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5. Ensuring Continued Financial Stability

Author(s):
Montfort Mlachila, Ahmat Jidoud, Monique Newiak, Bozena Radzewicz-Bak, and Misa Takebe
Published Date:
September 2016
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Key financial stability indicators—while stronger than in the past—have come under pressure more recently, possible presaging a slower pace of financial development in the future. Progress in supervisory standards varies substantially across countries, and challenges to implementation remain. Pan-African banks bring new opportunities and are an important driver of financial development, but also pose oversight challenges and may increase systemic risk. The results of an empirical analysis of episodes of commodity price shocks show that declines in commodity prices are associated with higher financial sector fragility, such as increased nonperforming loans and bank costs, and lower bank profitability and liquidity, especially in sub-Saharan Africa, where the level of dependency on commodities is high.

Banking crises in the region have become rarer, and financial soundness indicators have improved over recent decades—although they have weakened somewhat more recently (Figures 17 and 18). The reduced frequency of banking crises—a trend evolving in parallel with favorable macroeconomic conditions and improvements in supervisory frameworks from the early 2000s—has undoubtedly contributed to financial development. At the same time, the impact of the global financial crisis on financial sector stability has been moderate in most sub-Saharan African countries (Mlachila, Park, and Yabara 2013), possibly also reflecting the region’s relatively low financial integration. In fact, main financial soundness indicators have improved compared with a decade ago (Mecagni, Marchettini, and Maino 2015). However, in the past five years, indicators deteriorated somewhat, with capital adequacy ratios staying flat at best and nonperforming loans continuously rising, in line with evidence of overheating in some countries of the region (IMF 2016a).

Figure 18.Systemic Banking Crises, 1976–2010

Sources: Country authorities; and IMF staff estimates.

More recently, the decline in commodity prices, tighter external financing conditions, and exchange rate depreciations have exerted further pressures on various dimensions of financial soundness, in particular in commodity-exporting countries (IMF 2016a). This could be a harbinger of a slower pace of financial development in the medium term.

Progress in supervisory standards and implementation of deposit insurance schemes varies substantially across the region (Table 7; Enoch, Mathieu, and Mecagni 2015; Mecagni, Marchettini, and Maino 2015). Most countries have already moved to international reporting standards or plan to move toward them in the short term, while only six countries still rely on national standards (including Angola, Guinea, South Sudan). However, only a few countries and one monetary union have implemented deposit insurance schemes as of 2016 (CEMAC, Kenya, Nigeria, Tanzania, Uganda, Zimbabwe). Basel II standards have been implemented only in Malawi, Mauritius, Mozambique, and South Africa.

Table 7.Sub-Saharan Africa: Financial Sector Supervisory Standards
Accounting StandardCapital Adequacy Standard1Deposit InsuranceAsset Classification2
AngolaNationalNo Basel II yetNo< 90 days
BotswanaIFRSBasel II in progressNo90 days
BurundiIFRS PlanBasel II in progressNo> 90 days
Cabo VerdeIFRSBasel II in progressNo< 90 days
CEMACIFRS PlanNo Basel II yetImplemented> 90 days
ComorosNationalBasel II in progressNoN/A
Congo, Dem. Rep.NationalNo Basel II yetNo90 days
EritreaN/AN/ANoN/A
EthiopiaIFRS PlanNo Basel II yetNo90 days
GambiaIFRS PlanNo Basel II yetNo90 days
GhanaIFRSNo Basel II yetNo90 days
GuineaNationalNo Basel II yetNoN/A
KenyaIFRSParts of Base II/IIIImplemented90 days
LesothoIFRSNo Basel II yetNo90 days
LiberiaIFRSBasel II in progressNo90 days
MadagascarNationalNo Basel II yetNo90 days
MalawiIFRSBasel IINo90 days
MauritiusIFRSBasel IINo90 days
MozambiqueIFRSBasel IINo> 90 days
NamibiaIFRSParts of Basel IINo90 days
NigeriaIFRSBasel II in progressImplemented90 days
RwandaIFRSBasel II in progressNo90 days
São Tomé and PríncipeIFRS PlanBasel II in progressNoN/A
SeychellesIFRS PlanNo Basel II yetNo90 days
Sierra LeoneIFRSNo Basel II yetNo
South AfricaIFRSBasel IIINo90 days
South SudanNationalNo Basel II yetNoN/A
SwazilandIFRSNo Basel II yetNo90 days
UgandaIFRSNo Basel II yetImplemented90 days
TanzaniaIFRSNo Basel II yetImplemented90 days
WAEMUIFRS PlanNo Basel II yetNo> 90 days
ZambiaIFRSNo Basel II yetNo90 days
ZimbabweIFRSBasel II in progressImplemented91 days
Sources: Enoch, Mathieu, and Mecagni 2015; Mecagni, Marchettini, and Maino 2015.Note: CEMAC = Economic and Monetary Community of Central Africa; IFRS = International Financial Reporting Standards; N/A = not available.; WAEMU = West African Economic and Monetary Union.

The Financial Stability Institute conducts a survey on the current status report on implementation of Basel II, Basel 2.5, and Basel III for non-Basel Committee on Banking Supervision/non-European Union jurisdictions and publishes unedited responses. The column is based for Basel II on answers to Pillar 1 (standardized approach of credit risk, basic indicator approach, and standardized approach for operational risk), Pillar 2, and Pillar 3.

This category indicates the threshold of “number of days in arrears” after which loans are classified as nonperforming loans.

Sources: Enoch, Mathieu, and Mecagni 2015; Mecagni, Marchettini, and Maino 2015.Note: CEMAC = Economic and Monetary Community of Central Africa; IFRS = International Financial Reporting Standards; N/A = not available.; WAEMU = West African Economic and Monetary Union.

The Financial Stability Institute conducts a survey on the current status report on implementation of Basel II, Basel 2.5, and Basel III for non-Basel Committee on Banking Supervision/non-European Union jurisdictions and publishes unedited responses. The column is based for Basel II on answers to Pillar 1 (standardized approach of credit risk, basic indicator approach, and standardized approach for operational risk), Pillar 2, and Pillar 3.

This category indicates the threshold of “number of days in arrears” after which loans are classified as nonperforming loans.

Enforcement of prudential standards is quite weak in some cases, and the adoption of stricter financial standards in the future is likely to face implementation hurdles. Prudential standards are insufficiently enforced in many of the region’s countries. For example, while the WAEMU Banking Commission has put considerable effort into building operational capacity and enhancing banking supervision in the past few years, the average bank does not comply with the regionally required regulatory (Basel I) capital adequacy ratio of 8 percent (IMF 2015g) in half of the WAEMU member countries. This highlights that more ambitious norms in the future may face the risk of even weaker implementation capacity.

The rapid expansion of Pan-African banks brings new opportunities, but it also poses more risks. The role of PABs in enhancing financial intermediation, promoting greater economic integration, and fostering innovation is critical. However, there are also risks related to their systemic importance and interconnectedness. The most important risk is related to the lack of adequate supervisory oversight on a consolidated basis. At the same time, some banks have weak internal governance frameworks. These problems need to be addressed to mitigate against systemic risks that could endanger financial development.

Commodity Price Shocks and Financial Sector Fragility18

The current sharp decline in commodity prices is not unprecedented and frequent occurrence of such declines has led to a large number of studies analyzing the impact of lower commodity prices on economic growth (Deaton and Miller 1995; Dehn 2000), debt (Arezki and Ismail 2013), and conflict (Brückner and Ciccone 2010). However, the literature lacks a systematic empirical analysis of the impact of commodity price shocks on the financial sector of commodity exporters.

The analysis presented here attempts to fill this gap by investigating the impact of commodity price declines on financial sector fragility. In the recent past, countries such as Ecuador, Malaysia, Nigeria, and Russia suffered considerable financial sector dislocation following sharp commodity price declines. Financial fragility can be defined as the increased likelihood of a systemic failure in the financial system, for which the most obvious indicator would be a systemic banking crisis. A less dramatic definition would capture the sensitivity of the financial system to relatively small shocks. The analysis is based on a panel study of 71 commodity exporters among emerging and developing economies over 1997–2013, including 22 sub-Saharan Africa countries.19

Commodity price shocks can contribute to financial fragility through various channels. First, a decline in commodity prices in commodity-dependent countries results in reduced export income and fiscal retrenchment to deal with lower revenue, all of which can adversely impact economic activity and the ability of agents (including governments) to meet their debt obligations, thereby potentially weakening bank balance sheets. Second, a surge in bank withdrawals following a drop in commodity prices may significantly reduce bank liquidity and potentially give rise to a liquidity crisis. Third, if the authorities fail to curtail public spending in the face of declining revenues, payment arrears might start to accumulate, putting suppliers in a difficult financial situation and potentially at risk of defaulting on their bank loans. Fourth, commodity price shocks, if large enough, can also put downward pressure on the domestic currency. The currency depreciation can then lead banks to experience losses owing to net open foreign exchange positions in their balance sheets, or if unhedged borrowers are unable to service their loans.

Periods of declining commodity prices tend, indeed, to be associated with more deteriorated financial sector conditions, including nonperforming loans and the number of banking crises. These results hold for both the full sample and for sub-Saharan African countries (Figure 19).20 The empirical investigation therefore focuses on periods of commodity price declines and relies on two econometric models.

Figure 19.Sub-Saharan Africa: Financial Soundness Indicators, 2006–14

Sources: Country authorities; and IMF staff estimates.

Figure 20.Commodity Price Shocks and Selected Indicators of Financial Sector Fragility

Source: Authors’ estimates.

  • The financial fragility analysis is based on the following equation:
    Where FSIi,t is one of seven financial soundness indicators: (1) share of bank nonperforming loans (NPLs), (2) provisions to NPLs, (3) return on assets, (4) return on equity, (5) cost-to-income ratio, (6) liquid assets-to-deposits and short-term funding ratios, and (7) the ratio of regulatory capital to risk-weighted assets. We also develop a synthetic index of the various indicators—computed as the mean of the seven indicators, each normalized to take a value between 0 and 1 (with higher values corresponding to more stability of the financial sector);PriceShocksi,t represents commodity price shocks, computed as the residual of an econometric model that regresses the logarithm of commodity prices on its lagged values (up to three) and a quadratic time trend. This measure removes the predictable elements from our shock measure, ensuring that we capture only unforeseen price movements. The variable is rescaled to be 0 in case of positive shocks, and range from 0 to 1 in case of negative shocks—as a consequence, the variable represents only negative shocks, and a positive (negative) sign in the regressions presented thereafter means that negative commodity price shocks tend to increase (decrease) the indicator under study;Xmit denotes control variables such as inflation, credit growth, and income per capita; and ωi,t stands for the error term including a country-specific fixed effect and an idiosyncratic term. Equation (1) is estimated using the panel fixed effects estimator.
  • The banking crisis analysis is based on the following equation:
    where Bcrisisi,t is the banking crisis dummy from Laeven and Valencia (2013), and Bcrisisi,test is the estimated value from the regression. As above, Xmit denotes the control variables and ωi,t the error term. Equation (2) is estimated using the conditional logit fixed-effects estimator.

The results provide evidence that declines in commodity prices are associated with higher financial sector fragility, as measured by a wide range of indicators (Table 8). Drops in commodity prices are associated with higher nonperforming loans and bank costs, while they reduce bank profitability (return on assets and return on equity), liquidity, and provisions to nonperforming loans. As a result of this fragility, commodity price downturns tend to increase the likelihood of banking crises. While these results are found across regions, sub-Saharan African countries seem to be more affected, via both a higher impact on NPLs and a higher likelihood of banking crises following price declines. For instance, a 50 percent decline in commodity prices (similar to the order of magnitude experienced over the period July 2014–June 2015, and equivalent to a 3.6 standard deviation) results in an increase in nonperforming loans of 3.5 percentage points for the whole sample and 4.5 percentage points in sub-Saharan Africa. In addition, the results are robust to a battery of robustness checks, including (1) an alternative measure of commodity price shocks, (2) a differentiation between hydrocarbon and other nonrenewable commodities, (3) a focus on shocks lasting more than one year, and (4) a focus on large shocks.21

Table 8.Impact of Declines in Commodity Prices and Financial Sector Fragility
(1)(2)(3)(4)(5)(6)(7)(8)(9)
NPLsProvisions to NPLsROAROECostReg. CapitalLiq. AssetsIndexCrisis
Price shocks2.2840***−16.0300***−0.5810***−6.5350***1.5370*−0.3440−1.9730**−0.0083***1.8750**
(0.52)(3.69)(0.13)(1.58)(0.90)(0.37)(0.93)(0.002)(0.78)
Exchange rate, t-14.7850***−16.6900−1.1000−22.08004.9110−2.7760−0.6880−0.0133−0.6720
(1.34)(12.09)(1.35)(26.51)(11.71)(3.54)(3.74)(0.01)(1.12)
Real interest t-10.1160**−0.8220***−0.0223−0.23100.1380*0.0009−0.0502−0.0005**0.0977***
(0.05)(0.24)(0.01)(0.18)(0.07)(0.02)(0.05)(0.0002)(0.04)
M2/reserve, t-10.0500−0.70100.00990.10100.0828−0.0013−0.09800.00020.3730**
(0.19)(2.23)(0.01)(0.29)(0.34)(0.10)(0.48)(0.00)(0.15)
Infaton, t-10.00010.05230.00510.15100.00580.03880.03000.00010.0855**
(0.04)(0.28)(0.02)(0.40)(0.16)(0.04)(0.09)(0.00)(0.04)
Credit growth, t-1−5.009014.0000−0.2430−5.8580−0.3940−5.3770***−6.7660−0.0140**0.0444
(3.19)(17.88)(0.30)(3.85)(3.12)(1.55)(4.17)(0.01)(2.98)
Log(GDPPC), t-1−1.5950−3.6980−0.16600.0153−2.0160−0.1780−6.4890**−0.0132**−3.4290**
(1.50)(6.45)(0.24)(2.55)(1.76)(0.68)(2.73)(0.00)(1.55)
Debt t-10.1070**0.0298−0.0053*0.01000.0696***0.02180.0026−0.00004−0.0225*
(0.04)(0.17)(0.00)(0.05)(0.02)(0.03)(0.05)(0.00)(0.01)
Constant40.9800185.10006.047015.650099.5600**20.9800195.5000***0.8470***
(37.96)(159.60)(5.92)(63.20)(42.68)(17.50)(65.68)(0.16)
Observatons457426691691693454697697191
Countries454558585845585815
R-squared0.34700.12900.05800.04600.12300.12900.09200.0520
Source: authors’ estimations.Note: Fixed effects are included. Robust standard errors in parentheses.Note: ***p <0.01, significant at 1 percent, **p <0.05, signifcant at 5 percent, *p <0.10, signifcant at 10 percent. NPLs = nonperforming loams; ROA = return on assets; ROE = return on equity.
Source: authors’ estimations.Note: Fixed effects are included. Robust standard errors in parentheses.Note: ***p <0.01, significant at 1 percent, **p <0.05, signifcant at 5 percent, *p <0.10, signifcant at 10 percent. NPLs = nonperforming loams; ROA = return on assets; ROE = return on equity.

The recognition that commodity price declines are a major source of financial fragility raises questions about the appropriate framework to ensure financial stability in the face of these shocks. While there is not much that macroeconomic policy can do to prevent commodity price shocks, the analysis shows that the impact of these shocks on the banking system depends on the economic, financial, and institutional conditions in place when the shocks occur. Indeed, the adverse effects of commodity price shocks on financial fragility tend to occur more severely in countries with poor quality of governance and weak fiscal space, as well as those that do not have a sovereign wealth fund, do not implement macroprudential policies, and do not have a diversified export base. In addition, stronger public finance management capacities can help prevent the occurrence of domestic arrears in the wake of negative commodity price shocks. Addressing these weaknesses could reduce financial sector fragility and the probability of banking crises.

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