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Abstract

Gary Moser

Appendix I. Determinants of Inflation in Nigeria

Gary Moser

The rate of inflation in Nigeria has increased steadily and markedly since independence in 1960. During the period following independence (1965–75), Nigeria’s rate of inflation was about equal to that of its trading partners, averaging 10 percent annually (Figure 14). In the next decade (1975–85), the respective rates of inflation diverged dramatically, as Nigeria’s average annual rate nearly doubled, to 18 percent, while that of the trading partners narrowed significantly, to 4 percent. These trends continued between 1985 and 1990, as Nigeria’s annual average rose to 24 percent while its trading partners posted an average rate of 13 percent. More recently, since late 1990, Nigeria has experienced a period of stagflation. By the end of 1993, inflation had reached 60 percent and real per capita income growth had stalled.

Figure 14.
Figure 14.

Consumer Prices

(Annual percentage change)

Sources: IMF,International Financial Statistics; and IMF staff estimates.1 Rainfall defined as percentage deviation from average rainfall.

This study reviews previous empirical studies of the determinants of inflation in Nigeria, analyzes the dominant factors influencing inflation, presents the empirical results of an error correction model, and discusses the policy implications of the empirical results.

Consumer Price Index

The official consumer price index (CPI) is based on a composite of urban and rural price data compiled monthly by the Federal Office of Statistics (FOS)28 and reflects household expenditure patterns in the 1985/86 National Consumer Survey.29

Composite food prices dominate the CPI, representing 69 percent of the total market basket (Table 13), with staple food commodities alone representing 42 percent. Consequently, factors affecting food prices dominate movements in the CPI (Figure 14). These factors include agroclimatic conditions, wages, domestic inputs, and import prices, with rainfall playing a key role. Subsistence agriculture, which is not included in marketed production, is important in marginal supply and demand during periods of drought or abundant rainfall. Imports, while significant in the economy as a whole, have tended to be less significant in influencing the CPI since household consumption, which is predominantly food related, has a low import content.

Table 13.

Consumer Price Index Market Basket

(In percent)

article image
Source: Nigerian Federal Office of Statistics; based on the 1985/86 National Consumer Survey.

Figures may not add due to rounding.

Inflation During 1985–93

The rate of inflation dropped sharply in 1985 and 1986, as favorable weather conditions led to abundant crop production and tight fiscal and monetary policies substantially reduced excess liquidity in the economy (Figure 15). Anchored by a tight fiscal and monetary policy stance, and aided by favorable weather, the devaluation of the naira in 1986 (96 percent in domestic currency terms) had virtually no impact on that year’s rate of inflation. Inflation increased moderately in 1987, averaging 10 percent, with the onset of the 1987–88 drought and the lagged impact of the substantial devaluation in 1986. Table 14 presents data since the mid-1980s on some of the factors that have influenced inflation in Nigeria.

Table 14.

Matrix of Factors Influencing Inflation

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Sources: International Monetary Fund,International Financial Statistics; and IMF staff estimates.

End-of-period basis.

Broad money rose sharply during the second half of the year.

Figure 15.
Figure 15.

Inflation, Money, and Exchange Rate Developments

(Annual percentage change)

Sources: IMF,International Financial Statistics; and IMF staff estimates.

A severe drought in key growing regions of the country in 1987 and 1988, combined with fiscal and monetary expansion, led to a virtual doubling of food prices in 1988. Consequently, the rate of inflation jumped to 55 percent in 1988. While food prices actually fell during the second half of 1989 as rains and production improved, the average rate of inflation remained above 50 percent, primarily as a result of the cumulative impact of broad money growth and the sizable devaluation of the naira in 1989.

Inflation slowed considerably in 1990, to an average annual rate of 7.4 percent, largely reflecting the contractionary fiscal and monetary policies implemented during late 1989 and early 1990 and the improved harvests in 1989 and 1990 resulting from excellent rains. As a result, the increase in food prices was held to 3 percent in 1990. Toward the end of 1990, fiscal and monetary policies loosened considerably, which led to the upward movement in inflation in 1991 to 13 percent. The depreciation of the naira by 23 percent during 1991 also added to the upward pressure on prices.

The rate of inflation increased markedly in 1992, to 45 percent on an annual average basis, as a result of substantial excess liquidity in the economy brought about by the continued monetization of the growing fiscal deficit, which increased to 8 percent of GDP in 1992. The sharp devaluation of the naira (75 percent in local currency terms) during this expansionary period put further upward pressure on prices.

Inflation accelerated further in 1993, to an estimated 57 percent annually, reflecting the sharp increase in the fiscal deficit, to 18 percent of GDP. The devaluation of the official exchange rate (28 percent in local currency terms) also added upward pressure on the rate of inflation, but this pressure was tempered somewhat by the estimated 4 percent decline in the index of foreign prices.

Quantitative Analysis

Factors Influencing Inflation

Recent studies on inflation in Nigeria broadly agree on the key factors influencing the rate of inflation: money growth, income growth, and exchange rate movements. These factors are presented for period averages in Table 15. It is noteworthy that, as the table indicates, the widening of the differential between domestic and foreign inflation has generally occurred during periods of rapid monetary expansion, while the impact of exchange rate movements on inflation is less clear. However, recent empirical studies do not concur on the relative importance of each of these factors as determinants of inflation. Most of them conclude that excess domestic demand, generated by expansionary fiscal and monetary policies, has been the principal factor underlying the rising inflation rate in Nigeria.30 Others suggest that cost-push inflation resulting from excessive devaluations and wage increases has been the primary impetus for the upward inflationary spiral.31

Table 15.

Selected Price, Money, and Exchange Rate Indicators

(Average annual change)

article image
Sources: International Monetary Fund,International Financial Statistics; and IMF staff estimates.

End-of-period basis.

Weighted average of trading partner prices (in U.S. dollar terms).

Broad money growth has been found to be a fundamental determinant of inflation in many of the studies, while the impact of exchange rate movements on inflation has been less clear. This ambiguity is most likely the result of the time periods studied. During the 1960s and 1970s, when the official exchange rate was stable, there were numerous periods of high inflation. Subsequently, in the 1980s and early 1990s, the considerable devaluation of the naira occurred during a period of increasing price instability and rising inflationary pressures and most likely added to the upward movement in inflation. As the magnitude of the impact of exchange rate movements on inflation is unclear, it will be tested empirically below.

Many of the studies also reported that real income growth played a significant deflationary role by increasing the demand for real money balances. In addition, some studies reported a significant and negative relationship between agricultural production and inflation. While this latter result is intuitive, the linear relationship between the income and production variables may have led to spurious results since agricultural production has accounted for such a large share of total production.

Derivation of the Inflation Equation

To measure the impact of relevant explanatory variables discussed above and predict the likely inflationary outcome of a specific mix of policy measures and exogenous factors, an equation for inflation is derived and analyzed below. The overall price level (P) is a weighted average of the price of tradable goods (PT) and nontradable goods (PN), and can be represented in log-linear form as

logP=α(logPN)+(1−α)(logPT),(1)

where α represents the share of nontradable goods in total expenditure. The price of tradable goods (PT) is determined exogenously in the world market and, in domestic currency terms, can be represented by foreign prices (Pf) and the exchange rate (e):

logPtT=loget+logPtf.(2)

Both an increase in the exchange rate (in domestic currency terms) and an increase in foreign prices will lead to an increase in the overall price level.

The price of nontradable goods (PN) is assumed to be set in the money market, where demand for nontradable goods is assumed, for simplicity, to move in line with demand in the economy overall. As a result, the price of nontradable goods is determined by the money market equilibrium condition, real money supply (Ms/P) equals real money demand (md), which yields the following equation for nontradable goods prices:

logPN=β(logMs−logmd),(3)

where Ms represents the nominal stock of money,md is the demand for real money balances, and β is a scale factor representing the relationship between economy-wide demand and demand for nontradable goods. The demand for real money balances (md) is assumed to be a function of real income, inflationary expectations, and foreign interest rates:

mtd=f(yp+πp−rt+1−),(4)

where yt represents real income, πr represents expectations formed in period t–1 of inflation in period t, and rt+1 is the expected nominal foreign interest rate in period t+1 adjusted by the expected change in the exchange rate in period t+1.32 According to money demand theory, an increase in the stock variable (real income) will stimulate money demand, whereas an increase in the domestic opportunity cost variable (expected inflation) will lead to a decline. The expected rate of inflation in period t is assumed, based on adaptive expectations, to be equal to

πt=d1(ΔlogPt−1)+(1−d1)πt−1,(5)

where ΔlogPt–1 represents actual inflation in period t–1 and πt–1 is the expected rate of inflation in period t–1. In this analysis, we assume that d1 = 1, leading to the following reduced-form inflation equation:

πt=ΔlogPt−1.(6)

Moreover, based on similar assumptions regarding the formulation of expectations, we assume that the expected foreign interest rate (rt+1), corrected for the expected change in the exchange rate, is equal to the observed rate in period t:

E(rt+1)=rt.(7)

An increase in expected future foreign interest rates (rt + 1) is assumed to lead to a decrease in current real money demand as a result of substitution effects. Substituting equations (6) and (7) into equation (4) yields the following log-linear money demand function:

logmtd=c2logyt−c3ΔlogPt−1+c4rt.(8)

Substituting equation (8) into equation (3) yields

logPtN=β(logMt−c2logyt+c3ΔlogPt−1+c4rt).(9)

Equations (2) and (9) can then be substituted into equation (1), where

logPt=αβ(logMt−c2logyt+c3ΔlogPt−1+c4ri)+(1−α)(loget+logPft).(10)

As discussed above, based on casual observation, the independent role of rainfall in influencing the predominantly food-related consumer price index appears to be substantial. Accordingly, rainfall (Z) is investigated below as a potential additional explanatory variable.

Based on the underlying assumptions discussed above, the following a priori assumptions can be made regarding the signs of the explanatory variables:

Pt=f(Mt+,yt−,et+,rt+,ΔPt−1+,Ptf+,Zt−),(11)

where an increase in nominal broad money, the naira/U.S. dollar exchange rate, expected nominal foreign interest rates adjusted for the expected change in the exchange rate, expected inflation, or foreign prices leads to an increase in prices in period t, while an increase in real income or rainfall leads to a fall in prices.

Econometric Methods and Results

This appendix adopts a time-series approach to the development of an econometric price model to address the criticism of potentially spurious results encountered in most recent studies of inflation in Nigeria, based on the nonstationarity of the data series, and to analyze the short-run, dynamic structure of the relationship. Engle and Granger (1987) suggest a two-step approach. First, the existence of a cointegrating relationship among the variables in equation (10) is determined based on standard cointegration techniques. If the variables are cointegrated, a stable long-run relationship can be estimated using standard ordinary least squares (OLS) techniques. Second, the information in the error term of the long-run relationship is used to create a dynamic error correction model. According to Engel and Granger (1987), this error correction model produces consistent results even when the right-hand-side variables are not completely exogenous. The error correction model is then used to analyze the impulse response of inflation to a stimulus in the explanatory variables in a dynamic setting.

Testing for Cointegration

Testing for cointegration requires information on the order of integration of the variables, as vectors with multiple orders of integration require multiple-stage testing.33 Accordingly, the stationarity of the vector of variables was analyzed based on appropriate unit root tests, and the order of integration of the P, M, y, e, and Z variables (all in log form) was determined based on standard Dickey-Fuller (DF) and augmented Dickey-Fuller (ADF) statistics.34 All the variables were found to be integrated of order 1, I(1).

A cointegrating relationship was confirmed for the P, M, y, e, and Z variables. The DF and ADF test statistics rejected the hypothesis of the existence of a unit root in the error term of the regression of the variables, with P as the dependent variable, confirming that the error term was stationary.

Estimation of the long-run relationship yielded (with the T-statistic in parentheses)

Pt=−3.028(1.97)+0.689Mt(30.13)−0.561yt(9.24)+0.254et(7.64)+0.191Zt(1.15)+ut.(12)

Sample: 1960–1993 R2=.996 SE = 0.095 CRDW = 1.24

The model performed well in terms of explaining the price level as a function of money, income, and the exchange rate. All the coefficients had the appropriate signs with the exception of the rainfall variable. The rainfall variable, though, was found to be insignificant in the long run, consistent with one’s intuition.

Dynamic Model

The dynamic version of the long-run relationship estimated in equation (12) can be specified as an error correction model:

ΔPt=β0+Σi=0η(β1iΔMt−i+β2iΔyt−i+β3iΔet−i+β4iΔZt−i)+Σi=1η(β5iΔPt−i)+β6ECt−1+νt,(13)

where Δ represents the first difference operator,ECt the error correction term, and vt a disturbance term.

The error correction model utilizes information in the error term of the long-run model to approximate deviations from the equilibrium and represent the short-run response necessary to move the system back toward its equilibrium. The error correction term is calculated as

ECt=Pt−P̂t,(14)

where Pt is the actual value of P in period t andP̂t is the fitted value of Pt estimated in equation (12).

Equation (13) was used to estimate the short-run model, with the most parsimonious formulation of the model presented below, based on a simplification search with η = 2:

ΔPt=0.019(0.025)+0.356ΔMt(0.082)−0.294Δyt(0.102)+0.191Δet−1(0.064)−0.230ΔZt−2(0.107)+0.333ΔPt−1(0.118)−0.508ECt−1(0.153).(15)

R2 = 0.691 SE = 0.075 DW = 2.342

The model was estimated using standard OLS estimation techniques on annual data for 1963–93. It performed well in terms of the expected signs on the coefficients of the explanatory variables and in terms of its explanatory power, with an adjusted coefficient of determination (R2) value of 0.69.35 When the error correction model was fitted against historical inflation data, it performed well in terms of tracking the cyclical nature of price movements in Nigeria (Figure 16).

Figure 16.
Figure 16.

Actual and Fitted Inflation

(First difference Log(CPI))

Sources: IMF,International Financial Statistics; and IMF staff estimates.

The presence of serial correlation, or more general forms of autocorrelation, were rejected based on the Breusch-Godfey and Box-Pierce Q statistic. The Jargue-Bera test statistic confirmed normality, and the ARCH test rejected up to fourth-order heteroskedasticity in the disturbance term. The presence of a general specification error was rejected based on the results of the Ramsey RESET(1) test.

The estimated error correction model was found to be stable over the period studied based on the Chow breakpoint test. Four years were selected for the Chow F-test as possible breakpoints (1977, 1979, 1982, and 1985), consistent with previous empirical studies, representing years of pronounced structural reform or exogenous shocks. The CUMSUM recursive residuals test also confirmed the structural stability of the model. Figure 17 plots the CUMSUM cumulative recursive residuals, with deviations outside the 5 percent critical line implying structural instability.

Figure 17.
Figure 17.

Structural Stability of Price Equation

Impulse Responses and Policy Implications

The impact of changes in the exogenous variables on the inflation path can be studied using the dynamic structure of the error correction model above. More specifically, the impulse response of inflation to each of the explanatory variables can be calculated based on the dynamic multipliers. Figure 18 shows the impulse response of inflation (ΔPt) over time to a permanent 1 percent increase in each of the right-hand-side variables in equation (15).

Figure 18.
Figure 18.

Dynamic Response of Inflation

Based on the multipliers, a permanent 1 percent increase in the rate of money growth would yield a 0.36 percent increase in inflation in the initial year, increasing to 0.53 percent by the fourth year, moving toward a long-run increase in inflation of 0.69 percent. At the same time, a permanent 1 percent increase in the exchange rate (devaluation) would lead to an increase of only 0.19 percent in inflation by the second year, with no impact in the initial year, and an increase of 0.25 percent in the long run.

A permanent 1 percent increase in real GDP would be expected to reduce inflation by 0.29 percent in the first year, with a decrease of 0.44 percent after four years, moving toward a long-run decrease of 0.56 percent. Improved rainfall also reduces inflation. A 1 percent increase in rainfall would be expected to decrease inflation by 0.23 percent after two years, decreasing to 0.34 percent by the sixth year.

In addition to confirming that inflation is directly linked to growth in the money supply, the model also suggests that the Nigerian authorities could use appropriately tight financial policies to reduce the inflationary impact of a devaluation. Conversely, the model predicts that a devaluation during a period of excessively expansionary fiscal and monetary policies will have substantial inflationary consequences, as the impact of the monetary growth further adds to the inflationary pressures. Moreover, the inflationary impact of a devaluation during a period of loose financial policies would be especially strong if the country were in the midst of, or just pulling out of, a long period of drought.

Conclusions

Nigeria’s rate of inflation has increased markedly over the past two and a half decades. The results of this analysis confirm the basic findings of earlier studies, namely, that monetary expansion, driven mainly by expansionary fiscal policies, explains to a large degree the inflationary process in Nigeria. Other important factors were the devaluation of the naira and agroclimatic conditions.

It was found that concurrent fiscal and monetary policies had a major influence on the impact of the depreciation of the naira on inflation. The devaluation increases prices but the impact can be counteracted by implementing appropriate financial policies. As shown in 1986 and 1990, a tight fiscal and monetary policy stance during and shortly after a devaluation substantially reduces the impact of the devaluation on domestic prices, while a devaluation during a period of excessive expansionary financial policies magnifies the impact on inflation, as was seen in 1992.

Agroclimatic conditions were also found to be a factor influencing the rate of inflation. Given the considerable role of food commodities in the CPI, agroclimatic conditions (rainfall) have a significant influence on overall movements in prices, as was shown in 1988/89 and 1990/91.

Data Sources

The estimates were based on annual data from International Financial Statistics (IFS) for 1960–93 (Table 16). The IFS data were supplemented as necessary with staff estimates for 1992 and 1993. Real income is derived by deflating nominal GDP by the consumer price index.

Table 16.

Inflation Database

(In millions of naira, unless otherwise specified)

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Sources: International Monetary Fund,International Financial Statistics; and IMF staff estimates.

In millimeters per year.

Broad money is defined as the sum of narrow money plus quasi-money, and the official naira/U.S. dollar exchange rate index is used for the exchange rate variable. The Fund’s estimate of the exchange-weighted inflation rate of partner countries is used as the proxy for the foreign inflation variable and the U.S. three-month treasury bill rate is used to proxy foreign interest rates.

The rainfall variable was based on annual rainfall data (in millimeters). The source of the data for the period 1970–92 was The Central Bank of Nigeria Statistical Bulletin (June 1993) while the data for the period 1960–69 were compiled from the World Weather Database.

References

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Appendix II. Money Demand in Nigeria, 1970–94

Gary Moser

The demand for money is commonly described in terms of its ability to facilitate transactions and store wealth. Money demand functions typically include a scale variable (income or wealth) as a proxy for transactions demand and opportunity cost variables (including interest rates and/or the rate of inflation) as proxies for the return on financial and nonfinancial assets.36 In line with most recent studies of money demand in developing countries, this analysis uses real income as the scale variable, which is expected to positively influence money demand through both transactions and wealth considerations. In addition, the real exchange rate is included as a potential explanatory variable based on the assumption that economic agents in Nigeria’s oil-dominated economy desire to hold foreign currencies to expedite transactions and as a hedge against a real depreciation. Consequently, a real depreciation of the exchange rate (in terms of naira per U.S. dollar) is expected to reduce demand for real naira balances.

Expected inflation is included as an opportunity cost variable and is assumed to negatively influence the desire to hold real money balances. The expected rate of interest, which could have a positive or negative influence on money demand, depending on the definition of money and the competing transactions and wealth effects, is also included as an opportunity cost variable.

Accordingly, the proposed formulation of the longrun money demand equation, along with the expected signs on the coefficients of each of the variables, is

(Md/P)t=f(yt+,εt−,πt+1−,r*t+1?),(1)

in which:Md is the nominal demand for money, P is the price level,y denotes real income, ε the average real exchange rate,π expected inflation, and r* expected nominal return on money.37 The money, price, income, and exchange rate variables are in log form. Expected inflation is defined as the rate of inflation expected to prevail in period t+1 based on information in period t, and the expected real rate of return on money balances is defined in a similar fashion. The equation for money demand can subsequently be written in log-linear form as

mt=α1+α2yt+α3εt+α4πt+1+α5r*t+1.(2)

where m equals Md/P.

The expected rate of inflation in period t+1 is assumed, based on adaptive expectations, to be equal to

πt+1=λ1(ΔPt)+(1−λ1)πt,(3)

where ΔPt represents actual inflation and πt is the expected rate of inflation in period t. The coefficient Λt represents the adjustment lag and, for this analysis, is assumed to equal 1, leading to

πt+1=ΔPt.(4)

In a similar fashion, we assume that the expected return on money in period t+1, based on information (I) in period t, is equal to the observed rate in period t:

E[r*t+1|It]=rt.(5)

Substituting equations (4) and (5) into equation (2) yields

mt=α1+α2yt+α3εt+α4ΔPt+α5rt.(6)

In addition to the explanatory variables discussed above, three dummy variables will be included and investigated, based on the review of financial markets developments: one for 1974–75, covering the impact of the first oil shock; one for the 1989 period, when all deposits of the public enterprises were transferred to the Central Bank; and a variable representing financial market intermediation (the number of bank branches). The first two dummy variables represent sizable, though temporary, shocks to the financial system, while the third variable represents the broader expansion of financial services over the period.

Equation (6) assumes that actual money holdings adjust instantaneously and without cost to changes in money demand while, in reality, adjustments reflect a trade-off between the speed and cost of adjustment, as well as confusion as to whether a shift is permanent or transitory in nature. To embody this concept, and study the short-run impact of policy measures, a dynamic version of the model can be specified. While most recent studies of money demand in sub-Saharan Africa have utilized a standard partial adjustment mechanism to estimate the speed of adjustment, a more general error correction model is employed here. The error correction model fully utilizes the available information in the residual term of the long-run equilibrium model (equation (6)) to develop consistent short-run parameter estimates.

Econometric Methods and Results

Cointegration

A cointegration time series analysis is undertaken in this section to confirm the presence of a long-run equilibrium relationship between money and the explanatory variables. According to Granger and others, equation (6) represents a long-run equilibrium, and can be estimated using standard OLS estimation techniques, if a cointegrating relationship between the nonstationary (I(1)) variables exists.38 In the absence of such a relationship Granger found that OLS estimation is inappropriate and could lead to spurious results, given the presence of nonstationary series. Further, first differencing the 1(1) time series to achieve stationarity could lose important information. In practical terms, a long-run relationship can be confirmed if the residual term of the undifferenced 1(1) process is stationary.

After confirming that equation (6) represents a cointegrating relationship, the second step is to develop an error correction model to study the shortrun dynamics of the relationship:39

Δmt=β0+Σi=1η(β1iΔyt−i+β2iΔ2Pt−i+β3iΔεt−i+β4iΔrt−i)+Σi=1η(β5iΔmt−i)+β6ECt−1,(7)

where a change in real money balances in period t is a function of the current and/or lagged changes in real income, expected inflation, exchange rate, expected domestic interest rates, and lagged real money balances. The appropriate lag structure of the equation will be analyzed, based on standard general-to-specific simplification search procedures. In addition, the lagged error correction term (EC) from equation (6) is included, and is calculated as

ECt=mt−m¯t(8)

where mt is the actual value of real money in period t andm¯t is the fitted value ofm¯t from equation (6).40 This variable approximates deviations from long-run equilibrium real money balances and represents the short-run response necessary to move money demand toward its long-run equilibrium level. When the coefficient of the error correction term is significant and negative, convergence is assured. If β6 is less than 1 in absolute value, the adjustment process is stable and mt will adjust toward its long-run value. The closer β6 is to 1, the faster the adjustment process.

Summary of Main Findings

The existence of a true long-run equilibrium relationship was tested for each of three definitions of money (broad money, narrow money, and currency) based on the Johansen cointegration test.41 To do so, the stationarity of each of the time series was first analyzed, with the order of integration for each of the variables ascertained on the basis of appropriate unit root tests. The money, income, price, exchange rate, and nominal interest rate variables were found to be integrated of order 1, 1(1), based on the augmented Dickey-Fuller (ADF) unit root test (constant, no trend) at the 5 percent confidence level.42

The Johansen maximum likelihood cointegration test was employed to confirm the presence of cointegrating vectors for each of the money demand equations. The Johansen test provides information on all possible cointegrating vectors in the multivariate model, an improvement over the Engle-Granger cointegration tests.43 A review of the cointegrating vectors found a unique vector with the appropriate signs for each of the equations. In addition, the significance and the appropriate sign of the error correction term provides additional evidence/confirmation of the existence of cointegration among the various monetary aggregates and the explanatory variables.44 The long-run money demand equations were then estimated, using standard ordinary least squares (OLS) estimation techniques on annual data for the period 1970–94, and performed well in terms of the expected signs on the coefficients of the explanatory variables and in terms of explanatory power.

Long-Run Equations

The estimated long-run elasticity of real money demand with respect to real income ranged from 0.7 for currency, to approximate unit elasticity for narrow and broad money (1.1 and 1.0, respectively,Table 17). The signs and magnitudes of the coefficients were in line with the a priori assumptions, although they do not support an assumption of a high degree of monetization over the period. The estimated income elasticities are significantly below those that were reported in a recent Central Bank of Nigeria (CBN) study,45 although the CBN empirical results are based on a partial adjustment model and exclude the influence of the exchange rate.

Table 17.

Long-Run Real Money Demand

article image

Represents significance at 1 percent level.

Represents significance at 5 percent level.

Represents significance at 10 percent level.

Johansen’s maximum likelihood unit root test and significance of error correction term in partial adjustment model, as described by Kremers and others (1992) and Banerjee and others (1993).

Numbers in parentheses below coefficients represent the standard error.

The long-run elasticity of real broad money balances with respect to the real exchange rate was estimated in the range of -0.36 to -0.38 for narrow and broad money, confirming our assumption of the negative impact of an expected real devaluation on the demand for real naira balances. The elasticity was lower for currency, at -0.24, suggesting that the impact of an expected devaluation is more likely to affect portfolio balances demand than transactions demand. The inclusion of the exchange rate variable in the long-run model, an innovation in this study, is supported by its significant impact on the desire to hold real naira balances, and suggests that the increasing role of hard currency in the economy as a means of transactions and a store of wealth should not be excluded in the Nigerian context. The long-run nominal interest rate semi-elasticity of real money balances was estimated at 0.01 for narrow and broad money and somewhat higher, at 0.02, for currency. This result is consistent with one’s intuition regarding the broader money definitions, with a nominal interest rate hike (under a largely fixed rate regime) increasing positive, or decreasing negative, real interest rates.

The inflationary expectations variable was not included in the estimated equations, as it was not found to provide significant additional information in the long run. The previously discussed two dummy variables, including the 1974–75 oil price shock and 1989 transfer of public enterprise deposits to the Central Bank, were found to be significant and were included in the final long-run specification, while the financial deepening variable, represented by the number of bank branches, was not significant and was dropped from the model.

Dynamic Model

The short-run error correction models performed well in terms of their explanatory power and statistical properties, with adjusted R2 values of 0.70, 0.67, and 0.75 for currency, narrow money, and broad money, respectively (Table 18). The presence of serial correlation, as well as higher order autocorrelation, was rejected in each of the equations based on the Breusch-Godfrey and Ljung-Pierce Q-tests. The Jarque-Bera test confirmed normality and the ARCH test rejected heteroskedasticity in the disturbance terms. The RESET(1) and RESET(4) tests accepted the null hypothesis of no general misspecification in the models.

Table 18.

Short-Run Real Money Demand

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Represents significance at 1 percent level.

Represents significance at 5 percent level.

Represents significance at 10 percent level.

Inflation coefficient enters currency equation with no lag.

Numbers in parentheses below coefficients represent the standard error.

While the dynamic structure of the short-run models is complex, particularly with respect to currency, the results strongly support our a priori assumptions regarding the direction of the relationship between the right-hand-side variables and money demand, with the exception of inflation. When corrected to include the lagged impact of the dependent variable, the income coefficients in the short-run equations were not substantially different than in the long run. The real exchange rate and nominal interest rate variables were again found to be significant, with appropriate signs in the short-run model, while the inflation variable entered with the opposite sign than expected. The sum of the interest rate effect in the currency equation was positive, entering with a complicated lag structure. The positive impact of a change in inflation on real money demand may be explained by the increased transactions demand in the short run, as households increase commodity purchases in response to an increase in expected inflation. The significant impact of the error correction term in each of the models confirms that the short-run relationship adjusts toward its long-run equilibrium, adjusting quickly for narrow and broad money, while the coefficient for currency, which is greater than 1 in a absolute value, suggests that the short-run model may not be stable.

Stability

The long-run stability of the money demand functions was confirmed on the existence of a cointegrating relationship for each of the equations. The stability of the short-run money demand equations was tested on the basis of the Chow Forecast F-test and the results supported the assumption of stability. Three subperiods were selected on the basis of their potential for presenting a structural change in the economy, including the beginning of the debt crisis (1982); the introduction of the structural adjustment program (1986); and the end of the intensive phase of the adjustment effort (1990).

The stability of the models was also confirmed based on the recursive residuals test, which uses one-step-ahead forecast errors (recursive residuals) for increasingly large sample sizes. If the model is stable, the recursive residuals are expected to have a zero mean and constant variance. No residuals fall outside the band of two standard errors.

Policy Implications

The short-run forecasting models performed reasonably well in terms of explaining the changes in real money growth over the 1970–94 period, as shown in Figure 19. To review the policy implications of the models, the impulse response of money demand to changes in the exogenous variables was analyzed. The impulse response functions for the narrow and broad money demand equations are provided in Figures 20 and 21. (The currency model was dropped from this analysis because of the complexity of the lag structure and the possibility of instability suggested by the error correction term.) One interesting result is that the cumulative impact of short-run models suggests that there is an over-shooting of long-run equilibrium in most cases. This suggests that the return toward the long-run path, in fact, takes more time than indicated by the error correction term.

Figure 19.
Figure 19.

Actual and Fitted Money Demand

(First difference of the log value)

Figure 20.
Figure 20.

Dynamic Response of Broad Money

Figure 21.
Figure 21.

Dynamic Response of Narrow Money

A 1 percent permanent increase in real income was found to increase real narrow money by 0.75 percent in the initial period, rising to 1.20 percent after the fourth period, and to increase real broad money by 0.71 percent in the initial period and 1.08 percent after the fourth period. Both the narrow and broad money impulse responses trend toward the long-run income multiplier after four periods.

The impact of a 1 percent increase in the real exchange rate on narrow and broad money is not felt until after the second year of stimulus, though the dynamic response converges toward the long-run multiplier fairly quickly. A 1 percent permanent increase in the real exchange rate leads to 0.32 percent and 0.33 percent decreases in real narrow and broad money, respectively, with money demand stabilizing above the long-run multiplier after the fourth period.

The impulse response function shows that the impact of a 1 percent increase in the rate of inflation leads to about a 0.5 percent increase in real narrow and broad money demand after two periods, increasing further before stabilizing after the fourth period. As discussed earlier, this unanticipated outcome may result from increased transactions demand in the short run.

In addition to confirming the central role of real income growth in money demand, the empirical results show importantly that, with a stable money demand function, the Nigerian authorities can effectively use monetary policy to pursue broader inflation objectives. More specifically, with additional work on the relationship between base money and broader monetary aggregates and the monthly seasonality of demand, the authorities can effectively use indirect monetary policy to target central bank balance sheet aggregates to meet broader monetary objectives.

Conclusions

The demand for real money balances in Nigeria has been shown to be a stable function in the long run of real income, the real exchange rate, and nominal domestic interest rates. The empirical results confirm the outcome of a number of previous studies of money demand in Nigeria, in terms of the sizable role of real income in money demand but also confirm the central role of the exchange rate in the demand for real naira balances. The income elasticity of demand for narrow and broad money was found not to be significantly different than unity, consistent with our expectations, although it was lower than that found in previous studies in Nigeria.

A short-run forecasting model was estimated for the period 1970–94, providing a reliable one-step-ahead forecast for money demand. The short-run error correction model confirmed the presence of a prolonged adjustment process in returning the system to equilibrium after a shock, particularly with regard to currency demand.

The analysis confirmed a stable money demand function over the short and long term, providing robust results for the development of more market-oriented indirect monetary programming in Nigeria. With an appropriate interest rate structure and the continued expansion of the financial sector, the monetary authorities should be able to use a wider range of monetary instruments under the auspices of open market operations to meet specific annual and quarterly targets for monetary aggregates.

Data Sources

The data are based on annual observations from International Financial Statistics (IFS) for the period 1970–94 and have been supplemented as necessary with IMF staff estimates (Table 19). Real income and real exchange rate variables are derived by deflating the nominal variables by the consumer price index. Broad money is defined as narrow money plus quasi money as shown in the IFS.

Table 19.

Database

(In millions of naira unless otherwise specified)

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References

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Appendix III. Nigeria’s Non-Oil Exports: Determinants of Supply and Demand, 1970–90

Inutu Lukonga

The weakening of the world oil market in the early 1980s and Nigeria’s ensuing payment difficulties rekindled the urgency for diversifying the country’s export base. To promote non-oil exports, Nigeria introduced in 1986, as part of its structural adjustment program, a number of measures that included reform of the exchange rate system, elimination of export licensing, abolition of commodity marketing boards, and other export promotion initiatives.46

The overall success of the export promotion strategy depends, inter alia, on what factors constrain export growth and on the responsiveness of producers to changes in the exchange rate and relative prices. Accordingly, a better understanding is desirable of the determinants of past export performance and of the direction and magnitude of the relevant elasticities. This study, therefore, reviews the performance of Nigeria’s non-oil exports and investigates the price responsiveness of export supply, using data for 1970–90.

This appendix is organized as follows. It first synopsizes Nigeria’s export performance since 1970 and reviews the factors underlying Nigeria’s dismal export performance. Then it delineates a methodological framework to quantify the determinants of Nigeria’s exports and estimate supply elasticities. Its principal conclusions follow. Definitions of the data used in the estimation and the sources of these data are given in an annex.

Developments in Non-Oil Exports, 1970–90

Composition and Structure of Non-Oil Exports

Agricultural products dominate Nigeria’s non-oil export trade, accounting for nearly 70 percent of the value of non-oil exports. (For the composition of Nigeria’s trade, see Statistical Appendix,Tables 39–47.) Agro-manufactures and semi-manufactures have remained relatively insignificant, averaging 7.9 percent over the period under review. Miscellaneous and other manufactures, including tin metal, textiles, and fertilizer, account for the remainder. Small quantities of minerals, predominantly columbite, were exported during the 1970s, but exports of this mineral virtually disappeared in the 1980s (see Figure 22).

Figure 22.
Figure 22.

Structure of Non-Oil Exports

(In percent)

Source: Central Bank of Nigeria,Annual Report and Statement of Accounts.

Of the agricultural products, cocoa beans are the single most important export commodity, representing more than half the total value of non-oil exports since 1975. Rubber and palm kernels have been of limited importance, with each accounting for less than 10 percent of the total value of agricultural exports. Coffee exports have been small and erratic. Other agricultural commodities, such as hides and skins, groundnuts, groundnut oil, palm oil, and timber, were of great importance in the early 1970s, but have greatly diminished in significance since then because of restrictions governing their export.47 Since 1988, several agricultural products—including pineapples, cashew nuts, spices, fish, and shrimp—have been exported, albeit in small quantities.

Agro-manufactures consist mainly of processed cocoa products, including cocoa butter, powder, cake, and paste. Exports of groundnut cake diminished after 1976. Manufactured exports have been dominated by tin metal, while textiles and fertilizer have been exported only recently and account for a minute proportion.

The countries of the European Community absorb more than 70 percent of Nigeria’s non-oil exports. Germany, the Netherlands, and the United Kingdom represent the country’s major export markets. The share of the United States has been constant at about 10 percent and exports to Japan have remained below 3 percent. Despite efforts to stimulate inter-African trade through the creation of the 16-member Economic Community of West African States (ECOWAS) and other treaties, exports to African countries constitute only 3 percent of Nigeria’s non-oil exports.

Performance of Non-Oil Exports

Several indicators of performance show that nonoil exports fared poorly during 1970–90. The share of non-oil exports in total exports diminished from 40 percent in 1970 to less than 5 percent for much of the 1980s, while the contribution to GDP declined from 6.5 percent in 1970 to 0.4 percent by 1984, and only recovered somewhat thereafter, reaching 1.3 percent by 1990. In international markets, Nigeria lost market shares in all commodities, except palm kernels.

Although the diminishing importance of non-oil exports in the Nigerian economy was inevitable because of the colossal increase in oil exports, non-oil exports also declined in absolute terms, particularly during the 1980s. A composite volume index for non-oil exports shows that by 1980 exports were one third below the level obtained in 1970, and no major improvement was registered in the subsequent decade, except for the aberration in 1988, which was caused by the exceptional surge in cocoa exports (Figure 23). Virtually all commodities contributed, in varying magnitudes, to the decline. Cocoa exports showed a continual decline except in 1988, while palm kernels and rubber exports were virtually halved after 1978. Exports of cotton, hides and skins, timber, groundnuts, palm oil, and groundnut oil disappeared by the close of the 1970s. The value of non-oil exports exhibited a similar trend because world prices of most commodities were weak throughout most of the 1980s.

Figure 23.
Figure 23.

Developments in Non-Oil Exports

(Export volume index, 1970 = 100)

Source: Central Bank of Nigeria,Annual Report and Statement of Accounts.

The decline in Nigeria’s exports contrasts markedly with trends in world trade. It is also at variance with income growth in industrial countries during 1970–90. Comparative figures on export growth rates show that, with the exception of palm kernels, world trade of corresponding commodities grew, while Nigeria’s exports declined (Table 20). Real GDP of industrial countries, Nigeria’s major trading partners, also grew on average by 2.8 percent between 1970 and 1990.

Table 20.

Comparative Growth Rates of Selected Commodities1

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Sources: Central Bank of Nigeria,Annual Report and Statement of Accounts; and UNCTAD,Commodity Year Book.

These growth rates were obtained using the semi-log growth model, and therefore reflect trends that are not unduly influenced by exceptional values. Asterisks indicate that the outcome was not statistically significant, either because there is no discernible trend or available observations were insufficient.

Determinants of Past Export Performance

A dominant theme in studies that examined the erosion of Nigeria’s agricultural and other non-oil exports is that unfavorable domestic terms of trade for exports, declining agricultural output, a loss in international competitiveness, and increasing domestic demand are the principal contributors to the dismal performance.48 These developments, in large measure, reflect the interaction of the oil boom and inappropriate domestic policies.

The oil boom created disincentives for agricultural exports through its impact on relative product and factor prices, including the appreciation of the exchange rate, the enhanced profitability of investments in nontradable commodities and services, and rising wages in the public sector, which drained labor from rural areas and put an upward pressure on rural wages. Nigeria’s real effective exchange rate appreciated by 63 percent between 1970 and 1980 and by a further 84 percent between 1980 and 1984.49 Concurrently, labor costs increased at an annual rate of 20.7 percent during 1970–82, compared with an average annual increase of the consumer price index of 17.5 percent, indicating that wages rose in real terms.50 The price-cost squeeze, resulting from a real effective appreciation of the naira and the rising unit labor costs, adversely affected the profitability and competitiveness of exports.51

Another corollary of the oil boom is the high level of effective demand that it induced, which grossly curtailed exportable output. The oil boom during the 1970s enabled Nigeria’s real per capita GDP to increase at an annual average of 1.2 percent between 1973 and 1980, while the population grew at an average annual rate of 2.4 percent between 1970 and 1990. In the absence of changes in population characteristics, such increases in per capita income accelerate the average per capita growth in demand for domestically consumed crops beyond that prescribed by the population growth rate, particularly for crops with an income elasticity of more than 1.52 Increases in incomes that are not matched by output increases lead to inflationary pressures that raise profit margins on domestic sales in relation to exports, and goods may be diverted to the home market, leading to a fall in export surpluses. The restrictive effect of increasing domestic demand on exports is pronounced in Nigeria’s case, because most export commodities enter directly or indirectly into domestic consumption.

The overall growth in domestic demand and the increase that is attributable to the growth in per capita income are difficult to quantify in the absence of information on the size of the income elasticities of the commodities. However, to the extent that domestic demand, at a given period in time, is equivalent to domestic production and imports net of exports, developments in the magnitudes of these variables are indicative of the trends. Available data on exports and output show that, with few exceptions, domestic demand for consumption or industrial use exceeded output growth, resulting in a decline in the export-to-output ratio of most export commodities. In extreme cases, exports were completely eliminated, and imports were increased to supplement domestic output. For example, the expansion of Nigeria’s textile industry in the early 1970s led to the elimination of cotton exports and the growth of cotton imports from US$25,700 in 1970 to US$45 million in 1984.53 Similarly, increasing domestic demand for derivatives of oilseeds resulted in the elimination of groundnut and groundnut oil exports, a decline in the export-to-output ratio of palm kernels from 62 percent in 1970 to 10 percent by 1990, a colossal increase in imports of oilseeds, nuts, and kernels, and the increase in imports of complementary products, including soybean oil and other vegetable oils. Imports of oilseeds, nuts, and kernels increased from almost nothing in 1970 to US$26.7 million by 1984, while soybean oil and other vegetable oils increased from US$40,000 and US$204,000 in 1970 to US$26.2 million and US$75 million in 1984, respectively.54

The adverse impact of increasing domestic demand was amplified by the stagnation in agricultural output. Although it is not possible to provide generally accepted figures that demonstrate the structure and performance of agriculture in a definitive way,55 there is general consensus that the trend in the output of export commodities has been declining. Available data show that aggregate crop production increased at an annual rate of 3.5 percent between 1975 and 1990, and cash crops averaged 2.6 percent a year, but the principal export crops generally grew at a lower rate than the population.56 Cocoa, the major export commodity, declined at an average rate of 2.3 percent whereas groundnuts declined by 0.96 percent a year. Production of rubber, palm oil, and palm kernels increased at respective annual rates of 0.18, 0.64, and 3 percent.

The sluggish performance of agriculture exports also reflects the cumulative effect of the Nigerian Government’s agricultural policies, including the explicit taxation of agriculture exports in the early 1970s, unfavorable marketing and pricing of agricultural exports by marketing boards, the “exportable surplus” approach to trade enforced primarily by export bans, and the relative neglect of the sector in Nigeria’s overall development planning, particularly during the 1970s. Government intervention in Nigeria’s agricultural marketing and pricing system makes a distinction between export and food crops, even though a number of agricultural commodities belong to both categories. Between 1970 and 1975, agricultural exports were taxed at rates ranging between 15 percent and 30 percent for cocoa, palm kernels, groundnuts, and cotton, while the marketing and pricing of export crops were determined by marketing boards (until their abolishment in 1986). With the exception of palm kernels, domestic producer prices were far below their export parity prices for much of the 1970s, thus encouraging the smuggling of export commodities to neighboring countries.57

Restrictions on the export of selected commodities have been a recurrent phenomenon in the country’s trade policy in a bid either to avoid domestic shortages or to promote local processing that would permit export of higher value-added items. The export of groundnuts, groundnut oil, palm oil, and timber was first banned in February 1976 to ensure an adequate supply for domestic use, while hides and skins were subsequently prohibited in April 1978 in order to promote the domestic tanning industry. In 1986, most bans were eliminated as part of the structural adjustment program, but were soon reintroduced. Commencing with the ban on the export of timber in 1988, the export of maize, rice, cassava, yams, beans and derivatives, and all imported foods was subsequently banned in 1989. Most recently, the list of prohibited exports was expanded to include raw hides and skins (in 1990) and unprocessed palm kernels (in 1991).58

Finally, nonprice factors also play an important role in the determination of Nigeria’s export performance. Insufficient productive investment in agriculture, unreliable supply of inputs, poor or nonexistent extension services, inadequate infrastructure, lack of well-developed credit institutions, and the traditional system of land tenure have all contributed somewhat to the below-potential performance of the sector. The predominance of agricultural exports in the basket of non-oil exports also renders their export performance vulnerable to the vagaries of climate, while the long lags between acreage adjustment and output supply, characteristic of tree crops, delay the export response. The Sahelian drought adversely affected the overall performance of the agricultural sector in the early 1970s. For Nigeria, climatic conditions returned to more normal levels only after 1983. These problems have been compounded by the deteriorating age structure in existing stocks, and other crop-specific problems, including the black pod disease that affected cocoa.

Econometric Analysis of Export Performance

To assess the relative importance of the individual factors discussed above, econometric techniques are applied to quantify important economic variables that are presumed to affect the export behavior of Nigeria’s nonpetroleum products. We begin by examining the main methodological issues in the specification of export supply functions, and we discuss the variables that ought, in theory, to be included and the choices and compromises that have to be made in the measurement of the variables. We then derive a model that specifies both demand and supply side determinants of exports, measures the responsiveness of export volumes to these determinants, and distinguishes the long-term developments from short-term fluctuations.

Methodological Issues

There is general consensus on the empirical forms of the demand and supply function of exports,59 even though the theoretical modeling of export supply still raises controversial issues, particularly in connection with the transparency of its microeconomic foundations.60 The standard approach for specifying and estimating foreign trade equations is the imperfect substitutes model, in which the key assumption is that exports are not perfect substitutes for domestic goods. In this model, export demand is hypothesized to vary positively with world economic activity, and inversely with the export prices of the exporting country relative to the prices of foreign substitutes, while the export supply function is specified to depend positively on the price of exports, negatively on input prices, and positively on productive capacity.61

Demand and supply side determinants are estimated simultaneously, because the relationship between quantities and prices is, at least in theory, simultaneous. Nonetheless, most empirical studies estimate export demand functions by single equation methods, on the premise that, for an individual country, supply price elasticities for exports are infinite. Similarly, export supply functions are estimated independent of export demand functions, on the assumption that a typical developing country is a small supplier, facing an infinitely elastic foreign demand for the product it produces, and for which changes in foreign demand influence exports only through changes in world prices.

Although export supply is affected by forces that influence both domestic supply of and demand for the exported good, many of the studies naturally focus on domestic supply responses, because there is little or no domestic demand for many export commodities, particularly primary products, or it is assumed that in a perfectly competitive market economy, the diverse factors affecting supply and demand are fully captured in the price (see discussions in Bond (1985) and Riedel and others (1984)). There is, however, theoretical and empirical support for including domestic demand in an export supply equation, in spite of the uncertainty regarding the precise relationship between domestic demand and exports. The traditional argument is that an increase in domestic demand reduces the supply of export goods to the extent that it creates strong competition for resources that would have been devoted to export, while the alternate view posits that domestic demand reduces the average cost per unit and induces technological progress, making it easier for exporters to compete with foreign producers.62 Empirical studies that explicitly incorporated domestic demand also found it to be a significant explanatory variable of export supply.63

Equilibrium Model

In an economy where governmental intervention is pervasive, the diverse factors affecting supply and demand cannot be adequately captured by relative price changes. In Nigeria’s circumstances, the predominance of administrative controls in resource allocation and the treatment of exports as a residual activity indicate that the state of domestic demand could exert a negative and far more powerful influence on export performance than marginal fluctuations in relative prices at home and abroad, particularly because export commodities enter directly or indirectly into domestic consumption. Similarly, the shift in the direction of economic policy since 1986 has potential to foster greater export consciousness and thus increase the export growth rate.

The supply of Nigeria’s exports is therefore assumed to depend positively on the price of exports, negatively on input prices, and positively on productive capacity. In addition, an increase in domestic demand is posited to curtail exportable surplus, while export promotion policies are expected to cause a shift in the supply function.

The relationship is presented in log-linear form as follows:

LogXt=β0+β1log(Px/Pd)+β2logYt*+β3logDdt+β4Dum,(1)

where

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The supply function is specified independently of an export demand function, on the premise that Nigeria is a price taker in world markets and that primary commodities, which constitute a large proportion of Nigeria’s exports, are generally homogeneous in quality and are sold in perfectly competitive markets.64

The relative price variable incorporates the theory that the supply of exports will increase with the profitability of producing and selling exports.65 The use of the domestic price as divisor to the export price serves a dual role. First, for a given level of export price, the profitability of producing exports falls when factor costs in the export industries increase, and since these factor costs are likely to move with the general level of domestic prices, domestic prices serve as a proxy. Second, to the extent that resources involved in exportable production can be transferred to other uses, the relative profitability of selling exports falls with an increase in domestic prices. Finally, besides capturing production substitution elasticities between exports and nontradables, use of a relative price avoids problems of multicollinearity, because the two prices tend to move together.

The capacity variable embodies the hypothesis that exports will rise, ceteris paribus, where there is an increase in the country’s capacity to produce and thus captures shifts in the supply function associated with productivity gains or technological changes. The dummy is designed to capture shifts in the intercept or slope of the function induced by policy changes, which are distinct from movements along the function that are captured by the relative price variable. The domestic demand variable accommodates the “exportable surplus” approach to exports.

Equation (1) is presented in log-linear form because the relationship is assumed to be nonlinear, and, as such, the coefficients deriving thereof represent elasticities. Therefore, β1 and β2 are “price” and “capacity” elasticities, respectively, and are expected to be positive. β3, the elasticity of exports with respect to changes in domestic demand, is posited to assume a negative sign, while β4 is expected to be positive.

Finally, the relationships specified above reflect a static equilibrium framework, according to which changes in the explanatory variables affect the dependent trade variable within the same period. To incorporate lags in the adjustment of actual to equilibrium values, a short-run model, herein referred to as a disequilibrium model, is formulated below.

Disequilibrium Model

The long gestation period of tree crops suggests that exports may respond to changes in the explanatory variables with a lag.66 Therefore, in the short-run model, we assume the supply of exports adjusts partially to the difference between desired exports in period t and the actual supply of exports in period t–1.67 Thus

ΔlogXt=γ[logXt*−logXt−1],(2)

where γ, the coefficient of adjustment, is 0 < γ ≤ 1 and Δ is a first difference operator. Since, desired supply is not observed, but the determinants of export supply are known, we substitute equation (1) into equation (2), and derive the estimating equation as follows:

LogXt=c0+c1log(Px/Pd)+c2logYt*+c3logDdt+c4Dum+c5logXt−1,(3)

where c0 = γβ0,c1 = γβ1,c2 = γβ2,c3 = γβ3,c4 = γβ4, and c5 = 1 – y.

The γ denotes the speed of adjustment of actual exports to the desired quantity that occurs in a year. The mean time lag for a complete adjustment is therefore equal to γ–1, and can be calculated from the parameters of equation (3) as (1 –c5)–1.

Empirical Results

The determinants of Nigeria’s export performance were estimated for three commodities only: cocoa, palm kernels, and rubber. This is because aggregate relationships covering all commodities could produce misleading results, in view of the restrictions governing export trade of most commodities during the estimation period.68 In addition, aggregate relationships conceal intercommodity variations in sensitivity to price and income.

OLS estimation procedures were used to obtain the estimates. Where there was evidence of autocorrelation, the Maximum Likelihood iterative technique and Cochrane Orcutt iterative technique were used to correct for autocorrelation in the equilibrium and disequilibrium models, respectively.

Equilibrium Model

The model generally performs well in explaining the variation in export performance, yielding parameter estimates that are both of the expected sign and statistically significant, particularly for cocoa and rubber. The preferred equation includes a relative price variable lagged by one year (Table 21).69

Table 21.

Equilibrium Model, Export Supply Elasticities for Selected Export Crops

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t-values are in parentheses.

Cocoa and rubber yielded statistically significant price elasticities with the expected positive sign, indicating that the two commodities respond positively, albeit with a lag, to changes in relative prices. The coefficient for palm kernels, on the other hand, appeared in-significant with a wrong sign. The price elasticity marginally exceeds unity for rubber, but yielded coefficients below unity for both cocoa and palm kernels. Such a finding implies a fairly limited response of exports to changes in relative prices. Unfortunately, no estimates of export supply elasticities were found in the literature that could be compared to the estimates obtained here to draw inferences on their precise size.70

The dummy yielded statistically significant coefficients with the expected positive sign in the cocoa and rubber equations, denoting a change in intercept and slope since 1986. Estimates of palm kernel exports carried the expected positive sign, but appeared statistically insignificant. These results provide prima facie evidence that the export promotion policies introduced as part of the structural adjustment program increased the export growth rate and support the view that domestic market conditions strongly influence export behavior.

The weak relationship between the tonnage of palm kernel exports and the price incentives, indicated by the low coefficients for both relative prices and the dummy, is not surprising. Palm kernels and palm oil are joint products derived from the same fruit—“palm fruits.” The former is primarily produced for export while the latter is wholly consumed domestically. In a subsistence economy based on the products of a single species of a tree, which are both consumed locally and also exported, inducement to produce and export may be influenced by factors that bear little relationship to the export price.

The coefficient with respect to productive capacity indicates the degree of export bias associated with agricultural expansion, and our estimates lead to the conclusion that Nigerian agriculture is primarily oriented toward the domestic market. Cocoa yielded statistically significant coefficients carrying a wrong sign, while the capacity elasticity for rubber appeared insignificant with an incorrect sign. Estimates for palm kernels yielded the correct sign but appeared statistically insignificant. These results denote a weak relationship between agricultural output and export trends.

Domestic demand appears as a central explanatory variable, yielding statistically significant coefficients that carry the expected negative sign for all three commodities. This result confirms the earlier assertion that domestic demand posed a major impediment to export during the estimation period and is also consistent with the direction and size of the capacity elasticities obtained in the model, which indicate that Nigerian agriculture is primarily oriented toward domestic consumption. The outcome may be attributed to the Government’s interventionist and restrictive policies that accord priority to satisfying domestic consumption and local processing in order to promote the export of value-added items.

Disequilibrium Model

The disequilibrium model captures the short-run response of exports to the explanatory variables. Overall, the results obtained resemble the long-run responses, in terms of direction, but the coefficients are generally lower in magnitude (Table 22).

Table 22.

Disequilibrium Model, Export Supply Elasticities for Selected Export Crops

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t-values are in parentheses.

Cocoa and rubber exhibit a positive response to relative price changes even in the short term, whereas the size of the elasticities were uniformly lower than those obtained in the long-run model. Similarly, the coefficient with respect to the dummy appears with a correct sign in all equations and is statistically significant for cocoa and rubber. The negative effect of domestic demand on exports continues to feature prominently, yielding the expected negative sign for all commodities and appearing statistically significant in the equations for cocoa and rubber.

The equations perform relatively poorly with regard to the estimated elasticity to lagged exports, yielding coefficients with the expected sign, but none of them were statistically significant. The average lag computed from them shows that the adjustment of export supply to changes in the explanatory variables, on average, occurs in less than two years (Table 23).

Table 23.

Average Time Lags

(In years)

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Implications of Results

The empirical results generally support the view that domestic market conditions strongly influenced export behavior. Nigeria’s supply of commodity exports is sensitive to relative price changes, even though the magnitude of response is fairly low, while export promotion measures generally accelerate the export growth rate. Commodity exports show greater sensitivity to prices in the long run than in the short run. These results provide evidence of, and support for, the usefulness of pricing policy in eliciting export supply, particularly for cocoa and rubber.

The restrictive policies of the Government adversely affected the export performance of agricultural products. The Government’s unrelenting dedication to self-sufficiency amplifies the restrictive effect of domestic demand, while the requirement to export only processed or manufactured products, for which a comparative advantage may not have been established, negates the translation of output increases into corresponding export growth and limits the positive effect of growth promoting policies on export performance.

The lag in the response of exports to changes in relative prices, estimated to average one year, is relatively short considering the long gestation period of the export crops in our sample. The short-term response indicated by these results may therefore be attributed to improvements in yield, or the redirection of unrecorded exports into official channels, rather than an expansion of capacity arising from new plantings.

To a lesser extent, the results also reflect basic data inadequacies, such as large unrecorded exports. There is considerable disagreement among the different data sources about the actual amounts and growth rates of agricultural crops produced in Nigeria. Data problems in Nigeria’s agricultural sector can be explained by the nature of the sector, which is dominated by smallholders, shifting cultivation, fragmented farm holdings, and an enormous variety of intercropping systems, all of which combine to make record keeping difficult. The problems are compounded by severe weaknesses in the capacity of institutions charged with monitoring performance of the sector.

Annex I Data Definitions and Sources

The Sample

Data for the study consist of 21 observations pertaining to the years 1970–90. Annual observations are used because of the lack of monthly or quarterly series.

The Dependent Variable (Xs)

The dependent variable is represented by actual export volumes of the respective commodity exports, obtained from various editions of the Central Bank of Nigeria’s Annual Report.

Relative Prices (Px/Pd)

The choice of an export price is complicated in Nigeria’s case, because until 1986 producers of export crops received the administratively determined “producer price,” which diverged from the export price. Arguably, however, to the extent that producer prices accrue to agricultural producers, while the export price accrues to the exporters, the two prices constitute incentives to produce and export, respectively, and therefore export prices are the appropriate prices in modeling export supply.

In this study, like in previous studies, the numerator (Px) represents world export prices of the respective commodities converted into domestic prices by the average exchange rate. Domestic costs are proxied by the CPI. Data on export prices were obtained from the Commodity Division of the International Monetary Fund, while the average exchange rate and the CPI were extracted from the International Financial Statistics.

Productive Capacity (Y*)

The ideal construct, for our purposes, would be the index of agricultural production. This series was, however, only available commencing in 1975 and therefore provided insufficient observation for regression analysis. As an alternative, domestic capacity is proxied by the value of agriculture in real GDP, at constant prices. Data were obtained from the World Bank’s World Tables.

Domestic Demand Pressure (Dd)

The index of manufacturing has been used as a proxy for domestic demand on the grounds that Nigeria’s export commodities are not consumed directly but are intermediate inputs in the manufacture of consumption goods. Data for this series were obtained from the Annual Report and Statement of Accounts of the Central Bank of Nigeria.

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Appendix IV. Oil Smuggling, Fiscal Policy, and Macroeconomic Imbalances

Scott Rogers

The subsidization of gasoline for domestic use in Nigeria has a direct impact on the Nigerian fiscal balance and on the smuggling of gasoline from Nigeria to other countries in the region. In addition, Nigeria’s fiscal policy may itself affect the smuggling of gasoline through its impact on the parallel exchange rate. As many countries in the region depend on domestic gasoline taxes as a source of revenue, the smuggling of gasoline erodes their tax base and consequently worsens their fiscal balances. Thus, Nigeria’s fiscal policies have a regional impact.

This appendix analyzes the connections between Nigeria’s fiscal and domestic gasoline pricing policies and gasoline smuggling. It demonstrates that an increase in Nigeria’s fiscal deficit boosts the incentives for smuggling by causing the parallel exchange rate to depreciate and that an increase in the domestic retail price of gasoline would simultaneously improve the fiscal balance and reduce the incentives for smuggling. The domestic gasoline pricing policy directly affects smuggling by altering the differential between retail gasoline prices in the rest of the region and at home. It also indirectly affects smuggling through its impact on the fiscal deficit. By administratively setting the domestic price of gasoline well below import parity, revenues are forgone that could reduce the fiscal deficit significantly. A reduction in the fiscal deficit would reduce the Government’s recourse to domestic bank financing, which has been the principal cause of accelerating inflation and the depreciation of the parallel exchange rate.

Subsidization and Taxation in the Region

The domestic retail price of gasoline in Nigeria is set well below import parity, generating a large implicit subsidy.71 In contrast, retail gasoline prices in the neighboring CFA franc countries are set well above import parity, resulting in a substantial implicit tax (Figure 24). Retail gasoline prices in Nigeria and the CFA franc countries have changed infrequently; most changes in implicit subsidization and taxation arise from changes in the world price of gasoline and exchange rates (Table 24). Given domestic transportation and distribution costs (Table 25), the difference between the domestic and world price overstates the extent of taxation in the CFA franc countries and understates the extent of subsidization in Nigeria; it is, however, indicative of relative magnitudes and general trends. One trend seems clear: the implicit subsidy in Nigeria, as indicated by the decline in the ratio of the domestic price to the world price of gasoline, increased steadily between 1986 and 1993. The recent upward adjustment in domestic petroleum prices in late 1993 resulted in a sharp decline in the implicit subsidy.

Figure 24.
Figure 24.

Retail Gasoline Prices

(As a percent of world price)

Sources: Petroleum Market Intelligence; and IMF staff estimates.1 1994 is January-February average.
Table 24.

Retail Prices of Premium Gasoline in Nigeria and Neighboring Countries

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Sources:Petroleum Market Intelligence; and IMF staff estimates.

For 1992–94, wholesale price of premium gasoline in U.S. Gulf Coast as reported in Petroleum Market Intelligence. Prior years are estimated, using ratio of Gulf Coast price to the price of U.K. Brent crude oil.

Price of U.K. Brent.

Table 25.

Composition of Retail Prices of Premium Gasoline in Selected CFAF Countries, 1991

(In CFA francs per liter)

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Source: World Bank (1991),A Tax Reform Strategy for Cameroon.

The extent of the subsidy and tax depends on the domestic retail price, the world price of gasoline, and the exchange rate. Changes in world prices affect the implicit tax in the CFA franc countries and the implicit subsidy in Nigeria in opposite directions; an increase in the world price reduces the implicit tax and raises the implicit subsidy. Changes in the CFA franc/U.S. dollar exchange rate reflect the movement in the French franc/U.S. dollar exchange rate. Given the relative stability of the French franc/U.S. dollar exchange rate since 1990, the decline in world petroleum prices between 1990 and 1993 resulted in a general upward trend in the implicit tax in the CFA countries. In Nigeria, the depreciation of the naira in the parallel market has overwhelmed the impact of the decline in world gasoline prices, causing the implicit subsidy to rise substantially.

Incentives for Smuggling

The incentives for smuggling gasoline from Nigeria remain enormous despite the recent CFA franc devaluation and the increase in domestic product prices in Nigeria.72 The current spread between retail prices of premium gasoline in neighboring countries and in Nigeria ranges from a low of10.1 per liter for Benin to a high of26.4 per liter for Chad.

The actual volume of smuggling in the region is not known, although some partial estimates and anecdotal evidence exist. In the case of Benin, it is estimated that unrecorded imports have been rising rapidly since 1986, reaching 133,000 tons in 1991, nearly 70 percent of total consumption. While this represented a substantial share of the gasoline market in Benin, it constituted only 3 percent of the total stock of gasoline allocated to Nigeria’s domestic market in that year. Clearly, what may appear as a relatively small amount of smuggling from the point of view of the Nigerian market can constitute a substantial share of certain foreign markets.

The allocation of gasoline for domestic consumption in Nigeria has increased on average by 11.2 percent a year since 1988, reaching 5.3 million tons in 1993. Nonetheless, shortages of gasoline have regularly been reported in the border towns of Nigeria, where the incentives for smuggling are the greatest. More recently, shortages have appeared in Abuja and Lagos as well. The implicit gasoline subsidy amounted to an estimated30 billion in 1993, equivalent to 3.8 percent of GDP. It is estimated that as much as 20 percent of the gasoline allocated to Nigeria’s domestic market is smuggled abroad, implying that income derived from gasoline smuggling was equivalent to roughly 0.8 percent of Nigeria’s GDP in 1993.

Nigeria’s Fiscal Policy and the Incentive to Smuggle

The incentive to smuggle gasoline abroad is a function of the difference between the foreign retail price and the Nigerian retail price, measured at the parallel exchange rate. The quantity of gasoline smuggled (X in equation (1)) is a function of the retail price in CFA franc countries (Pc), converted at the parallel/CFAF exchange rate (En/Ec, where En and Ec are the naira and CFA franc bilateral exchange rates vis-à-vis the U.S. dollar, respectively) relative to the retail price of gasoline in Nigeria (Pn). The quantity of gasoline smuggled is constrained to be less than the total amount officially allocated for domestic consumption (DA).73 Domestic consumption in Nigeria is determined residually as the difference between the domestic allocation (DA) and the amount smuggled (X). The following equations describe these relationships:

X=b[(En/Ec)Pc−Pn],74b>0,0<X<DA(1)En=P/Pf,(2)P=νM/Y,(3)dM=−FB,(4)FB=R+Pn*DA−EXP,(5)DC=DA−X.(6)

The naira/U.S. dollar exchange rate in equation (2) is assumed to be determined by purchasing power parity (PPP), where P is the aggregate price level in Nigeria, and Pf is the aggregate price level of its trading partners. The Nigerian price level in equation (3) is equal to money velocity (v) times the stock of money (M) divided by real GDP (Y). The change in the stock of money (dM) in equation (4) is presumed to derive solely from the fiscal balance (FB). For the sake of simplicity, it is assumed that the entire deficit is financed by the domestic banking system. The fiscal balance (in equation (5)) is equal to revenues other than those derived from the sale of gasoline for domestic consumption (R) plus the value of domestic gasoline sales valued at the official retail price (Pn*DA), less expenditure (EXP). Equation (6) shows that domestic consumption (DC) equals the difference between domestic allocation (DA) and the amount smuggled (X).

Substituting equations (2) through (5) into (1) yields equation (7), which describes smuggling in terms of exogenous variables and parameters only:

X=b[n(Mt−1−R−Pn*DA+EXP)Y*Pf*Ec*Pc−Pn].(7)

Taking the total differential of (7) and dividing through by X yields an expression that describes the percentage change in the quantity of gasoline smuggled as a function of percentage changes in exogenous variables.

X̂=S1[−S2R̂+S4EX̂P]+S1[P̂c−Êc−Ŷ−P̂f]−[(S1−1)+S1S3]P̂,(8)

where

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The first term in brackets in equation (8) represents the impact of changes in non-gasoline related fiscal revenue and expenditure on smuggling. A decline in revenue or an increase in expenditure causes the deficit to rise. The stock of money rises, causing the aggregate price level to rise and the parallel exchange rate to depreciate. Smuggling increases because the depreciation increases the naira value of the retail price of gasoline in the neighboring countries. Since the cost of smuggling (Pn) is constant, the profitability of smuggling rises. This result clearly implies that the incentive for smuggling is affected not just by Nigeria’s domestic gasoline pricing policy, but by its overall fiscal policy as well. It also implies that smuggling could be curtailed by reducing the Nigerian fiscal deficit, even if the domestic price of gasoline in Nigeria remains unchanged.

The second term in brackets captures the impact of changes in the retail price of gasoline in neighboring countries, the CFAF/U.S. dollar exchange rate, real income in Nigeria, and the price level of Nigeria’s trading partners. An increase in the price of gasoline in neighboring countries increases smuggling for the obvious reason; it increases the price differential. An increase in any of the last three variables causes smuggling to decline. A devaluation of the CFA franc vis-à-vis the U.S. dollar reduces the/CFAF cross rate, reducing the profitability of smuggling. An increase in either real GDP in Nigeria or the foreign price level causes smuggling to fall because both cause the/US$ exchange rate to appreciate.

The last term in equation (8) defines the impact of a change in the domestic price of gasoline in Nigeria, and two separate effects can be identified. The first term in parentheses defines the direct impact; an increase in the Nigerian price reduces the price differential. The second term in parentheses defines the indirect impact; an increase in the retail price of gasoline reduces the fiscal deficit and hence indirectly induces an appreciation of the/CFAF exchange rate, which reduces the profitability of smuggling.

Equation (8) indicates that the increase in the domestic price of gasoline in Nigeria in November 1993 and the devaluation of the CFA franc in January should both serve to reduce the amount of smuggling in the region. However, it also indicates that the impact of these policy actions could be overwhelmed by Nigerian fiscal policies if the deficit continues to expand.

Conclusion

It is well known that Nigeria’s policy of maintaining a highly subsidized domestic price of gasoline generates an incentive to smuggle gasoline to neighboring countries, where the retail prices of gasoline are substantially higher. However, Nigeria’s expansionary fiscal policy of the past few years has also indirectly increased the incentive to smuggle gasoline by contributing to the rapid growth in broad money and the resulting acceleration of inflation and the depreciation of the naira in the parallel foreign exchange market. To the extent that this smuggling erodes the tax base of neighboring countries, Nigeria’s expansionary fiscal policy has had a regional impact. Raising the domestic retail price of gasoline in Nigeria would reduce the size of the fiscal deficit, thereby reducing the rate of growth of money, inflation, and depreciation, while simultaneously contributing to fiscal adjustment in the region as a whole.

Appendix V. Statistical Appendix

The tables on the following pages provide a statistical overview of the Nigerian economy. Starting with selected economic and financial indicators, the tables move on to fiscal and monetary statistics, as well as statistics on the balance of payments, public and publicly guaranteed debt, the gross domestic product at current and constant prices, and gross national expenditure. Other tables provide statistics on the evolution of petroleum prices, the index of agricultural production, the index of manufacturing production, and the structure of Nigeria’s exports. The final table provides figures on selected financial institutions—banks, foreign exchange bureaus, stockbrokers, and discount houses—in the Nigerian economy.

Table 26.

Selected Economic and Financial Indicators

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Sources: Data provided by the Nigerian authorities; and IMF staff estimates.

Figures prior to 1982 are based on constant 1977/78 prices.

Based on the weighted average of the official and foreign exchange bureau exchange rates.

Table 27.

Federal Government Fiscal Operations

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Sources: Dat a provided by the Nigerian authorities; and IMF staff estimates.
Table 28.

Summary of Budgetary Operations of State and Local Governments and Special Funds1

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Sources: Data provided by the Nigerian authorities; and IMF staff estimates.

These data, which are based on limited budgetary data and staff estimates, should be viewed only as illustrative of general budgetary trends.

State government only.

Lending to the Federal Government via the Federation Stabilization Account.

Table 29

Consolidated General Government Fiscal Operations1

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Sources: Data provided by the Nigerian authorities; and IMF staff estimates.

These data, which are based on limited budgetary data and staff estimates, should be viewed only as illustrative of general budgetary trends.

Excludes dedicated oil revenue earmarked for NNPC.

Includes 50 percent of estimated extrabudgetary expenditure by the Federal Government.

Table 30

Monetary Survey

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Source: Data provided by the Nigerian authorities; and IMF staff estimates.

Valuation account included in other items net prior to 1985.

Table 31.

Balance of Payments

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Sources: Data provided by the Nigerian authorities; and IMF staff estimates.
Table 32.

Stock of Public and Publicly Guaranteed Debt

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Sources: Central Bank of Nigeria; and IMF staff estimates.

Includes arrears as well as rescheduled medium and long-term debt. Also includes new disbursements.

Includes short-term arrears, rescheduled short-term claims, and payable debt.

Includes pre-SFEM and dedication account arrears.

Table 33.

Domestic Petroleum Prices

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Prices became effective on January 1.

Prices became effective on April 10.

Prices became effective on January 1.

Prices became effective on March 5.

Prices became effective on November 18.

Prices became effective on October 5.

A two-tier pricing system in which private vehicle owners paid0.60 per liter and commercial vehicle owners paid0.42 per liter was implemented in January 1989. The prices were unified toward the end of the year.

For 1992–94, average annual wholesale price of premium unleaded gasoline in U.S. Gulf Coast as reported in Petroleum Market Intelligence. Prior years are estimated using ratio of Gulf Coast price to the price of U.K. Brent crude oil.

Table 34.

Gross Domestic Product by Sector of Origin at Current Prices

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Sources: Nigerian Federal Office of Statistics and National Planning Commission.
Table 35.

Gross Domestic Product by Sector of Origin at Constant 1984 Prices

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Sources: Nigerian Federal Office of Statistics and National Planning Commission.
Table 36.

Gross National Expenditure

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Sources: Data provided by the Nigerian authorities; and IMF staff estimates.
Table 37.

Index of Agricultural Production

(1985=100)

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Source:Statistical Bulletin, Vol. 4. December 1993, Central Bank of Nigeria, and Annual Report and Statement of Accounts, various issues, Central Bank of Nigeria.
Table 38.

Index of Manufacturing Production

(1985 = 100)

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Source:Statistical Bulletln, Vol. 4, December 1993, Central Bank of Nigeria, and Annual Report and Statement of Accounts, various issues, Central Bank of Nigeria.
Table 39.

Non-Oil Exports, 1970–801

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Source: Central Bank of Nigeria,Annual Report and Statement of Accounts, various editions.

Figures were converted from naira into U.S. dollars using average exchange rates.

Table 40.

Non-Oil Exports, 1981–901

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Source: Central Bank of Nigeria,Annual Report and Statement of Accounts, various editions.

Figures were converted from naira into U.S. dollars using average exchange rates.

Table 41.

Structure of Exports, 1970–80

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Source: Central Bank of Nigeria,Annual Report and Statement of Accounts, various editions.
Table 42.

Structure of Exports, 1981–90

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Source: Central Bank of Nigeria,Annual Report and Statement of Accounts, various editions.
Table 43.

Structure of Non-Oil Exports, 1970–80

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Source: Central Bank of Nigeria,Annual Report and Statement of Accounts, various editions.
Table 44.

Structure of Non-Oil Exports, 1981–90

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Source: Central Bank of Nigeria,Annual Report and Statement of Account, various editions.
Table 45.

Agricultural Exports—Selected Indicators, 1970–80

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International Monetary Fund,International Financial Statistics Yearbook 1992.

Producer prices were obtained from Central Bank of Nigeria,Annual Report and Statement of Accounts, various editions; international prices were obtained from IMF, Commodities Special Division.

Central Bank of Nigeria,Annual Report and Statement of Accounts, various editions.

Nigeria’s exports were obtained from Central Bank of Nigeria,Annual Report and Statement of Accounts, various editions; world exports were extracted from UNCTAD,Commodity Year Book, various issues.

Export volumes were obtained from Central Bank of Nigeria,Annual Report and Statement of Accounts, various editions; output figures were extracted from Central Bank of Nigeria,Statistical bulletln, Vol. 4, No. 1, 1993.

Table 46.

Agricultural Exports—Selected Indicators, 1981–90

article image

International Monetary Fund,International Financial Statistics Year book 1992.

Producer prices were obtained from Central Bank of Nigeria,Annual Report and Statement of Accounts; international prices were obtained from IMF, Commodities Special Division.

Central Bank of Nigeria,Annual Report and Statement of Accounts, various editions.

Nigeria’s exports were obtained from Central Bank of Nigeria,Annual Report and Statement of Accounts; World exports were extracted from UNCTAD,Commodity Year Book, various editions.

Export volumes were obtained from Central Bank of Nigeria,Annual Report and Statement of Accounts, various editions; output was extracted from Central Bank of Nigeria,Statistical Bulletin, Vol. 4, No. 1, 1993.

Table 47.

Export Volumes, Export Prices, Consumer Price Index, GDP at Factor Cost, and Index of Manufacturing

article image

Central Bank of Nigeria,Annual Report and Statement of Accounts, various editions.

International Monetary Fund, Commodities Special Division.

International Monetary Fund,International Financial Statistics Yearbook, 1992.

World Bank,World Tables, 1992.

Table 48.

Selected Financial Institutions

article image
Source: Central Bank of Nigeria.

Excluding community banks.

1

The terms “Government,” “fiscal deficit,” and “public expenditure” refer to the Federal Government, unless stated otherwise.

2

High protective tariffs, import bans, an import licensing scheme, and export bans on food crops characterized the external trade regime. The proliferation of government controls was reflected in the establishment of price controls (Price Control De-cree of 1971), marketing boards (Commodity Board Decree of 1977), state trading corporations (in 1977, the Nigerian National Supply Company, the Nigerian National Freight Company, and the National Fertilizer Board), and the effective nationalization of all land (Land Use Decree of 1978, which brought all land under the control of state governments). In addition, through the Nigerian Enterprise Decree (1972), the Government promoted indigenous participation in industrial investment and discouraged foreign investment.

3

The distinctions between north, south, east, and west are made to simplify what is actually a more fluid geographic distribution of religious and ethnic affiliations.

4

The Transitional Council was sworn in on January 4, 1993, together with the members of the House of Representatives and of the Senate.

5

Official unemployment statistics, while providing an indication of the trends in the labor market, substantially underestimate trends by excluding underemployment, which was estimated to be in the range of 40 percent in 1985.

6

The Cocoa Board (cocoa, coffee, and tea), the Groundnut Board (groundnuts, soya beans, benniseed, peanuts, and ginger), the Cotton Board, the Palm Produce Board (palm oil, palm kernel, and copra), the Rubber Board, the Grains Board (corn, millet, maize, wheat, rice, and beans), and the Tuber and Root Crops Board (yams and cassava).

7

At the average official exchange rate for 1989; the tariff was only 0.5 U.S. cents at the parallel exchange rate.

8

The price of household kerosene remained unchanged. With this exception, the lowest increase was for liquefied petroleum gas (24 percent).

9

Measured at the official exchange rate, the domestic price of gasoline was 186 percent of the world wholesale price after the increase. Measured at the parallel exchange rate, the domestic price was still 10 percent below the world price.

10

Only authorized dealer banks were allowed to participate in the auction, which was designated as the Secondary Foreign Ex-change Market (SFEM).

11

The foreign exchange surrender requirement to the Central Bank for non-oil export proceeds was lifted in 1986, but exporters were still required to surrender 75 percent of foreign exchange earnings to commercial banks at the prevailing interbank rate. In 1987, the surrender requirement was eliminated altogether.

12

The two rates were unified at3.73 per U.S. dollar (the prevailing auction rate) and the SFEM was renamed the FEM (foreign exchange market).

13

The remaining import bans covered cigarettes, poultry, vegetables, rough wood, eggs, fruit, most textile fabrics, plastic wares, mineral water, jewelry and precious metals, rice, maize, wheat, selected alcoholic beverages, gaming machines, and vegetable oils.

14

A 6.02 percent surcharge was reimposed in January 1987.

15

Creditors agreed to reschedule: (1) all principal and interest (excluding late interest) due from January 1, 1989, up to April 30, 1990 on medium- and long-term debt contracted before October 1, 1985 (the cutoff date used for the previous rescheduling); (2) all arrears (including late interest) outstanding as of end-1988 on medium- and long-term debt contracted before the cutoff date; (3) up to a maximum of 60 percent of the amounts that were due be-fore December 31, 1988, and not paid, on previously rescheduled debt; and (4) all arrears outstanding at end-1988 on short-term credits, contracted before that date.

16

Since the personal income tax is levied at the state level, this measure had virtually no impact on federal government revenue. The Federal Government collects income taxes only from resi-dents of the Federal Capital Territory (Abuja), and the armed forces.

17

Data limitations preclude a comprehensive accounting of the fiscal operations of the state and local governments and the special funds. Data are available for allocations from the Federation Account, statutory claims on transfers to the Federation Stabilization Account, highly aggregated state budgetary data, and net bank credit to state and local governments. Little information is available on the financial operations of the special funds or revenue collected directly by local governments.

18

Local governments collect some fees and municipal taxes, but these revenues are relatively small.

19

The exchange included 217 securities at the end of 1990, including 131 equities, 43 government securities, and 43 industrial loans and preferred stocks. The market is heavily concentrated, with 20 stocks representing over 70 percent of the total equity capitalization during the same period.

20

Nigeria’s external terms of trade declined by 9½ percent annually during 1986–90, compared with an annual average decline of 2½ percent during 1980–85.

21

See Appendix III for an empirical analysis of the major factors influencing Nigeria’s agricultural exports.

22

See Central Bank of Nigeria (1991),The Impact of SAP on Nigerian Agriculture and Rural Life.

23

Estimates of savings and investment balances for the public and private sectors are based on official GDP data and Fund staff balance of payments and fiscal estimates.

24

The official unemployment statistics exclude a significant share of the labor force that is underemployed or not actively seeking employment.

25

Approved Budget of the Federal Republic of Nigeria, 1992, p. xxiii.

26

Failed Banks (Recovery of Debts) and Financial Malpractices in Banks Decree, November 9, 1994.

27

More current data on government equity in and loans to public enterprises are not available on a comprehensive basis.

28

Price data are collected for 256 items in 83 urban towns and 312 rural centers on a weekly or monthly basis. The FOS com-piles the data monthly to prepare a CPI for each of the 21 states and an aggregate rural and urban CPI as well as the national composite CPI.

29

The FOS completed a new National Consumer Survey during the period April 1992 to March 1993. A preliminary analysis suggests that expenditure on food items is broadly in line with the data from the 1985/86 national survey.

31

See, for example, Adamson (1989) and Aigbokhan (1991).

32

As a result of fixed interest rates over most of the period, domestic interest rates were not included as they do not add significant additional information.

34

The inflation, foreign interest rate, and foreign prices variables were dropped from the analysis as they were found in earlier versions of this paper to be insignificant.

35

All the coefficients were significant at the 1 percent level with the exception of the constant term, which was insignificant at the 10 percent level.

36

See, for example, Laidler (1993) for a detailed discussion of money demand models.

37

Interest rates were controlled and significantly negative in real terms over much of the period. Real interest rates were tested as a possible opportunity cost variable but were not found to have significant explanatory power. Future empirical work could investigate real curb rates as an alternative opportunity cost variable.

38

That is, if a linear combination of the 1(1) variables is stationary, or 1(0).

40

See Engle and Granger (1987 and 1991) for a detailed discussion of error correction models. See Lahiri (1991), Tseng and Corker (1991), and Tseng and Khor (1994) for recent examples of error correction cointegration models applied to money demand.

41

See Johansen (1988 and 1991) for a detailed discussion of the Johansen test.

42

The ADF test for the income variable excludes both a constant and trend term.

43

See Appendix III and IV of Tseng and Khor (1994) and Rein-hart (1995) for a detailed discussion of the mechanics of using the Johansen test.

44

See Kremers and others (1992) on the superiority of this test over the conventional tests of cointegration. Harris (1995) also provides an excellent discusison of this. Kremers and others argue that htis test is more pwoerful than the ADF test, as it uses the inofrmation scope efficiently.

45

See Oresotu and Mordi (1992). The CBN study estimated an income elasticity of 2.03 in the long run for real broad money based on a partial adjustment model.

46

For a detailed account of the incentives proffered, see Central Bank of Nigeria,Annual Report and Statement of Accounts, and Export (Incentives and Miscellaneous Provisions) Decree 1986.

47

A chronological account of quantitative restrictions on ex-ports is provided below.

48

See for instance Olayide and Olatunbosun (1970), Ojo (1977), Scherr (1989), Okonkwo (1989), Oyejide (1986), and Nigeria’s Ministry of Agriculture (1988).

49

During the 1970s, exchange rate policy in Nigeria aimed at maintaining a stable nominal exchange rate in order to moderate the impact of external inflation on the domestic economy. This policy stance was reinforced by the presumption that cheap im-ports were essential to political stability, and that the benefits of higher agricultural exports were modest (Scherr (1989)).

50

No official data on rural wages are available. These estimates were computed by Duncan and Rouis (World Bank (1985), pp. 21–22).

51

There is evidence that wages in Nigeria’s oil palm subsector were well above average wages in other oil palm producing coun-tries, including Brazil, Cameroon, Cote d’Ivoire, Ghana, Indonesia, and Malaysia. Assuming that these wages are representative of the agriculture sector in general, it is clear that Nigeria’s agri-cultural exporters had a competitive disadvantage vis-a-vis their competitors. (See World Bank (1981); also quoted in World Bank (1982) Report No. 3771-UNI, p. 12).

52

The growth in demand for a commodity is expressed as D =GZ +P, where D = growth rate in demand, Z = income elasticity,G =GNP per capita growth rate, and P = population growth rate.

53

Disaggregated trade statistics were available for the years 1970 to 1984 only.

54

The import figures were obtained from Nigeria Trade Sum-mary, an annual publication of the Federal Office of Statistics of Nigeria.

55

Nigeria’s official production figures for exportable crops relate to purchases of commodity boards, and may therefore be underestimated, because the share of crops that are domestically consumed is not known with a reasonable degree of certainty.

56

Estimates of growth were computed using the log-linear model, and are based on the index of agricultural production reported by the Central Bank of Nigeria. Estimating the average growth by the compound method produced lower estimates of 2.05 for aggregate crops and 2.1 for cash crops.

57

No reliable estimates of the volume of smuggling are available, but there is evidence of large-scale smuggling of cocoa and other manufacturing exports, particularly to neighboring coun-tries, part of which serves as capital flight. In 1985, the Nigerian Cocoa Board estimated that more than 20,000 metric tons of cocoa were smuggled out of Nigeria yearly, fueled by delays in the payment of farmers by licensed buying agents. Efforts to curb the illicit trade flows by closing the country’s land borders from mid-1984 to March 1986 only terminated official trade with Nigeria’s neighbors, while falling short of its objective.

58

The ban on the export of cocoa beans announced in January 1991 was rescinded only because of opposition from domestic producers and exporters who pointed out that domestic processing capacity fell short of bean production.

59

Surveys of econometric work, on foreign trade price elastici-ties and their weaknesses, are available in Leamer and Stern (1970), Magee (1975), and Goldstein and Khan (1985).

60

The prominent controversial issues are outlined in Riveros (1989) and Faini (1988) and include the use of either partial or general equilibrium models, the definition of the prevailing market structure, the assumed degree of substitution between domestically consumed and exported goods, the treatment given to factor costs, and the role taken with regard to relative prices and productive capacity vis-a-vis more “Keynesian” variables such as domestic absorption.

61

Satisfactory results have been obtained in many studies that applied the model in its basic form, to both developed and developing countries, and for agricultural and manufactured exports. See for instance Goldstein and Khan (1978), Lundborg (1981), Arize (1988), Balassa (1987,1989), Okonkwo (1989), Lord (1989), and N’geno (1991).

62

The competing views on the impact of domestic demand on exports are discussed in Artus (1970) and Dunlevy (1980).

63

See for instance the country study Spain by Donges (1972). The study by Islam and Subramanian (1989) is one of the few studies that estimated an export supply function for agricultural exports and incorporated domestic demand among the explanatory variables. The variable was, however, not found to be statistically significant even though it yielded the expected sign.

64

The procedure adopted is fairly standard, see Stern and Zupnick (1962), Basevi (1973), Isard (1977). Besides, attempts to estimate the supply and demand functions simultaneously yielded poor results, particularly for export demand.

65

A detailed discussion on the rationale for including particular variables in the export supply function is available in Goldstein and Khan (1985).

66

For a detailed discussion of the sources and types of lags in adjustment see for instance Junz and Rhomberg (1973), Goldstein and Khan (1985), Moran (1988).

67

The adjustment mechanism adopted has been used in other similar studies, including Goldstein and Khan (1978), Okonkwo (1989), N’geno (1991).

68

The export of groundnuts, cotton, hides and skins, timber, and palm oil has been prohibited for several years and available data do not provide sufficient observations to permit some econo-metric analysis.

69

Lagging the relative price variable allows for the possibility of delayed supply adjustment beyond the period of one year. This form of specification was also adopted by Bond (1987) and yielded equally good results.

70

In Arize’s (1989) study, export demand and supply functions were estimated for Nigeria’s aggregate exports. However, to the extent that oil exports account for over 90 percent of total exports, the results are technically incomparable and are of limited use for our purposes. Similarly, although N’geno (1991) estimated export supply equations for Kenya’s agricultural exports and for the individual commodities, coffee and tea, the results were of equal limited importance for our purposes because of the difference in the composition of the commodities and also because the commodity markets are constrained by the quota system.

71

Import parity is defined as the world price of gasoline valued at the parallel exchange rate. The analysis is limited to the gaso-line market for ease of exposition and because most smuggling involves gasoline. The analysis applies to other petroleum products as well.

72

The impact of these two actions, both of which reduced the profitability of smuggling, was partially offset by increases in retail gasoline prices in most CFA franc countries.

73

It is generally assumed that the gasoline smuggled into the neighboring countries originates from the allocation from domestic consumption.

74

The smuggling function is derived from the following maximization problem: max II = (En/Ec)PcX –C (X) where II represents profits arising from smuggling and C (X) =PnX +zX2 de-fines the cost of smuggling. Equation (1) follows where b = 1/zt.

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Cover Nigeria
Nigeria
Experience with Structural Adjustment
ISBN:
9781557756305
ISSN:
0251-6365
Publication Date:
04 Apr 1997
Publisher:
International Monetary Fund
DOI:
https://doi.org/10.5089/9781557756305.084
Pages:
114
Figure 14.

Consumer Prices

(Annual percentage change)
Figure 15.

Inflation, Money, and Exchange Rate Developments

(Annual percentage change)
Figure 16.

Actual and Fitted Inflation

(First difference Log(CPI))
Figure 17.

Structural Stability of Price Equation
Figure 18.

Dynamic Response of Inflation
Figure 19.

Actual and Fitted Money Demand

(First difference of the log value)
Figure 20.

Dynamic Response of Broad Money
Figure 21.

Dynamic Response of Narrow Money
Figure 22.

Structure of Non-Oil Exports

(In percent)
Figure 23.

Developments in Non-Oil Exports

(Export volume index, 1970 = 100)
Figure 24.

Retail Gasoline Prices

(As a percent of world price)

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