between dollarization and exchange rate volatility: nigeria's portfolio diversification option

Journal of Policy Modeling 30 (2008) 811–826

Available online at www.sciencedirect.com

Between dollarization and exchange rate volatility:Nigeria’s portfolio diversification option

Dauda Olalekan Yinusa ∗Room 119, Department of Economics, Obafemi Awolowo University, Ile-Ife, Nigeria

Received 1 October 2006; received in revised form 1 August 2007; accepted 1 September 2007Available online 16 October 2007

Abstract

This paper investigates the relationship between nominal exchange rate volatility and dollarization inNigeria by applying Granger causality test for the period 1986 (1)–2003 (4). Previous theoretical and empir-ical studies on this issue provided conflicting results. The empirical results of Granger causality test support abi-directional relationship. However, causality from dollarization to exchange rate volatility appears strongerand dominates. This suggests that policies that aim to reduce exchange rate volatility in Nigeria must includemeasures that specifically address the issue of dollarization. An important factor in this case is the supplyof sufficient domestic currency assets that would permit portfolio diversification and capable of dousingnegative expectations about future inflation in the country.© 2007 Society for Policy Modeling. Published by Elsevier Inc. All rights reserved.

JEL classification: F31; E41

Keywords: Exchange rate volatility; Dollarization; Granger causality

1. Introduction

The impact of exchange rate volatility on macroeconomic variables has been investigated in anumber of empirical and theoretical studies (see for example, Arize & Malindretos, 1998; Calvo,

� This paper was completed while the author was a Fulbright Visiting Scholar at Fordham University, New York, USA.The financial support provided by African Economic Research Consortium, Nairobi, Kenya and CODESRIA, DakarSenegal is gratefully acknowledged. The author is however exclusively responsible for any error or omission that thepaper may contain.

∗ Tel.: +234 803 404 8150.E-mail addresses: [email protected], [email protected].

0161-8938/$ – see front matter © 2007 Society for Policy Modeling. Published by Elsevier Inc. All rights reserved.doi:10.1016/j.jpolmod.2007.09.007

mailto:[email protected]

mailto:[email protected]

dx.doi.org/10.1016/j.jpolmod.2007.09.007

812 D.O. Yinusa / Journal of Policy Modeling 30 (2008) 811–826

1996; Chowdhury, 1999; Honda & Schumacher, 2006; Osakwe, 2002). The major assumptionof most of these studies is that causality runs from exchange rate volatility to other macroeco-nomic variables. Recently however, researchers are divided as regards the direction of causationespecially in the dollarization literature. Mizen and Pentecost (1996) argued that exchange ratevolatility motivates domestic residents in switching to hold and using foreign currency for pur-poses of unit of account, transactions, and store of value functions of money. Specifically, theyargued that exchange rate depreciation lowers the value of domestic money in the portfolio ofassets of an economic agent thereby leading to a higher share of foreign currency in the port-folio of assets. They concluded, “The exchange rate is clearly the crucial variable driving theprocess of dollarization. . .” On the other hand, Friedman and Verbetsky (2001) while discussingdollarization in Russia noted that there are several policy issues arising from dollarization thatare important for emerging market and transition economies. In particular, they noted the issueof exchange rate behaviour in the presence of dollarization. In their review of some literature,they came to the conclusion that “Dollarization makes exchange rate very volatile in response topolicy changes”. This is consistent with Willett and Banaian (1996) argument that slight changesin dollarization would cause a “huge exchange rate movements”. McKinnon (1982, 1993) andBofinger (1991) maintained that dollarization is the main cause of instability in flexible exchangerates. This view implies that dollarization has been a significant destabilizing force in the worldeconomy (Willett & Banaian, 1996). This become more relevant for a developing economy likeNigeria where exchange rate instability has strangulated most productive sectors of the economyespecially manufacturing which is import dependent. McKinnon (1996) supports this positionwhen he argues that “The concept of international dollarization is useful for explaining whyfloating exchange rates have been so volatile.”

Gruben and McLeod (2004) considered dollarization and inflation convergence in Latin Amer-ican countries. The study finds that dollarization causes inflation convergence (causes a reductionin inflation) as inflation in theses countries mimic that of the US whose currency is being usedfor transaction and store of value purposes. Although this study was not directly addressed toexchange rate volatility, inferences can be drawn as exchange rate volatility tends to manifestitself through inflation whether full, partial or delayed pass-through is assumed. These conflict-ing observations make the causal relationship between exchange rate volatility and dollarizationto be an empirical issue. Indeed, this issue is particularly important for Nigeria operating aflexible exchange rate system especially after the implementation of Structural Adjustment Pro-gramme (SAP) supported by the World Bank and International Monetary Fund (IMF) since1986.

While many Sub-Saharan African countries especially Nigeria, have moved from fixed toflexible exchange rate system at some point in the recent past, studies that explores the causalrelationship between exchange rate volatility and dollarization have been rare. Yet, we need tounderstand the causal relationship between exchange rate volatility and dollarization in Nige-ria. The identification of the causal direction will be particularly relevant for policy makers indeveloping and transition economies, where designing appropriate sequencing of stabilizationprogrammes targeted at reducing vulnerability of their economies (as indicated by a significantshare of their monetary base held in foreign currency denominations) have been a challenge.Therefore, the focus of this paper is to provide an empirical evidence on the causal relation-ship between exchange rate volatility and dollarization in Nigeria for the period 1986 (1)–2003 (4).

The remaining part of this paper is structured as follows: Section 2 provides some facts aboutthe macroeconomic environment in Nigeria that lay the foundation for dollarization. Model and

D.O. Yinusa / Journal of Policy Modeling 30 (2008) 811–826 813

econometric procedure is presented in Section 3 while Section 4 contains data measurement andsources. Section 5 presents estimation results, discussions and policy implications of the resultwhile Section 6 concludes.

2. Exchange rate volatility and dollarization in Nigeria: some macroeconomicbackgrounds

During the last few years, a number of emerging market economies including Nigeria havemoved from fixed to flexible exchange rates. This has led to the removal of many foreign exchangerestrictions as part of the comprehensive structural adjustment programme implemented in mostof these economies. In Nigeria, late 1980s and the early 1990s were characterized by massivedepreciation of the Naira as the country sought to reduce and/or eliminate the influence of parallelmarket for foreign exchange that had existed in the country over the years. More importantly, thepolicy was designed to move the real exchange rate of Naira closer to equilibrium rate. Also, thispolicy was adopted in the hope that it would improve the competitiveness of Nigeria’s exportsand also boosts non-traditional exports especially manufacturing exports.

The need for adjustment in Nigeria was brought about by economic decline and stagnationoccasioned by external shocks and internal factors which, characterized the economy in the late1970s and early 1980s. The external shocks include huge decline in commodity prices, deterio-rating terms of trade, high-real interest rates, the global recession, from 1979 to 1982, increasingprotectionism, and declining capital inflows (Obadan, 1996). On the other hand, the internal fac-tors of economic decline and stagnation include: poor domestic polices, inadequate trade andpricing policies, over valued exchange rates, mounting fiscal deficits (signaling fiscal misman-agement and/or instability), dominant role of the state in production and economic regulation,political instability and policy inconsistencies. Aside from these, the fixed exchange rate regimeof the government encouraged the inordinate taste and preference for imported goods by house-holds and government while most of the manufacturing firms in the country are import dependent.However, with the collapse of the international oil market in the early 1980s (specifically in 1981),it became obvious that the policy of financial repression could not be sustained.

Another major feature of Nigerian economy has been the presence of informal financialmarkets.1 The imposition of trade controls and exchange restrictions on foreign exchange trans-actions was responsible for the emergence of informal or parallel markets for foreign currency.These controls, often imposed for balance of payment reasons, generate an unofficial marketwhich are both dependent upon conditions in the official market and other domestic macroeco-nomic forces. Indeed, parallel market activity is basically a market response of economic agentsto their economic environment. As such, this activity is demand driven generated purely by theneed of the market place (Montiel, Agenor, & Haque, 1993). Such markets have been known toexist alongside similar activity in the formal sector. In fact, recent evidence suggests that parallelmarkets operate alongside the more visible and better-recorded official economy in virtually allcountries of the world (Montiel et al., 1993; p. 8). In Nigeria, the two markets have been existingside by side, which is a fallout of long periods of economic regulation, and macro-economicmismanagement, which characterized the economy since independence. The logical and obvious

1 Aryeetey and Udry (1994) discussed the characteristics of informal financial, Nwanna (1996), looks at the roles,experience and constraints of informal financial markets for promoting rural development in West Africa, while Soyibo(1997) investigated the relationship between formal and informal financial markets in Nigeria.


implication is that if parallel markets emerge in response to the imposition of controls, the mosteffective way to reduce their size is to eliminate these restrictions and let prices reflect the fullscarcity of foreign exchange. Hence, the move by Nigeria for economic reforms became obvious.

The first response of the government in Nigeria was the implementation of stabilization ordemand management policies in the late 1970s and early 1980s. The economic realities of theperiod revealed that the structural bottlenecks, which have characterized the economy for manyyears, could not be corrected by these short-term measures. Hence, there was the need for a morecomprehensive policy to address these structural distortions and imbalances in the economy.In view of the above, Nigerian government commenced the implementation of the StructuralAdjustment Programme (SAP) supported by the World Bank and the International MonetaryFund (IMF) in 1986. However, the policy shift led to instability in the exchange rates therebycreating an atmosphere of uncertainty exacerbated by speculative bubbles, which aggravates theproblem of inflation in the economy. For example, the behaviour of nominal official and nominalparallel exchange rate of Naira against the US dollar is shown in Figs. 1 and 2 below.

Fig. 1. Graph of nominal official exchange rate (NOER) in Nigeria.

Fig. 2. Graph of nominal parallel market exchange rate (NPER) in Nigeria.

One observed trend in the behaviour of nominal official exchange rate is that it depreciatedmarkedly immediately after the commencement of the liberalization exercise but became relativelystable thereafter. This was due to official devaluation of the Naira at the wake of the introduction offinancial liberalization in an attempt to find a realistic exchange rate for Naira and also to reducethe parallel market premium that have been wide especially during the early years of policyshift to a deregulated regime. However, a very interesting discovery although not unexpectedis the behaviour of nominal official exchange rate as from 1986 to 1992. It can be observed


that the nominal official exchange rate depreciated sharply from 1986 up to 1992. However, thedepreciation thereafter was not as noticeable as the earlier periods of Adjustment (see Fig. 1).Specifically, there was a policy reversal in 1994 when the then Military Head of State halted theliberalization process by resulting to a fixed exchange rate system. As such, the official exchangerate was not just stable during the period, but fixed by government administrative fiat from 1994to 1998 after which Nigeria disengaged completely with official exchange rate arrangement (seeFig. 1). A comparative picture for parallel market exchange rate is presented in Fig. 2, whichdisplays a noticeable volatility throughout the period of study.

This level of exchange rate instability and its pass-through effects to domestic inflation hasencouraged the move towards the use of foreign currencies in the domestic economy for transac-tional, unit of account and store of value purposes. This phenomenon has been referred to in theliterature as dollarization or currency substitution (see, for example, Calvo, 2000; Chang, 2000;Dean, 2000). The evolution of dollarization in Nigeria is presented in Fig. 3 below.

Fig. 3. Evolution of dollarization in Nigeria.

Theoretically, dollarization can be thought of as symmetrical and asymmetrical. Accordingto McKinnon (1985), the underlying concept of dollarization in developed countries involvedsymmetrical dollarization, where domestic and foreign residents hold both domestic and foreigncurrencies. However, dollarization is asymmetrical in the context of developing and transitionaleconomies, where domestic residents hold domestic and foreign currencies but foreign residentsdo not hold domestic currencies and in some transition economics, the US dollar is the preferredforeign currency. In these countries, US dollar plays almost all of the three traditional role ofdomestic currency. First, the US dollar is used as a store of value and as the process goes on,prices of goods begin to be quoted in US dollar and, its role as a means of payment starts,especially for purchases of durable goods, rent and other high-cost items. In the context of thisstudy, dollarization is viewed as asymmetrical currency substitution.

As inflation rate grows and exchange rate instability increases, following many years of mal-administration, massive corruption and other macroeconomic mismanagement, leading to loss ofpublic confidence in the domestic economic policy management, domestic residents in Nigerialearned to protect themselves against the loss of purchasing power of their national currencies byswitching to the dollar. Over time, the government of Nigeria validated semi-official dollarizationby allowing residents to open bank accounts denominated in dollars (domiciliary account). Con-tracts, foreign and domestic debts were valued and quoted in dollars while monetary compensationto athletes and footballers were made in dollar denominations. In fact, many big super-marketsin big cities, in Nigeria, quote the prices of their products in dollars and many big estate agents


and valuers only accept dollars as rents for houses in some reserved areas of Lagos, Abuja, PortHarcourt and other highly industrialized cities in Nigeria. All these developments points to theco-existence of dollarization and exchange rate volatility in Nigeria. The issue now is which onecauses the order? This study sheds light on this issue.

3. Model and econometric procedure

The main focus of this paper is the determination of the causal relationship between exchangerate volatility and dollarization in Nigeria. Consequently, a pair wise Granger causality testbetween nominal exchange rate volatility (NERV) and dollarization index (DI) was estimatedwithin a VAR setup. Since correlation does not necessarily imply causation in any meaning-ful sense, Granger (1969) approach to the question of whether x causes y is to see how muchof the current y can be explained by past values of y and then to see whether adding laggedvalues of x can improve the explanation. y is said to be Granger-caused by x if x helps inthe prediction of y, or equivalently if the coefficients on the lagged x’s are statistically signif-icant. Note that two-way causation is frequently the case; x Granger-causes y and y Granger-causes x.

It is important to note that the statement “x Granger-causes y” does not imply that y is theeffect or the result of x. Granger causality measures precedence and information content butdoes not by itself indicate causality in the more common use of the term. From the above def-inition, it follows that optimal choice of lag length of the variables of interest to be includedin the model plays a pivotal role in the appropriate determination of Granger causality. Indeed,wrong lag order selection can cause spurious rejection or acceptance of no causality. Hence, ingeneral, it is better to use more rather than fewer lags, in carrying out Granger causality test,since the theory is couched in terms of the relevance of all past information. For our purposewe picked optimal lag length suggested by Akaike Information Criteria (AIC) and SchwarzInformation Criterion (SIC). However, where these two information criteria produces conflict-ing lag length choices, a feasible empirical procedure will be to examine the stability of theunderlying VAR and settle for the model with a lag length that produce a stable VAR. This isa reasonable choice as the probability of spuriously accepting or rejecting the null hypothesisof no-causality is greatly reduced (Hamilton, 1994; Lutkepohl, 1993). This corresponds to rea-sonable beliefs about the longest time over which one of the variables could help predict theother.

In a bivariate VAR describing x and y, y does not Granger-cause x if the coefficient matricesΦj are lower triangular for all j:

[xt

yt

]=[

c1

c2

]+(

φ111 0

φ121 φ1

22

)[xt−1

yt−1

]

+(

φ211 0

φ221 φ2

22

)[xt−2

yt−2

]+ · · · +

(φ

ρ11 0

φρ21 φ

ρ22

)[xt−ρ

yt−ρ

]+[

ε1t

ε2t

](1)

From the first row of the system, the optimal one-period-ahead forecast of x does not depend onlagged values of y but on its own lagged values:

E(xt+1 |xt, xt−1, . . . , yt, yt−1, . . . ) = c1 + φ111xt + φ2

11xt−1 + · · · + φρ11xt−ρ+1 (2)


To implement this test, we used the optimal autoregressive lag length ρ suggested by the variousinformation criteria and Eq. (3) was estimated:

Zt = (DIt , NERVt)′ (3)

within the VAR structure. Zt is the column vector of our variables. More explicitly:

DIt = c1 + α1DIt−1 + α2DIt−2 + · · · + αρDIt−ρ

+ β1NERVt−1 + β2NERVt−2 + · · · + βρNERVt−ρ (4)

NERVt = c2 + α1NERVt−1 + α2NERVt−2 + · · · + αρNERVt−ρ

+ β1DIt−1 + β2DIt−2 + · · · + βρDIt−ρ (5)

for all possible pairs of DIt and NERVt and ρ is the optimal lag length adopted in this study. Thereported F-statistics are the Wald statistics for the joint hypothesis:

β1 = β2 = · · · = βρ = 0

for each equation. The null hypothesis is therefore that NERVt does not Granger-cause DIt inEq. (4) and that DIt does not Granger-cause NERVt in Eq. (5). The null hypothesis that NERVt

(DIt) does not Granger-cause DIt (NERVt) is rejected if the βi coefficients are jointly significantlydifferent from zero, using a standard F-test. Bi-directional causality (or feedback) exists if βi

coefficients are jointly different from zero in both equations.

4. Data measurement and sources

Quarterly time series data on dollarization and Naira exchange to US dollar is used for theanalysis. Data on broad money was collected from the Central Bank of Nigeria statistical bulletin.Also, parallel market exchange rate data sourced from Nigerian Deposit Insurance Corporation(NDIC) was updated from central bank data from 1998 to 2003.

The next task is to provide an operational measure of the key variables in this study. Dol-larization Index (DI) was measured as the ratio of foreign currency deposits (FCD) and broadmoney (M2). However, domestic money in circulation was subtracted from M2 so as not tounder-estimate the relative weight of foreign currency deposits in the banking system. It is ourmeasure of dollarization from the store of value perspective. However, it is important to mentionthat ideally, foreign currency holdings should include foreign currency deposits (FCD) in thedomestic banking system, foreign currency in circulation (FCC) within the domestic economyand cross-border deposits (CBD) held at foreign banks. But, in the context of developing countriesand transitional economies, measuring FCC is empirically impossible since there may be fear offorced conversion into domestic currency (Viseth, 2001). Instead of bank deposits, households inmany developing and transitional economies usually hold currency (domestic or foreign) in theform of cash, kept under the mattress or in the safe. Thus, FCC is normally not included in themeasurement of dollarization.2

2 Attempts to identify a better measure of dollarization have interested many scholars in the literature. However, examplesof measurement of foreign currency holdings (FCC) can be found in some studies on dollarization in Latin America (seefor example, Dean, 2000; Feige, 2003; Krueger & Ha, 1996, etc.). For instance, Melvin and Ladman (1991) attempted to


Yet, the use of the ratio of FCD over broad money is still the most common approach togauge the extent of dollarization in a domestic economy especially in countries where there hasbeen no restrictions of holding dollar denominated accounts (see, for example, Agenor & Khan,1996; Clements & Schwartz, 1992; Rennhack & Nozaki, 2006; Sahay & Vegh, 1996; Savastano,1996). The use of this ratio is reasonable for the estimation of dollarization in Nigeria, becauseduring the period under study there was no legal restriction on FCD holdings in the domesticbanking system. In other words, without government restrictions on foreign currency holdings,it is argued that FCD forms a stable relationship with FCC and CBD so that changes in FCDadequately reflect changes in total foreign currency holdings. Komarek and Melecky (2001) usedthis ratio to measure dollarization in the Czech Republic; Dean (2000) for Canada; Viseth (2001)for Cambodia and Rennhack and Nozaki (2006) for a group of Latin American countries. For ourpurpose, foreign currency deposits in the domestic economy would be considered as the lowerbound of the level of dollarization in Nigeria.

Finally, operational measure of exchange rate volatility is presented. The exchange rate usedis the nominal parallel market exchange rate of the naira against the US dollar. This is becausethe true scarcity of dollar in Nigeria can easily be assessed by looking at the exchange rate in theparallel market than in the official market rate which was basically regulated and kept low forbalance of payment reasons. Hence, exchange rate volatility (NERV) used was extracted via astate-space representation (a form of signal to noise extraction) of the form:

Zt = σεte(1/2)ht ; iid(0, 1) (6)

where,

ht+1 = πht + μt NID(0, σ2μ) |π| ≤ 1 (7)

Zt is the exchange rate. The term σ2 is a scale factor and subsumes the effect of a con-stant in the regression of ht. π a parameter, μt a disturbance term that is uncorrelated with εt,εt is an iid(0,1) which are random disturbances symmetrically distributed about zero. The ht

equation is a transition equation in autoregressive form where the absolute value of π is lessthan unity to ensure that the process in Eq. (7) is stationary (Ndung’u, 2001; p. 12). The mainadvantage of this approach lies in its ability to generate unforecastable part of volatility whichseems to be more relevant in the dollarization literature (Mizen & Pentecost, 1996). Indeed,if the volatility is forecastable, it can be planned for. However, volatility becomes a problemwhen it cannot be planned for. It is the best approach to use since we can model the noise.These equations generate the conditional volatility of exchange rate used in Eq. (3) for estimationpurpose.

5. Estimation results, discussion and policy implications

Non-stationarity is a major feature of time series data. The starting point in any empirical studyinvolving time series therefore, will be to investigate this property before estimation proper toavoid spurious results. In applying the VAR technique, there are three basic approaches by which

measure the supply of foreign currency in Bolivia by relating it to statistics on the illegal drug trade. Alternatively, Kaminand Ericsson (2003) used data on shipments of US dollar notes to Argentina to estimate the stock of foreign currency inthat country. In another study, Melvin and Fenske (1992) used the loans market in Bolivia to provide a measure of thedollar holdings in the country.


non-stationary data can be handled. However, experts differ in the advice offered for appliedresearch. One option is to ignore the non-stationary altogether and simply estimate the VAR inlevels, relying on standard t- and F-distributions for testing any hypothesis. A second option is toroutinely difference any apparently non-stationary variables before estimating the VAR. If the trueprocess is a VAR in differences, then differencing should improve the small sample performanceof all the estimates and eliminate altogether the non-standard asymptotic distributions associatedwith certain hypothesis tests (Hamilton, 1994). The third approach is to investigate carefully thenature of the non-stationarity, testing each series individually for unit root and then testing forpossible cointegration among the series. Once the nature of the non-stationarity is understood,a stationary representation for the system can be estimated.3 At the application level, Hamilton(1994) suggests a combination of the three approaches. Therefore, in what follows, the stationaryproperties of the series were carefully examined; tests for cointegration and structural breakscarried out and unknown break points determined to avoid spurious rejection or acceptance ofcausality.

5.1. Unit root tests

To test for causality, it is important to ensure that the series are stationary to avoid spuriousrejection or acceptance of causality. Therefore, the stationary of the variables of interest wasinvestigated using Augmented Dickey-Fuller (ADF), and Philip-Perron (PP) tests. The result ispresented in Table 1.

Table 1Unit root tests

Variables Unit root tests Likely degree ofintegration

ADF PP

Levels 1st diff. 2nd diff. Levels 1st diff. 2nd diff.

With intercept onlyDI −2.4630 −8.9426* – −2.2823 −9.7715* – I (1)NPERV −5.2250* −8.1140* – −8.1856* −49.7843* – I (0)

With intercept and trendDI −2.5798 −8.8768* – −2.4846 −9.8553* – I (1)NPERV −8.4850* −8.0660* – −8.4865* −53.7913* – I (0)

ADF is the Augmented Dickey-Fuller test and PP is the Phillips-Perron test. It shows the t-statistic from a specificationthat includes a constant, without time trend. *Indicate rejection if the null hypothesis (Σ = 0) of non-stationarity at 1%,and **indicates stationarity at 5% critical values.

The tests indicate that DI is not stationary at levels but it is first difference stationary. Onthe other hand, NERV has no unit root both at levels and at first difference. Since one of thevariables is integrated of order one and the second integrated of order zero, cointegration analysiswas employed to examine possible long run relationship between the variables. For this purpose,Johansen technique (see Johansen & Juselius, 1990) was employed. Hamilton (1994) and Hayashi

3 See Hamilton (1994) for a discussion of the drawbacks of each of these empirical procedures.


(2000) argue that testing and analyzing cointegration in a VAR model is superior to the Engle-Granger single equation method. Moreover, specific restrictions suggested by economic theorycan be tested in this framework. The cointegration test indicates one cointegrating relationshipsuggesting the existence of long run relationship between dollarization and exchange rate volatility(see Table 2).

Table 2Trace test result

H0:rank< Eigen values Trace test Prob. of trace testb

0 0.270927 23.08114 0.0030a

1 0.060492 3.80630 0.0511

a Rejection of the hypothesis at 5% significance level. Trace test and LR test indicates 1 cointegrating equation(s) at5% significance level.

b MacKinnon-Haug-Michelis (1999) p-values.

Next, lag length selected for VAR estimation play a critical role in causality tests. The optimallag length of one (1) suggested by the various information criteria reported in Appendix A. FromTable 3, the hypothesis of no causality could not be rejected in either direction. This is becausethe respective F-statistics are not significant judging by the probability (p) values.

Table 3VAR causality test

Variables NERV DI

c 0.2373 (0.99) 0.007754 (1.88)NERV (−1) 0.0033 (0.03) 0.003269 (1.48)DI (−1) −4.4570 (−1.12) 0.840291 (12.23)

Summary statisticsF-statistic 0.6256 75.5062S.E. equation 1.0227 0.0176Chi-sq 7.5398 2.1879Prob. 0.2636 0.1391

Hence, we tested for possible structural break in the data using CUSUM tests for stability andone-step forecast test to determine the break point in the data.

5.2. Recursive residual tests for structural breaks

To test for structural breaks in our variables, the recursive test for stability was conductedusing both the CUSUM test and the one-step forecast test. The CUSUM test is based on thecumulative sum of the recursive residuals suggested by Brown, Durbin, and Evans (1975). It plotsthe cumulative sum together with 5% critical lines. Parameter instability is found if the cumulativesum goes outside the area between the two critical lines. So, movement of the sample CUSUMtest outside the critical lines is suggestive of coefficient instability. The CUSUM tests performedon both DI and NERV is presented in Figs. 4 and 5, respectively, below.

The CUSUM tests on both variables indicate a case of variance instability or the presenceof structural breaks in DI. To be able to identify the specific point of break in the data series, aone-step forecast test was conducted on DI which shows sign of instability. The test result for


Fig. 4. Recursive CUSUM test on dollarization index.

Fig. 5. Recursive CUSUM test on exchange rate volatility.

Fig. 6. Recursive one-step forecast test on dollarization.

dollarization is presented in Fig. 6. The upper portion of the graph (right vertical axis) reportsthe recursive residuals and standard errors while the lower portion (left vertical axis) shows theprobability values for those sample points where the hypothesis of parameter stability wouldbe rejected at the 5, 10 and 15% levels. The point with p-value less than 5% corresponds tothose points where the recursive residuals go outside the standard error bounds. In this case,the graph will sometime show dramatic jumps as the postulated equation4 tries to digest astructural break. As shown in Fig. 6, structural break was detected in the dollarization data in

4 See Perron (2005) for a detailed review and alternative derivations.


Fig. 7. Recursive one-step forecast test on exchange rate volatility.

1991. On the other hand, no break point was found in the nominal exchange rate volatility dataas shown in Fig. 7.

Therefore, to account for this structural break in the data, we included a dummy as an exogenousvariable in the VAR. The dummy variable is essentially zero-one function which is equal to oneafter 1991q1 (break point) and zero elsewhere. The inclusion of exogenous variable enables usto capture the effect of structural breaks in the regressions. Eq. (3) was estimated using ordinaryleast square estimation technique within a VAR structure in EViews, version 5.1. The result of theregressions is presented in Table 4. Interestingly, the result changed dramatically.

Table 4VAR causality test with dummy variable

Variables NERV DI

c 1.4573 (2.71) 0.0177 (1.94)NERV (−1) −0.0269 (−0.12) 0.0030 (1.40)DI (−1) −14.2536 (−2.66) 0.7764 (8.56)Dummy −1.1797 (−2.36) −0.0078 (−1.20)

Summary statisticsF-statistic 2.5104 61.4147S.E. equation 1.0000 0.0170Chi-sq 7.1000 1.9643Prob. 0.0077 0.1611

From this result, we cannot reject the hypothesis that NERV does not Granger-cause DIt at 5%level but we do reject the hypothesis that DIt does not Granger-cause NERV at a similar percentagelevel of significance. However, at 10% significance level, the hypothesis that NERV does notGranger-cause DI is rejected. Therefore it appears that Granger causality runs two-way fromdollarization to nominal exchange rate volatility and vice versa but causality from dollarization toexchange rate volatility appears stronger and dominates. However, this relationship was initiallyblurred by the structural break in 1991q1 when the then military head of state (Ibrahim Babangida)put embargo on bank licensing. Also, the demand for democratic rule was at its peak at this time andthe then military president was asked to vacate office. This period was characterized by massivestrikes and nation wide stay-at-home protests in the country. This must have been responsible forthis break at this time.


5.3. Policy implications

The result indicates that dollarization causes exchange rate volatility Nigeria. This raises anumber of policy issues for Nigeria: (1) whether dollarization should be curtailed; (2) whatexchange rate policy to adopt that maintains macroeconomic equilibrium, including financialsystem stability; and (3) what sequence should economic reforms take. The direction of causalityindicates that Nigeria is not a candidate for dollarization since it causes exchange rate volatil-ity capable of creating micro- and macro-economic uncertainties. This is because dollarizationmay worsen the vulnerability of the country through exchange rate risk exposure. Aside fromthis, Nigeria does not seem to satisfy the optimum currency area criteria for dollarization:large, open and but not tightly linked to the US financially and commercially (Eichengreen,2001).

In view of the above, it is important to consider a number of other policy options. At the heartof this causality result is the role of dollarization in ensuring exchange rate stability (financialstability) which requires slowing down dollarization. Slowing down deposit dollarization can havecosts since it may reflect optimal portfolio choices of agents. Taking away portfolio diversificationpossibilities (reducing dollarization) may result in welfare losses due to the loss of risk hedgingoptions. Currently, limited risk-hedging options are available in Nigeria. Other types of welfarelosses can also occur, and it would be a mistake to ignore them when proposing policies thatcan reduce dollarization. Yet, it is pertinent to balance household/asset holder welfare needs withoverall macroeconomic objectives of the country (stability). This is because buoyant aggregateeconomic activities will be difficult to nurture in an environment characterized by exchange ratevolatility with its pass-through effects to the domestic economy.

This boils down to the question raised by Eichengreen (2001) as to the kinds of problemsdollarization can solve. One of the critical problems asset holders face in Nigeria is that of limitedoptions for hedging prolonged inflation following many years of military rule with their charac-teristic economic wastage and fiscal mismanagement. Under capital account restrictions coupledwith fragile (poorly supervised and weakly capitalized) banking system, federal government fiscalimbalances and inflation; asset holders seek alternative avenues for keeping their assets. Possiblecandidates are physical assets and foreign currencies with relative stability. However, the preva-lence of currency and maturity mismatches in Nigerian credit markets and the consequent fragilityof the latter manifest itself in the desire for foreign currency. Hence, the process driving exchangerate volatility (dollarization) may be outside the control of domestic policy makers. Therefore,optimal policy responses to exogenous disturbances may be very challenging especially whendomestic institutional structures are lacking or weak at best. This view seems to underlie most ofthe recommendation for a fixed exchange rate arrangement in the face of dollarization found inthe dollarization literature (see, Bofinger, 1991; McKinnon, 1982, 1993).

Another effective but clearly undesirable measure to curb dollarization would be to reverse theopening of Nigerian economy and engage in direct administrative measures such as the introduc-tion of capital controls or the prohibition of foreign currency deposits. But such measures wouldreverse the broadly successful liberalization and global market integration and would almost cer-tainly provide only a short-lived solution. In fact, capital controls and the prohibition of foreigncurrency deposits are unlikely to boost the demand for domestic currency assets in Nigeria.5

5 This is because there is still insufficient supply of domestic currency assets that would permit portfolio diversification.Fear of confiscation of assets on the part of political office holders is another reason.


Without capital controls, the prohibition of foreign currency deposits would likely result in amove of foreign currency deposits abroad.

Alternatively, given the size of the country, distance from and trade relation with the US, afeasible policy option to reverse dollarization episode in Nigeria will be to float its currency aftersome macroeconomic conditions are met. However, this must be properly sequenced. Indeed,floating should not be attempted until the financial system had been successfully strength-ened: appointment of truly independent central banker, improved banking system regulationand supervision, improved banking system capitalization and consolidation or overall finan-cial system stability, development of domestic currency assets which serves as alternatives todomestic money, and attainment and sustainability of fiscal balance. In this direction, the cur-rent efforts at repositioning the Nigerian financial markets for improved efficiency are laudable.Noticeable stability in the Naira—US dollar exchange rate in recent times could be a manifes-tation of a more truly independent and proactive central banker capable of implementing radicalreform programmes especially banking system recapitalization and consolidation in Nigeria. Thishad helped in no small measure in reducing dollarization and thereby stabilizing the exchangerate.

Finally, while the possibility of exchange rate instability due to dollarization cannot be dis-missed from the empirical evidence presented above, it must be bore in mind that there aremany other types of shocks that could cause exchange rate instability (e.g. term of trade shocks).Hence, it may not be safe to conclude that dollarization disturbances should dominate the for-mulation of exchange rate policies. Yet, it should be explicitly considered in policy design andimplementation.

6. Conclusion

This paper investigates the relationship between nominal exchange rate volatility and dollariza-tion in Nigeria by applying Granger causality test for the Nigeria data for the period 1986 (1)–2003(4). Previous theoretical and empirical studies on these issues provided conflicting results. Thisstudy therefore was an attempt to provide further empirical evidence using Nigeria data. Theempirical results of Granger causality test support a bi-directional relationship. However, causal-ity from dollarization to exchange rate volatility appears stronger and dominates. This suggeststhat policies that aim to reduce exchange rate volatility in Nigeria must include measures thatspecifically address the issue of dollarization. An important factor in this case is the supply of suf-ficient domestic currency assets that would permit portfolio diversification and capable of dousingnegative expectations. In this respect, attention should be paid to dollarization in exchange rateregime choice and other macroeconomic factors that may affect expectations about exchange ratemovements.

Acknowledgements

Dollarization and Exchange Rate Volatility in Nigeria: Exploring the Causal Relationship.


Appendix A. VAR lag order selection criteria

Lag Log L LR FPE AIC SC HQ

0 76.79245 NA 0.000231 −2.696017 −2.548684 −2.6391961 92.44645 28.98890* 0.000150* −3.127646* −2.832982* −3.014006*2 93.82992 2.459498 0.000166 −3.030738 −2.588741 −2.8602773 96.69882 4.887763 0.000173 −2.988845 −2.399517 −2.7615644 101.1669 7.281334 0.000171 −3.006182 −2.269521 −2.7220815 102.9351 2.750515 0.000187 −2.923522 −2.039529 −2.5826016 106.7027 5.581646 0.000190 −2.914915 −1.883590 −2.5171747 107.0506 0.489675 0.000221 −2.779653 −1.600996 −2.3250928 112.1609 6.813722 0.000215 −2.820775 −1.494786 −2.3093939 117.5882 6.834287 0.000209 −2.873636 −1.400314 −2.305433

10 120.9800 4.019928 0.000219 −2.851110 −1.230457 −2.226088

*Indicates lag order selected by the criterion. LR: sequential modified LR test statistic (each test at 5% level); FPE: finalprediction error; AIC: Akaike Information Criterion; SC: Schwarz Information Criterion; HQ: Hannan-Quinn InformationCriterion.

References

Agenor, P.-R., & Khan, M. S. (1996). Foreign currency deposits and the demand for money in developing countries.Journal of Developing Economics, 50, 101–118.

Arize, A. C., & Malindretos, J. (1998). The long-run and short-run effects of exchange-rate volatility on exports: The caseof Australia and New Zealand. Journal of Economics and Finance, 22(2–3), 43–56.

Aryeetey, E., & Udry, C. (1994). The characteristics of informal financial markets in Africa. Paper presented at the plenarysession of the workshop of the African economic research consortium, Nairobi, (December 4–9).

Bofinger, P. (1991). The transition to convertibility in Eastern Europe: A monetary view. In J. Willianson (Ed.), Currencyconvertibility in Eastern Europe. Washington, DC: Institute for International Economics.

Brown, R. L., Durbin, J., & Evans, J. M. (1975). Techniques for testing the constancy of regression relationships overtime. Journal of the Royal Statistical Society Series B, 37, 149–192.

Calvo, G. A. (1996). Money, exchange rates and output. Massachusetts, USA: MIT Press.Calvo, G. A. (June 22, 2000). Testimony on dollarization. Paper presented before the sub-committee on domestic and

monetary policy committee on banking and financial services (pp. 1–5), Washington, DC.Chang, R. (2000). Dollarization: A score card. Federal Reserve Bank of Atlanta Economic Review, Third Quarter, 85(3),

1–11.Chowdhury, M. B. (1999). The determinants of real exchange rate: Theory and evidence from Papua New Guinea. Asia

Pacific school of economics and management working papers (SP99-2). http://ncdsnet.anu.edu.au.Clements, B., & Schwartz, G. (1992). Currency substitution: The recent experience with Bolivia. World Development,

21, 1883–1893.Dean, J. W. (2000). De facto dollarization. In Paper presented at a conference on: To dollarize or not to dollarize:

Exchange rate choices for the western HemisphereEichengreen, B. (2001). What problems can dollarization solve? Journal of Policy Modeling, 23, 267–277.Feige, E. L. (2003). The dynamics of currency substitution, asset substitution and defacto dollarization and eurorization

in transition countries. In Proceeding of the 8th Dubrovnik conference volume on monetary policy and currencysubstitution in emerging markets.

Friedman, A., & Verbetsky, A. (2001). Dollarization in Russia, Economics Education and Research Consortium (EERC).Working Papers Series 01/05 (Moscow). http://www.eerc.ru/publications/workpapers/WP 01-05r.pdf.

Granger, C. W. J. (1969). Investigating causal relations by econometrics models and cross spetral methods. Econometrica,37(3), 424–438.

Gruben, W. C., & McLeod, D. (2004). Currency competition and inflation convergence Center for Latin Americaneconomics. Federal Reserve Bank of Dallas. http://www.fordham.edu/economics/mcleod.

Hamilton, J. D. (1994). Time series analysis. Princeton, NJ, USA: Princeton University Press.Hayashi, F. (2000). Econometrics. Princeton, NJ, USA: Princeton University Press.

http://ncdsnet.anu.edu.au/

http://www.eerc.ru/publications/workpapers/WP_01-05r.pdf

http://www.fordham.edu/economics/mcleod


Honda, J., & Schumacher, L. (March 2006). Adopting full dollarization in postconflict economies: Would the gainscompensate for the losses in Liberia? IMF Working Paper, WP/06/82.

Johansen, S., & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration with applications tothe demand for money. Oxford Bulletin of Economics and Statistics, 52, 169–210.

Kamin, S. B., & Ericsson, N. R. (2003). Dollarization in post-hyperinflationary Argentina. Journal of International Moneyand Finance, 22, 185–211.

Komarek, L., & Melecky, M. (2001). Currency substitution in the transition economy: A case of the Czech Republic1993–2001. WARWICK Economic Research Papers, No. 613, Department of Economics, The University of Warmich,pp. 1–36.

Krueger, R., & Ha, J. (1996). Measurement of cocirculation of currencies. In Mizen & Pentecost (Eds.), The macroe-conomics of international currencies: Theory, policy and evidence (pp. 61–76). USA: Edward Elgar PublishingLtd.

Lutkepohl, H. (1993). Introduction to multiple time series analysis (second ed.). New York: Springer-Verlag.McKinnon, R. (1982). Currency substitution and instability in the World dollar standard. American Economic Review,

72, 320–333.McKinnon, R. I. (1985). Two concepts of international dollarization. In M. Connolly & J. McDermott (Eds.), The economics

of the Caribbean Basin (pp. 101–118). New York: Praeger.McKinnon, R. I. (1993). The rules of the game: International money in historical perspective. Journal of Economic

Literature, 31, 1–44.McKinnon, R. I. (1996). Direct and indirect concepts of international dollarization. In P. Mizen & E. J. Pentecost (Eds.), The

macroeconomics of international currencies: Theory, policy and evidence (pp. 44–59). UK: Edward Elgar PublishingLtd.

Melvin, M., & Fenske, K. (1992). Dollarization and monetary reform: Evidence from the Cochabamba region of Bolivia.Revista de Analisis Economico, 7(1), 125–138.

Melvin, M., & Ladman, J. (1991). Coca dollars and the dollarization of South America. Journal of Money, Credit andBanking, 23, 752–763.

Mizen, P., & Pentecost, Eric J. (1996). Dollarization in theory and practice. In P. Mizen & E. J. Pentecost (Eds.), Themacroeconomics of international currencies: Theory, policy and evidence (pp. 8–43). US: Edward Elgar PublishingLtd.

Montiel, P. J., Agenor, P. R., & Haque, U. I. (1993). Informal financial markets in developing countries: A macroeconomicanalysis. Oxford UK: Blackwell., pp. 1–44

Ndung’u, N. S. (2001). Liberalization of the foreign exchange market and the short-term capital flows problem. AERCResearch Papers 109. Nairobi, Kenya: African Economic Research Consortium.

Nwanna, G. I. (1996). Rural financial markets in West Africa: Roles, experiences constraints and prospects for promotingrural development. New Jersey, USA: Centre for Economic Research on Africa.

Obadan, M. I. (1996). Short-term and medium-term economic management strategies. In M. I. Obadan & M. Iyoha(Eds.), Macroeconomic policy analysis: Tools, techniques and applications to Nigeria, National Centre for EconomicManagement and Administration. Nigeria: Ibadan.

Osakwe, P. N. (February 2002). Currency fluctuations, liability dollarization, and the choice of exchange rate regimes inemerging markets. Bank of Canada Working Paper 2002–2006.

Perron, P. (2005). Dealing with structural breaks. Paper presented for the palgrave handbook of econometrics, vol. 1,Econometric Theory.

Rennhack, R., & Nozaki, M. (January 2006). Financial dollarization in Latin America. IMF Working Paper, WP/06/7IMF.

Sahay, R., & Vegh, C. A. (1996). Dollarization in transaction economies: Evidence and policy implications. In Mizen &Pentecost (Eds.), The macroeconomics of international currencies: Theory, policy and evidence (pp. 193–224). USA:Edward Elgar Publishing Company.

Savastano, M. A. (1996). The pattern of currency substitution in Latin America: An overview. In P. Mizen & J. Pentecost(Eds.), The macroeconomics of international currencies: Theory, policy and evidence. USA: Edward Elgar PublishingLtd.

Soyibo, A. (1997). The informal financial sector in Nigeria: Characteristics and relationship with the formal sector.Development Policy Review, 15, 5–22.

Viseth, K. R. (2001). Currency substitution and financial sector development in Cambodia. In Economics of development.Australia: The Australian National University., pp. 1–31.

Willett, T. D., & Banaian, K. (1996). Currency substitution, seigniorage and the choice of currency policies. In P. Mizen &J. Pentecost (Eds.), The macroeconomics of international currencies: Theory, policy and evidence (pp. 77–95). USA:Edward Elgar Publishing Ltd.

between dollarization and exchange rate volatility: nigeria's portfolio diversification option

Documents