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Exchange Rate Variability and Non-Oil Exports in Nigeria:

I J M T P : 7(1-2) January-December 2015 17

EXCHANGE RATE VARIABILITY ANDNON-OIL EXPORTS IN NIGERIA:

EMPIRICAL EVIDENCE

H. E. OaikhenanDepartment of Economics and Statistics, University of Benin, Benin City,

Nigeria, (Corresponding Author: E-mail: [email protected])

G. A. NwokoyeDepartment of Banking & Finance, University of Benin,

Benin City, Nigeria

Abstract: The paper examines empirically the impact of exchange ratevariability, captured as exchange rate depreciation and exchange rateinstability, on non-oil exports in Nigeria over the 1975 to 2005 sampleperiod. The study finds that exchange rate instability has a significantnegative effect on non-oil exports in Nigeria. Exchange ratedepreciation affects it positively but in an insignificant way. The resultssuggest that efforts at boosting the country’s non-oil exports may bemore successful if efforts are made at arresting the problem of instabilityin exchange rate rather than promoting its depreciation.

Keywords: Exchange Rate, Variability, Non-oil Exports.

1. INTRODUCTION

Exchange rate is the number of units of a particular currency thatmay be exchanged for one unit of another currency. It is a veryimportant price in every economy owing to its significance in thedetermination of relative prices of domestic and foreign goods andservices.

Exchange rate changes have been a topical and highly debatedissue among academicians, policy makers, and concerned monetaryauthorities, on account of the vital role an optimal and sustainableexchange rate plays in the achievement of sustainable growth and

H. E. Oaikhenan & G. A. Nwokoye

18 I J M T P : 7(1-2) January-December 2015

development. Arising from this realization, government andmonetary authorities in Nigeria, over the years, have made severalattempts at finding an appropriate exchange rate managementstrategy. For about four decades now, exchange rate arrangementsin Nigeria have undergone significant changes. It shifted from afixed regime in the 1960s to a pegged arrangement between the 1970sand the mid-1980s, and finally to the variant floating regime since1986, consequent upon the adoption and implementation of thestructural adjustment programme (SAP).

According to Iyoha and Unugbro (2002), under SAP, a marketdetermined exchange rate was adopted as a means of eliminatingthe overvaluation of the naira and allocating scarce foreign exchangeresources. However, the continuous fluctuations in the exchangerate with a positive bias towards depreciation has led to an opposingview that the naira as it currently stands may actually be sufferingfrom undervaluation rather than overvaluation. Obadan (2006)corroborates this view in his observation that “with the introductionof the market-based exchange rate system in 1986, the naira exchangerate has exhibited the features of continuous instability, for most ofthe period, reflecting unidirectional depreciation in the official,bureau de change, and parallel market for foreign exchange”.

A priori reasoning considers this variability in exchange rate asdetrimental to overall economic stability (Iyoha and Unugbro, 2002).

The Nigerian economy is mono-product, and heavily importdependent. The high import-dependence in turn leads to a heavypublic and private demand for hard currencies, which often exceedsthe amount of such currencies the country is able to earn from itsmajor export commodity, crude oil.

The existence and persistence of such demand-supply gapultimately drives up the cost of the foreign currency relative to thenaira, thereby leading to changes in exchange rate. Exchange ratechanges have serious implications for macroeconomic objectives.An example of such implications was aptly given by Iyoha (2003)who noted that “a 10% depreciation of the domestic currency



(also called 10% devaluation) is equivalent to a simultaneous 10%increase in import tariffs and a 10% rise in export subsidies”. Theinference from the above is that exchange rate depreciation isexpected to reduce imports and increase exports. But whether thisargument holds true for Nigeria’s non-oil exports remains an issueto be resolved empirically.

A study by Adubi and Okunmadewa (1999) shows that prior tothe policy reforms that came in the wake of the StructuralAdjustment Programme (SAP) in 1986, agricultural commoditiesdominated the export list of the country from 1960 until the early1970s. However, a cursory look will reveal that as at today, the exportlist contains mainly crude oil and few agricultural produce such ascocoa, and rubber.

Given the foregoing background, this study seeks to verify,empirically, the response of Nigeria’s non-oil exports to such changesor variability in exchange rate. The need to conduct an empiricalverification stems from the desire to contribute quantitatively to thegrowing literature on exchange rate variability as it affects non-oilexports. Accordingly, the rest of the study is organized as follows:Section 2 examines the existing literature on exchange rate system,exchange rate variability, and non-oil exports. Section 3 presentsthe empirical model and the econometric methodology that will beemployed in verifying the effect of exchange rate variability onnon-oil exports in Nigeria. Section 4 contains the discussion of theempirical results. Finally, section 5 provides a summary of the majorfindings, the suggested recommendations and conclusion.

2. SURVEY OF RELATED LITERATURE

Existing empirical works on the relationship between exchange rateand exports appear to concentrate on the causal effect of exchangerate volatility or risk on export. For example, Yol and Baharumshah(2005), employing the techniques of co integration and vectorerror-correction model, investigated the effects of exchange ratechanges on the bilateral trade balance in North Africa-Egypt,



Morocco and Tunisia-vis-à-vis the US and Japan. Their result showsthat in all cases, real exchange rate impacts positively andsignificantly on trade, except in the case of Egypt/US. Theinsignificance of the coefficient of real exchange rate in the case ofEgypt/US was attributed to the shrinking trade between Egypt,which is a non-oil exporting nation, and the U.S.A.

Arize et al (2005) studied empirically the impact of real exchangerate volatility on the export flows of Latin America, using cointegration and ECM technique. Their results show that there is asignificant negative long-run relationship between export flows andexchange rate volatility in each of the Latin American countries inthe sample.

Fang and Miller (2004) tested the effects of exchange ratedepreciation on exports of Singapore using a bivariate GARCH-Mmodel. Evidence from their result shows that depreciation does notsignificantly improve exports but the exchange rate risk significantlyimpedes exports.

Employing panel data analysis, Cho et al (2003) obtainedempirical results showing that overvaluation (undervaluation) ofthe nominal exchange rate negatively (positively) affects theperformance of agricultural exports to a large extent. Prasad (2000)in his study of the determinants of exports in Fiji concluded amongothers that in the long run, trading partner’s income largely drivesmovements in Fiji’s exports. In the short run, however, exports aremainly influenced by changes in weather conditions, relative priceand foreign demand. Maskus (1986) found that agriculture,compared with manufactured goods trade is more responsive toexchange rate changes because according to him, (a) agriculturaltrade is relatively open to international trade, and (b) agricultureexhibit a low level of industrial concentration.

Known empirical works on non-oil exports in particular, andexports in general, in Nigeria, include Okoh (2004), Olaniyan (2004),Iyoha (2002), Jimoh (1989), and Adubi and Okunmadewa (1999).



Okoh (2004) in analyzing the effect of global integration ongrowth of Nigeria’s non-oil exports used a vector error-correctionmodel. She found out that growth in GDP and world income,(and not global integration) are significant in explaining growth ofnon-oil exports in the long-run and short-run, respectively.

Olaniyan’s (2004) results indicate that non-oil exportsperformance is significantly influenced by its lag, gross domesticinvestment, and lag of foreign partner’s income in the long-run.While the influence of relative price, domestic sales among otherfactors are relatively insignificant.

Adubi and Okunmadewa (1999) using an extended vectorautoregressive (EVAR) model, tested empirically the relationshipbetween price, exchange rate volatility and Nigeria’s agriculturaltrade flows. Their conclusion was that exchange rate volatility has anegative effect on agricultural exports. Thus, the more volatile theexchange rate changes, the lower the income earning of farmerswhich subsequently also lead to a decline in output production andhence reduction in exports trade.

Iyoha’s (2002) result indicates that agricultural exports andthe deflator for agricultural output satisfactorily explain Nigeria’snon-oil exports.

Jimoh (1989) used a small-sized macroeconomic model forNigeria to simulate the effects of the alternative exchange ratepolicies on the Nigerian economy and its external sector in particular.The study shows that exports of non-oil product is negativelyaffected by the 1973 oil shock dummy but positively affected byforeign income and the ratio of government expenditure to GDPdeflator.

2.1. Determinants of Exchange Rate Variability

Variability in exchange rate has been a subject of concern since 1920s.The interest deepened in 1970s following the collapse of the BrettonWoods system of fixed exchange rate. Sharing this view is Krugman1



who posits that “many analyst of international economics concurthat the generalized floating of system in operation since the postBretton Woods period have engendered substantial volatility in bothdeveloped and developing economies”. The earliest belief was thatexchange rate variability was caused by speculative activities. Nurtse(1942)2 was one proponent of this view. According to him, currencymarkets were subject to “destabilizing speculation” which createdpointless and economically damaging fluctuations. Milton Friedmanrefuted this view in his 1953 seminal paper in which he argued thatunstable exchange rates in the 1920s were caused by unstablepolicies, not by destabilizing speculation. According to Friedman,profit-maximizing speculators would always tend to stabilize, notdestabilize, the exchange rate. Friedman’s view was corroboratedby Dornbusch (1976) who argued that “even without destabilizingspeculations, exchange rates will be highly variable because of thephenomenon called overshooting”. In the 1990s, however, a numberof other elements influencing exchange rate variability have beenidentified. Engel and Hakkio (1993) blamed the instability inexchange rate on volatility in market fundamentals, changes inexpectation due to new information, and speculative bandwagon.While the relationship between money supply and exchange rate isexpected to be direct, the relationship between interest rate changesand variability of exchange rate is usually inverse (Engel and Hakkio,1993, Osler, 1994).

In Nigeria, Ahmad and Zarma (1997), Obadan (2006), andOlisadebe (1991) provided evidence of exchange rates variability.Specifically, Ahmad and Zarma (1997) argued that “the deregulationof the foreign exchange market in the face of serious supplyconstraints and government interference caused serious fluctuationin the exchange rate for the naira”. In corroborating this position,Obadan (2006) observed that “with the introduction of the market-based exchange rate system in 1986, the naira exchange rate hasexhibited the features of continuous instability…”. Olisadebe (1991)blamed the instability of the naira exchange rate on the continuousexistence of parallel markets in the country.



2.2. Macroeconomic Policy and Non-Oil Exports

In the early 1960s in Nigeria, exchange rate policy had almost nosignificance in economic management (Adubi and Okunmadewa,1999). The period between 1960 and the mid-1980 however,witnessed a host of policies among which are the fixed parity and,the peg arrangements. The adoption of the SAP in 1986 brought inits wake a market-determined exchange rate regime. This createdinstability in the exchange rates (Obadan, 2006, Ahmad and Zarma,1997, Olisadebe, 1991). In the quest for the stability of the exchangerate, the Nigerian monetary authorities have made variousmodifications to the institutional framework. These modificationssaw the Second-Tier Foreign Exchange Market (SFEM) adopted in1986. The SFEM metamorphosed progressively into the AutonomousForeign Exchange Market (AFEM), Dutch Auction System (DAS),Inter-bank Foreign Exchange Market (IFEM), and lately, to theWholesale Dutch Auction System (WDAS). A lot have been writtenon the operations of these institutions {see for example, Obadan(1993, 2006), Sanni (2006), Odusola (2006)}. However, the stringrunning through them is that each was introduced with the hope offinding viability as well as arresting the problem of instability inthe Naira exchange rate.

Instability or variability in exchange rate is believed to haveadverse effect on key sectors of the economy, the non-oil exportsector inclusive. Nigeria’s non-oil exports, which comprisedagricultural produce, manufactured exports, and solid mineral, havea lot of potential for poverty reduction and employment generation(Ebong, 2004). With respect to policy, in the 1960s and 1970s,manufactured non-oil exports grew under high protective fiscalbarriers (Adubi and Okunmadewa, 1999). Within the same period(i.e. 1960s), agricultural policy was limited to marketing and pricingcarried out by marketing boards (Osamwonyi and Ogurin 2003).With the adoption of SAP in 1986, and its resultant liberal foreignexchange allocation regime, the expectation was the non-oilexporters would take advantage of the system and thus increasethe share of non-oil exports in total exports. A careful observation



would reveal that such expectations never materialized. In fact, Iyoha(2002) noted that while manufacturing accounted for 8.4% of GDPin 1980, this share dropped to 5.2% in 1989, with an average of 8.2%for the decade. In this connection, Okoh (2004) ascribed theunsustainable growth in manufactured non-oil exports to a host offactors, including the increasing cost arising from market determinedexchange and interest rates.

What immediately becomes clear from the foregoing survey ofrelated literature is that the impact of exchange rate variability onNigeria’s non-oil exports has not received adequate empiricalattention. It is of interest to note that the prerequisite for success inthe design and implementation of policies that are aimed atpromoting non-oil exports lies in proper understanding of the factorsaffecting activities in the sector. And this is all the more so, if suchunderstanding is obtained from an empirical investigation. Ourobjective in this paper is to attempt a contribution towards fillingthis felt gap in the literature, given numerous policy pronouncementson the need to diversify the country’s economy away from relianceon a single export commodity, crude oil.

3. MODEL SPECIFICATION

According to Prasad (2000), the standard approach for specifyingand estimating foreign trade equation is the imperfect substitutionmodel in which the key assumption is that exports are not perfectsubstitutes for domestic goods in the importing countries. Thus, themodel used in majority of the studies on export demand is of thefollowing functional form:

nx = f (rp, y) (1)

Where: nx = Export demand

rp = Relative prices

y = Foreign income

Studies done in Nigeria3, however, reveal that Nigeria’s non-oilexports are influenced by other demand-side as well as supply-side



variables. Expression (1) may thus be modified and expanded toinclude these variables as follows:

xno = f (exrv, fy, ago, gdp, pxag) (2)

Taking an empirical version of expression (2) we obtain thefollowing;

xno = 0 + 1exrv + 2fy + 3ago + 4 gdp + 5 pxag +e (3)

Where, xno = value of non-oil exports

exrv = exchange rate variability

fy = foreign income, proxied by the gdp of the u.s.

ago = agricultural output

gdp = gross domestic product

pxag = agricultural export prices

e = stochastic error term assumed to satisfy the usualproperties of zero mean, unit variance and zerocovariance.

0, 1, 2… 5 = parameters to be estimated.

The presumptive signs of the parameters in the specification arethat, 1><0 while 2, 3, 4, and 5 >0.

The presumptive sign of the exchange rate variability variablecan be explained by the theoretical proposition that exchange ratevariability can be beneficial or detrimental to all categories of exports,non-oil exports inclusive.

In theory, exchange rate variability that manifest by way of adepreciation is supposed to be beneficial to exports. The reasoninghere is that a depreciation in a country’s exchange rate, expectedly,should make exports cheaper to foreigner. This is expected, ceterisparibus to engender a rise in the demand for non-oil exports. Andthis was one of the policy objectives of the market driven exchangerate management strategy that was adopted with the introductionof the Structural Adjustment Programme (SAP) in 1986.



On the other hand, exchange rate variability that manifest byway of exchange rate instability is expected to affect adversely thedemand for the country’s non-oil exports, by virtue of its destabilizingeffects on projections, which is inimical to planning by economicagents, the consumers of the country’s non-oil export goodsinclusive.

3.1. Variable Definition, Estimation Techniques and Data Sources

We used two alternative measures of exchange rate variability inthe specification represented by equation 2 above. The first measureused was exchange rate depreciation. This was obtained by takingthe successive changes in the exchange rate series. A positive changeimplies a depreciation of the local currency in terms of the foreigncurrency. A negative difference on the other hand, implies anappreciation of the local currency relative to the foreign currency.

The other measure of exchange rate variability we used in theestimation of the model is the instability in the exchange rate series.To obtain this, we fitted the series to a trend variable over the sampleperiod and thereafter obtained the deviation from the trend as ourmeasure of exchange rate instability. In all cases, we used theexchange rate of the naira to the US dollar, in view of the fact that asignificant proportion of Nigeria’s international economictransaction is denominated in the US dollar.

We utilized the OLS regression technique in the estimation ofthe empirical model represented by equation 2 above, using theMFIT 4.1 computer software package (Pesaran and Pesaran, 1997).

Data used in the estimation of the model were obtained fromvarious secondary sources, including such publications of the CBNas the Annual Report and Statement of Accounts, CBN StatisticalBulletin as well as relevant publications of the National Bureau ofStatistics (NBS), the Bureau of Economic Analysis (BEA), andrelevant publications of the Federal Ministry of Agriculture. Theempirical results obtained are reported in Table 1 and 2 below andanalysed thereafter.



4. EMPIRICAL RESULTS

An analysis of the empirical results that are contained in Table 1shows that exchange rate depreciation, as expected, impactedpositively on the country’s non-oil exports over the period cover bythe study. A depreciation in the exchange rate is expected, in theoryto impact positively on non-oil exports via its effects on the demandfor and supply of non-oil export goods. On the demand side,depreciation in exchange rate is expected to make export goodscheaper for foreign consumers, thus encouraging them to demandmore of such goods. On the supply side, a depreciation of the localcurrency is expected to increase the local currency equivalent of theearnings of domestic suppliers of non-oil exportables, thusencouraging them to supply more of such goods.

Table 1OLS Regression of Non-Oil Exports on its Determinants

xnoDependent Variable

Explanatory Coefficients t-values Level of significanceVariables (p-value)

Constant 8036.2 0.2947 0.771

exrdpr 131.5050 0.6750 0.506

fy -8.0333 -1.6170 0.118

ago 2.4409* 2.7469 0.011

gdp 0.0050* 2.8841 0.008

pxag 8.0663* 5.3475 0.000

Other diagnostic statisticsR² = 0.95 R¯² = 0.93 F(7,21) = 55.4 D.W = 1.899

Note: *implies statistical significance at 1% level.

The empirical evidence obtained in the case of this variableaccords with the observed situation in the Nigerian economy, asevidenced by the remarkable upswing in non-oil exports that camein the wake of the phenomenal depreciation of the local currency,the naira with the adoption of the SAP in 1986. Obadan (2005)observed in this connection that:



the euphoria of high naira prices of agricultural products, coupled withthe liberalization of export trade and export incentives that were put inplace with the introduction of SAP led to the emergence of all sorts ofexporters with different motives scrambling to partake in the foreignexchange earnings from export

The exchange rate depreciation variable, however, failed the testof statistical significance at all levels, indicating that although itaffected non-oil exports positively, its impact was insignificant. Theinsignificant impact also accords with the existing body of empiricalevidence. For example, Fang and Miller (2004) obtained empiricalresults showing that exchange rate depreciation does notsignificantly affect Singaporean non-oil exports, which are mainlyof the non-oil variety.

The foreign income variable was negatively signed, contrary toexpectation. The perverse sign of the coefficient estimate may beascribed to the development of synthetics as alternatives to suchnatural products as rubber, cocoa, and palm kernel, which areimportant and significant components of Nigeria’s non-oil exports.The implication of this, if true, is that even when foreign income

Table 2

OLS Regression of Non-Oil Exports on its Determinants

xnoDependent Variable

Explanatory Coefficients t-values Level of significanceVariable (p-value)

constant 55.598 0.3192 0.752exrinstb -15.4488* -1.3807 0.181fy -7.3459** -2.2195 0.037ago 2.4344*** 2.7879 0.010gdp 0.0061*** 3.4053 0.002pxag 7.6749*** 4.1928 0.000

Other diagnostic statisticsR² = 0.95; R–² = 0.93; F(7, 19) = 51.1460; D.W. = 1.98

Note: *, **, *** implies statistical significance at 10%, 5% and 1% levels,, 1% level,respectively.



rises, the demand for the country’s non-oil exports by foreignersmay actually fall. The variable in addition, failed the significancetest at all levels, implying that while it cannot be a policy relevantvariable, it is indeed not relevant to policy formulation regardingthe promotion of the country’s non-oil exports.

The empirical evidence obtained in the case of agriculturaloutput variable accord with the theoretical expectation sinceagricultural produce constitute a significant share of non-oil exportsfrom the country. Thus, the country’s non-oil exports increases withincreases in the agricultural output. This variable interestinglypassed the test of statistical significance at all levels, an indicationthat growth in agricultural output impacts significantly on thecountry’s non-oil exports.

The findings with respect to level of domestic economic activity(GDP) variable were also satisfactory in terms of sign and statisticalsignificance. The coefficient estimate was positively signed asexpected; an indication that increases in the level of economic activitytranslates to increases in the capacity to supply non-oil export goods.The low magnitude of the coefficient estimate, however, suggeststhat the impact of an increasing level of domestic economic activityon non-oil export growth is negligible, although statisticallysignificant. The significant nature of this variable suggests thatconcerted efforts should be deployed to the production of non-oilexports goods within the total framework of the production of goodsand services in the domestic economy.

The price of agricultural export variable exhibited a positivelysigned and statistically significant coefficient estimate. The positivesign accords with a priori expectation and it indicates that a rise inthe price of non-oil export goods elicits increases in the supply ofnon-oil export goods, a plausible finding, since suppliers of thesegoods would strive to increase supply so as to take advantage ofthe high and perhaps, rising prices of non-oil exportables.

The summary statistics in Table 1 were satisfactory and theyattest to the robustness of the estimated model. For example, we



were able to account for up to 93% of the systematic variations inthe dependent variable with the explanatory variables in thespecification. This represents a good fit. In addition, the modelpassed the test of overall significance as can be seen from theF statistic value of 55.41, which was significantly greater than thetheoretical F statistic. And the value of the DW statistic obtainedshowed that the problem of serial correlation was not serious enoughto undermine the results of the estimated model.

In estimating equation 2 above, we utilized exchange rateinstability (as measured) in place of exchange rate depreciationretaining, however, all the other explanatory variables.

The results obtained this time closely mirrored those that arereported as Table 1. Here, however, the empirical evidence indicatesthat exchange rate instability impacts adversely, as expected, onnon-oil exports. It, however, passed the test of statistical significanceat the 10% level. What the sign and statistical significance of thisvariable suggest is that exchange rate instability can result in asignificant reduction in Nigeria’s non-oil exports. And this is to beexpected, since wide swings and volatility in exchange rate isharmful to planning and projections by economic agents, consumersof the country’s non-oil exports inclusive. In addition, suppliers ofnon-oil exportables find it difficult to project their earnings in theface of wide swings and volatility in exchange rate, thus, inhibitingtheir drive to produce and supply more.

The coefficient of foreign income was again negatively signed.It was, however, statistically significant at the 5% level.

The empirical evidence obtained in the case of agriculturaloutput, Gross Domestic activities, and prices of agricultural exportsare consistent with those reported in Table 1. The agriculturaloutput variable appeared with a positively signed coefficientestimate, in consonance with theoretical expectation that non-oilexports stand to increase with increases in the level of agriculturaloutput. In addition, the variable was statistically significant at alllevels.



Thus, it can be concluded on the basis of the empirical evidenceobtained in our study that agricultural output acts as an importantstimulant to non-oil exports in Nigeria.

The level of economic activity (GDP) variable, as well as theprice of agricultural exports variable, have positively signedcoefficient estimates in accordance with theoretical expectation. Thevariables also passed the test of significance at all levels.

The diagnostic statistics obtained lend credence to the robustnessof the estimated model. For instance, the R–2 shows that we wereable to account for about 93% of the systematic variations in thedependent variable with the set of explanatory variables in thespecification. This indicates a good fit. In addition, the F-statisticvalue of 51.15 shows that the overall model is significantly differentfrom zero. And the value of the DW statistic obtained points to theabsence of any serious serial correlation problem in the estimatedmodel.

5. SUMMARY, RECOMMENDATIONS, AND CONCLUSION

In this paper we conducted an empirical verification of the impactof exchange rate variability on Nigeria’s non-oil exports. In addition,we admitted four other explanatory variables thought relevant toexplaining the behaviour of the country’s non-oil exports. Data usedcovered the 1975-2005 sample period.

The major findings in the study include:

(a) Exchange rate depreciation has a positive effect on Nigeria’snon-oil exports. Its impact is, however, not significant.

(b) Exchange rate instability affects the country’s non-oil exportin a significantly negative way.

(c) A rise in the income of the foreign consumers of thecountry’s non-oil exports causes a reduction in the demandfor the country’s non-oil exports. This situation may be dueto non-standardization and perhaps poor packaging of mostNigeria’s non-oil exports. This may have put them in the



class of inferior goods (or exports) relative to competitivesupplies from other countries.

(d) Agricultural sector output impacts positively andsignificantly on the country’s non-oil exports.

(e) The impact of domestic production on non-oil exports fromthe country is positive and significant.

(f) Agricultural export prices affect non-oil exports fromNigeria in a positive and very significant way.

5.1. Recommendations

The empirical results indicate the need to ensure a stable exchangerate regime rather than promoting exchange depreciation as astrategy to boost non-oil exports. Indeed, this remains an absoluteimperative that should be considered by policy makers, if theobjective is to elicit broader and strong non-oil export performance.In addition to the foregoing, there is the need to re-evaluate theexisting policy framework and incentives that are aimed at boostingagricultural production in the country, having regard to the factthat agricultural output remains the most significant of the threemajor components of the country’s non-oil exports.

Finally, concerted effort should be deployed to the productionof non-oil export goods within the total framework of the productionof goods and services in the domestic economy, since successfullyarresting such indicators of macroeconomic instability as unstableexchange rate, high and rising inflation rates, erratic and low powersupply, etc, will ultimately raise the country’s capacity to produceand export non-oil goods.

5.2. Conclusion

In concluding this study, we note that it is important on the part ofpolicy makers to articulate policy measures that are capable ofmitigating the wide swings and volatility that has characterized thecountry’s exchange rate, especially since the adoption of SAP in 1986,



in view of its severely detrimental impact on the country’s non-oilexports.

We are grateful to Dr. R.I. .Udegbunam of the Department ofEconomics and Statistics and two other anonymous referees for theirhelpful comments on an earlier draft. The usual caveat, however,applies.

NOTES

1. See Krugman. P. (www.ecolib.org)

2. Detail of this discussion can be obtained from “Exchange Rate” by Krugman. P.

3. See the reviewed empirical work.

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