Does exchange-rate volatility affect import flows in G-7 Countries? Evidence from cointegration models
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Does exchange-rate volatility affect importflows in G-7 Countries? Evidence fromcointegration modelsA. C. Arize & S. S. ShwiffPublished online: 04 Oct 2010.
To cite this article: A. C. Arize & S. S. Shwiff (1998) Does exchange-rate volatility affect import flowsin G-7 Countries? Evidence from cointegration models, Applied Economics, 30:10, 1269-1276, DOI:10.1080/000368498324887
To link to this article: http://dx.doi.org/10.1080/000368498324887
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1Recently, Engel and Hakkio (1993) noted that t`he perception is widespread that foreign exchange rates are too volatile indeed, someobservers recommend that the United States, Japan, and Germany abandon their exible exchanges and adopt a target zone system inorder to reduce exchange-rate volatility.2 Arize (1995) and Chowdhury (1993), among others, provide recent reviews and empirical results.3 For space and time reasons, we have not done the additional investigation of the short-run dynamics in an error-correction setting.According to the Granger Representation theorem developed in Engle and Granger (1987, p. 255), presence of cointegration implies theexistence of an error-correction model. It is important to establish whether cointegration exists prior to attempting to model the short-rundynamics.
Applied Economics, 1998, 30, 1269 1276
Does exchange-rate volatility a ect import ows in G-7 Countries? Evidence fromcointegration models
A. C. ARIZE and S. S . SHWIFF
College of Business and T echnology, T exas A&MUniversity Commerce, Commerce,T exas 75429, USA
This paper provides new evidence on the long-run relationship between imports andexchange-rate volatility in G-7 countries. The period examined is 1973 :2 through1995 :1. Cointegration analyses are based on Johansens (1991, 1994) approach androbust single-equation methods of Stock andWatson (1993) and Phillips and Loretan(1991). In conformity with theoretical considerations, the results indicate thatexchange-rate volatility has a signi cant negative e ect on the volume of imports ofmost G-7 countries whereas for Canada, it is positive and signi cant. These ndingsare reasonably robust in terms of measures of exchange-rate volatility and di erentestimation methods.
I . INTRODUCTION
There has been widespread concern among nancial marketparticipants, trade economists, the popular press, andpolicymakers over the high degree of volatility of mostmajor exchange rates since the inception of oating rates inMarch 1973.1 Much of this concern stems from the adversee ects of increased uncertainty from high volatility in ex-change rates on international trade. Work by De Grauwe(1988, p. 63) notes that t`he growth rate of internationaltrade among industrial countries has declined by more thanhalf since the inception of oating rates. A number ofstudies also have examined this issue, and most conclude infavour of the existence of a negative and statistically signi -cant relationship between exchange-rate volatility and
export ows.2 Except for Kenen and Rodrik (1986) andKoray and Lastrapes (1989), however, little attention hasbeen devoted to assessing the extent of such volatility onimport ows.The main objective of this analysis, which focuses exclus-
ively on the long-run, is to provide new evidence on thee ects of exchange-rate volatility on the imports of G-7countries the United States, the United Kingdom, Japan,Italy, Germany, France and Canada.3 The evidence present-ed will add a dimension to this literature and determine theextent to which the conclusions reached by previous authorsmay be con rmed by applying recently developed tech-niques of time-series analysis.The approach followed in this paper is di erent in several
ways from that of previous papers in this area. First, it
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4 A number of authors (e.g., Campbell and Perron, 1991; Phillips and Loretan, 1991; Stock and Watson, 1993; Haug, 1996) give reasons forconsidering possibly more robust single-equation estimation methods.5 For example, on the US import side, prior to the September 1985 exchange-rate conference at the New York Plaza Hotel, there was anextended rise in the dollar, which resulted in a group of new foreign producers selling goods in the US market. Once some of theseproducers had met the xed cost of setting up distribution networks, gaining brand name recognition, and so forth, they were unwilling tostop exporting to the US market when exchange rates returned to their initial levels.
uses a longer and more recent sample period, 1973Q2through 1995Q1. In general, the studies by Kenen andRodrik (1986) and Koray and Lastrapes (1989) examinedthe period 1973 through 1985, and it is possible that tradeelasticities underlying recent data may be di erent fromthose found in these earlier studies, especially in view of thehigh degree of volatility and uncertainty of exchange-ratemovements in the modern periods of the generalized oat-ing rates.Secondly, we explicitly test the time-series properties
of the variables in this study. The speci cations used byKenen and Rodrik (1986) as well as Koray and Lastrapes(1989) implicitly assumed data stationarity. However, if thisassumption is incorrect, inferences made concerning in-come, price and exchange-rate volatility are potentiallyhighly misleading. Therefore, this paper focuses upon thecorrect representation of the data to avoid misleading in-ferences.Thirdly, the study examines whether real imports are
cointegrated with its determinants. Unlike all other studiesin this literature, this one represents the rst applicationof a system as well as robust single-equation tests for co-integration. We carried out cointegration tests based onJohansens (1991, 1994) FIML (Full Information MaximumLikelihood) approach and robust single-equation methodssuggested by Stock and Watson (1993) and Phillips andLoretan (1991).4 The advantage of carrying out cointegra-tion testing is that it provides evidence on the existence ofa stable long-run linear relationship among real imports,real income, relative prices and exchange-rate volatility,which is in itself interesting from a theoretical perspective.Furthermore, it is now known that evidence of cointegra-tion implies that the resulting parameter estimates are notsubject to t`he spurious regression phenomenon rst de-scribed in Granger and Newbold (1974).Finally, we compare our results with those obtained by
previous authors. This comparison would provide usefulguidance in drawing conclusions regarding any general hy-pothesis.The rest of the paper is organized as follows: Section II
contains a brief discussion of the theory and methods usedto study the short- and long-run e ects of exchange-ratevolatility on real import demand. Section III represents anddiscusses the empirical results. Section IV contains majorconclusions of the paper. The data used are quarterly andcover the period 1973Q2 through 1995Q1. Details of thedata de nition and sources are presented in Appendix A.
II . THEORETICAL CONSIDERATIONS ANDMODEL SPECIFICATION
Import demand model
A traditional speci cation of the long-run equilibrium im-port demand in the exible exchange-rate environment isthat of Gotur (1985); empirical evidence in favour of thisspeci cation was presented by Kenen and Rodrick (1986);
VMdt = t o + ft + t 3 s (hi)t + e t (1)
where VMdt denotes the logarithm of desired real imports,s (hi)t is the logarithm of a moving sample standard devi-ation, ft comprising traditional variables (the logarithm ofthe gross domestic product in constant prices (yt) and thelogarithm of relative prices, proxied by the ratio of importprices to the domestic price level (pt)) and e t is a disturbanceterm.Standard demand theory concerning the e ects of real
income and relative prices on import demand is well knownand needs no elaboration here (see Arize and Ndubizu, 1992for details). Regarding the e ects of exchange-rate volatility,it has been argued that higher exchange-rate volatility leadsto higher import cost for risk-averse traders and to lessforeign trade. This is because the exchange rate is agreed onat the time of the trade contract, but payment is not madeuntil the future delivery actually takes place. If changes inexchange rates become unpredictable, this creates uncer-tainty about the pro ts to be made and, hence, reduces thebene ts of international trade. Sercu (1992, p. 579) notesthat t`he argument views traders as bearing undiversi edexchange risk; if hedging is impossible or costly and tradersare risk-averse, risk-adjusted expected pro ts from tradeshould fall when exchange risk increases .On the other hand, recent theoretical developments sug-
gest that there are situations in which the volatility ofexchange rate could be expected to have either negative orpositive e ects on trade volume. De Grauwe (1988) hasemphasized that the dominance of income e ects over sub-stitution e ects can lead to a positive relationship betweentrade and volatility.Theoretical models of hysteresis in international trade
(see Baldwin and Krugman, 1989, p. 635 and Dixit, 1989,p. 206) have shown that increased uncertainty from highvolatility in exchange rates can also in uence foreign trade.Hysteresis refers to e ects that continue steadily after theconditions that brought them about have been removed.5
1270 A. C. Arize and S. S. ShwiD
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6 There may be s`unk costs for research and development (R&D), relocation, marketing e orts and capital investment.7 Following the suggestion of the referee, the BLS results are not reported here.
Although these theoretical models show that trade owsare characterized by hysteresis, they also suggest that hys-teresis in trade ows can be explained by the combination ofsunk costs (that are nonrecoverable by a foreign rm uponexit) and exchange-rate uncertainty.6 A foreign rms abilityto enter or exit is linked to the levels of exchange rate. Insum, their work suggests that, when signi cant sunk costsare involved in international transactions, exchange-rateuncertainty can a ect trade behaviour, including that ofrisk-neutral rms. However, it is di cult to identify whichway trade will be a ected. Dixit (1989) also shows that, inthe presence of sunk costs, the hysteresis band widens as theexchange rate becomes more volatile. In such a case, uncer-tainty engenders a wait-and-see attitude among agents.Therefore, trade can be a ected because neither entry norexit of rms occurs.To summarize, the discussion above suggests that the
impact of exchange-rate volatility on foreign trade is anempirical issue, because theory alone cannot determine thesign of the relation between foreign trade and exchange-ratevolatility.Before presentation of the empirical results, four technical
notes regarding Equation 1 and the method of estimationare in order. First, to make Equation 1 estimatable, wemake the assumption that, in the long-run, any deviation ofactual (observable) from desired (unobservable) real importsshould have disappeared (i.e., VMdt = VMt).Second, it is necessary to derive an operational measure
of exchange-rate uncertainty. In this paper two measuresare used. The rst measure incorporates deviations of indi-vidual observations of real e ective exchange-rate , Rt, fromthe predicted value, R t, obtained from tting a fourth-orderautoregressive process. The proxy de ned as s (h1 )t is cal-culated as an eight-term moving average deviation aroundthe predicted values of exchange rate. Speci cally, ifDEV t = Rt - R t , then s (h1 )t is calculated as
s (hi)t = ln 3 17
(Devt i)2 /82 4
0 . 5
where ln is the natural logarithm. The second measure,s (h2 )t , is obtained in a similar fashion, using the predictedvalues of the change in real e ective exchange rate betweenquarter t - 1 and t. Both of the measures were utilized forall countries in an attempt to determine whether the rela-tionship between import demand and variation in theexchange rate was consistent across measures or countries.The next step is to test the null hypothesis of no cointe-
gration (against the alternative of cointegration) usingJohansens multivariate cointegration technique. The tech-nique provides two likelihood-ratio (LR) statistics for the
number of cointegrating vectors: the trace and the max-imum eigenvalue (l -max) statistics.We have estimated our cointegration model under three
alternative speci cations (see Johansen, 1994) for the deter-ministic components of the system, namely H1 (r),H*1 (r) andH0 (r). Model H1 (r) allows for the presence of deterministictrends in the data, but the r cointegrating vectors annihilatethese stochastic and linear trends. Thus, the model allowsfor a linear trend in each variable, but not in the cointegrat-ing relations.ModelH*1 (r) allows for no deterministic trendsin the data, but does allow a nonzero mean of the equilib-rium relationship (a constant in the cointegrating vector).Finally, model H0 (r) restricts the mean of the equilibriumrelationship to be zero (a constant term is not allowed in thecointegrating vector). Since models H*1 (r) and H0 (r) arenested within H1 (r) , we have tested these restrictions usingthe likelihood-ratio procedure described in Johansen (1994).We stopped the rst...