RUHR. Exports and Capacity Constraints A Smooth Transition Regression Model for Six Euro Area Countries ECONOMIC PAPERS #449

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1 RUHR ECONOMIC PAPERS Ansgar Belke Anne Oeking Ralph Setzer Exports and Capacity Constraints A Smooth Transition Regression Model for Six Euro Area Countries #449

2 Imprint Ruhr Economic Papers Published by Ruhr-Universität Bochum (RUB), Department of Economics Universitätsstr. 150, Bochum, Germany Technische Universität Dortmund, Department of Economic and Social Sciences Vogelpothsweg 87, Dortmund, Germany Universität Duisburg-Essen, Department of Economics Universitätsstr. 12, Essen, Germany Rheinisch-Westfälisches Institut für Wirtschaftsforschung (RWI) Hohenzollernstr. 1-3, Essen, Germany Editors Prof. Dr. Thomas K. Bauer RUB, Department of Economics, Empirical Economics Phone: +49 (0) 234/ , Prof. Dr. Wolfgang Leininger Technische Universität Dortmund, Department of Economic and Social Sciences Economics Microeconomics Phone: +49 (0) 231/ , Prof. Dr. Volker Clausen University of Duisburg-Essen, Department of Economics International Economics Phone: +49 (0) 201/ , Prof. Dr. Christoph M. Schmidt RWI, Phone: +49 (0) 201/ , Editorial Offi ce Sabine Weiler RWI, Phone: +49 (0) 201/ , Ruhr Economic Papers #449 Responsible Editor: Volker Clausen All rights reserved. Bochum, Dortmund, Duisburg, Essen, Germany, 2013 ISSN (online) ISBN The working papers published in the Series constitute work in progress circulated to stimulate discussion and critical comments. Views expressed represent exclusively the authors own opinions and do not necessarily reflect those of the editors.

3 Ruhr Economic Papers #449 Ansgar Belke, Anne Oeking, and Ralph Setzer Exports and Capacity Constraints A Smooth Transition Regression Model for Six Euro Area Countries

4 Bibliografische Informationen der Deutschen Nationalbibliothek Die Deutsche Bibliothek verzeichnet diese Publikation in der deutschen Nationalbibliografie; detaillierte bibliografische Daten sind im Internet über: abrufbar. ISSN (online) ISBN

5 Ansgar Belke, Anne Oeking, and Ralph Setzer 1 Exports and Capacity Constraints A Smooth Transition Regression Model for Six Euro Area Countries Abstract Traditional specifications of export equations incorporate foreign demand as a demand pull factor and the real exchange rate as a relative price variable. However, such standard export equations have failed to explain the export performance of euro area countries during the crisis period. In particular, the significant gains in export market shares in a number of vulnerable euro area crisis countries did not coincide with an appropriate improvement in price competitiveness. This paper argues that, under certain conditions, firms consider export activity as a substitute of serving domestic demand. The strength of the link between domestic demand and exports is dependent on capacity constraints. Our econometric model for six euro area countries suggests domestic demand pressure and capacity constraint restrictions as additional variables of a properly specified export equation. As an innovation to the literature, we assess the empirical significance through the logistic and the exponential variant of the non-linear smooth transition regression model. In the first case, we differentiate between positive and negative changes in capacity utilization and in the second case between small and large changes of the same transition variable. We find that domestic demand developments are relevant for the short-run dynamics of exports when capacity utilization is low. For some countries, we also find evidence that the substitution effect of domestic demand on exports turns out to be stronger the larger is the deviation of capacity utilization from its average value over the cycle. JEL Classification: F14, C22, C50, C51, F10 Keywords: Domestic demand pressure; error correction models; asymmetry; play-hysteresis; modeling techniques; switching/spline regression; smooth transition models; exports; sunk costs October Ansgar Belke, University of Duisburg-Essen, Monetary Experts Panel, European Parliament, and IZA, Bonn; Anne Oeking, University of Duisburg-Essen and RGS Econ; Ralph Setzer, European Central Bank, Frankfurt. The views expressed are those of the authors and do not necessarily reflect those of their institutions. The authors would like to thank Joscha Beckmann, Philippe de Rougemont, Florian Verheyen, participants of the conference European Economics and Finance Society 2013 in Berlin and the RGS Jamboree 2013 for valuable comments and suggestions. All correspondence to: Anne Oeking, University of Duisburg-Essen, Universitätsstr. 12, Essen, Germany. anne.oeking@uni-due.de.

6 1. Introduction A number of euro area countries which recorded large current account deficits in the precrisis period have seen a significant correction of their external imbalances over recent years. Although driventoalargeextentbyfallingimports,asignificantpartofthecorrectionhasresultedfromrising exports (see ECB 2013). Interestingly, the standard approach to model exports appears unable to exactlytracefortheexportperformancesince2009.therecentsignificantandcontinuousincrease of exports market shares cannot be explained by changes in the usual price competitiveness indicators as positive developments such as shrinking unit labor costs and falling real effective exchangeratesareabletoexplainonlyapartofthegainsinexportmarketshares.thissuggeststhat nonprice related factors have been important in explaining export performance of euro area countries.theemergingresidualscan,however,bepotentiallymatchedbytheparalleldramaticfall of domestic demand, as shown by Esteves and Rua (2013) for the case of Portugal. In fact, the relationshipbetweendomesticdemandandexportscouldbeparticularlyimportantinthecurrent economicscenarioofcyclicalweakness.itmayhaveabearingbeyondtheportuguesecaseandmay well extend to other euro area member countries facing significant macroeconomic adjustment needsandthusastrongdeclineindomesticdemand. While studies on the effects of domestic demand pressure on the inclination and/or capacity to export are not numerous, they have their roots already in the 1960s. 2 Generally, it is argued that increasesinexportdemandcannotbesatisfiedintheshortrunwhencapacityutilizationishighand whenproductionismainlysoldonthedomestic market.conversely,duringadomesticrecession, firms will be able to shift more resources to export activities. In these periods, firms strive to compensateforthedeclineindomesticsalesthroughincreasedeffortstoexportinordertostayin themarketorentertheexportmarket.thestudiesoverallidentifiedasignificantnegativeeffectof domesticdemandpressureonexportsforseveralcountries,amongthemtheunitedkingdom,the United States, Germany, Spain, Israel, Turkey, Morocco and India. Our study goes beyond this countrysamplebyfocusingonsixeuroareacountrieswithsignificantcurrentaccountdeficitsinthe precrisisperiod(spain,portugal,italy,france,irelandandgreece),usinganadequatesetofnon lineareconometricproceduresnotapplieduptonowinthiscontext.buildingonhysteresismodels ofinternationaltrade,weexplicitlytestforanonlinearrelationshipbetweendomesticdemandand foreignsalesintheshortrun.thebasicideaisthatnonexportingfirmsaremorewillingtopaysunk costs of export market entry in an environment of weak domestic demand and low capacity utilization, while exporting firms strive to stay in the foreign market and accept lower or even negative profits in order to avoid exit costs and costs of reentry. Moreover, we try to put the empiricalanalysisonamoresoundandcoherenttheoreticalfootingbyexplicitlyincorporatingthe tradehysteresisapproach.thelatterintegratesthemicroapproach(whichtendstodominatethe precedingstudiesonthetopic)andthemacroapproachinaunifiedapproachallowingforasocalled symmetricnonlinearity.bythis,weareenlargingthesetoftestablehypothesesontheimpactof domesticdemandpressureontheexportequation. Thepaperproceedsasfollows.Insection2,wepresentdifferenttheoreticalapproacheswhichhelp toexplainanegativerelationshipbetweendomesticdemandandexports.weconsiderasimplesunk costbasedmodelwhichservestocapturethenonlinearhysteresistypedynamicsinherentinthe 2 See,forinstance,Balletal.(1966),Smyth(1968),Artus(1970,1973),Zilberfarb(1980),Faini(1994)and Sharma(2003). 4

7 relationbetweenthedegreeofcapacityutilizationandexportsasthemostpromisingone.taking thismodelasastartingpoint,weconductsomepretestingintermsofunitrootsandcointegration insection3.thisenablesustomodelalinearerrorcorrectionexportequationandtoincorporate nonlinearities imposed by our theoretical considerations. In section 4, we explicitly refer to two differentkindsofnonlinearities:exportsmightreactsharperinarecessionthanduringaneconomic expansion,ormightreacttoanegligiblylowextenttoasmallchangeineconomicconditions,butthe effectmaystronglyincreaseforlargerchangesinthebusinesscycle.whereasthepreviousliterature investigatesonlytheformerhypothesis(seee.g.bermanetal.2011,estevesandrua2013,),wealso focus asaninnovation onthelatter.indoingso,weintroducecapacityutilizationasthesocalled transition variable to capture business cycle effects. We structure our proceedings in accordance withthemodelingcycleforthesmoothtransitionregressionmodelsuggestedbyteräsvirta(1994) whichconsistsofthreestages:specification,estimationandevaluation.inthefirststage,weperform linearitytestsforourbasiclinearmodel,andthenselectbetweenalogisticandanexponentialstr model. In the second stage, we estimate the parameter values by multivariate nonlinear least squares,andinalaststageevaluateandtestourmodel.section5finallyconcludes. 2. Theoreticalmotivation Theexportresponsetoadomesticdemandshockisnotstraightforward.Astandardhypothesisin international trade has been that firms face constant marginal costs and maximize profits on the domesticandexportmarketsindependentlyofeachother.dasetal.(2007)argueforinstancethat shocksthatshiftthedomesticdemandscheduledonotaffecttheoptimallevelofexports.other theoreticalconsiderationssuggestapositivelinkbetweendomesticandforeignsales,atleastinthe long run. This may be due to learning by doing effects emerging from domestic sales to export activitiesandinoppositedirectionwhichinturnraisesoverallefficiencyinthelongrun(belkeetal. 2013,EstevesandRua2013).Apositivecorrelationmayalsoemergeintheshortrunifthereisa liquidityconstraintandthecashflowgeneratedbyexportsisusedtofinancedomesticoperations (seebermanetal.2011). More recently, however, much theoretical and empirical research at the firm level has been conductedwhichallowsforadeeperfoundationoftherelationshipbetweendomesticdemandand exports (Berman et al. 2011, Blum et al. 2011, Vannoorenberghe 2012). These studies generally argue that, in the short term, exporting firms substitute sales between their domestic and export markets. Vannoorenberghe (2012) shows theoretically and empirically that a higher than average salesgrowthinonemarketisassociatedwithalowerthanaveragegrowthintheother.máñezetal. (2008)findthatforeignmarketsbecamearelevantalternativeinperiodsoflowdomesticdemand, andthattheprobabilityofexportingincreasesintheseperiods.inturn,ahnandmcquoid(2012) and Ilmakunnas and Nurmi (2007) conclude that positive domestic demand shocks may exert a downwardpressureonexports. The arguments put forward to motivate a shortrun substitutive relationship between domestic demandandexportsaretwofold:afirstpossiblereasonisrelatedtothedemandsideofexports. Withgrowingdomesticdemandinflationarypressureincreaseswhichinturnshoulddiminishprice competitiveness of exports and therefore reduce export demand. This effect is usually taken into accountbymeansoftherealexchangerateinempiricalexportdemandequations(estevesandrua 5

8 2013).Alternatively,onecouldarguethatpricesarerelativelyrigidintheshortrun,especiallyinthe downwarddirection.hence,theymaynotreactadequatelytochangesindomesticdemandpressure (Zilberfarb 1980). In this case, domestic demand would exert an impact on exports (via export demand)onlyaftersometimehaselapsedand/orifbusinesscyclefluctuationsarepronounced. Asecondandmoredirectimpactofdomesticdemandpressureonexportsreferstothesupplyside of exports. In their excellent survey, Ahn and McQuoid (2012) deal in detail with the sources of exportdomestic sales tradeoffs and assess the growing literature that traces back a negative correlationbetweendomesticandexportsalestocapacityconstraintsorincreasingmarginalcosts. 3 UsingastandardCobbDouglasproductionfunction,theassumptionofincreasingmarginalcostsis motivatedbyproductionfactorswhicharedifficult(orcostly)toadjustintheshortrun,asevidenced bylengthyhiringproceduresorovertimepayforlabor.thesamepatterncanbeexplainedusinga Melitz (2003) type of model of international trade with demand uncertainty in which firms face marketspecificshocksandshortrunconvexcostsofproduction.intheseframeworks,theoptimal outputforthedomesticandtheforeignmarketarenotindependentofeachother.firmsreacttoa shockinthedomesticmarketbyadjustingtheirsalesintheforeignmarket.facedwithanegative domesticdemandshock,firmswouldsellrelativelylesstothedomesticmarketandtargettheirsales moretowardsforeignmarketsasthecostsofexcesscapacitymayoutweightheadditionalcostsand effortofsellingintheforeignmarket.bycontrast,firmswillprefersellingtothedomesticmarketin detrimentofexportsalesifdomesticdemandincreases. Overall, the main lesson from the available literature is that any exercise of modeling export performanceshouldtakeintoaccountnotonlythefactorsdrivingexternaldemand(andthusimpact export activity from the demand side), but also those influencing domestic demand (which affect export activity through the supply side). Moreover, the studies underline the necessity of clearly differentiatingbetweentheshortandthelongrun. One potential limitation of the previous literature is that the complementarity versus substitutability propertyofdomesticdemandandexportactivityhastypicallybeenanalyzedina linear framework. The relationship between domestic demand and exports performance may however be nonlinear because firms need to pay an irreversible cost, which are sunk ex post, to enter a foreign market (Baldwin and Krugman 1989). If there is uncertainty about returns, the decision to switch on or off export activity can be analyzed based on the Dixittype investment under uncertainty model (Dixit and Pindyck 1994). As a modern variant, Impullitti et al. (2013) deriveexportmarketentryandexitdecisionsinageneralequilibriumcontextwithheterogeneous firms.theyshowthatsunkcostsinducehysteresiswhenitcomestoexportmarketsparticipation. Empiricalstudieswithfirmleveldata,amongthemBernardandJensen(2004),BernardandWagner (2001),RobertsandTybout(1997)andCampa(2004)confirmthesefindings. Activity in export markets and building a global network for exports requires considerable set up costs. Examples for these ex post sunk costs consist of market research costs, marketing, finding suitable foreign suppliers and setting up networks for distribution. Most of these costs cannot be reversedonleavingtheexportmarkets;quitethecontrary,thesecostsmainlyrefertoknowledge 3 SupportingempiricalevidenceisdeliveredbyBlumetal.(2011)forChilean,Soderbery(2011)forThaiand AhnandMcQuoid(2012)forIndonesianfirms. 6

9 andinformationthatneedstobegatheredtosetupaglobalexportnetwork.assoonasthefirm leavestheexportmarket,thesignificanceofthisknowledgediminishesrapidly(belkeetal.2013). Inthesemicromodelsofhysteresisinexportmarketsparticipation,thus,abandofinactiondueto switchingcostsforfirmsbetweenservingthedomesticandforeignmarkettypicallyemerges,which isinsomecasesevenwidenedbyoptionvalueeffectsofreturnuncertainty.theexistenceofsunk costs thus suggests that substitutability among serving domestic and export demand will only materialize if the deviation of capacity utilization from its normal level is either highly positive or highly negative ( symmetric nonlinearity ). It will require a significant negative domestic demand shockforfirmstopaythesunkentrycostsandswitchtoexportactivity.inthesamevein,inorderto avoid paying exit costs and repaying the entry costs, active exporters may only leave the export market if domestic demand pressure increases strongly and capacity constraint considerations becomepressing(belkeandgoecke2005,estevesandrua2013). Inthecontextofthispaper,wewillthereforeanalyzetherelationshipbetweendomesticdemand andexportactivityinanonlinearframework.basedonthistypeofmicrofoundation,wedevelopan aggregation approach which appears to be adequate to fit a macro data set as used in this contribution.intervalsofweakresponsetocapacityutilizationreversalsareintroducedonthemacro level.spurtsinnewexportsorareductioninexportsmayoccurafteraninitiallyweakresponseto changesincapacityutilization.inthefollowingempiricalanalysis,wewilltestfortherelevanceof thehysteresischannelbymodelinganexponentialsmoothtransitionregressionmodelwhichisable to differentiate between small and large changes of the socalled transition variable, i.e. capacity utilization. 3. Estimationdesignandpretesting Standardinternationaltrademodelspredictthatthevolumeofexportsofacountryisinthelong termafunctionofitsforeigndemandanditsrelativepricelevelvisàvisitsmaintradingpartners.as a first step, we therefore estimate an export equation which relates real exports of goods and services torealforeigndemand andtherealeffectiveexchangerate.weconsiderthe(non) stationarityofourseriesandthenapplytheenglegrangercointegrationtechniquetofindalong termrelationbetweenexports,foreigndemandandtherealeffectiveexchangerate. 4 Asasecond step,weestimateanerrorcorrectionmodelwhichincludestheshortrunadjustmenttothelongrun equilibrium.asexplainedinsection2,itisratherstraightforwardfromtheorythatdomesticdemand mayexertanimportantshortruneffectonexportsand that thestrengthanddirection ofthis effect depends on the business cycle stance. Deviating from Esteves and Rua (2013) and the literaturecitedtherein,wedonotonlytakeintoaccountthepossibilitythatdownturnsoftenhavea sharperimpactonexport activitiesofacountrythanrecoveriesandthatthiseffectisparticularly strongforlargechangesineconomicconditions.instead,wefocusonwhetherexportactivityreacts onlytoanegligiblylowextenttoasmallchangeineconomicconditions(asmeasuredbythedegree of capacity utilization), but the effect strongly increases for larger changes in conditions. We thereforeapplyanonlinearframeworktocaptureanyasymmetricimpactregardingthestateofthe 4 Sucha standard exportdemandequationhasalsobeenestimatedbymanyothers,asforinstancebythe EuropeanCommission(2011). 7

10 economies.weconsidereachcountry seconomicconditionsbylookingatdeviationsofitscapacity utilizationfromitsmean. Data Ourdatastemsfromdifferentsources:Dataonrealexportsandrealdomesticdemandcomesfrom thenationalstatisticaloffices(eitherobtainedfromeurostatoroxfordeconomics).therealeffective exchange rate is an index deflated by consumer price indices with a country s 15 main trading partnersavailableateurostat. 5 Theseriesonforeigndemandisbasedontradeweightedimportsfor 15maintradingpartners andcomesfromtheecb. Finally,thedataoncapacityutilization(in the manufacturing industry) stems from the Business and Consumer Surveys by the European Commission,availableonEurostat.ForFranceandIreland,thisdatawasnotavailable(oronlyfora veryshorttimeperiod).forthesecountries,weusedtheoutputgapinstead(interpolateddatafrom AMECO).Theseriesareallavailableasquarterlydata,formostvariablesinthetimeperiod1980:Q1 to2012:q4. 6 Unitroottests Asiscommonlydone,wetakeeachseriesin(natural)logarithms.Inafirststep,wecheckwhether thevariablesinourmodelarestationaryornot,i.e.whethertheyareintegratedoforderzero,i(0), orofahigherorder,e.g.i(1).forthispurpose,weapplytheaugmenteddickeyfullertest(adftest) with different auxiliary regressions: for the real effective exchange rate series, the regression includesanintercept,butnodeterministictimetrend;allotherseriesshowatimedependentmean whichisthenincorporatedintotheauxiliaryregressionsviabothaninterceptandatimetrend. To account for possible structural breaks in the series, we also apply the LM unit root testing procedurebasedonleeandstrazicich(2003).iftherewerestructuralbreaksintheseries,theadf testwouldhaveverylowpowerandwouldbebiasedtowardsnonrejection.thus,itmakessenseto applyanothertestforthosetimeswhenthenullhypothesisoftheadftestcannotberejected;the testwillthereforeonlybeappliedtothelevelsoftheseriestotestforthecorrectnessoftheadf testresults. 7. The results for both the ADF test and the LeeStrazicich test can be found in Table 1. The null hypothesisofaunitrootcannotberejectedfortheseriesinlevelsfortheadftest.atthesame time, the null hypothesis can be rejected for the series in first differences. Complementing these results with the LeeStrazicich test, we find that when controlling for structural breaks, for every seriesthenullhypothesiscannotberejectedinlevels.thus,weconcludethattheseriesarealli(1). Table1abouthere 5 WealsousedREERsforthemain24tradingpartnersanddeflatedbyunitlaborcosts;resultsdidnotchange withthesedifferentmeasures. 6 Fortheexactdefinitionsofvariablescf.TableA1. 7 TheLMtestbyLeeandStrazicichwillbeappliedtoeachserieswithbothonebreakandtwobreaks(each breakrepresentingashiftinlevels),wherethestructuralbreakisallowedtooccuratanendogenouslysetdate 8

11 Testingforcointegration As the variables are nonstationary, we cannot estimate an export equation in a straightforward fashion,butfirstneedtoconsidercointegration.thiswillbedonebytheenglegrangerapproach. TheEngleGrangerapproachestimatesthefollowinglongrunequilibriumrelationship: (1) withlogofexports,logofforeigndemand,andlogoftherealeffectiveexchangerate.with timeseriesdataforthecountriesinquestion,theremightbetheissueofstructuralbreaksintheir longrunrelationship,mostlyduetotheintroductionoftheeuroandthetimeleadinguptoit.for thispurpose,weallowforastructuralbreak()inthisrelation.thebreakpoint(s)foreachcountry arefoundbyamultiplestructuralchangeanalysisasdescribedinbaiandperron(2003) 8 andbya GregoryHansencointegrationtest(GregoryandHansen1996a,1996b)whichallowsforonebreakin the cointegration regression. The identified break points all lie in the time period between the EuropeanExchangeRateMechanism(ERM)crisisof1992/1993andtheintroductionoftheeuroin 1999.ForSpainandFrance,thebreakpointoccursin1993,thetimeoftheERMcrisis.ForItaly whichlefttheermduringitscrisis,socanbeassumedtohavebeenaffecteddifferentlythanthe formermentionedcountries theintroductionoftheeuroin1999constitutesthebreakpoint.the breakforgreeceis1998whenitjoinedtheerm.forirelandandportugal,thestructuralbreakswere identifiedin1995,aroundthestartofconvergencetotheeuro.ithaswidelybeendocumentedthat Ireland has had a strong and sustained growth performance (Murphy 2000) ever since the mid 1990s, due e.g. to the increased presence of high tech multinational corporations. Similarly, the Portuguese economy changed in the mid1990s mostly attributable to the prospect of joining the euro.asblanchard(2007)argues,thisledtoaboominoutputandastrongincreaseinitscurrent accountdeficit. Thedummyisdefinedas if,otherwise.thedummyandinteraction termswiththeregressorsareincludedintheequation,sothatwehave: (2) Iftherewasalongrunlinearrelationbetweentheseseries,theresiduals fromthisregressionhad to be stationary. In this case, the OLS results would yield superconsistent estimates for the cointegratingparameters.weestimateequation(2)byfullymodifiedleastsquares(whichcorrects the OLS estimator for endogeneity and serial correlation) and compute an EngleGranger test for cointegrationusingtheresidualsfromthisfirststageregression.thenullhypothesisforthistestis thatthereisnocointegration(i.e.thattheresidualserieshasaunitroot).thetestresultswiththe respectivecriticalvaluesfrommackinnon(1991)canbefoundintable2. Table2abouthere 8 Themaximumnumberofbreaksallowedwastwo,butduetotherelativelyshorttimeseriesathandwe concentrateononebreakforestimationofthecointegrationrelation.otherwise,eventssuchastheglobal crisisin2008wouldhavebeenconsideredasanotherbreak(which,however,wouldhaveincludedonlyashort numberoftimeperiodsafterthebreak). 9

12 Foreachcountry,wefindthatandthereforeconcludethatthevariablesarecointegrated. TheresultinglongrunrelationshipcomesfromtheresultsoftheFMOLSestimationandcanbe foundintable3. Table3abouthere Basedontheory,theexpectedoutcomeforthelongtermrelationshipisapositiverelationbetween and,i.e.whenforeigndemandincreases,sodoexports.for and weexpectanegative relation,asthereerisameasureofthechangeincompetitivenessofacountry.ariseintheindex oftherespectivereermeansalossofcompetitiveness,i.e.exportsshoulddecline.thisisexactly whattheresultsshow:apositivesignfor and andanegativesignfor and. Also,thesizeofthecoefficientsisoverallplausible.Theyaregenerallynottoomuchdifferentfrom onefortheincomeelasticityandbroadlyinlinewithotherstudiesforthepriceelasticity(seee.g. EuropeanCommission2011). Testingfornonlinearity Asanextstep,welookatshorttermadjustments(inparticularattheshorttermrelationbetween exports and domestic demand) taking into account the longrun equilibrium we have estimated above.forthispurpose,weapplyanerrorcorrectionmodel.asmentionedalready,inthiscontext wearealsotakingintoaccountthepossibilityofnonlinearities.nonlinearitiesallowustoinvestigate an asymmetric adjustment process to a linear longrun equilibrium relationship depending on the state of a system. A variable might e.g. react sharper in a recession than during an economic expansion, or might react negligibly low to a small change in economic conditions, but the effect stronglyincreasesforlargerchangesinconditions.thiscouldbeestimatedinthecontextofasimple threshold model. However, for some processes such as an economy s export equation where individual firm level decisions are aggregated, it may not seem reasonable to assume that this thresholdisasuddenandabruptchange;thesmoothtransitionregression(str)modelsthusallow forgradualregimechangeorforachangewhentheexacttimeoftheregimeswitchisnotknown with certainty. The error correction model with nonlinear shortrun adjustment in STR form then lookslikethis: (3) (4) suchthatthechangeof isafunctionofpastequilibriumerrors(theerrorcorrectionterm, where refers to the error term of the long run cointegration relation between, and determinedinthepreviousstep),changesofthevariablesdomesticdemand,foreigndemand, the real effective exchange rate and past changes of its own value. The parameter is thereforetheadjustmenteffectwhichgivesinformationaboutthespeedofadjustmentwhenthere 10

13 is disequilibrium and parameters are the shortrun effects. The parameter is the parameterwearemostinterestedin,namelytheelasticityofachangeindomesticdemandonthe changeinexports. Themaindifferencebetweenourshortandlongrunspecificationistheinclusionofthedomestic demand variable. Based on the theoretical arguments in section 2 above, we include domestic demandintheshortrunspecificationonly.wealsoincludeditinthelongruncointegrationrelation, butitdidnotturnouttobesignificant.thisisafindingalsosupportede.g.byestevesandrua(2013) whoarguethatitisunclearinwhichwaydomesticdemandshouldtheoreticallyenterthelongrun export demand equation. We therefore concentrate on domestic demand in the short run specification.contrarytothelongrunestimation,wealsodonotincludeastructuralbreakinthe shortrunspecification.mostimportantly,ourshortrunspecificationalreadyincludesnonlinearities byapplyingthesmoothtransitionregressionmodel.besides,abreakinthelongrunrelationdoes notimplythatshortrundynamicschangeaswell;byexcludingbreakswealsoreducethecomplexity ofourmodel. Thepartoftheregressionmodel(3)inthefirstbracketsisastandardlinearerrorcorrectionmodel. The second set of brackets picks up the same regressors, but this part is multiplied with function andconstitutesthenonlinearpartofthemodel.iscalledatransitionfunctioninthe smoothtransitionmodel.thisisasmoothandcontinuousfunctionwhichisalwaysboundedandlies between0and1.here,weconsidertwodifferentformsofsmoothtransitionmodels,dependingon thespecificationofthetransitionfunction.thesearethelstrmodel(logisticstrmodel)andestr (exponentialstrmodel). TheLSTRmodelreliesonalogistictransitionfunctionofthefollowingform: with (5) Here,isthetransitionvariable;inourcasethisisthepercentageofcapacityutilization.Weemploy capacityutilizationtocapturebusinesscycleeffectsinparticularinthemanufacturingindustry.we look at deviations of from a threshold value which we set as the average value of capacity utilizationineachcountry.representsthesmoothnessparameterwhichdeterminesthespeedof transitionand isthestandarddeviationofthetransitionvariable.asthesmoothnessparameter dependsonthescalingofthetransitionvariable,wenormalizeitby inordertobescalefree(cf. Teräsvirta(1998)).Thisway,themeaningofthesmoothnessparameterwillnotdependonthescale of. Thelogisticfunctionincreasesmonotonicallyfrom0to1whenthevalueofthetransitionvariable increases. The threshold thus separates two different regimes: 9 (i) negative deviations of the transitionvariablefromitsthresholdvalue:,i.e.themodelcollapsesto just the linear part, and (ii) positive deviations of the transition variable from its threshold value: 9 Therearetwodifferentwaysofinterpretingasmoothtransitionmodel.Ontheonehand,itcanberegarded asamodelwithtworegimes(thetwoextremeswhenthetransitionfunctiontakesonthevalues0or1)anda smoothtransitionbetweenthesetworegimes.ontheotherhand,itmaybeinterpretedasacontinuous numberofregimesbetweenthetwoextremes. 11

14 . The coefficients smoothly change between these two extremevaluesasthevalueof changes. Oneexampleofapplicationisthehypothesisthatdomesticdemandissubstitutedbyexportswhen thedegreeofcapacityutilizationisbelowitsnormallevel(themorestronglyitisbelowitsnormal level the more significantly the substitution between domestic demand and exports) whereas domesticdemandsubstitutesexportstoalesserextentif,inturn,capacityutilizationishigherthan normal. The exponential form of the STR model uses an exponential transition function of the following functionalform: with. (6) Duetothequadraticterm,thistransitionfunctionissymmetric(Ushaped)around sothat thetwodifferentregimestodistinguishbetweenare:(i)largedeviationsofthetransitionvariable from the threshold: and (ii) small deviations of the transition variable fromthethreshold:,i.e.thenonlinearpartdisappearsinthelatterextreme. One example of application is the hypothesis of symmetric hysteresis in exports, i.e. only small effectsonexportsifthechangeoftheforcingtransitionalvariablecapacityutilizationissmall( band of inaction ) and large effects if the change of the capacity utilization variable is large ( spurt of exports ). In our context, we define the change as the difference of current capacity utilization fromitsaverage. Thus,thetwoformsofnonlinearerrorcorrectionmentionedhererefertodifferentdeviationsofthe transition variable from its threshold value: positive vs. negative deviations in the case of LSTR or largevs.smalldeviationsfromequilibrium(butsymmetricdeviationsaboveorbelowthethreshold) inthecaseofestr. 4. Themodelingcycleandempiricalresults The modeling cycle for the STR model as suggested by Teräsvirta (1994) consists of three stages: specification,estimationandevaluation.inthefirststage,weperformlinearitytestsforthelinear model, and then propose either an LSTR or ESTR model. In the second stage, we estimate the parametervaluesbymultivariatenonlinearleastsquares,andinalaststageevaluateandtestour model. Specification TotestforthepresenceofaSTRmodel,Teräsvirta(1994)developedthefollowingframeworkwhich testsbothforthepresenceofnonlinearbehaviorandforanlstrvs.estrprocess.thebasisforthis testisataylorseriesexpansionofthestrmodelinwhichthetransitionfunctionisapproximatedby athirdordertaylorexpansion.theapproximatedmodelhasthefollowingform: 12

15 where and withequaltothenumberofregressors(i.e.thenumberofelementsin ).To getafirstideaofhowmanyregressorsandhowmanylagsofeachvariabletoincludein,wefirst estimatethelinearpartofthevecmmodelwithalldifferentcombinationsoflags(upto )and choosethenumberoflagsbasedontheschwarzinformationcriterion. Testingforlinearitymeanstestingthejointrestrictionthateverynonlinearterminthisexpressionis zero.thealternativehypothesisisthatofastrmodel.formally,thisis for against the alternative for at least one of, implying nonlinearity due to significant higher order terms (Teräsvirta 1998). The test assumes that all regressors and the transitionvariablearestationary,i.e.olsisvalid.weapplythetestfordifferentlaglengthsofthe transitionvariableandselectthevalueofthatresultsinthesmallestpvalue,asthisisbelievedto providethebestestimateof;wherethepvaluesarethesame,wealsoconsiderthevaluesof of the particular regression model. Plausible values for the lag length for quarterly data are here assumedtobe. 10 TheresultsofthetestinTable4showthatthenullhypothesisof linearitycanbeclearlyrejectedforeachcountryandeverylaglength. 11 Anonlinearmodeltherefore seemstobesuitableforeverycountryinoursample. Table4abouthere Based on equation (7), we also approach the choice between an ESTR and an LSTR model (cf. Teräsvirta 1994, 1998). After the first null hypothesis has been rejected (i.e. the model is regardedasnonlinear),wetestthenullhypothesis against.arejectionof this null hypothesis can be seen as a rejection of the ESTR model. Next, we test the hypothesis against.notrejecting canbeseenasevidencein favor of an LSTR model. Lastly, one can test the hypothesis against.if isrejected,thisagainpointstothelstrmodel. In short, the specification tests point to an LSTR model if is rejected and if is rejected after couldnotberejectedandtoanestrmodelif cannotberejected,orif wasnot rejectedafterrejecting.teräsvirta(1994)argues,however,thatthisway,anlstrmodelcould beerroneouslyselectedandsuggeststocomparetherelativestrengthsoftherejectionsinstead,i.e. thepvalues.foranlstrmodel, and areusuallymorestronglyrejectedthan andthe oppositeisexpectedforanestrmodel.resultsforthetestareshownintable5includingthemodel tentativelyproposedforeachcountry. Table5abouthere Oneproblemwiththistest,however,isthefactthatinparticularinsmallsamples,ifthetruemodel is an ESTR model which behaves closely to an LSTR model, the Teräsvirta test often erroneously choosesanlstrmodel(cf.teräsvirta1994).becausethetestdoesnotgiveclearcutresultsforthe selection of the transition function, we also apply another procedure, proposed by Escribano and Jordá(1999).Theyclaimthatusingequation(7)abovedoesnotcaptureallimportantfeaturesand suggestasecondordertaylorapproximationyieldingthefollowingauxiliaryregression: 10 Longerlaglengths(uptoj=8)werecarriedoutasrobustnesschecks,butturnedouttobelesssuitable. 11 However,forFrancewithlaglength thenullhypothesiscanonlyberejectedatthe5%level. 13

16 The hypotheses tested here are and. Escribano and Jordá suggesttochooseanlstrmodelifthelowestpvalueisobtainedfor andanestrmodelifthe lowestpvalueisobtainedfor.resultsforthistestcanbefoundintable6. Table6abouthere However,ingeneralitcanbearguedthatoncelinearityhasbeenrejected,theLSTRandESTRmodel formveryclosesubstitutes.thedecisionrulesmightnotbefullyimportant,butcanratherbeseen as a starting point for estimation. As Teräsvirta (1998) argues, it might make sense to estimate differentmodelsandchoosebetweenthemonlyduringthenextstages,i.e.duringtheestimation andevaluationoftheestimationresults(thesameholdsforthechoiceofthelaglength). EstimationandEvaluation Thesecondstageofthemodelingcycleconsistsofestimatingourparametervalues.Weestimate equation(3)incombinationwitheither(5)or(6)asthetransitionfunction withnonlinear leastsquares(nls).theresultsforourmaincoefficientofinterestarethusmadedependenton thestateoftheeconomy.thethirdandlaststageofthemodelingcycleconsistsofevaluation.the estimation results are examined by simple judgment concerning the convergence of the models, goodnessoffitandbyinspectingtheregimesthemodelsimply.ourresultsarealsosubjectedtothe misspecificationtestofnoresidualautocorrelation.totestforthis,weapplyaspecialcaseofthe BreuschGodfrey Lagrange Multiplier (BG) test suitable for nonlinear estimation (Teräsvirta 1998). Thenullhypothesisforthetestisthatthereisno th orderserialcorrelationinourresiduals.the testregressesourestimatedresiduals onlaggedresiduals andthepartialderivatives of the regression function with respect to. Where necessary, we then respecify our estimated models.finalresultsforcanbefoundintable7. 12 Asubstitutioneffectbetweenexportsanddomesticdemandshouldresultinanegativecoefficient for.thetwoextremeregimesinournonlinearestimationarecoefficient for (i.e. the linear model) and for the case when. To show how evolves between these two extremes (and thus through all stages of the business cycle), is drawn in combination with the transition variable in Figures 1 to 6. In these figures, is defined as. Table7abouthere Figures1to6abouthere EstimationResults LetusfirstturntothecountriesforwhichtheeconometricspecificationwarrantsanESTRmodel.As evidentfromfigure1,whichisbasedonanestrmodelforspain,displaysnegativevaluesforlow 12 CompleteestimationresultsareshowninTableA2alongwithR 2 valuesandpvaluesforthetestofno autocorrelation. 14

17 and high levels of past capacity utilization. This suggests a substitutive relationship between domesticandforeignsaleswhentheeconomyisclosetopeakortrough.whencapacityutilizationis verylow,firmsreacttoafallindomesticdemandbyincreasingtheireffortstoexport.similarly,if the economy operates at high capacity utilization, capacity constraints imply that an increase in domestic demand triggers a reallocation of resources from external to domestic clients. The estimation for Spain yields statistically significant results and the economic significance is also meaningful. For very low capacity utilization, a one percentage point fall in domestic demand generatesclosetoaonepercentagepointincreaseinexports(cf.table7);forpeaks,thiselasticityis slightlylower.bycontrast,apositivelinkisidentifiedbetweendomesticdemandandexportsduring normaleconomicconditions.asarguedabove,thisisinlinewiththeprevalenceofhysteresisand thebandofinactionduetoswitchingcostsforsuppliersbetweenservingthedomesticandforeign market. It is likely that during this period, the shortrun liquidity channel, whereby the cash flow generatedbyexportsisusedtofinancedomesticoperationsandtheexistenceofincreasingreturns dominatesthecapacityconstraintschannel(bermanetal.2011). Similarresults(thoughsomewhatlessstrongineconomicterms)arefoundforPortugalandItalyas evidentinfigures2and3.whereastheestimatedcoefficientsfordomesticdemandarestatistically significant for Portugal (both the substitution effect during peak and trough and the positive link duringnormaltimes),thisisnotthecaseforitaly.here,thesmallsubstitutioneffectduringtrough and peak is found not to be different from zero contrary to the statistically significant positive coefficientfornormaltimes.overall,theresultsindicatethat,asareactiontoanegativedomestic demandshock,firmswhicharealreadyintheexportmarketandhavethusalreadyincurredmarket entry costs would sell relatively less to the domestic market and just switch to foreign markets. EspeciallyinthePortuguesecase,thereappearstobeamplescopeforrelocationintermsofmarket destination from the home to the foreign market. In 2010, only one third of the firms in the Portuguese manufacturing sector was exporting and for them the exports to sales ratio was on averagearound30percent(estevesandrua2013).duringnormaleconomictimes,therelationship isstronglycomplementaryforbothcountries.asformerentrycostscanbeconsideredtobesunk, onecouldarguethatinordertoavoidexitingthemarketsandpayingentrycostsanewinthefuture (BelkeandGoecke2005),firmstrytoservebothdomesticandforeignmarkets. TheresultsforFrance(Figure4)donotcorrespondwithourtheoreticalpriorsbutwiththeresultsby Berman et al. (2011) who suggest that exports and domestic sales are not substitutive but complementary for a panel of French firms. Our results also show that this complementary relationshipisnotasstrongasitisforothercountries;wefindanelasticityofaround0.3.contrary to most other countries results, the coefficients on domestic demand also do not turn out to be jointly statistically significant. These findings may be related to the lower openness of the French economyandpotentiallythelowerforeigndemandelasticityoffrenchexports.generally,theeffect of increases in marginal costs increases with foreign demand elasticity, which make a substitute relationship between domestic demand and exports more likely in small open economies characterizedbyhighlyelasticforeigndemand. LookingatIrelandandGreece,thetwocountriesforwhichweestimateanLSTRmodel,weequally findevidenceforanegativelinkbetweendomesticandforeignsalesduringperiodsoflowcapacity utilization(figures5and6).thiseffect,however,isstatisticallyinsignificantforbothcountriesand economicallyonlyofverymodestsize.butgenerally,exportsreactsharper(andslightlypositive)toa declineindomesticdemandinarecessionthanduringaneconomicexpansion.andevenmorethan 15

18 that:afterpassingacriticalthresholdexportsanddomesticdemandbecomecomplementswithan increasing degree of capacity utilization. In the case of Ireland, the finding that only economic recessionsbutnotperiodsofboomsleadtoasubstitutiverelationshipbetweendomesticandexport sales may be explained by the higher flexibility of the Irish economy compared to its Southern European counterparts. Flexible prices and immigration may have made capacity constraints less binding. For Greece, the estimated model somewhat resembles a simple tworegime threshold modelwheremarginalchangesofcapacityutilizationarounditsaveragehavestrongeffectsonthe relationbetweendomesticdemandandexports.furtherstrongchanges,however,donothaveany furthereffects. Overall,ourempiricalresultsstronglysuggestthattherelationshipbetweenexportsanddomestic salesdependsonthebusinesscycle.asubstitutiverelationshipbetweendomesticandforeignsaleis evidentduringeconomicdownturns.weobtainanegativecoefficientforinallcountriesexcept France.Thisisinlinewiththegaininexportmarketsharesinseveraleuroareacrisiscountriesduring thecurrentrecession.thereismorediversityacrosscountriesduringotherstagesofthebusiness cycle suggesting that capacity constraints and the liquidity channel play a different role across countriesand/orpartlycanceleachotherout. AdjustmentEffects Besides the effect of domestic demand on exports, we are also interested in the adjustment coefficient, which shows how much of the longrun disequilibrium between exports and its explanatoryfactorsisbeingcorrectedineachperiod.inparticular,thecoefficienttellsustheextent towhichdisequilibriuminthepreviousperiodhasanimpactonexportadjustments. If there was a negative shock and exports in the previous period were below its longrun equilibriumpath,thevalueoffromequation(4)wouldturnnegative.sinceweaddwitha positive sign in the errorcorrection model of equation (3), we expect a negative adjustment coefficientinorderfor toreturntothelongrunequilibrium.theoppositeholdsforapositive shocktoexports.thespeedwithwhichexportsreturntoequilibriumdependsonthesizeof.inour specification, the adjustment coefficient depends on the transition function (and therefore the transition variable). To show the adjustment effect for the respective countries over the business cycle (i.e. as the transition variable changes), coefficient is displayed in Figure7forthedifferentcountries. Figure7abouthere For Spain and Italy, the adjustment coefficient turns out to be somewhere between 0.1 and 0.3 dependingonthestateoftheeconomy,i.e.10to30percentoftheadjustmentfromdisequilibrium takesplaceinonequarter.theadjustmentforfranceandgreecedoesnotvarysubstantiallyover thebusinesscycleandrangesfrom30toabout37percent.forportugalandireland,thecaseis different:themaximumcorrectionofthedisequilibriumbetweenexportsanditsexplanatoryfactors is one fifth (Portugal) and one tenth (Ireland), while no adjustment takes place during strong economicdownturns. 16

19 RobustnessChecks In the following, we are performing some robustness checks to our estimations by e.g. changing someoftheparametersorsplittingoursample.asoneoftheserobustnesschecks,wemodifythe laglengthofthetransitionvariable.intable4,weproposedsuitablelaglengthsbasedontestsfor nonlinearity and chose the one with the lowest pvalue (given that it passed the estimation and evaluation stage). Now, we also estimate our nonlinear error correction model with the second lowestpvalue slaglength.thisalsoreducestheproblemoftherelativelylonglaglengthforsome countries,notablyportugal,italyandfrance.ascanbeseenintablea3andinfigure8,ourresults quantitatively do not change for most countries due to a different lag length of the transition variable.exceptionsareitalyandfrance,thosetwocountriesthatdidnotyieldsignificantresultsfor theestimationofjointintheoriginalestimation.forfrance,thereisalsotheproblemofveryfew observations around the threshold value of its transition variable. Most of the observations are foundintheleftandrighttail,andforthesepartstheestimationresultsstayroughlythesame. In addition, we vary the initial values for our smoothness parameter when our estimations are iteratedbynonlinearleastsquares.weoriginallystartedwithasmallvalueof=2,butnowalsouse smallerandlargervalues.when,ourmodelresemblesasimpletworegimethresholdmodel. When,thetransitionfunctionbecomesaconstant(0.5forthelogisticversionand0forthe exponentialversion)andourmodelcollapsesintoalinearerrorcorrectionmodel.foralargerange ofstartingvaluesforouriteration,theestimationsconvergetotheoriginalresultsandouroriginal. Only for some values very close to zero, the models do not converge anymore. We take this as furtherevidencefornonlinearestimation. Last, we estimate our results for a shorter time period to judge how our results could have been influencedbytherecentcrisisperiod.wesplitoursamplerightbeforethefinancialcrisis(takingthe LehmanBrothers bankruptcyinseptember2008asbreakpoint),i.e.between2008q2and2008q3. Because the time span after and including the financial crisis is very short and estimations of this timeperiodwouldincludeaverylimitednumberofobservations,weconcentrateonestimatingthe firsttimeperiod,i.e.uptoandincluding2008q2.resultscanbefoundintablea4andfigure9. 13 Comparedtotheoriginalestimation,resultsarequantitativelyrobustforSpain,Italy,France,Ireland andgreece.forthesecountries,inclusionofthecrisistimeperiodthusdoesnotseemtostrongly impact our findings. Results change, however, for Portugal. Whereas we originally found a small substitutioneffectbetweendomesticdemandandexportswhencapacityutilizationwasparticularly highorlow,thiseffectnowdisappears.therecentyearsthusseemtohaveinfluencedportugal s relationofexportsanddomesticdemand.themostimportantreasonforthismightbethefactthat verylowcapacityutilizationinoursampleonlyoccurredduringthelastfewyears,sosubstitution effectssimplymightnothavebeenanissuebefore.overall,theresultsfromourrobustnesschecks confirmtheresultswepresentedabovewithslightrefinements. 13 Theaveragevalueofthetransitionvariablechangedaswellduringtheshortersampleandcanbefoundin Figure9. 17

20 5. Conclusions Theresultsofourmacroeconometricsmoothtransitionregressionapproachindicatethatdomestic demand behavior is relevant for modeling the shortrun dynamics of several euro area member countries exports. In particular, the estimation results suggest that contemporary and lagged domesticdemanddevelopmentsaffectacountry sexportperformancesignificantlyandnegatively. In the cases of Spain, Portugal and Italy, the asymmetry of the relation expresses itself in a substitutive relationship between domestic demand and export activity if deviations from average capacityutilizationarelarge,independentoftheirsign.tobemoreconcrete:ifourdataindicatethat theestrmodelhastobeapplied,thesubstitutioneffectfromdomesticdemandonexportsturns out to be stronger and more significant the larger the deviation of capacity utilization from its averagevalueoverthecycleis.onthecontrary,inthecasesofirelandandgreecewherethelstr modelturnsouttobethebettermodelingchoice,wefindthattherelationshipbetweendomestic demandandexportsisasymmetric.domesticdemandandexportsaresubstitutesduringabusiness cycle trough and complements in a boom. In other words, positive versus negative deviations of capacity utilization from its normal level matter. For France, we find evidence for complementary relationshipsinstead. Whataretheimplicationsoftheseresultsforthediscussionofmacroeconomicadjustmentandthe reduction of euro area current account imbalances? Prima facie, our results suggests that the negativelinkbetweendomesticdemandandexportsisashorttermphenomenonlinkedtocurrent economic conditions. In the longterm export performance has to be linked closely to price developments.thiswouldimplythatalotofthegainsinexportmarketsharesofvulnerableeuro areacountriesarecyclicalandcouldbelostinthelongterm.analysesofcyclicallyadjustedcurrent account balances, as done in the context of the macroeconomic imbalance procedure or the macroeconomicadjustmentprograms,couldthenpossiblyoverestimatethestructuraladjustmentof thecurrentaccounttotheextentthatweakdomesticeconomicconditionsexertanimpactnotonly ontheimportsideofthenettradeequation,butalsoontheexportside. On the other hand, at least three factors give rise to the hope that the gains in export market performancemaybeofamorelongtermnature.first,ifdomesticproducershavepaidsunkcosts forexportmarketentryandadaptedtheirproductiontomeettherequirementsofforeignclients, attractionbyforeignmarketsshouldremainhigheveninaneconomicupswing.second,theeffect may also be more longterm to the extent that the current economic crisis leads to a change in investmentactivities:withaneyeonthedepresseddomesticdemandconditions,firmsinvulnerable euro area countries may increasingly consider exportoriented foreign direct investment into distribution networks and other hedging activities (Belke et al. 2013). This, in turn, renders the hypothesizednegativerelationshipbetweendomesticdemandandexportsmorelongterm.third,as arguedabove,apositivecorrelationbetweendomesticsalesandexportsmightemergeinthelong term due to overall efficiency improvements induced by learningbydoing effects. Overall, it can thereforebeexpectedthatasubstantialpartofthegainsinexportmarketsharesmayindeedbe structural. 18