment, and Shocks

According to the World Bank’s classification, of 67 low-income and lower middle-income countries (including the eight WAEMU members) over the period 1995-2012, the WAEMU can be compared to two other country groups. The first group is comprised of 28 other sub-Saharan African low-income and lower middle-income countries (excluding the WAEMU). The second group is comprised of 31 other low-income and lower middle-income countries in the rest of the world (see Annex Table 11.1.1 for group definitions). As Table 11.1 shows, at 3.6 percent on (unweighted) average, annual real GDP growth in the WAEMU ranks well below comparator groups. Growth volatility in the WAEMU, as measured by the coefficient of variation of annual GDP growth, has been higher than in other low-income and lower middle-income countries, but lower than in other sub-Saharan African comparator countries. Public investment in proportion to GDP has also been low in the WAEMU. At 6 percent of GDP on average, it ranks well below the percentage seen in the other two country groups. Reflecting weak public investment, unsurprisingly perhaps, the WAEMU lags behind the rest of sub-Saharan Africa as a whole on almost all infrastructure indicators, with the most notable gaps in paved-road density, mainline density, and generation capacity (IMF 2010). Such infrastructure gaps could be partly responsible for WAEMU’s “missing growth”.2

Table 11.1GDP Growth and Public Investment, 1995–2012(in percent)
WAEMU (8 countries)Other SSA LIC and LMIC (28 countries)Other LIC and LMIC (31 countries)
GDP growth per year
Average3.564.124.34
Standard deviation4.326.584.15
Standard deviation/average1.211.600.96
Public investment/GDP
Average6.027.857.15
Standard deviation2.646.209.48
Standard deviation/average0.440.791.32
Source: Authors’ calculations based on data from World Economic Outlook.Note: LIC = low-income countries; LMIC = lower middle-income countries; SSA = sub-Saharan Africa; WAEMU = West African Economic and Monetary Union.
Source: Authors’ calculations based on data from World Economic Outlook.Note: LIC = low-income countries; LMIC = lower middle-income countries; SSA = sub-Saharan Africa; WAEMU = West African Economic and Monetary Union.

Turning to the degree of synchronization of shocks, as Table 11.2 shows, over 1995-2012, the average correlation of each WAEMU member country’s annual GDP growth with the unweighted average annual GDP growth of other WAEMU members was 0.117. Burkina Faso and Togo had the highest GDP growth correlation (0.56 and 0.47, respectively) with average GDP growth of other WAEMU members, while all others had no significant correlations with the rest of the WAEMU members. The low correlations of real GDP growth among WAEMU members contrast with the much higher correlations of GDP growth observed in monetary unions among advanced economies where economic integration is much higher. For example, the average real income growth correlation among 48 U.S. states over 1960-90 was 0.72, while the average real GDP growth correlation among 15 euro area members over 1961–96 was 0.56 (Fatas 1998). The terms of trade changes as a more direct measure of exogenous shocks points to a similar conclusion (Table 11.2, last column). The average correlation of individual WAEMU members’ terms of trade changes with the rest of the WAEMU is 0.21, with only Benin, Burkina Faso, and Mali exhibiting relatively high positive correlations with the rest of WAEMU members.

Table 11.2Asymmetric Shocks in the WAEMU, 1995–2012
GDP Growth (in percent)Comparison with Other WAEMU Members
AverageStandard DeviationCorrelation of GDP GrowthCorrelation of Terms of Trade Changes
Benin4.11.00.0310.440
Burkina Faso5.92.00.5560.551
Côte d’Ivoire1.73.60.157−0.120
Guinea-Bissau1.18.9−0.257−0.204
Mali4.23.70.1930.556
Niger4.94.6−0.169−0.023
Senegal3.91.7−0.0440.307
Togo2.42.70.4690.172
Average3.53.50.1170.210
Source: Authors calculations based on data from World Economic Outlook.
Source: Authors calculations based on data from World Economic Outlook.

Procyclicality of Fiscal Policy

Evidence suggests that, contrary to high-income countries where fiscal policy is mostly uncorrelated with the business cycle, in developing countries, fiscal policy is largely procyclical. That is, it turns expansionary in good times and contractionary in bad times (Talvi and Vegh 2005). The procyclicality of fiscal policy is often explained by the loss of international capital market access during bad times, which, in the absence of fiscal space through accumulated savings, makes it expensive, if not impossible, to finance expansionary policies during downturns (Aizenman, Gavin, and Hausmann, 2000; Gavin and Perotti,1997).

Another explanation of the procyclicality of fiscal policy, suggested by Talvi and Vegh (2005), emphasizes the large variations in tax bases in developing countries during the cycle. Reflecting large revenue swings, countercyclical fiscal policy would cause large budget surpluses in good times, exacerbating pressure on policymakers from various constituencies to spend the accumulated savings. To deflect such pressures and avoid wasteful use of resources, it is possible that policymakers would be tempted to avoid large surpluses by imparting procyclicality to fiscal policy.

The procyclicality of fiscal policy has been also documented in African countries. Government consumption has been found to be procyclical, the more so when dependence on foreign aid is high (Thornton 2008). Procyclicality of total public expenditure has been also found by Lledo, Yackovlev, and Gadene (2011), but with a mitigating impact of foreign aid and debt relief.

Whether fiscal rules exacerbate procyclicality of fiscal policy is largely an empirical matter. The outcome will depend on the design of rules and the incentives they create for policymakers. Strict fiscal rules that target the overall fiscal balance on an annual basis may, arguably, amplify procyclicality, as shocks would trigger immediate expenditure and tax adjustments to meet the fiscal targets. By contrast, fiscal rules targeting the structural deficit or the deficit over the cycle could mitigate procyclicality. Importantly, fiscal rules could mitigate procyclicality if they changed the incentives of policymakers toward creating fiscal space in good times for countercyclical response in bad times. There is evidence that policy incentives do change over time: experience with credit rationing during bad times, especially after the East Asian crisis in the late 1990s, prompted many developing countries to self-insure by building buffers of savings during good times. This made it possible for several emerging economies to respond countercyclically to the 2008–09 global financial crisis, including, to some extent, in Africa (Krumm and Kularatne 2013).

In what follows, we analyze the procyclicality in the WAEMU of the two components of public expenditure (public investment and current expenditure), but also of the fiscal balance. To this end, we regress these variables on the annual GDP growth rate for WAEMU countries, but also for a large sample of other low-income and lower middle-income countries.3

A positive relationship between government expenditures and GDP growth could reflect not only a procyclical behavior of fiscal variables but also an increase in infrastructure and/or social services demand resulting from a higher level of income. To account for this possible simultaneity between GDP growth and the fiscal variables, a generalized method of moments estimator was used with standard errors robust for both heteroskedasticity and autocorrelation. Lags of the independent variable (the real GDP growth) are used as instruments, together with an additional instrument constructed as the product of world GDP growth and each country’s ratio of exports to GDP. The overidentifying restrictions are tested through the Hansen J test, which provides a test of the general validity of the instruments used. Regression coefficients for the WAEMU countries are estimated separately from the other countries of the sample. Results for the period 1995-2012 are reported in Table 11.3.

Table 11.3The Procyclicality of Fiscal Policy (1995–2012)
(1)(2)(3)
Dependent VariableDLNKFIGDLNKCURXDEF/NGDP
W*DLNKGDP7.213**−0.0386−0.0152
(2.072)(−0.0382)(−0.0185)
(1-W)*DLNKGDP1.4091.2250.590***
(0.502)(1.522)(2.643)
AC dummy4.6090.4590.0034
(1.126)(1.535)(0.0301)
Observations1,0861,1081,147
Number of countries677878
Hansen J test:
Statistic2.9584.6096.03
Chi-sq (6), p-value0.81400.59490.4199
Source: Authors’ calculations based on IMF IFS database.Note: D and LN denote the first difference operator and the natural logarithm operator, respectively. DEF = fiscal balance; KCURX = current real public expenditure (total expenditure excluding public investment); KFIG = real public investment; KGDP = real GDP; NGDP = nominal GDP; W = dummy variable for WAEMU countries. AC is a dummy with value 1 for armed conflict episodes in a given year and 0 otherwise. Robust z-statistics (to both arbitrary heteroskedasticity and arbitrary autocorrelation) are in parentheses. ***, **,* indicate significance at 1%, 5%, and 10% confidence levels, respectively.
Source: Authors’ calculations based on IMF IFS database.Note: D and LN denote the first difference operator and the natural logarithm operator, respectively. DEF = fiscal balance; KCURX = current real public expenditure (total expenditure excluding public investment); KFIG = real public investment; KGDP = real GDP; NGDP = nominal GDP; W = dummy variable for WAEMU countries. AC is a dummy with value 1 for armed conflict episodes in a given year and 0 otherwise. Robust z-statistics (to both arbitrary heteroskedasticity and arbitrary autocorrelation) are in parentheses. ***, **,* indicate significance at 1%, 5%, and 10% confidence levels, respectively.

The results confirm the validity of the overidentifying restrictions and thus of the instruments used. Public investment has been procyclical in WAEMU over the estimation period, as the estimated elasticity to real GDP growth is positive at a 95 percent confidence level. By contrast, there is no significant procyclicality of public investment in other low-income and lower middle-income countries (Table 11.3, column 1). The results for current public expenditure show an acyclical behavior of this fiscal policy variable for the two groups of countries (Table 11.3, column 2). Procyclical public expenditure is thus associated with public investment, rather than with current expenditure, in the WAEMU. This supports the perception that public investment, more than current expenditure, is a major shock absorber, or residual fiscal variable. As to the fiscal balance, there is evidence of countercyclicality in other low-income and lower middle-income countries, as the fiscal deficit (surplus) decreases (increases) when growth is stronger (Table 11.3, column 3). By contrast, in the WAEMU, the fiscal balance is acyclical. The absence of counter-cyclicality of fiscal deficits in the WAEMU may reflect the large compensating changes in public investment when fiscal revenues are affected by shocks. In bad (good) times, when fiscal revenues shrink (expand), a contraction (increase) of public investment offsets the impact of the shock on the budget, resulting in only small changes in the fiscal deficit in proportion to GDP.

Estimating the same set of regressions over the period 1981–94, preceding the introduction of the fiscal convergence criteria in the WAEMU, provides evidence on the possible impact of this fiscal framework on the cyclical patterns of public investment and current expenditures. As Table 11.4 shows, public investment exhibited a similar pattern of procyclicality in other low-income and lower middle-income countries in 1981–94 (Table 11.4, column 1). However, in the WAEMU, contrary to the more recent period (1995–2012), there is no evidence of procyclicality of public investment over the 1981–94 period. Current public expenditures in WAEMU were also found acyclical in both the 1981–94 and 1995–2012 periods (Table 11.4, column 2). This confirms the perception that since the introduction of the fiscal convergence framework, public investment, more than current expenditure, has responded procyclically in the face of shocks that affected the budget in WAEMU countries.

Table 11.4The Procyclicality of Fiscal Policy (1981–94)
(1)(2)(3)
Dependent VariableDLNKFIGDLNKCURXDEF/NGDP
W*DLNKGDP0.2302.587−0.450*
(0.111)(1.162)(−1.810)
(1-W)*DLNKGDP0.9461.616**0.209
(0.385)(2.140)(0.751)
AC dummy0.2610.272−0.0664
(0.490)(1.082)(−0.664)
Observations432207229
Number of countries483234
Hansen J test:
Statistic6.1173.02911.521
Chi-sq (6), p-value0.41020.80520.0735
Source: Authors’ calculations based on IMF IFS database.Note: D and LN denote the first difference operator and the natural logarithm operator, respectively. KFIG = real public investment; KCURX = current real public expenditure (total expenditure excluding public investment); DEF = fiscal balance; NGDP = nominal GDP; KGDP = real GDP; W = dummy variable for WAEMU countries. We convert nominal variables into real variables using the GDP deflator. AC is a dummy with value 1 for armed conflict episodes in a given year and 0 otherwise. Robust z-statistics are in parentheses. **,* indicate significance at 5% and 10% confidence levels, respectively. The method of estimation is GMM with standard errors and statistics robust to both arbitrary heteroskedasticity and arbitrary autocorrelation. Instruments include: 1, 2, 3, and 4 lags of the two independent variables and the ratio of exports to GDP for each country multiplied by the world GDP growth. Accordingly, there are six overidentifying restrictions, equal to the total number of instruments minus the number of regressors. Each regression includes country fixed effects and time fixed effects. The null hypothesis of the Hansen J test (overidentification test) is that all moment conditions are valid; that is, the instruments used are not correlated with the residuals.
Source: Authors’ calculations based on IMF IFS database.Note: D and LN denote the first difference operator and the natural logarithm operator, respectively. KFIG = real public investment; KCURX = current real public expenditure (total expenditure excluding public investment); DEF = fiscal balance; NGDP = nominal GDP; KGDP = real GDP; W = dummy variable for WAEMU countries. We convert nominal variables into real variables using the GDP deflator. AC is a dummy with value 1 for armed conflict episodes in a given year and 0 otherwise. Robust z-statistics are in parentheses. **,* indicate significance at 5% and 10% confidence levels, respectively. The method of estimation is GMM with standard errors and statistics robust to both arbitrary heteroskedasticity and arbitrary autocorrelation. Instruments include: 1, 2, 3, and 4 lags of the two independent variables and the ratio of exports to GDP for each country multiplied by the world GDP growth. Accordingly, there are six overidentifying restrictions, equal to the total number of instruments minus the number of regressors. Each regression includes country fixed effects and time fixed effects. The null hypothesis of the Hansen J test (overidentification test) is that all moment conditions are valid; that is, the instruments used are not correlated with the residuals.

The procyclical changes in fiscal policy in developing countries have often been found to be asymmetric in good and bad times. For example, Gavin and Perotti (1997) found that fiscal balances in Latin America were more procyclical in bad times, when negative deviations of GDP growth from average were large. In the WAEMU, Guillaumont-Jeanneney and Tapsoba (2011) found total public expenditure to be more procyclical in recessions than in good times. In our larger sample, this issue is studied by examining whether the elasticity of public investment to GDP is different when countries face negative and positive shocks. Public investment was found to be procyclical in the WAEMU over the recent period (1995–2012). For each country, periods of negative shocks are identified as years with below-average real GDP growth (and periods of positive shocks as years with above-average real GDP growth). Regressions of real public investment growth on real GDP growth are estimated separately on periods of negative and positive shocks, while distinguishing the coefficients for WAEMU and non-WAEMU countries (Table 11.5).

Table 11.5Procyclicality of Public Expenditure in “Good” and “Bad” Times (1995–2012)
Dependent VariableGDP Growth > Average (1) DLNKFIGGDP Growth < Average (2) DLNKFIG
W*DLNKGDP8.1669.423*
(1.328)(1.814)
(1-W)*DLNKGDP4.6554.513
(1.374)(1.156)
AC dummy−0.949−0.538
(−0.689)(−0.216)
Observations592493
Number of countries6666
Hansen J test:
Statistic9.7524.329
Chi-sq (6), p-value0.13550.6322
Source: Authors’ calculations based on IMF IFS database.Note: D and LN denote the first difference operator and the natural logarithm operator, respectively. KFIG = real public investment; KGDP = real GDP; W = dummy variable for WAEMU countries. We convert nominal GDP into real GDP using the GDP deflator. AC is a dummy with value 1 for armed conflict episodes in a given year and 0 otherwise. Robust z-statistics are in parentheses. **,* indicate significance at 5% and 10% confidence levels, respectively. The method of estimation is GMM with standard errors and statistics robust to both arbitrary heteroskedasticity and arbitrary autocorrelation. Instruments include: 1, 2, 3, and 4 lags of the two independent variables and the ratio of exports to GDP for each country multiplied by the world GDP growth. Accordingly, there are six overidentifying restrictions, equal to the total number of instruments minus the number of regressors. Each regression includes country fixed effects and time fixed effects. The null hypothesis of the Hansen J test (overidentification test) is that all moment conditions are valid, that is, the instruments used are not correlated with the residuals.
Source: Authors’ calculations based on IMF IFS database.Note: D and LN denote the first difference operator and the natural logarithm operator, respectively. KFIG = real public investment; KGDP = real GDP; W = dummy variable for WAEMU countries. We convert nominal GDP into real GDP using the GDP deflator. AC is a dummy with value 1 for armed conflict episodes in a given year and 0 otherwise. Robust z-statistics are in parentheses. **,* indicate significance at 5% and 10% confidence levels, respectively. The method of estimation is GMM with standard errors and statistics robust to both arbitrary heteroskedasticity and arbitrary autocorrelation. Instruments include: 1, 2, 3, and 4 lags of the two independent variables and the ratio of exports to GDP for each country multiplied by the world GDP growth. Accordingly, there are six overidentifying restrictions, equal to the total number of instruments minus the number of regressors. Each regression includes country fixed effects and time fixed effects. The null hypothesis of the Hansen J test (overidentification test) is that all moment conditions are valid, that is, the instruments used are not correlated with the residuals.

In WAEMU, the elasticity of public investment to GDP is not significant in good times (Table 11.5, column 1). By contrast, in bad times, the elasticity of public investment to GDP is significant at a 90 percent confidence level (Table 11.5, column 2). Public investment seems thus to respond asymmetrically to growth shocks. That is, it contracts more in recessions than it expands in booms. In non-WAEMU countries, we do not find evidence of an asymmetric response of public investment to growth shocks

The asymmetric pattern in the response of public investment in bad and good times observed in the WAEMU suggests that shocks may affect the level of public investment, in addition to increasing its volatility. The overall public investment level will be lower with negative and positive shocks of equal variance than without shocks. This phenomenon could contribute to explaining why WAEMU countries record lower average public investment levels than do other low-income and lower middle-income countries, as documented in Table 11.1. Negative shocks in the WAEMU over 1995–2012 (in 58 instances out of 136; or, for 42 percent of observations in the sample) were, on average, equivalent to a 2.8 percentage point drop in the GDP growth rate. Positive shocks (78 observations) averaged 2.1 percentage points of GDP. With negative GDP shocks larger, on average, than positive shocks, and occurring with almost similar frequency as positive shocks, the asymmetric response of public investment in bad and good times could partly explain the lower level of public investment observed in WAEMU compared with non-WAEMU countries.

Countercyclical Fiscal Rules

Rules that target the overall budget balance and (binding) public debt impart procyclicality to fiscal policy, as expenditures and/or taxes have to be adjusted to be in compliance. At the same time, such rules may not lead to sufficient restraint in good times, as strong cyclical tax revenues may help meet targets concerning the overall budget balance. Procyclical rules would thus risk making the fiscal stance overexpansionary while failing to realize savings for bad times. Moreover, the existing WAEMU fiscal convergence framework that requires balancing the annual budget of domestically financed expenditure does not guarantee debt sustainability, as it excludes expenditures financed through the accumulation of foreign debt. A fiscal convergence rule accounting for all sources of financing would be a better safeguard for debt sustainability (IMF 2013). Excluding foreign-financed expenditure from the definition of the basic budget balance has not succeeded in protecting public investment from volatility, as total public investment has become procyclical since 1994.

There are various options for amending fiscal rules to allow some cyclical flexibility.4 At least four different options can be considered for setting the budget balance target:

  • 1. Overall budget balance with ad hoc adjustments
  • 2. Cyclically adjusted (structural) budget balance
  • 3. Overall budget balance over the cycle
  • 4. A “golden rule” with exclusion of the capital budget from the target

These options have advantages and disadvantages. When fiscal rules target overall budget balance, some degree of cyclical flexibility is possible on an ad hoc basis through changes in the numerical value of the budget balance target to accommodate shocks. Adjustments made to fiscal rules during the global financial crisis provide examples of such attempts to accommodate cyclical shocks (see Schaechter and others 2012). Latin American countries—especially Peru, Colombia, and Panama—offer recent examples of rules-based fiscal policies that target overall budget balance, as well as of changes designed to accommodate the incidence of external shocks (Berganza 2012).

The main risk of ad hoc adjustments is that it could come at the expense of the credibility of rules-based fiscal policy. A cyclically adjusted or structural budget balance target would allow flexibility to respond to output shocks. One drawback of structural budget balance rules is that output gaps and tax elasticities to income are difficult to estimate with sufficient reliability, especially for developing countries. A variant of the structural budget balance rule would require the government to achieve budget balance on average over the cycle—or any level of overall deficit or surplus deemed consistent with debt sustainability. A possible drawback could be a requirement for procyclical tightening toward the end of the cycle if fiscal policy were too loose in the earlier phases (IMF 2009).

Another drawback is that the rule requires accurate timing of the cycle and stable national accounts data to preserve the credibility of the fiscal policy framework. The so-called “golden rule” excludes capital expenditure from the targeted budget balance. Protecting this category of expenditure can be justified on the grounds that public investment contributes to long-term growth. The downside is that this approach reduces the comprehensiveness of the budget balance target and, in turn, weakens its link with the objective of debt sustainability. It also implicitly assumes that all capital expenditure is productive, while at the same time excluding current expenditures (especially in human development) that may also raise productivity growth. In any case, gradual adjustment to deviations from fiscal targets would also be warranted. The Swiss and German fiscal rules are noteworthy examples of gradual adjustment mechanisms to deviations from fiscal rule targets (Beljean and Geier 2013). Both rules allow for countercyclical flexibility by targeting the cyclically adjusted budget balance and use a notional control account to correct deviations from fiscal targets.

Targeting the structural fiscal balance may be difficult in the WAEMU zone. Flexibility could be introduced through a framework targeting the overall budget balance over the cycle, inclusive of foreign-financed expenditures. Creating a correction mechanism based on “notional control accounts” would create incentives for WAEMU countries to exercise fiscal restraint in good times in order to accumulate credits in these accounts. These savings could be used as fiscal space in bad times to offset the impact of adverse shocks. The rule could require corrective action to be exercised once accumulated deficits have reached a certain limit in proportion to GDP. It should be noted, however, that in the case of resource-rich countries where a large fraction of fiscal revenues comes from primary commodity exports, focusing on the overall balance over the cycle may not suffice. For short-term stabilization purposes, the fiscal framework would need to be supplemented by a focus on the nonresource primary fiscal balance, targeted over the cycle, as three WAEMU countries (Côte d’Ivoire, Mali, Niger) are natural resource producers, with Togo being a prospective resource exporter

Fiscal Federalism and Risk Sharing

Cushioning the impact of asymmetric shocks on monetary union members typically calls for fiscal federalism, in the form of some centralization of national budgets at the level of the union. A centralized budget works as a shock absorber, by allowing countries hit by negative shocks to receive larger transfers from, and/or pay less tax to, the federal budget. This is equivalent to an interregional transfer within the union from countries affected by positive shocks. These countries pay more tax to the central budget—thus financing transfers to those countries hit by negative shocks—or, alternatively, receive fewer transfers from the central budget. Interregional transfers can be complementary to intertemporal transfers achieved through some degree of national budget flexibility. This is because relying only on decentralized national budgets to offset shocks reduces the degrees of freedom of future national fiscal policy, as the debt issued to counter the shocks will need to be serviced in the future.

There is space for pooling resources in the WAEMU, but large-scale fiscal federalism through budget centralization might be premature. Pooling resources to finance regionally important expenditure programs—especially in infrastructure, to facilitate trade and regional integration—might produce economies of scale, as well as provide a step toward fiscal federalism. This would also shield part of the national public investment budgets from the procyclicality that they currently suffer. On the revenue side, a guiding principle for intergovernmental taxation is that local governments should tax less mobile tax bases, such as consumption or real estate, while corporate and personal income taxes should be centralized (Cottarelli 2012). It remains questionable whether significant centralization of corporate or personal income tax revenues is feasible in the WAEMU given the narrow fiscal bases and the weakness of tax mobilization mechanisms in most of its member countries.

The risk sharing implicit in fiscal federalism could also be achieved through group insurance in the form of a solidarity fiscal fund. Such a fund could perform transfers to adversely hit monetary union members. In its simplest form, a solidarity fund would be financed by contributions from all members. Adversely hit members would be entitled to withdrawals from the fund. This would enable them to cover revenue shortfalls or other insured fiscal risks. The more asymmetric the shocks that affect union members, the greater the gains from pooling resources or from contributing to a group insurance scheme, such as a solidarity fund. This would compare positively to a policy of self-insurance, which would be equivalent to using only national resources (or budgets) to offset the shocks. Intuitively, as all members are not affected at the same time by the asymmetric shocks, the pooled resources necessary to cushion shocks affecting union members at any time would be lower than the sum of resources that individual members would need to put aside to cushion shocks under self-insurance. Hence, for the same level of risk coverage, the contributions of individual union members to a solidarity fund would be lower than the amounts that member states would have to set aside under self-insurance schemes.

A solidarity fiscal fund would collect contributions from all WAEMU member states during good times, with the objective of redistributing resources to member states when they face idiosyncratic shocks. As with all insurance schemes, this would raise the issue of moral hazard. It would also require verification that idiosyncratic shocks affecting the budget are exogenous and not policy-induced by systematic slippages or manipulation of the budget. In addition, such an approach would need incentives to ensure that fiscal insurance does not dilute efforts to maintain fiscal discipline through adequate revenue mobilization and spending controls. To address these concerns, the fund could feasibly cover fiscal revenue shortfalls attributable to measurable shocks up to a certain amount or up to a proportion of the shock. One option would be to cover a certain proportion of shortfalls in revenue that derive from terms of trade shocks (Dos Reis 2004). Moreover, a risk-sharing mechanism could be designed with the aim of strengthening compliance incentives with a rules-based fiscal framework. An option would be to condition a member country’s access to the fund on its compliance with a countercyclical fiscal rule, if such a rule were to be applicable to the monetary union.

Policy Implications

Evidence suggests that in the WAEMU, public investment is procyclical and highly elastic to shocks, especially in bad times. Protecting public investment against shocks would help accelerate growth as infrastructure is comparatively weak in WAEMU. Some policy options for protecting public investment and mitigating the incidence of asymmetric shocks were discussed. These range from injecting more countercyclical flexibility into WAEMU’s rules-based fiscal framework, to designing fiscal federalism and risk-sharing arrangements through solidarity funds. These options could be explored technically in more detail, from an implementation and coordination perspective. Ways and means to make foreign assistance more countercyclical could also be usefully explored. Despite being currently excluded from the fiscal convergence criteria, the results suggest that foreign-financed investment in the WAEMU did not contribute enough to mitigate the procyclicality of public investment. A better understanding of why this is so is warranted.

The weak response of public investment in good times raises the question of why WAEMU governments find it difficult to increase capital budget execution despite efforts in public financial management and public procurement reforms. Judging by the World Bank’s Country Policy and Institutional Assessment indicators, as well as by the evidence available through Public Expenditure and Financial Accountability assessments, these efforts have resulted in significant improvements to public financial management and procurement institutions, as well as legal frameworks, policies, and systems. However, progress appears to have been uneven—stronger on upstream budget processes (budget preparation and classification) than on downstream ones (procurement, budget and contract execution, financial reporting, oversight). Change has been more evident in central finance agencies than in line ministries and at lower levels of government, and generally more focused on the de jure than on the de facto dimensions of public financial management and procurement. These reforms have arguably improved aggregate fiscal discipline compared with the situation that prevailed in the 1990s. The extent to which they have translated into a more strategic allocation of resources (to investment in particular) and, crucially, into more efficient and effective public spending remains less clear. Progress in public investment management will be critical for any risk-sharing mechanism to deliver intended results. Improving project selection, appraisal, procurement, budgeting, implementation, and ex-post evaluation will strongly contribute to reducing the negative impact of shocks.

In a monetary union, fiscal rules are important anchors of medium-term fiscal policy over the cycle so as to preserve fiscal discipline at the aggregate level. However, injecting some flexibility to existing fiscal convergence criteria could help mitigate the procyclicality of public expenditure, especially that of public investment. Because of the procyclicality of public investment, the fiscal deficit has been largely uncorrelated to GDP growth in the WAEMU while in other low-income countries the fiscal balance appears to have been mildly countercyclical. A countercyclical fiscal rule would allow for some positive correlation, with smaller deficits (larger surpluses) in booms and larger deficits (smaller surpluses) in contractions.

At the same time, because shocks affecting WAEMU countries are highly asymmetric, there is room for establishing fiscal federalism arrangements or for adopting a form of risk sharing (or group insurance) to mitigate the incidence of these shocks. Risk-sharing mechanisms would aim to allocate larger financial resources to the Union members exposed to negative shocks. As countries facing difficulties seem compelled to drastically cut back investment in bad times, such mechanisms would also help raise average public investment rates in the WAEMU.

Annex 11.1
Annex Table 11.1.1Groups of Countries
WAEMUSub-Saharan African CountriesLower Income and Lower Middle-Income Countries
BeninBurundiAfghanistan
Burkina FasoCameroonArmenia
Côte d’IvoireCape VerdeBangladesh
Guinea-BissauCentral African RepublicBhutan
MaliChadBolivia
NigerComorosCambodia
SenegalDemocratic Republic of the CongoDjibouti
TogoRepublic of CongoEgypt
EritreaEl Salvador
EthiopiaGeorgia
The GambiaGuatemala
GhanaGuyana
GuineaHonduras
KenyaIndia
LesothoIndonesia
MadagascarMoldova
MalawiMongolia
MauritaniaMorocco
MozambiqueMyanmar
NigeriaNepal
RwandaNicaragua
São Tomé and PríncipePakistan
Sierra LeoneParaguay
SudanPhilippines
SwazilandSri Lanka
TanzaniaSyrian Arab Republic
UgandaTajikistan
ZambiaUkraine
Uzbekistan
Vietnam
Yemen, Republic of
Source: World Bank Classification (http://data.worldbank.org)Note: For regressions explaining the current expenditure and the fiscal balance variables, the available data allowed us to increase the sample by 11 additional countries. We added Haiti, Kiribati, Kosovo, Kyrgyz Republic, Lao PDR, Liberia, Micronesia, Samoa, Solomon Islands, Timor-Leste, and Vanuatu to the sample. Bhutan and Mauritania were dropped since no data for these variables were available.
Source: World Bank Classification (http://data.worldbank.org)Note: For regressions explaining the current expenditure and the fiscal balance variables, the available data allowed us to increase the sample by 11 additional countries. We added Haiti, Kiribati, Kosovo, Kyrgyz Republic, Lao PDR, Liberia, Micronesia, Samoa, Solomon Islands, Timor-Leste, and Vanuatu to the sample. Bhutan and Mauritania were dropped since no data for these variables were available.
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1

Previously published in Journal of International Development, Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/jid.3047.

2

Infrastructure gaps may cost sub-Saharan Africa up to 2 percent per year of foregone GDP growth (Calderon 2009).

3

Data are taken from the World Economic Outlook and the IMF’s IFS database. We include country and time-specific effects. The specification also includes a dummy for the years of armed conflict. We use the UCDP/PRIO data on armed conflict first presented in Gleditsch and others (2002) and updated in Themnér and Wallensteen (2014).

4

When considering flexibility, it is important to distinguish temporary from permanent (or persistent) shocks. While temporary shocks can be accommodated to the extent that there is fiscal space for countercyclical response, adjustment to permanent shocks is inevitable. Such adjustment has to happen through some combination of price, labor, and capital movements. Fiscal policy can only delay, often unproductively, the necessary adjustment to permanent shocks.

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