The 8 reference contexts in paper Christopher F Baum, Mustafa Caglayan (2007) “Effects of Exchange Rate Volatility on the Volume and Volatility of Bilateral Exports” / RePEc:mmf:mmfc06:64

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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)
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    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),
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    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 higher-frequency 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 first-differenced 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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