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Exchange rate volatility and export growth in NigeriaOlugbenga A. Onafowora a & Oluwole Owoye ba Department of Economics , Susquehanna University , Selinsgrove, PA 17870, USAb Department of Social Sciences/Economics , Western Connecticut State University ,Danbury, CT 06810, USAPublished online: 11 Apr 2011.

To cite this article: Olugbenga A. Onafowora & Oluwole Owoye (2008) Exchange rate volatility and export growth in Nigeria,Applied Economics, 40:12, 1547-1556, DOI: 10.1080/00036840600827676

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Applied Economics, 2008, 40, 1547–1556

Exchange rate volatility and export

growth in Nigeria

Olugbenga A. Onafoworaa,* and Oluwole Owoyeb

aDepartment of Economics, Susquehanna University, Selinsgrove, PA 17870,

USAbDepartment of Social Sciences/Economics, Western Connecticut State

University, Danbury, CT 06810, USA

This article examines the impact of exchange rate volatility on Nigeria’s

exports to its most important trading-partner–the United States over the

quarterly period January 1980 to April 2001. Using cointegration and

vector error correction (VECM) framework, empirical tests indicate the

presence of a unique cointegrating vector linking real exports, real foreign

income, relative export prices and real exchange rate volatility in the long

run. Furthermore, the results show that increases in the volatility of the

real exchange rate raise uncertainty about profits to be made which exert

significant negative effects on exports both in the short- and long-run.

Our results also show that improvements in the terms of trade (represented

by declines in the real exchange rate) and real foreign income exert positive

effects on export activity. Most importantly, we found that the trade

liberalization and economic reform policies implemented in the post-1986

structural adjustment period contributed to Nigeria’s export performance.

Overall, our findings suggest that Nigeria’s exporting activities can be

further boosted by policies aimed at achieving and maintaining a stable

competitive real exchange rate.

I. Introduction

The high degree of volatility and uncertainty of

exchange rate movements since the collapse of the

Bretton Woods system of fixed exchange rates in early

1970s has generated a plethora of theoretical and

empirical studies on the effects that such volatility has

on international trade. The results of these studies

have been ‘a mixed bag’. While some studies have

concluded that exchange rate volatility impede trade,

other studies disagreed. This is because an increase in

exchange rate risk has a substitution and an income

effect. The substitution effect leads traders to sub-

stitute away from foreign trade towards domestic

trade, while the income effect leads to increase foreign

trade activity.1 In addition, some studies have reported

no significant relationship between exchange rate

volatility and exports.2

*Corresponding author. E-mail: onafowor@susqu.edu1 See Secru and Raman (2000, Ch. 6) for theoretical examples showing an ambiguous relationship between variability ofexchange rate and exports, and Baccheta and Wincoop (2000) for a theoretical example showing no relationship. Empiricalstudies by Bahmani-Oskooee (2002), Choudhry (2001), Arize et al. (2000), Hook and Boon (2000), Adubi and Okumadewa(1999), Kim and Lee (1996), Caporale and Doroodian (1994), Arize (1995) and Chowdhury (1993) report a negativerelationship. On the other hand, Baum et al. (2001), Doyle (2001), Chou (2000), McKenzie and Brooks (1997), Qian andVarangis (1994), Assery and Peel (1991) report both positive and negative implications on exports for some countries.2 For example, Aristotelous (2001), Bahmani-Oskooee and Payesteh (1993), and Hooper and Kohlhagen (1978) report aninsignificant relationship.

Applied Economics ISSN 0003–6846 print/ISSN 1466–4283 online � 2008 Taylor & Francis 1547http://www.tandf.co.uk/journalsDOI: 10.1080/00036840600827676

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It is important to point out here that most of the

theoretical and empirical debates about the effects of

exchange rate uncertainty on trade have centered onthe experiences of developed economies in Western

Europe and North America. In less developed

countries (LDCs) where the forward markets are

less developed and the cost of adjusting to changes inthe economic environment is higher, exchange rate

volatility coupled with protectionism, could have a

major impact on trade and income. It is well

documented in the literature that one of the majorshortcomings of developing countries is the absence

of or underdeveloped financial markets. Because of

this, developing economies incur higher transactionscosts, yet there are few studies that analyze the impact

of exchange rate volatility on trade in LDCs,

particularly, African countries. Intuitively, one

would conclude that it is in the developing countriesthat the need to understand the policy implications of

volatile exchange rates is paramount.The objective of this article is to partially fill the

gap in the literature by examining the impact ofexchange rate volatility on Nigeria’s export trade with

its single most important trading-partner – the United

States (US).3 The focus on Nigeria, Africa’s most

populous nation and second-largest economy, shouldprovide valuable insights into the effects of exchange

rate volatility on exports trade in small, but increas-

ingly open, developing countries. An understanding

of the effects that a volatile exchange rate has onNigeria’s trade is critical to policymakers who are

trying to devise exchange rate and trade policies to

promote export activities. Such knowledge of whethervolatility depresses exports should result in policies

that aid the attainment of real exchange rate stability,

which in turn, promotes economic growth.

Furthermore, this may help to lessen the potentialadverse effects of high-exchange rate uncertainty.

The empirical analysis is carried out within a

cointegration and vector error correction model

(VECM) framework using quarterly data coveringthe period January 1980 to April 2001. The results

from the cointegration analysis show that there exists

a long-run equilibrium relationship among real

exports demand, real foreign income, relative exportprices and exchange rate volatility. The empirical

results show that real foreign income has positive

effects on the demand for exports. Furthermore, we

found that worsening terms of trade (increases in

relative export prices) and increased volatility of thereal exchange rate have adverse effects on exportsdemand, and that the economic reforms and tradeliberalization policies implemented in the post-1986period contributed significantly to boosting Nigeria’sexports. The short-run estimates of the VECMcorroborate the results of the long-run parameterestimates.

The remainder of this article is organized asfollows. Section II provides a brief background onexchange rate policy and export performance duringthe past three decades in Nigeria. Section III presentsthe export demand model. The data and theestimation technique are also discussed in thissection. The empirical results are presented inSection IV. The main conclusions of the study aresummarized in Section V.

II. Historical Trends

Prior to adoption of structural reform and adjust-ment programs in July 1986, Nigeria was widelyrecognized as an exporter of primary agriculturalcommodities and, to a smaller extent, one or twosolid minerals.4 Between 1960 and 1970, the Nigerianeconomy was largely sustained by export earningsfrom its primary agricultural commodities. In 1970,Nigeria became a member of the Organization forPetroleum Exporting Countries (OPEC), and sincethen, oil has become the dominant sector of theNigerian economy. Although oil is an enclave sectorin Nigeria with few forward and backward linkageswith the rest of the economy, it is still importantfor economic performance. The revenues from oilproduction contribute about 90–95% of Nigeria’sforeign exchange earnings, 40% of GDP, and morethan 80% of government revenue.

In the early 1960s, Nigeria did not havean independent monetary policy. The conduct ofmonetary policy was largely dictated by the prevailingeconomic conditions in Britain. The instrument ofmonetary policy at that time was the exchange rate,which was fixed at par with the British pound.This fixed parity lasted until 1967 when the Britishpound was devalued. Owing to the civil war inNigeria in the later part of the 1960s, the monetaryauthorities did not consider it prudent to devalue the

3 Since the 1980s, Nigeria’s exports to the US have on average made up about 47% of the country’s total exports. BeforeOPEC (Organization of Petroleum Exporting Countries) quota production limitations in 2001, Nigeria was exporting about1.8 million barrels of oil per day, with half of that oil destined for the US market.4 The brief discussion in this section benefits greatly from the studies by Nnanna (2001), Adubi and Okumadewa (1999) andEgwaikhide (1999).

1548 O. A. Onafowora and O. Owoye

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Nigerian pound in line with the devaluedBritish pound. Rather than devalue, the monetaryauthorities chose to peg the Nigerian currency(then pound) to the US dollar. When the interna-tional financial crisis of the early 1970s led to thedevaluation of the US dollar, Nigeria abandoned thedollar peg and shifted back to the British pound peguntil 1973 when the Nigerian currency (now Naira)was once again pegged to the US dollar. This fixedparity system was abandoned in 1976 when anindependent exchange rate management policy wasadopted that pegged the Naira to either the US dollaror the British pound; whichever currency wasstronger in the foreign exchange market (Adubi andOkumadewa, 1999). During this phase, the mainobjective of exchange rate policy was to manage theexchange rate of the Naira in order to influence realeconomic variables and lower the rate of inflation.

The sharp rise in world oil prices and oil exportvolumes during the 1970s encouraged a policy ofprogressive appreciation of the Naira. As a result ofthe increased revenue accruing to the governmentfrom crude petroleum exports, Nigeria persistentlyran appreciable external surpluses in the balance ofpayments, which supported the appreciation of theNaira. Between 1973 and 1978, the value ofthe real exchange rate increased more than 100%.An exchange rate policy that allowed the Naira toappreciate with rising oil revenue in tandem withrising domestic wages and prices placed Nigeria’sexports at a competitive disadvantage in the worldmarket. By 1978, economic problems began tomanifest as real world interest rates turned positive,coinciding with the deterioration in Nigeria’s termsof trade.

By 1981, Nigeria’s balance of payments situationdeteriorated sharply due to a combination of excessiveborrowing and a precipitous drop in world oil prices.The absence of policy reforms and the overvaluationof the Naira exacerbated the situation. The distortedexchange rate prevented the government from allocat-ing resources efficiently to purchase imports, hence,the government implemented several measures andstringent trade controls in the Economic Stabilization(Temporary Provisions) Act of 1982. Some of thesemeasures included the rationing of foreign exchange,increases in import duties/tariffs, restrictions onimport licenses, increases in the price of petroleumproducts, the initiation of an import deposit programand drastic cuts in public investment spending.Although these measures attempted to correct thesituation, they were insufficient in the absence ofcurrency devaluation.

The economy reached a crisis point in 1983when oil prices declined markedly by 45% from

the 1980 level. Consequently, Nigeria’s export rev-enue and budgetary receipts dropped significantly.However, public spending did not slow downproportionately during this period. This resulted inthe build-up of large fiscal and external deficits. Inthe bid to finance the domestic deficits, governmentresorted to borrowing heavily from the bankingsystem, especially from the Central Bank of Nigeria(CBN). Similarly, the financing of foreign deficits ledto massive foreign borrowing and the drawing downof external reserves. In 1983, the Federal budgetdeficit amounted to 12% of GDP, the real interestrate reached 20%, the external account deficit grew to6% of GDP, and the GDP recorded a negativegrowth rate of 6.7%. By 1985, the terms of trade hadplummeted to about 35% of their 1980 level.At the same time, the exchange rate was still grosslyovervalued. The budget deficits experienced in theearlier years still prevailed and import controls weremore stringent.

As Nigeria’s economic crisis deepened, thegovernment allowed the exchange rate to bedetermined by market forces. This led to many ratesthat diverged widely from one another. In its questfor stability of the exchange rate, the CBN experi-mented with several bidding systems, including theDutch auction system (DAS). Attempts to ensureviability of the Naira exchange rate in the market ledto frequent policy changes, interventions by the CBNand opening of different foreign exchange windows.During this period of economic malaise, the govern-ment introduced various budget tightening austeritymeasures to address these problems in order to reducethe country’s financial imbalance. In addition,stringent monetary and fiscal measures were ineffec-tive in addressing the country’s economic problems.At this same period, the government could not reachan agreement with the Bretton Woods institutions onseveral macroeconomic issues including devaluationof the Naira and import liberalization. By 1986, thegrave external and internal economic imbalancesforced the Nigerian government to adopt thestructural adjustment program (SAP) as a policyoption to put the economy back on a sustainablegrowth path. A deliberate policy to depreciate theNaira was effected though this was not systematic.In an attempt to realign the Naira exchange rate, theNaira exchange rate was pegged to a basket of12 currencies of Nigeria’s major trading-partners.

In general terms, the SAP strategy involved bothstructural and sectoral policy reforms. The reformsincluded liberalization of foreign exchange and inter-est rate controls, devaluation of the exchange rate andthe adoption of a system of floating exchange rate inSeptember 1986. The vigorous implementation of SAP

Exchange rate volatility and export growth in Nigeria 1549

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over the 1986–1992 period resulted in considerableimprovements in the performance of the Nigerianeconomy. For instance, between 1987 and 1992, themanufacturing, agricultural and oil sectors, experi-enced positive growth with an average GDP growthrate of about 5% per year (Moser et al., 1997).We should point out that SAP evoked strongopposition and sentiments among many Nigeriansbecause of its perceived adverse effects. The belt-tightening measures implemented under the SAP andthe relentless opposition from different sectors to thispolicy option culminated in the official abandonmentof structural adjustment in 1994, when the authoritiesannounced a reversal of the policies of deregulationand structural reforms. The government thenre-imposed interest rate controls, eliminated the freemarket for foreign exchange and reaffirmed itsbelief in the stability of the official exchange rate,irrespective of underlying economic fundamentals.The reversals and weakening of policies in 1994resulted in prolonged stagflation.

In 1995, the government shifted, once again, to apolicy of partial deregulation of the economy because

of the failure of its policy reversals of 1994. The new

policy measures included the liberalization of the

foreign exchange market, interest rate and direct

foreign investment. By the end of 1995, the new

policy reform began to yield substantial economic

growth and expansion in Nigeria’s volume of exports.

As we can see in Table 1, real GDP grew by an

average of 3.25% per year between 1996 and 2001 as

compared to the 1985–1995 period.5

Inflation rate, as measured by the 12-monthincrease in the consumer price index, which rose toa peak of 72.9% in 1995, has moderated significantlysince 1997 reaching single digit between 1998 and2000 before rising again to double digits in 2001.During the period 1986 to 2000, the Nigerian Naira/US dollar exchange rate changed from US$1¼Nairato US$1¼ 100 Naira. In 2001, the total value ofexports amounted to US$17.26 billion compared toUS$5.92 in 1986. Over the period 1986 to 2001,exports from Nigeria to US increased from US$2.53billion to US$8.77. In addition, the share of USexports in total Nigerian exports increased from23.9% in 1985 to 50.8% in 2001.

From a cursory examination of Table 1, it isapparent that the real exchange rate fluctuatedbetween 1985 and 2001 – a period that includedSAP implementation, policy reversal and partialderegulation of the economy. However, the mainquestion is whether (or not) the exchange rate

Table 1. Nigeria: total exports, exports to US, real exchange rate and selected economic indicators, 1985–2001

YearTotala

exportsExportsb toUS

Shareof US exports intotal exportsc

Real exchangerated

Real GDPgrowthe

Inflationratef

1985 12 537 3000 23.9 16.9 5.51986 5923 2503 42.7 51.6 5.41987 7344 3574 48.7 59.4 10.21988 6916 3279 47.4 51.6 56.01989 7876 5284 67.1 51.5 50.51990 13 596 5982 44.0 58.5 7.51991 12 264 5168 42.1 56.8 4.8 12.71992 11 886 5102 42.9 78.7 3.0 44.81993 9908 5301 53.5 56.6 2.7 57.21994 9415 4430 47.1 36.7 1.3 57.01995 12 342 4931 39.7 21.9 2.2 7291996 16 153 5978 37.0 17.3 3.4 29.31997 15 207 6349 41.8 16.0 3.2 8.51998 9855 4194 42.6 14.1 2.4 10.01999 13 856 4385 31.6 60.9 2.8 6.62000 20 975 10 538 50.2 62.9 3.8 6.92001 17 261 8775 50.8 58.1 4.0 18.9

Source: Foreign Trade Division, Data Dissemination Branch, US Census Bureau; International Monetary Fund, InternationalFinancial Statistics 2002 CD-ROM; Federal Office of Statistics; and Central Bank of Nigeria: Annual Report and Statementof Accounts (various issues).Notes: a,bUS$ million.c,e,fpercent (%).dNaira/US$.

5 In Obasonjo’s Economic Direction, 1999–2003, the government targeted output growth of at least 6–10% a year by the end ofits administration.

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volatility observed during this period had anysignificant effects on the level of exports in Nigeria.

III. Model Specification, Data andEstimation Procedure

To analyse the impact of exchange rate volatility onNigeria’s exports, we specify the following long-runreal exports demand function:

Xt ¼ �1 þ �2Yt þ �3Pt þ �4Vt þ �5D86t þ "t ð1Þ

where Xt is the logarithm of real exports; Yt is thelogarithm of real foreign income; Pt is the logarithmof relative export prices; Vt is a measure of exchangerate volatility; D86t is a (0, 1) dummy variable thatcaptures the effect of the liberalization and economicreform policies implemented since 1986, and "t is awhite-noise disturbance term.

Economic theory suggests that an increase in realforeign income should lead to an increase in thedemand for exports, while a rise (fall) in relative exportprices would cause the domestic goods to become less(more) competitive than foreign goods, thereforeexports would fall (increase). The effect of exchangerate volatility on exports is ambiguous; it depends ontraders’ attitude to risk. For example, De Grauwe(1988, p. 67) suggests that if unpredictable movementsin the exchange rate increase uncertainly about theprofits to be made, very risk-averse individuals mayexport more to avoid the possibility of a decline intheir revenues, thereby leading to an increase in overalltrade flows. On the other hand, if traders are risk-neutral or less risk-averse, they are less concerned withextreme outcomes. Risk-neutral traders see the returnon export activity as less attractive given the increasein risk and may decide to export less, leading to adecline in overall trade flows. In this context, theimpact of an increase in exchange rate volatility onexports has to be determined empirically since it can beeither positive or negative.

Data and estimation procedure

This study uses data covering the period from January1980 to April 2001 drawn from the IMF’sInternational Financial Statistics 2002 CD-ROM.

Previous studies (for example, Learner and Stern,

1970) suggest that the quantity or volume of exports is

more appropriate to use than value of exports as themeasure of total exports demand. However, as with

most developing countries, the trade data in Nigeria

are available in value terms rather than in quantity

terms. To obtain the required volume and pricecomponents, some studies deflate the value series

using actual transactions or contractual export prices

as deflators. However, such export price indices that

are based on international transactions are morereadily available for the industrialized countries, and

in cases where the deflators are available for develop-

ing countries, their coverage of commodities are notuniform and their frequency is such that it does not

allow for meaningful econometric analysis. Some

studies have used price deflators such as unit value

prices, which although not precise, are more readilyavailable. However, Goldstein and Khan (1985) note

that the problem with unit value indices is that they

change with the commodity composition of trade evenwhen the ‘true’ prices of traded products remain

unchanged. Moreover, many studies that have used

available proxies such as unit value prices and

producer prices acknowledge that the estimatedelasticities may be biased. Given these problems, we

employ the real value of exports series as our

dependent variable.In this article, the real foreign income is

represented by the US real GDP, while the relative

export price is proxied by the real exchange rate.

The real exchange rate (RERt) between the Nigerian

Naira and US dollar is calculated from a purchasingpower parity relationship formulated as follows:

RERt ¼ERt � PFt

PDtð2Þ

where ERt is the effective nominal exchange rate, PFt

is the foreign price of tradeable goods, PDt is the

domestic price of nontradable goods, and t denotes a

time index. In the absence of data for foreign and

domestic export prices, we proxy the foreign exportprice by the US wholesale price index (WPI) and the

domestic export price is represented by the consumer

price index (CPI).Exchange rate volatility is not directly observable,

but various statistical measures of volatility have been

used in the literature to measure exchange rate

volatility.6 In this article, we use a generalized

6 Some examples include: the moving average SD (MASD) of the growth rate of the exchange rate (e.g. Chowdhury, 1993;Arize et al., 2000; Bahmani-Oskooee, 2002); the absolute percentage change of the exchange rate (e.g. Bailey et al. (1987); theresiduals from an autoregressive integrated moving average (ARIMA) model (Assery and Peel (1991), and the measuresgenerated by various types of autoregressive conditional Heteroskedasticity (ARCH) models (e.g. Kroner and Lastrapes,1993; Caporale and Doroodian, 1994; Mckenzie, 1998; Chou, 2000).

Exchange rate volatility and export growth in Nigeria 1551

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ARCH-type model (GARCH) to measure the

volatility of the exchange rate. We make use of real

as opposed to nominal exchange rates in the

measurement.7 Unlike other measures of exchange

rate volatility which can potentially ignore informa-

tion on the stochastic processes by which exchange

rates are generated, ARCH-type models capture the

time-varying conditional variance as a parameter

generated from a time-series model of the conditional

mean and variance of the growth rate, and thus are

very useful in describing volatility clustering.

The GARCH (1,1) model we estimate is based on

an autoregressive model of order 2 (AR (2)) of the

first difference of the real exchange rate and it takes

the following form:

logRERt ¼ �0 þ �1 logRERt�1 þ �2 logRERt�2

þ et, where et � Nð0,V2t Þ ð3Þ

V2t ¼ �0 þ �1e

2t�1 þ �2V

2t�1 ð3bÞ

The conditional variance equation (Equation 3b) is a

function of three terms: (i) the mean �0, (ii) the news

about volatility from the previous period, measured

as the lag of the squared residual from the mean

equation: e2t�1 (the ARCH term), and (iii) the last

period’s forecast error variance, V2t�1 (the GARCH

term). Estimation of Equation 3b yielded the

following result (SEs are in parentheses):

V2t ¼ 0:00006

ð0:000005Þþ 0:038ð0:009Þ

e2t�1 þ 0:717ð0:0068Þ

V2t�1 ð4Þ

The results of Equation 4 may be interpreted as

market participants’ prediction of the current

period’s real exchange rate variance. This variance

is measured as a weighted average of a long-term

average (the constant term in Equation 4) and the

ARCH and GARCH terms. Thus, the predicted

values of V2t provide us with a measure of the

volatility of the Naira exchange rate against the US

dollar. A graphical representation of the volatility of

the real exchange rate is presented in Fig. 1. It is

evident from the figure that the real exchange

rate had become highly volatile since after the

liberalization of exchange controls and the shift to a

floating exchange rate in 1986.

IV. Empirical Results

Because the data used in this study are time seriesdata, they could change over time and do not havefixed or stationary means. The presence of nonsta-tionarity may invalidate standard tests used ininference testing and thereby lead to erroneousconclusions. Thus, as a preliminary step thestationarity property of the individual series isexamined using the augmented Dickey–Fuller(ADF) unit roots test procedure. The results of theADF unit roots tests, reported in Table 2, indicatethat all variables are nonstationary at their level andstationarity is achieved after first difference.

Given the unit-root properties of the variables, weproceed to establish whether there is a long-runequilibrium relationship among the variablesin Equation 1 by using the Johansen maximumlikelihood cointegration method8 (Johansen, 1988;Johansen and Juselius, 1990). The results of thecointegration test, reported in Panel A of Table 3,show that the maximum eigenvalue trace statisticsreject the null hypothesis of no-cointegration vector(r¼ 0) at the 5% significance level. The conclusioncan be reached that there exists a unique stationarylong-run relationship between X,Y,P,V and D86.

0.0

0.2

0.4

0.6

0.8

1.0

80 82 84 86 88 90 92 94 96 98 00

Volatility (GARCH)

Fig. 1. Volatility of the Naira/US Dollar exchange rate,

1980–2001

7 Previous empirical studies show that there are no qualitative differences in using nominal or real exchange rate volatility (seeMcKenzie and Brooks (1997) and Qian and Varangis (1994)).8 Among some of its many advantages, the Johansen and Juselius approach produces asymptotically optimal estimatesbecause it incorporates a parametric correction for serial correlation (which comes from the underlying vector autoregression(VAR)) and the system nature of the estimator means that the estimates are robust to simultaneity bias. Moreover, theJohansen method is capable of detecting multiple cointegrating relationships (if they exist) and it does not suffer fromproblems associated with normalization.

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Since there is one cointegrating vector, in order toinfer the response of exports demand to a change inits economic determinants, we report the parameters(long-run elasticities) of the cointegratingvector representing the log-run real exportsdemand equation in Panel B of Table 3.These parameters are obtained by normalizing theestimates of the unconstrained cointegrating vectoron real exports.

As can be seen in Panel B of Table 3, the estimatedreal foreign income elasticity carries the expectedpositive sign and is statistically significant at the 5%level. The size of the long-run income elasticityaccords with Riedel’s observation that most estimatesof income elasticities in export demand functions‘whether for developed or developing countries, orfor country aggregates or in individual countries,generally lie in the range between 2.0 and 4.0’ (Riedel,1988a, p. 140). The coefficient on the relative pricevariable and on the real exchange rate volatility arenegative and statistically significant, implying thatappreciation of the real exchange rate and exchangerate uncertainty adversely affect exports demand inlong-run. The coefficient on the dummy variablethat captures the effect of liberalization policiesimplemented in the post-1986 period is positiveand statistically significant, suggesting that thesepolicies had contributed positively to boostNigeria’s international competitiveness and exportingactivity.

The short-run dynamics

The estimated cointegration relationship reveals thefactors affecting exports demand in the long-run.However, in the short-run, deviations from thisrelationship could occur as shocks to any of therelevant variables. Given the existence of cointegra-tion and based on the representation theoremdeveloped by Engle and Granger (1987), theshort-run dynamics can be modeled using a

vector error correction model (VECM) of thefollowing form:

�Xt ¼ �0 þXk�1

i¼1

�1�Xt�i þXk�1

i¼0

�2�Yt�i þXk�1

i¼0

�3�Pt�i

þXk�1

i¼0

�4�Vt�i þ �5ECt�1 þ �6D86t þ et ð5Þ

where all the coefficients retain their prior meaningsand expected signs as previously discussed inEquation 1; ECt�1 is the lagged error correctionterm and it is the residual generated from thecointegrating Equation in 1, and et is a white noiseerror term.

The VECM shows how the system converges to thelong-run equilibrium implied by the cointegratingEquation 1. The coefficient on the lagged errorcorrection term (ECt�1) represents the response of thedependent variable in each period to departure fromequilibrium. A crucial question concerning theVECM is what the optimal lag on the right-handside variables should be. A popular technique isHendry’s (1987) ‘general-to-specific’ methodology,which proceeds by eliminating all insignificant lags.Accordingly, we initially estimated a VECM withfour lagged differences of the key explanatoryvariables (real foreign income, relative prices, andvolatility), a constant, one error correction termand a (0, 1) dummy variable. The dimensions ofthe parameter space were then reduced to afinal parsimonious VECM specification usingsequential F-tests to exclude the statisticallyinsignificant lags.

The estimated coefficients, SEs and t-values for thereduced VECM are reported in the upper panel ofTable 4. The signs of all estimated coefficients areas expected. A statistically significant negativecoefficient is obtained on the error-correction term.The absolute value of the coefficient of theerror-correction term indicates that 34% of thedisequilibrium in the real exports demand is offsetby short-run adjustment in each quarter.More importantly, the statistically significanterror-correction term confirms that a long-run coin-tegration relationship exists between real exports, realforeign income, relative prices and exchange ratevolatility. This finding suggests that overlooking thecointegrating relationship among the variables wouldhave introduced misspecification in the underlyingdynamic structure.

The results in Table 4 also show that real exportsdemand is positively related to real foreign incomeand negatively related to relative export prices.The positive and statistically significant coefficient

Table 2. Augmented Dickey–Fuller Statistics for testing forunit roots

Variables Level First difference

X �2.066 �4.417*Y �1.010 �2.701***P �0.469 �2.952**ER 0.484 �3.973*V �0.874 �4.041*

Notes: *, **, and *** indicate statistical significance at the1, 5 and 10% levels respectively. The McKinnon (1991)Critical values at 1, 5 and 10% are: �3.534, �2.906and �2.590.

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on the dummy variable (D86) suggests that theeconomic reforms and liberalization policies adoptedin the post-1986 period contributed to boostingexport growth. In addition, a statistically significantnegative coefficient is obtained on the real exchangerate volatility. This suggests that the volatility of thereal exchange rate has significant and adverse effectson Nigeria’s export trade with the United States.This result can be further generalized to argue thatrisk-averse market participant react to exchange rate

volatility by favoring domestic trade over foreigntrade. This result also confirms the earlier findingsreported in Arize et al. (2000), Bahmani-Oskooee(2002), De Grauwe and Skudelny (2000) andChowdury (1993) both for developed and developingcountries. To summarize, the estimates of theshort-run dynamics of the VECM indicate thatexchange rate volatility has a significant short-runnegative effect on export demand, in addition to itslong-run adverse effect.

Table 3. Johansen’s cointegration test for the series: X,Y,P,V and D86

Hypothesized no. of CE(s) Eigen value Likelihood ratio 5% critical value 1% critical value

PANEL ANone* 0.3490 72.86 68.52 76.07At most 1 0.1941 36.80 47.21 54.46At most 2 0.1299 18.67 29.68 35.65At most 3 0.0530 6.98 15.41 20.04At most 4 0.0282 2.40 3.76 6.65

PANEL BNormalized cointegrating coefficients:

Xt ¼ �22:726ð1:436Þ

þ 3:274Ytð0:348Þ

� 1:163Ptð5:991Þ

� 17:195Vtð0:587Þ

þ1:916D86

Notes: * denotes rejection of the hypothesis at the 5% significance level. The numbers in parentheses beneath the estimatedcoefficients are the SE.

Table 4. Regression results of the error-correction model

Variable Coefficient SE t-Statistics

ECt�1 �0.340 0.061 �5.573�Xt�1 �0.305 0.132 �2.316�Yt�1 4.028 1.833 2.197�Pt�1 �0.574 0.185 �3.094�Pt�3 �0.241 0.083 �2.904�Vt �8.320 3.079 �2.702�Xt�2 �3.040 1.014 �3.001D86t 0.627 0.271 2.310

Summary and diagnostic statisticsAdj. R2 0.677SSR 3.304 Probability

NormalityJarque–Bera �2 (2) 0.485 0.635

Serial CorrelationBreusch–Godfrey serial F-statistics 0.797 0.642LM (AR-4) �2-statistics 1.533 0.441

AR cond. heteroskedasticityARCH LM test F-statistics 2.208 0.148

�2-statistics 2.410 0.129HeteroskedasticityWhite heteroskedasticity test F-statistics 2.442 0.175

�2-statistics 12.243 0.721StabilityChow breakpoint test: 1994:2 F-statistics 1.072 0.369

�2-statistics 17.243 0.631Specification errorRamsey RESET test F-statistics 1.490 0.266

�2-statistics 1.984 0.162

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The results of the various diagnostic tests carriedout on the error-correction model of real exportsdemand are reported in the lower panel of Table 4.The coefficient of determination (Adjusted R2) thatmeasures the goodness-of-fitness of the model showsthat about 68% of variations in real exports demandare explained by the fundamentals. This suggests thatthe model fits the data well. The normality test(Jarque–Bera test statistic) accepts the residualnormality. The Lagrange Multiplier (LM) test ofno autocorrelation against fourth-order residualautocorrelation is accepted. The computed Whitetest statistic is less than the critical value, thus, thenull hypothesis of homoskedasticity of the residualscannot be rejected. The Ramsey RESET results revealthat the calculated F-value is less than the criticalvalue and therefore, there is no specification error inthe model. Furthermore, the results of the Chowbreakpoint test suggest that the estimated parametersof the model are stable and therefore there is nostructural break. Our finding that the export demandfunction is stable over the period of estimationssuggests that the elasticities can be considered stableenough for policy simulation and forecasting.

V. Conclusion

This study investigated the impact of exchange-ratevolatility on Nigeria’s exports to the United Statewithin a cointegration and vector error-correctionframework using quarterly data for period 1980 to2001. The results of the cointegration analysis revealthat there exists a long-run equilibrium relationshipamong the variables of the real exports demandfunction. The results of the long run parameterestimates are consistent with economic theory.Increase in the real foreign income has a significantlypositive impact on real exports demand; improve-ment in the terms of trade (declines in the realexchange rate) was found to encourage exports, whileincreased exchange rate volatility was found toadversely affect exports demand. In addition,the liberalization and economic reform policiesimplemented in the post-1986 period were found tohave contributed significantly to increasing thedemand for Nigeria’s exports. The short-runestimates of the vector error correction modelcorroborate the results of the long-run parameterestimates.

From the empirical findings in this article, one cansafely conclude that export activities in Nigeria can beimproved further if the government employs (a)policies with the aim to maintain a stable competitive

real exchange rate, and (b) prudent macroeconomicpolicies that avoid overvaluation of the real exchangerate and enhance export competitiveness withthe incentives for export diversification. Therefore,the policymakers should establish a transparentexchange rate system under which the stability ofthe real exchange rate is achieved and maintained,and they should incorporate ‘getting the realexchange rate right’ as part of the overall trade andeconomic growth strategy.

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