内容发布更新时间 : 2024/5/10 11:34:15星期一 下面是文章的全部内容请认真阅读。

Postal parceldeliverypricescanbebrokendownintwocomponents:costsatthesending end and costs at the receiving end. These two price componentsvaryconsiderably across countries and are often affected by the extent of liberalisationofpostal markets and competition with commercial couriers. Unfortunately, we havenoindependent data sources to check the consistency of these data with transportcostsfor commercial couriers and for major online retailers that have their ownlogisticsnetworks.

4. Summar y andconclusions

WecouldparaphraseMarcTwainandsaythat“rumoursaboutthedeathofdistancearegreatlyexaggerated”.Nevertheless,thereissometruthinthisrumour.First,theresultsshowthattheimportanceofgeographicaldistanceis stronglyreduced in online trade, compared to offline trade, due to a drastic reductionininformationcostsinthedigitaleconomythatenablesconsumerstoscanamuchwiderterritorytosatisfytheirwishesandplacetheirbuyingorders.Ontheotherhand,thereisastrongincreaseinthetradecostsassociatedwithcrossinglinguisticborders.Thechangeincoefficientvaluesfordistanceandlanguageisconfirmedacrossdifferentregression models. Second, the models that we run do not attribute anystatisticalsignificancetothecostofparceldeliveryintheobservedpatternsofcross-bordere-commerce in the EU. However, the efficiency of online payments systems isanimportant driver for cross-border online trade in the EU. This leaves policy makerswithlittleregulatorymargintoboostcross-borderonlinetrade.Thedataonlydemonstratethatimprovementsincompatibilityandinteroperabilitybetweenonlinepayment systems would be a step in the right direction. Third, the results

provideapreliminaryindicationthathomebiasisnotsignificantlydifferentinonlinemarketscomparedtotraditionalofflinetrade.Despitethefactthatreducedinformationcostswidenthemarketforconsumersandfacilitatebuyingabroad,consumersstillhaveastrongtendencytobuyathome.Languagebarrierscertainlyplayanimportantrolehere, but other as yet unobserved variables may also be part of the explanation.

EU policy makers have fixed Digital Agenda policy targets for e-commerceintermsofincreasingvolumesofonline(cross-border)trade.Thismightbesurprisingbecause trade is only a means to enhance consumer welfare, not an end initself.E-commercecanboostconsumerwelfarethroughlowertransactioncosts,increaseddiversity of supply and more price competition. Our data do not allow aninvestigationof these welfare effects though we can assume that the volume of online trade is agood proxy indicator of consumers’perceived benefits. In that sense,e-commercepolicy follows in the footsteps of the EU offline Single Market that aims toreducetrade barriers and boost cross-border trade with a view to stimulate pricecompetitionand increase the diversity of supply. E-commerce dramatically reduces thetransportcost of information. This opens up a much wider geographical catchment areaforconsumers and suppliers. This paper shows however that (cross-border) e-commerceis still subject to trade barriers; not only in terms of physical delivery costsand

regulatorybarriersbutalsonewtradecostsinducedbylinguisticmarketsegmentationand online paymentssystems.

Thetotalvolumeofconsumeronlineexpenditureislikelytoincreaseovertimeasmoreconsumersbecomemoreconfidentwithonlineshoppingandmovealargershare of their shopping online. An important limit on that growth potential isthecompositionoftheonlineshoppingbasket.Theconsumersurveydatathatweuseshow that this is heavily biased towards a limited number of goods such aselectronics,clothing,music/filmandafewotheritems.Theonlineshoppingbasketdiffersconsiderablyfromtheoverallconsumergoodsbasket,probablybecauseothertypesofgoodsdonot lendthemselvessoeasilytoonlinetrade.Furtherresearchisalsoneededtoexplainthecompositionandrestrictionsontheonlineconsumerbasketandexploreways to widen the range of goods that can be traded online. Even if the total volumeofonlineshoppingstillhasveryconsiderablegrowthpotential,thegravitymodelindicatesthattheratioofdomestictoforeignonlineshoppingmaynotchangethatmuchbecauseit

isheldbackbylinguisticfragmentationintheEUmarket.Sinceonly36 out of 729 EU27 country pairs share a common language, online retailers whowanttoexpandtheirbusinessabroadarestronglyadvisedtohavearangeoflanguageversionsoftheirwebsites.However,itisdifficulttoseehowlanguagecouldbecomean instrumental variable for policymakers.

A final word of caution. This analysis is based on a single EU consumer surveydatasetthatofferssomeuniqueinsightsintothevalueanddirectionofonlinecross-border trade between EU countries. Obviously, these data do not have thesamevalidity as the far more comprehensive and detailed international offline trade ingoodsstatisticsthathaveaccumulatedovertheyears.Theyofferafirstinsightbutmoreeffortwillhavetogointotheconstructionofmorecomprehensiveandreliableonline cross-border trade data sets that will enable a more detailed and rigoroustesting of the drivers and impediments to online cross-border trade. Furtherworkwouldhavetoincludemoredetailsonproduct-specificcross-bordertrade,transportcosts, prices and information costs.

参考文献

[1] Anderson and Van Wincoop, 2003J. Anderson, E. VanWincoop

Gravitywithgravitas:asolutiontotheborderpuzzle.Am.Econ.Rev.,93(2003),pp.170–192

[2] Baier and Bergstrand, 2009S.L. Baier, J.H.Bergstrand

Estimating the effects of free trade agreements on international trade flowsusingmatchingeconometrics.J. Int. Econ.,77(2009),pp.63–76 [3] Berthelon and Freund, 2008M. Berthelon, C.Freund

On the conservation of distance in international trade.J. Int. Econ., 75 (2008),pp.310–320

[4] Blum and Goldfarb, 2006B. Blum, A. Goldfarb.Does the internet defy the law ofgravity.J. Int. Econ.,70(2006),pp.384–405

[5] CapGemini et al., 2011CapGemini, Royal Bank of Scotland, EFMA, 2011.World PaymentsReport,

[6] Coughlin and Novy, 2009C. Coughlin, D.Novy. Is the International Border Effect Larger than the Domestic Border Effect:Evidencefrom US Trade, Research Article Series 2009/29Nottingham University,LeverhulmeCentre (2009)

[7] Disdier and Head, 2008A. Disdier, K.Head

Thepuzzlingpersistenceofthedistanceeffectonbilateraltrade.Rev.Econ.Stat.,90(2008),pp.37–48

[8] Helpman et al., 2008E. Helpman, M. Melitz, Y. Rubinstein.

Estimatingtradeflows:tradingpartnersandtradingvolumesQ.J.Econ.,123(2008),pp.441–487