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rate volatility, and countries considered (developed versus developing).2More recently Baum, Caglayan and Ozkan
(2004) rely on a nonlinear specification rather than linear alternatives while integrating the
role of foreign income uncertainty in evaluating the impact of exchange rate uncertainty
on trade flows. Although their findings for developed countries are mixed, a subsequent
analysis by
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Grier and Smallwood (2006)
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using a group of developed and developing countries finds a significant role in developing countries’ exports for exchange rate uncertainty
as well as a strong role for income uncertainty in most countries.
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In contrast to these studies, this paper presents an empirical investigation motivated
by the theoretical findings of Barkoulas, Baum and Caglayan (2002) that exchange rate
uncertainty should have an impact on both thevolumeandvariabilityof trade flows. Our
1Several theoretical studies
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(Ethier (1973), Clark (1973), Baron (1976),
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Peree and Steinherr (1989)) have
shown that an increase in exchange rate volatility will have adverse effects on the volume of international
trade. Others, including Franke (1991), Sercu and Vanhulle (1992) have shown that exchange rate volatility
may have a positive or ambiguous impact on the volume of international trade flows depending on aggregate
exposure to currency risk (Viaene and deVries
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Our
1Several theoretical studies (Ethier (1973), Clark (1973), Baron (1976), Peree and Steinherr (1989)) have
shown that an increase in exchange rate volatility will have adverse effects on the volume of international
trade. Others, including
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Franke (1991), Sercu and Vanhulle (1992)
 Suffix

have shown that exchange rate volatility
may have a positive or ambiguous impact on the volume of international trade flows depending on aggregate
exposure to currency risk (Viaene and deVries (1992)) and the types of shocks to which the firms are exposed
(Barkoulas, Baum and Caglayan (2002)).
2Negative effects of exchange rate uncertainty on trade flows are recently reported by Arize, Osang and
S
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Vanhulle (1992) have shown that exchange rate volatility
may have a positive or ambiguous impact on the volume of international trade flows depending on aggregate
exposure to currency risk (Viaene and deVries (1992)) and the types of shocks to which the firms are exposed
(Barkoulas, Baum and Caglayan (2002)).
2Negative effects of exchange rate uncertainty on trade flows are recently reported by
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Arize, Osang and Slottje (2000), Sauer and Bohara (2001),
 Suffix

while Gagnon (1993) finds insignificant effects. Baum, Caglayan
and Ozkan (2004) report that the impact of exchange rate volatility on export flows differs in sign and
magnitude across the countries studied.
2
investigation concentrates on bilateral trade flows between a broad set of data that contains
information from 13 countries including the U.
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a positive or ambiguous impact on the volume of international trade flows depending on aggregate
exposure to currency risk (Viaene and deVries (1992)) and the types of shocks to which the firms are exposed
(Barkoulas, Baum and Caglayan (2002)).
2Negative effects of exchange rate uncertainty on trade flows are recently reported by Arize, Osang and Slottje (2000), Sauer and Bohara (2001), while
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Gagnon (1993)
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finds insignificant effects. Baum, Caglayan
and Ozkan (2004) report that the impact of exchange rate volatility on export flows differs in sign and
magnitude across the countries studied.
2
investigation concentrates on bilateral trade flows between a broad set of data that contains
information from 13 countries including the U.
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To match the monthly frequency of export data,
we must generate a proxy for monthly foreign GDP as the available data is on a quarterly
basis.5Hence, we apply the proportional Denton benchmarking technique
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(Bloem et al., 2001) to
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the quarterly real GDP series in order to produce monthly GDP estimates. The
proportional Denton benchmarking technique uses the higherfrequency movements of an
associated variable in our case monthly industrial production as an interpolator within
the quarter, while enforcing the constraint that the sum of monthly GDP flows equals the
observed quarterly total.
3.1 Generating proxies for the vol
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We assume that the errors are jointly conditionally normal with zero means and conditional
variances given by anARMA(1,1)structure as expressed in equation (9). The system is
estimated using the multivariateGARCH–BEKKmodel introduced by
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Karolyi (1995)
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as
implemented in RATS 6.10.
3.2 Modeling the dynamics of the mean and the variance of trade flows
In this study, we investigate two sets of relationships. Both sets of relationships require
us to introduce lags of the independent variables to capture the delayed effects in each
relationship.
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by order (d−1).
9For a survey of the applications of fractionally integrated time series processes in economics, see Baillie
(1996).
10Of the 14 fractional series, eight yield adestimate significantly exceeding unity. Those series were
firstdifferenced and then fractionally differenced withd∗=d−1.
11Transformation of the series via fractional differencing was performed by Stata routinefracdiff
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(Baum, 2006)
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using themodlprpoint estimate ofd.
9
4.2 Generation of proxies for conditional variance
We have employed the bivariate GARCH model described above to estimateHt, the conditional covariance matrix of log real trade flows and log real exchange rates, for each point
in time.12Although the conditional covariance between GARCH errors is not currently
employed in our analysis, it is important to note t
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