Abstract
This paper presents a simple structural model of inflation adapted for Nigeria based on the methodology of Berg, Karam, and Laxton. This approach allows different policy options to be considered systematically in a baseline forecasting exercise. The development and calibration of this model are ongoing. The consolidation of the banking system has transformed Nigeria’s financial system and created opportunities for financial institutions and market participants; but, it also poses challenges for financial stability. Efforts must therefore be stepped up to strengthen supervision and regulatory interventions.
I. Nigerian Inflation: A Structural Model for Policy Analysis1
1. Macroeconomic conditions in Nigeria have improved in recent years. Inflation has fallen to single digits. An oil-price-based fiscal rule has helped contain government spending to levels consistent with macroeconomic stability. Financial markets have developed; the maturity structure of the domestic bond market is longer and the size and importance of the interbank foreign exchange market have increased, resulting in a more flexible exchange rate. These developments augur well for the implementation of monetary policy.
2. At the same time, money demand has become increasingly unpredictable. Financial market development and rapid financial deepening are affecting the relationship between money and prices. Meanwhile, increased foreign investor interest in Nigerian assets has spurred capital inflows. These developments will likely continue, further complicating forecasts of money demand.
3. Against this backdrop, the Central Bank of Nigeria (CBN) has announced that it intends to adopt inflation targeting (IT). The authorities are working to put the right conditions in place before implementing the new regime. In examining experience with IT, the Fund’s board recommended the following conditions be in place before IT is implemented: (i) target credibility (including central bank independence, target specification, and a communication strategy); (ii) a reasonably good understanding of the inflation process at the central bank; (iii) considerable exchange rate flexibility; and (iv) the absence of fiscal dominance.
4. This chapter describes a simple forecasting and policy analysis system (FPAS) for forecasting inflation and assessing economic risks in Nigeria.2 The model is designed to support policy analysis in an inflation-targeting regime, which principally aims to provide anchors for inflation and inflation expectations. It should help inform the CBN’s view of the inflation process and help the bank structure its communication strategy.
5. This chapter is divided into five sections. Section A explains the model’s structure. Section B discusses the key assumptions underlying the estimated equilibrium values for inflation, output, interest rates, and the exchange rate. Section C discusses Nigeria’s current policy mix and describes the model’s baseline forecast. Section D analyzes risks to the baseline forecast and illustrative examples of the impact of a more expansionary fiscal stance, a real appreciation of the naira, and higher food prices. Section E concludes.
A. The Model
6. The model captures the link between the policy instrument (a short-term interest rate) and the nexus of output, inflation, and the exchange rate in a small-open economy. The model expresses key variables as deviations-from-equilibrium, and does not try to explain the underlying real equilibrium values. However, the model can address many policy issues that arise routinely in making decisions about monetary policy actions and communicating the reasons to the public.
7. The model provides a helpful organizing framework for establishing near- and medium-term baseline forecasts. This approach encourages a more-structured and transparent discussion of current policy. In generating alternative scenarios, the model is a valuable tool for assessing key risks to the baseline forecast and in analyzing the relative importance of various assumptions.
8. There are four core equations: (i) an aggregate demand equation (IS curve) that relates the level of real activity to expected and past real activity, the real interest rate, the real exchange rate, and the level of foreign activity; (ii) a price-setting equation (Phillips curve) that relates inflation to past and expected inflation, the output gap, the exchange rate and the relative price of oil; (iii) an uncovered interest parity condition for the exchange rate, with some allowance for backward-looking expectations; and (iv) a rule for setting the policy interest rate as a function of the output gap and expected inflation. Appendix I.A1 provides the full list of model equations. Appendix I.A2 provides details on calibration.
9. Because Nigeria is an open economy, the model considers the impact of foreign shocks on the domestic environment using the United States as a proxy for the world economy.3 The equations for the U.S. economy have a similar structure to the Nigerian equations but exclude the open-economy linkages.
10. The monetary transmission mechanism of the model is depicted in Figure I.1. The policy rate affects the economy through an internal and external channel. The internal channel is the long run interest rate, which first affects aggregate demand, then output, and finally inflation. The external channel is the exchange rate, which impacts inflation directly (through pass-through) and aggregate demand indirectly through its impact on foreign demand. Inflation expectations are influenced by the inflation outcome and vice versa. The structure of the economy determines the strength of the different arrows in Figure I.1.
Model Diagram
Citation: IMF Staff Country Reports 2008, 065; 10.5089/9781451829075.002.A001
Source: Laxton and Scott (2000)11. The model may not adequately capture the structure of Nigeria’s economy in two areas. First, weather-related supply shocks heavily influence the CPI in Nigeria but are not captured in the model. Instead, the impact of weather on food prices is captured in the error term, making this a key forecasting variable when rainfall deviates from normal conditions. Second, the strength of the interest rate channel of monetary policy, while evolving, is still relatively weak. There are still difficulties in managing the overnight interbank interest rate, and the link between the monetary policy rate and lending and savings is not well defined. Over time, however, as the financial system develops and global capital flows increase, this channel of monetary policy should strengthen.
12. In line with modeling practices in many policymaking institutions, the parameter values in the model equations were derived based on economic principles, the econometric evidence available, and an understanding of how the economy functions. The rationale for the coefficient choices are in the descriptions of the four key equations that follow. (The appendices provide additional details).
Aggregate demand equation
13. Domestic output depends on the real interest rate, the real exchange rate, and demand in the rest of the world (represented by the United States). Dynamics are added through past and future domestic output gaps. Parameters on lead and lag values of the output gap are set such that the shocks take two years to work through the economy, based on the norm in emerging markets. The real exchange rate is assumed to have a larger impact on output than real interest rates, because the interest rate channel is still evolving. U.S. output is assumed to have a low impact on domestic demand since U.S. business cycles typically have little relation to conditions in Nigeria.
Phillips curve equation
14. Inflation depends on expected and lagged inflation, the output gap, the exchange rate gap, and movements in the real price of oil. Parameters on lead and lag values of inflation are set such that monetary policy has a low level of credibility, i.e., a high degree of inflation inertia is assumed, since economic agents typically view past inflation as a better predictor of outcomes than the officially announced inflation target. Therefore, the parameter value is set such that only large increases in the policy rate would impact current inflation. Exchange rate pass-through is assumed to be high, but the level of imports in the CPI is relatively low. Because wage contracts and indexation may be less prevalent in economies that are growing rapidly, it is assumed that inflation responds to excess demand without significant lags.
Uncovered interest parity
15. The exchange rate and interest rates are linked by an interest-parity condition. This states that, with international capital mobility, the expected return on a short-term investment should be the same at home as abroad, ignoring country-risk premiums. If the exchange rate is expected to depreciate, therefore, an investor will demand to be compensated in the form of a higher domestic interest rate. For forward-looking exchange-rate expectations, the model permits, but does not impose, model-consistent (“rational”) expectations.
16. The basic FPAS model has been modified to reflect the current trend real appreciation in Nigeria. In such an environment, in addition to the last period’s value, agents add in the observed rate of trend appreciation to forecast the value of the currency in the next period.4
Monetary policy reaction function
17. The monetary policy reaction function mirrors the specification in many similar models. The policy instrument is a short-term nominal interest rate; the central bank sets it to anchor inflation to a target rate, π*. The central bank may also adjust its actions when output deviates from equilibrium. Here it is assumed that (i) given the low level of policy credibility, the monetary stance is aggressive when inflation deviates from the target; (ii) the output gap is less important than inflation in policy decisions; and (iii) the CBN prefers to smooth changes in the interest rate.
B. Assumptions on Equilibrium Values
18. The results of the model depend on the assumed equilibrium values. The model expresses each variable in terms of its deviation from equilibrium, but does not attempt to explain movements in equilibrium real output, the real exchange rate, the real interest rate, or in the inflation target. Estimating these equilibrium values is likely more important than getting the model’s parameters accurate, as discussed in the previous section. A key question, therefore, is how to choose these values so that they accurately reflect the Nigerian economy. Figure I.2 provides initial estimates; below are the key assumptions.
Equilibrium Values
Citation: IMF Staff Country Reports 2008, 065; 10.5089/9781451829075.002.A001
Inflation target. It is assumed that the monetary authorities have been setting the interest rate according to a criterion that is similar to inflation targeting. The inflation target is assumed to be given by the trend of actual inflation until end-2005.5 Since 2005 and the start of Nigeria’s reform program supported by the Policy Support Instrument, the target is assumed to be 8.5 percent, the higher end of the authorities’ announced target of single digits. Currently, Nigeria’s inflation rate is below its inflation target at end-2007.
Equilibrium real interest rate. The equilibrium real interest rate is assumed to be 5 percent, which implies a risk premium of about 300 basis points. While lower than the risk premium of Nigerian sovereign bonds traded in 2006 (before the London Club buyback), this is broadly consistent with issues of African sovereign debt in 2007. The actual real interest rate has fluctuated widely over the years, with the current level below the assumed equilibrium level.
Equilibrium real exchange rate. Staff estimates indicate the naira could be undervalued by up to 15 percent over the medium term. It is unlikely that this gap is adding to aggregate demand through the external sector. To close this gap, therefore, we assume a trend real appreciation in the equilibrium value through 2010; after that, the equilibrium value is assumed to be constant. The historical equilibrium value is given by the trend value as calculated using the LRX filter.
Equilibrium non-oil output. The equilibrium value is calculated using an HP filter on the log level of non-oil output. Potential non-oil output growth is 8 percent. This variable is the most difficult to estimate because data sources are weak: GDP is calculated annually, and the growth series is relatively uniform. There are also few other measures of economic activity with high frequency. Using the HP filter, Nigeria is assumed to be marginally above potential. The historical values show minimal deviations from trend, with the output gap never above 1 percentage point. Swings in the gap in 2003 relate to changes in agricultural output and are correlated with trends in the headline inflation rate.
C. Baseline Forecast
19. The model is helpful in preparing baseline forecasts. The model is a relatively simple and tractable representation of the economy; as such, the results are best used to frame discussions about the baseline forecast and to help shape medium- and long-term forecasts, where issues of consistency and dynamics are resolved as economic fundamentals converge to the estimated equilibrium path.
20. The baseline forecast is a combination of judgment in the near term and a pure model forecast in the medium-term. 2007 forecasts are judgment. 2008 forecasts are a combination of judgment and model forecast, as model residuals are gradually phased out over the four quarters. Forecasts beyond 2009 are a pure model forecast.
21. Nigeria’s economy is growing robustly, aided by low interest rates (Figure I.3). Output is above potential, supported by strong fiscal demand and lower interest rates, which are stimulating private sector credit growth. Short-term interest rates are below the neutral rate as Naira appreciation pressures continue and inflation remains well below target (aided by positive weather conditions that helped lower the headline rate in 2006 and 2007). Monetary conditions will add to aggregate demand as the output gap is projected to average 1.6 and 3.7 percentage points in 2008 and 2009, respectively.
Baseline Scenario
Citation: IMF Staff Country Reports 2008, 065; 10.5089/9781451829075.002.A001
22. Nonetheless, rates in the medium term will need to rise to return the real interest rate to its neutral rate and contain excess aggregate demand. The rise in interest rates should cause output to dip in the medium term and push the output gap to slightly negative levels in 2011.
D. Risk Analysis
23. This section describes the results of shocks to the baseline assumptions. An increase in domestic demand after a fiscal shock, an exogenous appreciation of the naira, and a higher food price scenario are considered. The strength of the model is in evaluating risks to the forecast, appropriate responses to a variety of shocks, and dependencies of the forecast and policy recommendations on various assumptions about the economy (see Figure I.1).
Fiscal expansion (Figure I.4)
24. An illustrative example of a fiscal expansion in 2008–10, stemming from additional spending of 5 percentage points of non-oil GDP a year, is considered. This is implemented through an add-on shock to the residual in the aggregate demand equation.
Fiscal Expansion Scenario
Citation: IMF Staff Country Reports 2008, 065; 10.5089/9781451829075.002.A001
25. The results show that the additional spending would likely exceed the economy’s absorptive capacity. After initially accelerating, growth slows sharply as the central bank raises interest rates to keep inflation in single digits. Higher interest rates, in turn, squeeze credit and dampen private sector activity, causing the naira to appreciate. The loss of competitiveness further constrains the private sector.
Exogenous appreciation of the naira (Figure I.5)
26. In this shock, it is assumed the naira appreciates fifteen percent above trend for two quarters. The net effect in the two quarters is that the naira appreciates to a level below N 110 per US$1.
Naira Appreciation Scenario
Citation: IMF Staff Country Reports 2008, 065; 10.5089/9781451829075.002.A001
27. This shock dampens inflation and lowers foreign demand and tradable output in the short run. The policy response is to lower interest rates and keep their path lower than under the baseline, thus muting the shock’s impact on aggregate demand.
High food prices (Figure I.6)
28. In this shock, it is assumed food prices are higher than projected in the first three quarters of 2008. This is implemented through an add-on shock to the residual in the Phillips curve equation. High food prices are assumed to add 2 percentage points to the headline inflation rate.
High Food Price Scenario
Citation: IMF Staff Country Reports 2008, 065; 10.5089/9781451829075.002.A001
29. To keep headline inflation within its target range, the monetary authorities would need to raise interest rates more rapidly than under the baseline scenario.6 The consequences of this policy are reduced output (and a smaller output gap) and a somewhat more appreciated naira. Over the medium-term, the growth rate decreases more gradually (compared to the baseline), as the build up in excess demand is less pronounced in the short-run.
E. Conclusions
30. This chapter presents a simple structural model of inflation adapted for Nigeria based on the methodology of Berg, Karam, and Laxton (2006a, 2006b). The model embodies the principle that monetary policy in an inflating targeting framework aims to anchor inflation and inflationary expectations.
31. This approach allows different policy options to be considered systematically in a baseline forecasting exercise. The chapter analyzes the impact of three shocks on the baseline forecast—a fiscal expansion, an unexpected appreciation of the naira, and higher food prices.
32. The development and calibration of this model are ongoing. As we learn more about the transmission mechanism in Nigeria, the model will continue to be refined. Given the importance of oil in the Nigerian economy, a more detailed treatment of the price of oil on fiscal policy and the real equilibrium exchange rate could be considered.
References
Berg, A., P. Karam, and D. Laxton, 2006a, “A Practical Model-Based Approach to Monetary Policy Analysis—Overview,” IMF Working Paper (Washington: International Monetary Fund).
Berg, A., P. Karam, and D. Laxton, 2006b, “Practical Model-Based Monetary Policy Analysis—A How-to Guide,” IMF Working Paper (Washington: International Monetary Fund).
Epstein, N., P. Karam, D. Laxton, and D. Rose, 2006, “A Simple Forecasting and Policy Analysis System for Israel: Structure and Applications,” in Israel: Selected Issues, Country Report No. 06/121 (Washington: International Monetary Fund).
Harjes, T. and L. Ricci, 2007, “A Quantitative Analysis of Inflation Dynamics in South Africa,” in South Africa: Selected Issues, Country Report No. 05/345 (Washington: International Monetary Fund).
International Monetary Fund, 1999, “Inflation Targeting—Implications for IMF Conditionality,” IMF Policy Paper (Washington: International Monetary Fund).
International Monetary Fund, 2006, “Inflation Targeting and the IMF,” IMF Policy Paper (Washington: International Monetary Fund).
Laxton, Douglas and Alasdair Scott, 2000, “On Developing a Structured Forecasting and Policy Analysis System Designed to Support Inflation-Forecast-Targeting,” in Inflation Targeting Experiences: England, Finland, Poland, Mexico, Brazil, Chile, (Ankara: The Central Bank of Turkey), pp. 6–63.
Tiffin, A., 2007, “Modeling Monetary Policy in Romania,” in Romania: Selected Issues, Country Report No. 07/220 (Washington: International Monetary Fund).
Appendix I.A1. Complete Model Equations
The following are the equations used for the Nigerian economy. The equations for the U.S. economy have a similar structure but exclude the open-economy linkages.
Behavioral equations
Steady-state and equilibrium equations
Identities
Variable definitions
| ygap |
output gap, percentage points |
| yt |
log of real GDP |
|
|
log of potential real GDP |
|
|
growth rate of potential GDP, quarter/quarter at annual rate, percentage points |
|
|
steady-state growth rate of potential GDP, quarter/quarter at annual rate, percentage points |
| π |
cpi inflation, quarterly at annualized rate, percentage points |
| πc |
core cpi inflation, quarterly at annualized rate, percentage points |
| π * |
target inflation rate, annualized rate, percentage points |
| π4t |
four-quarter change in the CPI, annualized rate, percentage points |
|
|
Steady-state inflation target, annualized rate, percentage points |
| πrpoil,t |
change in the relative price of oil, quarterly at annualized rate, percentage points |
| π4rpoil,t |
four-quarter (moving average) change in the relative price of oil, percentage points |
| CPIt |
level of the domestic consumer price index |
|
|
level of the U.S. consumer price index |
| RS |
nominal interest rate, percentage points |
| RRgap |
real interest rate gap, percentage points |
| RR |
real interest rate, percentage points |
| RR* |
equilibrium real interest rate, percentage points |
|
|
steady-state equilibrium interest rate, percentage points |
| RRUS |
U.S. real interest rate, percentage points |
| RR*US |
equilibrium U.S. real interest rate, percentage points |
| zgap |
real exchange rate gap, percentage points |
| z |
log of the real exchange (an increase implies a depreciation) |
| S |
nominal exchange rate, value of foreign currency in local currency |
| z* |
log of the equilibrium real exchange rate (an increase implies a depreciation) |
|
|
log of the steady state equilibrium exchange rate |
| ρ* |
equilibrium risk premium, percentage points |
Appendix I.A2. Calibration
This appendix outlines the assumptions in the model.
Aggregate demand:
Aggregage Demand Equation
Aggregage Demand Equation
| Parameter | Lower range | Upper range | Nigeria | U.S. |
|---|---|---|---|---|
| Beta_ld | 0.05 | 0.15 | 0.05 | 0.10 |
| Beta_lag | 0.50 | 0.90 | 0.85 | 0.85 |
| Beta_RRgap | Sum 0.10 | Sum 0.30 | 0.05 | 0.10 |
| Beta_zgap | 0.10 | … | ||
| Beta_USygap | … | … | 0.10 | … |
Aggregage Demand Equation
| Parameter | Lower range | Upper range | Nigeria | U.S. |
|---|---|---|---|---|
| Beta_ld | 0.05 | 0.15 | 0.05 | 0.10 |
| Beta_lag | 0.50 | 0.90 | 0.85 | 0.85 |
| Beta_RRgap | Sum 0.10 | Sum 0.30 | 0.05 | 0.10 |
| Beta_zgap | 0.10 | … | ||
| Beta_USygap | … | … | 0.10 | … |
The output gap tends to exhibit substantial inertia (high βlag), which is normally lower in developing than in developed countries, while the effect from lead output (βld) is usually limited.
The effect of interest rates is crucial for the monetary transmission mechanism, as a larger βRRgap would imply a more effective monetary policy.
The effects of exchange rates (βzgap) and foreign output (βUSygap) tend to be larger in more open economies.
Significant lags in the transmission of monetary policy imply that the sum of βRRgap and βzgap should be smaller than βlag.
Phillips curve and core Phillips curve:
Phillips and Core Phillips Curve
Phillips and Core Phillips Curve
| Parameter | Lower range | Upper range | Nigeria | U.S. | |
|---|---|---|---|---|---|
| Phillips curve | |||||
| Alpha_pie_ld | >0 | 1.00 | 0.10 | 0.20 | |
| Alpha_ygap | 0.25 | 0.50 | 0.40 | 0.30 | |
| Alpha_z | … | … | 0.20 | … | |
| Alpha_0 | … | … | .074*(1/3) | .018*(1/3) | |
| Alpha_1 | … | … | .074*(1/3) | .018*(1/3) | |
| Core phillips curve | |||||
| Alpha_c_pie_ld | >0 | 1.00 | 0.10 | 0.20 | |
| Alpha_c_ygap | 0.25 | 0.50 | 0.40 | 0.30 | |
| Alpha_c_z | … | … | 0.20 | … | |
| Alpha_c_3 | 0.25 | 0.50 | 0.25 | 0.25 | |
Phillips and Core Phillips Curve
| Parameter | Lower range | Upper range | Nigeria | U.S. | |
|---|---|---|---|---|---|
| Phillips curve | |||||
| Alpha_pie_ld | >0 | 1.00 | 0.10 | 0.20 | |
| Alpha_ygap | 0.25 | 0.50 | 0.40 | 0.30 | |
| Alpha_z | … | … | 0.20 | … | |
| Alpha_0 | … | … | .074*(1/3) | .018*(1/3) | |
| Alpha_1 | … | … | .074*(1/3) | .018*(1/3) | |
| Core phillips curve | |||||
| Alpha_c_pie_ld | >0 | 1.00 | 0.10 | 0.20 | |
| Alpha_c_ygap | 0.25 | 0.50 | 0.40 | 0.30 | |
| Alpha_c_z | … | … | 0.20 | … | |
| Alpha_c_3 | 0.25 | 0.50 | 0.25 | 0.25 | |
απld determines the importance of forward- (and backward-) looking components in inflation expectations. For example, a lower απld makes it more difficult for the monetary authorities to change inflationary patterns.
αygap characterizes the relation between the output gap and inflation. It increases, for example, with the number of firms that adjust prices every period. The larger αygap, the less output responds to price level fluctuations. Hence, the larger αygap is, the smaller the sacrifice ratio would be (i.e., the cumulative loss in output as a percent of potential output necessary to permanently lower inflation by 1 percentage point).
αz relates directly to the weight of imported goods in the CPI basket and the pass-through of foreign-currency prices (and hence the nominal exchange rate) on to the domestic-currency prices of imports.
α0 and α1 relate to the weight of oil related products in the CPI basket and the pass-through to prices.
αc,3 allows for some feedback from headline inflation to core inflation.
Monetary policy reaction function:
Monetary Policy Rule
Monetary Policy Rule
| Parameter | Lower range | Upper range | Nigeria | U.S. |
|---|---|---|---|---|
| Gamma_pie | >0 | 5.00 | 4.00 | 2.00 |
| Gamma_RSlag | 0.50 | 1.00 | 0.50 | 0.50 |
| Gamma_ygap | >0 | … | 0.25 | 0.50 |
Monetary Policy Rule
| Parameter | Lower range | Upper range | Nigeria | U.S. |
|---|---|---|---|---|
| Gamma_pie | >0 | 5.00 | 4.00 | 2.00 |
| Gamma_RSlag | 0.50 | 1.00 | 0.50 | 0.50 |
| Gamma_ygap | >0 | … | 0.25 | 0.50 |
A key parameter in this function is γπ, which captures the degree of aggressiveness of the monetary authorities. Hence, a higher value for γπ implies that the authorities will respond to a given shock with a larger change in interest rates. This tends to frontload the output costs but is appropriate for economies with lower credibility.
The parameter γRSlag measures the aversion of the authorities to alter the interest rates, so that a higher coefficient implies monetary reaction to a given shock is relatively slow.
Given the high degree of uncertainty about the output gap and substantial real-time measurement errors in output, the parameter on the output gap (γygap) is usually small.
Uncovered interest parity
Exchange Rate
Exchange Rate
| Parameter | Lower range | Upper range | Nigeria | U.S. |
|---|---|---|---|---|
| Delta_z | >0 | 1.00 | 0.50 | 0.50 |
Exchange Rate
| Parameter | Lower range | Upper range | Nigeria | U.S. |
|---|---|---|---|---|
| Delta_z | >0 | 1.00 | 0.50 | 0.50 |
The parameter δ (with 0<δ<1) determines the degree to which exchange rate expectations are forward looking as opposed to backward looking. A value closer to 1 implies expectations are much more forward looking and will thus prompt a much greater exchange rate response to anticipated changes in fundamentals.
Prepared by Chad Steinberg.
This model calibrates and modifies a model developed by Berg, Karam, and Laxton (2006a, 2006b), which has now been adopted for over 20 countries within the IMF.
The United States has the largest links to Nigeria’s economy. However, if we exclude oil receipts, by some measures Europe’s links to the Nigerian economy are even stronger. Future versions of this model may thus use Europe as a proxy for the world’s economy.
In several transition economy versions of this model, the trend appreciation is also subtracted from the Phillips curve equation such that in the steady state there is a positive rate of real appreciation (e.g., Tiffin (2007)). This would also imply that the trend real appreciation does not reduce inflation. Future versions of this model may consider this extension.
This is calculated using the Laxton-Rose-Xie (LRX) filter (a more general version of the univariate Hodrick-Prescott (HP) filter), which is described in detail in Appendix IV of Berg, Karam, and Laxton (2006b).
The authorities may choose not to respond to this supply shock if core, rather than headline, inflation is included in the monetary policy reaction function.
Prepared by Stephen Swaray and Jennifer Moyo.
Two banks have merged since the initial consolidation.
Some banks that failed to meet the higher minimum capital requirement challenged the NDIC’s petition to liquidate them. To date, approval for liquidation has been granted to 11 banks; 3 banks remain in court.
