Trade and investment patterns Lecture for the course STV4284B

1. Trade and investmentpatternsLecturefor thecourse STV4284B Carl Henrik Knutsen Department ofPolitical Science, UiO 8/4-2008

2. Importantquestions • Whichfirms import and export, and why? • Whichfirmsinvest, and why? • Whatcharacterizes FDI flows and stocks? • Whatarethefactorsinfluencingallocationof FDI? • Howdoes trade relate to FDI?

3. Actors • Firmsinvest • However, weareofteninterested in aggregatepatterns at thenationallevel, evenifindividualinvestmentdecisionsaretaken by firms (and evenindividualswithinthefirm). • Structuralfactors, politicaleconomic systems • Generalization

4. The profit-maximizingfirm in neo-classicaleconomics • Invest or not? • Investif: p*f(x) –w*x – c > δ • A wideinterpretationof c: plant investment, administrative costs, corruption, reputationeffectsetc.. • Uncertainty and risk-aversefirms • Are investors rational? Otherimportantfactors more or less compatiblewithrationalchoicetheory: • knowledge and learning; boundedrationality • externaleffectsonotheractivities • market power (mergers and acquisitions) • maximizingprofits or size? • Parsimony: Benefits and drawbacks.

5. Empiricalstudies • Aggregatevsfirmlevel data • Firmlevel data areonlyavailable for a certainnumberofcountries, and this limits thenumberof studies • Secrecy • Short time series • Comparabilityacrossnations; data at thenationallevel • Definitions and comparability. OECD.

6. Norwegian FDI • Data from theStatisticsNorway (SSB) • Data oninvestmentprojects • 1998-2005 • Basedon survey • Reporting, bias and lackof data • Availability and secrecy

7. Project onNorwegian FDI • Hveem et al (2008a and 2008b) are first outputs from thisprojects. • Aggregate studies onFDI-patterns. Descriptions and causalanalysis. • Forthcoming: State-ownedenterprises and FDI • Need for nuance: Sector studies and firm studies. Studies onparticular host countries? • A verygoodopportunity for writingMA-thesis!

8. ”The Latecomer Investor” • Large-scaleoutward FDI from Norway is a relativelynovelphenomenon, withsomeexceptions (e.g. shipping) • Historically, Norway has been a net importer of FDI • Butthis has changed! In 2005: Outward = 2x Inward FDI • Economicgrowth and growthoffirms (large firmsaremuch more likely to engage in FDI) • Capital accumulation • Business culturechanges, even in state-ownedenterprises? • According to UNCTAD statistics, NorwegianoutwardFDI-stock in 1980 wasonly0,4% ofthat in 2006, and in 1990 it was9,0% ofthat in 2006.

9. Somenumbers • Total outward FDI stock: • 1998: 238 864 million NOK • 2005: 665 349 million NOK • Annualgrowth rate of 15,8% from 1998 to 2005. The growth rate from 1980 to 1998 was 25,1%, starting from a verylowlevel! • The growth rate in globalFDI-stocks over theperiod from 1998 to 2005 was 10,9%. The growth rate from 1980 to 1998 was 11,6%. • Norwegianoutward FDI as a shareof global FDI went up from 0,09% in 1980 to 1,04% in 2005. The Norwegianpopulationaccounts for about 0,08% oftheworld’spopulation. • Total outward FDI stock in oil and gas production: • 1998: 87 408 million NOK • 2005: 216 755 million NOK • Annualgrowth rate of 13,9%

10. Norwegian FDI from 1980-2006

11. GeographicaldispersionNorwegian FDI

12. Someclaims from thepaper • Norwegian FDI has had a dramaticincrease in later years, outgrowingeventhe global trend • Norwegian FDI has been and still is veryconcentratedgeographically, butthetrend is deconcentration, as Norwegian investors have increasinglyturned to for exampleAfrica and Asia • The largest ”receivers” of FDI in 2005: Sweden, USA, Belgium, Canada, Netherlands, Singapore, Denmark, Great Britain, Germany, Angola, Azerbaijan • Norwegianoil and gas investmentsare a substantial part ofthe story, but not thewhole story. Othersectors: Telecom, aluminium, mechanicalindustries, shipping • Norwegian FDI has grownbecauseof 1) New investments in existingprojects, 2a) Mergers and acquistions, 2b) Greenfieldinvestments • In addition to FDI, Norway’sstateownedpetroleum/pension fund is a very large global investor in stocks and bonds. • Not in paper: State ownedcompaniesareimportant: 30,3% of 2005 FDI, whenapplying a 50% ownershipcriterion.

13. ”Blue-eyed investors” • Underlyingpremise: A verywide range ofhost-countrycharacteristicscanaffecttheallocationofNorwegian FDI. • Economic, geographic, political and socialfactors. • Earlier studies have tended to focusoneconomicfactors • No existingcoherentmodel is able to capturethese diverse factors A need for theoreticaleclecticism and an explorativestrategy, empirically.

14. Somemethodology • A regression-basedframework, butappliedon a panel data set OLS does not suffice • Pooled Cross Section Time Series analysis: OLS with panel corrected standard errors. Takesintoaccountheterogenous standard errorsacross panels, autocorrelation and contemporaneouscorrelation • Time series from 1998-2005. Country-yearsareunits. • Data from severalsources: SSB, WDI, FHI, WGI, ILO, CEPII…. • Regressionequation: Y = α + β1Xi1 + β2Xi2 + …. + βnXin + εi • Interpretationofcoefficients (Controlled for all otherfactors!)

15. Methodologicalpitfalls • Data: Measurement errors from survey. Lacking data classified as 0 underreporting • Systematicbiasesif FDI in someparticularcountriesaresystematicallyunderreported (tax-havens?) • Transitcountries and final investment location: Belgium and Singapore!! • Bi-directionalcausality: Onlyaffectssome variables in thisstudy • Omitted variable bias • Controllingawayindirecteffects • Multi-colinearity and uncertainty • All thesepointsimplythattheresults from thearticle have to be interpretedwithcare. Nevertheless, thesearethe best estimateswecanget!

16. The mainempiricalresults • Thesefactorsseem to significantlyincreaseNorwegian FDI: • Large market • Smallgeographicaldistance • EU-membership • Being Nordic • Hightertiaryschoolenrollment rate • Lowcapitaldensity • Energy-resources • Lowcorruption • Stricterlabour standards • Thesefactors show divergingresults or areinsignificant in most analyses: • Wages • Democracy • Ruleoflaw • Trade-taxes • Bilateral investmenttreaties • Tax-haven status • Primaryschoolenrollment rate

17. Economicfactors • The ”gravitymodel” in studies of trade. Works quitewellhere as well. • The roleof a big market and welldevelopedfactor markets • Distance and FDI. Verticalvshorizontal FDI and theoreticalpredictions • Factorsofproduction • Type ofeducation and sectors • The roleofwages • Investment and twotheoreticalpredictions (SolowvsKrugman)

18. Economic policy and trade • Bilateral investmenttreaties and tax-havens: Whysuchweakresults? • Trade taxes and alternative explanationsofthe negative relationshipwith FDI • EU/Nordic • Trade and FDI: The issueofcausaldirection and interpretationofregressionresults

19. Politicalstructures • Highcorrelationbetweenpoliticalstructures. Institutionalstructuresthattend to og togetherMulti-colinearity and thedifficultyofdetermining relative effects. • But: Politicalstructuresclearly matter! • Rational investors and costofdoing business • Rational investors and uncertainty • Business leaders and norms • Reputationeffects

20. Specifications • The choiceoffunctional form: Logarithmictransformations and interpretationofcoefficients • Alternative operationalization and robustnessofresults • The largest problem however is choosingthe most suitablemodel-specification • Rememberthatweareonlydealingwithmodel-contingentestimates: The most importantthing is not thenumbers, but ”sign” ofcoefficients and statisticalsignificance.

21. How to read a regressiontable

22. Interpretation and nuance • Estimatesareestimates • Wearedealingwithaggregate data: wayofgeneralizing, does not strictlysayanythingaboutfactorsmovingdecisions in concrete, singular instances • Nuancingtheaggregate data: Sectors and diversity!

23. Bernard et al. (2007) • Firms and trade in the US. • Whatarethecharacteristicsoftradingfirms, and how do theyperform? • Data from 1993-2000: Noticetheshort time intervalwheninterpreting trends • Trends versus levels, shares versus growth • Links customs data with data onfirms • Paper is mostlydescriptive, and does not conductanyrigorousanalysis. Correlation and causation.

24. Main findings • Importing and exportingarecorrelatedactivities (omitted variables? Size?) • Trade is veryconcentrated: Top 1% tradingfirmsaccount for 81% of trade, and concentrationincreases over time. • Only a smallnumberoffirmsengage in trade, butthenumber is growing (entry and exit mechanisms) • Butthesefirmsare in general big! • Greatesshareoftradingfirmsare ”wholesale and retail trade” firms, butthelargestvolumeof trade takesplace in thegoodssector • Most ofthe trade is withother OECD countries, and theaveragenumberoftrading partners is low (approx 3), butgrowing. • Tradingfirms have betterperformances (employmentgrowth and exit). Causalinterpretation: Learning and spill-overs as well as profits from trade AND/OR self-selectioninto trade by most successfulfirms: Trade as symptom (Dani Rodrik) • ”Most GloballyEngagedFirms” arefirmsthatboth import and exportwithrelatedparties. Theseaccount for 80% of US exports and imports and are more likely to trade with less developedcountries • Intra-firm trade is onthe rise in MGEs, and in general, thesefirmsalso have highergrowth rates in exports and imports thanotherfirms.

25. Hummels et al. (2001) • Point ofdeparture: Productionprocessesincreasinglyinvolvesequential, verticaltradingalongthevaluechain. Import ofinputs - production - exportofgood (alternatively used as new input in receivingcountry) • (International) Verticalspecialization: Useofimportedgoodsthatare used in producinggoodsthatare later exported • More formally: • Good is produced in two or more stages • Two or more countriesprovidevalueadded to good • At leastonecountry must useimported inputs and exportsomeoftheproduction

26. Data and main findings • Usesinput-outputtables from OECD database for 10 OECD countries, plus separate data from Ireland, Korea, Taiwan and Mexico (Thesecountriesaccount for more than 60% of world exports). • VerticalSpecialization as shareof trade for thesecountries: From 0,165 in 1970 to 0,21 in 1990. A 30% growth. • VerticalSpecializationaccounts for 30% ofthegrowth in total exports over theperiod.

27. Other findings • Heterogeneity: Smallcountries have a highershareofVS/export, and the US in particular has a lowshare. • VS/export has grown in most countries, butsomecountriesexperienced a slow-down in the 1980’s. VS wasparticularlyimportant in increasingexportgrowth rates in Mexico and Taiwan. • The VS share has mainlygrownbecausethere has been an increasing VS sharewithinsectors, and not becausecountries have changedtheirsectoralcomposition

28. Causes • Countriesareable to reapbenefits from Ricardian ”comparativeadvantages” not only in trading ”home-grown” final goods, butalso by trading inputs: gains from trade. • Why has thisbecomeincreasinglypossible? • Technologicalchange • Transport costs • Loweringof tariffs • The transnationalcorporation and intra-firm trade (organizationalchange)

29. Feenstra • Increase in trade, and economicintegration (mainlyfocusingonthe US). • ”The skeptic”: Pre WWI trade levelswerehigh! • Feenstra: Sectoralcomposition has changed as GDP has increased. Less trade in services than in goods: Merchandisetrade/production is muchhighertoday (1998) • Economicintegrationgoestogetherwithdisintegrationofproductionprocess(”outsourcing”). Relate to Hummels et al and verticalspecialization • US trade in goods and long-rundevelopments: From agriculture and raw materials to manufacturedconsumergoods and particularlycapitalgoods • Capital goods, butalsomanufacturingareincreasinglydoneabroad, butoften by affiliatesbelonging to US TNCs or by firmsengaged in different types oflong-runcontractualrelations (licensing etc.) • ”Low skill” productionundertakenabroad, and ”high skill” production at home (a simplifiedmodel). Advertising, marketing and productdevelopmentremains in the US. The logicofcomparativeadvantage

30. The politicaldebate and theacademicdebate • The politicaldebate, especially in the US, has focusedonthe negative effectsofglobalization and outsourcingon real wagedecline or at leaststagnation for low-skilledworkers and uneployment • Economists, with a basis in empirical studies, have arguedthattechnologicalchange, which has reduceddemand for low-skilledworkers, is largely to blame for declining real wages (US) and highunemployment (Europe) • Feenstraarguesthatonecannot separate easilybetweeneffects from technologicalchange and theeffects from trade, and thattheseeconomists have basedtheir studies on trade in final goods. According to Feenstra, thepicturechangesifwetakeintoaccountverticalspecialization and trade in inputs. • In addition, increasedmobilityofcapital has increasedthe relative bargainingpowerofcapitalowners over laborers. Often, thethreat to movethefactory is enough to reducewages, and we do not need to seeoutsourcing for thethreatofoutsourcing to have an effectonwages. • Feenstra’spoint is welltaken, but in my view, thepublicdebate has one-sidedlyfocusedoneconomicintegration as a cause for theseeconomicills, and has not takenintoaccounttheroleoftechnologicalchange. Bothfactors have probablybeen at work.

31. Policy-remedies • Trade policy: From altering and usingthe ”escapeclauses” in WTO to outright unilateral protectionism: Efficiencyissues! • Subsidizethe losers, but let theeconomyrestructure: Norman and Dixit’s subsidies and taxes • Rodrik and theneed for a strongwelfarestate in a globalizedeconomy • Labour-market policies: Retrain and reeducatetheunempolyedindustrialworkers • Technologicaldevelopment and newsectors: Findyournewcomparativeadvantage! • Provide a well-functioning and broadeducational system.