Koray sample period using panel data. The variables

Koray and Lastrapes (1989) studiedexchange rate volatility and US multilateral trade flows in the context of aVector Auto-Regressive model. The model is estimated for US multilateral tradeover the current floating period (1973-1987) and includes a moving standarddeviation measure of real exchange rate volatility. Eight US variables areincluded in the VAR system – the narrow money supply M1(M), 3-Month treasurybill rate (R), industrial production index (Y), consumer price index (P), realmultilateral exchange rate (Z), real multilateral exports (X), realmultilateral imports (I), and a measure of real exchange rate volatility (V).They argued that exchange rate volatility had no effect on international tradeespecially on export performance.

 Chowdhury (1993) in his study ‘Doesexchange rate volatility depress trade flows? Evidence from Error CorrectionModels’ examined the impact of exchange rate volatility on the trade flows ofthe G-7 countries over the 1973-1990 sample period using panel data. Thevariables employed by him include; real export volume (Xt), relative price(Pt), real foreign economic activity (Yt) and the measure of exchange ratevolatility (Vt). His result indicated that the exchange rate volatility has anegative impact on the volume of exports in each of the G-7 countries. Taglioni (2002) carried out a studyon exchange rate volatility as a barrier to trade. He covered the 12 europeanunion countries before 1995 enlargement.

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He adopted the ‘gravity model’ withborder effect and also employed panel data as his estimating technique. Heemployed disaggregation of data using 3-digit industrial specific bilateral tradecovering the period 1976-1995. His variables include; Bilateral imports(3-digit industry level), production (3-digit industry level), prices, distancefrom Head and Mayer (2000). His result drawing from the border effectestimations carried out in a multi-country multi-currency context revealed astrongly negative influence of volatility on trade. Drawing from the studies carried outby Baum and Caglayan (2009), they studied the volatility of international tradeflows and exchange rate uncertainty.

Their data covered the period (1980-2006).Variables used by them include; measures of foreign GDP, real exchange rate andtrade flow. They implemented a bivariate GARCH-in-mean (GARCH-M) system for thereal exchange rate and the volume of trade flow data to estimate the volatilitymeasures. Their data set contains information on bilateral trade flows for bothindustrialized and newly industrialized countries and the eurozone countriesover the period 1980 – 2006. Their result showed that exchange rate uncertaintyhas a consistent positive and significant effect on the volatility of bilateraltrade flows. A one standard deviation in exchange trade uncertainty leads to an8 percent increase in trade volatility. These effects differ markedly for tradeflows between industrialized countries and non-industrialised countries (NICs)and are not mitigated by the presence of the Eurozone.

Their result alsosuggested that exchange rate uncertainty does not affect the volume of tradeflows of either industrialized countries or Non-industrialized countries (NICs). In the Nigerian context, Ngene (2010)researched on exchange rate fluctuations and trade flows in Nigeria: Atime-series econometric model for the period 1980 to 2008, usingthe General Auto-Regressive Conditional Heteroscedasticity (GARCH) modelling,Mundell-Fleming model, multivariate johansen cointegration test, vector errorcorrection mechanism, and complemented by variance decomposition and impulse responseanalysis. The following variables were employed; trade flows (oil and non-oilexports plus imports) at time t (Xt), domestic income at time t (Ydt), foreignincome at time t (Yft), bilateral exchange rate at time t (Ext) and exchangerate fluctuations at time t (Wt).

Her result revealed that exchange ratefluctuations are found to have a negative and significant effect on Nigeria’strade with the US. Omojimite and Akpokodje (2010) carriedout a study on ‘A comparative analysis of the effect of exchange ratevolatility on exports in the Communaute Financiere Africaine (CFA) and Non-CFAcountries of Africa’. Pooled time series data were collected for 1986 – 2006,covering the flexible exchange rate period. Exchange rate volatility serieswere generated utilizing the GARCH model. These series were then incorporatedinto an export equation with export, foreign income, exchange rate volatility,imports and real exchange rate, and estimated using the Ordinary Least Square(OLS), fixed effect, first difference Generalized Method of Moment and systemsGMM equation techniques. The results reveal that the system Generalized Methodof Moment (GMM) technique performed better than the other estimationtechniques.

Exchange rate volatility was found to negatively impinge on theexports of both panels of countries. However, exchange rate volatility has alarger effect on the panel of the non-CFA countries than on the CFA. Furthermore, Ojebiyiand Wilson (2011) studied ‘Exchange rate volatility: an analysis of therelationship between the Nigerian naira oil prices, and US dollar using monthlydata from 1999 to 2009’. The research employed the fundamental variables whichwere assumed to be month spot crude oil price, monthly average exchange rate ofNigerian naira and monthly average exchange rate of United States dollar. Theempirical result adopted the Ordinary Least Square (OLS) using regressionanalysis and also the correlation model which shows that there is aweak/negative relationship between exchange rate and oil price as there areother factors that brings about changes in oil price other than the exchangerate such as; cartel oil pricing and oil speculators. Danmola (2011)analysed the ‘Impact of exchange rate volatility on the macroeconomic variablesin Nigeria.

The period covered ranged from 1980 to 2010. His variables includedGross Domestic Product (GDP), inflows of Foreign Direct Investment (FDI), TradeOpenness (TO), inflation (INF) and Exchange Rate Volatility (EXRV). Adoptingcorrelation matrix, Ordinary Least Square (OLS) and Granger Causality test, thefindings of the study shows that exchange rate volatility has a positive effecton GDP, FDI, and TO but has a negative effect on the inflation rate in thecountry. Similarly, Dicksonand Andrew (2013) studied ‘Exchange rate volatility effect on trade variationsin Nigeria.’ Their data set covered the period 1970 – 2010. They employednominal import/export deflated by consumer price index (Mt and Xt), exchangerate volatility (EXV), oil price in domestic currency, (OPN) and externalreserve (RES) as variables.

Using the Ordinary Least Square (OLS), their resultrevealed that exchange rate volatility is insignificant in explainingvariations in imports but significant and positive with respect to