global production and trade in the knowledge economy economics... · global production and trade in...

Global Production and Trade in the KnowledgeEconomy

Wolfgang KellerUniversity of Colorado, CEPR, and NBER

Stephen R. YeaplePenn State University and NBER

March 2009

Keller and Yeaple () Costly Trade and Knowledge Transfer March 2009 1 / 33

General Motors sales in the US versus in Europe


GM and VW sales in Europe versus in the US


Multinational sales are declining with trade costs


Why is FDI o¤shoring easier to nearby locations?

Technology transfer between multinational parent and a¢ liate iscostly

I Case studies often nd a¢ liate productivity lower than parentsI Compare to usual assumption of no-cost transfer since Helpman 1984,Markusen 1984

Multinational compares costly technology transfer to a¢ liate withtrade costs of exporting that rise in distance

I A¢ liate production: disembodied tech transfer + employing hostcountry factors

I Parent exports: embodied tech transfer + using source country factors


This paper

Global production sharing is explained through the new mechanism oftrade versus technology transfer costs

We build a general equilibrium model where this determines the (1)export, (2) FDI, and (3) technology transfer decisions of individualrms

The models predictions are tested using rm-level data


Related work

Intermediate inputs trade and its determinantsI Feenstra; Hanson, Mataloni, and Slaughter; Yi

The extent and consequences of o¤shoringI Blinder; Grossman and Rossi-Hansberg; Jensen and Kletzer; Levy andMurnane

Factor-cost versus market-access seeking FDII Brainard; Burstein and Monge-Naranjo

Gains from trade and FDI from multi-country GE modelsI Garetto; Irarrazabal, Moxnes, and Opromolla; Ramondo andRodriguez-Clare


A three-country world

There are three countries, East, West, and South, each endowed witha single factor, L

East and West are two identical Northern (N) countries, where thewage is wN

In South (S), the wage is given by wS , where wS < wN


Consumer preferences

Preferences in the Northern countries are

U =I

∑i

χiαlnZ

ω2Ωixi (ω)αdω

+

1∑

iχi

!lnY ,

where α = 1 1/σ and σ > 1

Consumers in the South buy only good Y

The di¤erence between wS and wN arises from productivitydi¤erences in Y production


Final good production

Firm ω in industry i produces its variety according to

xi (ω) = ψi expZ ∞

0βi (z) ln (m(ω, z)) dz

,

where m (ω, z) is the quantity of a variety-ω specic intermediate oftechnological complexity z

whereβi (z) = φi exp (φiz)

is the cost share of intermediate zI Low φi means industry i is on average technologically complex


Firm heterogeneity in productivity

Firms in the North draw their productivity level ϕ by paying an entrycost (as in Melitz)

This ϕ determines how e¢ cient the rm can produce theintermediates that go into its nal good variety ω

A Northern rm can produce any intermediate in East, West, or South


Determinants of the optimal sourcing decision

Firm productivity, ϕ

Wages in the North and the South, wS and wN

Trade costs; iceberg-typce τS from South to North, τN betweenNorthern countries

Costs of transferring the technological knowledge pertaining to theproduction of intermediate z


Intermediate goods ("tasks") production cost choice set

Choice set of a rm entering in the East of productivity ϕ producingintermediate z

Location Part of MNE Technology Labor costsEast Parent (HQ) ϕ wNWest A¢ liate ϕ exp(λN z) wNSouth A¢ liate ϕ exp(λS z) wS

We assume λS > λN > 0 : technology transfer costs to South arehigher than to North

High-z intermediates are more di¢ cult to o¤shore in that technologytransfer costs are higher

I Microfoundations for an idea by Arrow


Optimal Intermediate Production: onshore and o¤shore

Firms simply buys intermediate z from the lowest cost location


Intermediate good sourcing summarized

1 A¢ liates buy a greater range from South than parent rms2 A¢ liates buy a smaller range from parent rm as τN increases; parentexports become on average more technologically complex


Intermediate sourcing decisions imply marginal costs

A parent rm with productivity ϕ in industry i has marginal costs of

CPi (ϕ) =1ϕ

Southern a¢ liate prodnz | (ΓSi wSτS )

θi(zPS )

Parent prodnz | (wN )

1θi (zPS )

A Northern a¢ liate rm has marginal costs

CAi (ϕ) =1ϕ

Southern a¢ liate prodnz | (ΓSi wSτS )

θi(zAS )

Northern a¢ liate prodnz | ΓNi wN

θi (zAN )θi (zAS )

Parent prodnz | (τNwN )

1θi (zAN )

and the log a¢ liates cost share of intermediates imported from theparent is

lnh1 θi (zAN )

i= φi

λNln τN


A¢ liate sourcing and marginal costs: the impact oftechnological complexity

As trade costs to the parent increase, the a¢ liate will rely less onimported intermediates from the parent

This occurs less in technologically complex industries (low φi )[Hypothesis 1]

I Reason: In those industries tech transfer is di¢ cult so its hard tosubstitute for imports from parent

The a¢ liates marginal costs are increasing in trade costs to theparent

This occurs more so in technologically complex industriesI Reason: In those industries the a¢ liate cannot substitute easily too¤shore a¢ liate production


Multinational entry and sales across countries

Conditional on serving country k, k 2 fa¢ liate country, parentcountryg, local sales are inversely related to marginal costs

Rki (ϕ) = AiC ki (ϕ)

1σ,

where Ai is the endogenous mark-up adjusted demand level

Prots in country k are equal to scaled sales minus xed costs

πki (ϕ) =1σRki (ϕ) wN f ,

which denes a cut-o¤ productivity level ϕki needed to operatewithout making a loss


Intensive and extensive margin predictions

For given demand level Ai ,

Conditional on entry, local a¢ liate sales are declining in trade costs tothe parent

This rate of decrease is faster in technologically complex industries[Hypothesis 2]

The probability that a rm opens an a¢ liate is decreasing in tradecosts to the parent

This rate of decrease is faster in technologically complex industries[Hypothesis 3]


Trade costs and global production

Closing the model with the free entry condition allows comparative staticson trade costs

Proposition: A decrease in either τS or τN results in a decrease in ϕAiand an increase in ϕPi .

Lower trade costs leads to an increase in the range of rms engagedin FDI

A¢ liates use a wider range of intermediate inputs imported from theSouth


Model predictions to be tested

Hypothesis 1 (trade vs FDI): As trade costs to the parent increase,the a¢ liate will rely less on imported intermediates from the parent,particularly in technologically non-complex industries

Hypothesis 2 (intensive margin): A¢ liate sales are declining intrade costs to the parent, especially in technologically complexindustries

Hypothesis 3 (extensive margin): The probability that a rmopens an a¢ liate is decreasing in trade costs to the parent, especiallyin technologically complex industries

Hypothesis 4 (parent exports): A¢ liates buy a smaller range fromparent rm as τN increases, and parent exports become on averagemore technologically complex


The range and complexity of parent exports


Empirical strategy

We employ two distinct datasets to test these predictions

Firm-level data from the BEA Benchmark Survey of 1994 onI locations of U.S. a¢ liates and their sales to local customersI intra-rm trade between U.S. parent and each of its a¢ liatesI parent rm sales in the U.S., its R&D expenditures, and its industry

F for Hypotheses 1, 2, and 3

Product-level trade data from Census on the range and compositionof exports from parent to a¢ liate

I Combined with O*NET skill by occupation data andI Non-production versus production worker data

F for Hypothesis 4


Deriving the estimation equations

The log cost share of intermediates from the parent rm j to itsa¢ liate in country k is

ln1 θj (zAk )

=

φjλN

ln τk

where φj measures technological complexity, λN is the North techtransfer parameter, and τk are unit trade costs from US to country k

τk is measured by FCk , the cost of shipping between the US andcountry k

φj is specied as φj = δ0 + δ1RDj , where RDj is the R&D intensity ofrm j


Trade versus FDI equation

We estimate

lnMjk

TCjk= γj + κ lnXk +

δ0λN

+δ1λNRDj

lnFCk + εjk

The model implies that δ0/λN < 0 and δ1/λN > 0

FCk = ad-valorem measure of trade costs btw US and k (cif/fob)

RDj = Parent j [R&D expenditures/Sales]

Xk = GDP per capita, population, and corporate tax rate


A¢ liate activity at the intensive and extensive margin

Intensive margin: we estimate the following equation for local a¢ liatesales

lnRjk = ηj + ρ lnXk + (ς0 + ς1RDj ) lnFCk + εjk (1)

The model implies that ς0 < 0 and ς1 < 0

Extensive margin: linear probability model for the probability thatrm j opens an a¢ liate in country k, with the same regressors as inequation (1)


Summary statistics


Transport costs and the structure of US multinationals

Hypothesis 1Exports vs FDI

Hypothesis 2Intensive mg.

Hypothesis 3Extensive mg.

Dep. var.Import cost share

Dep. var.A¢ liate sales

Dep. var.A¢ liate y/n

FC -30.3 (2.34) -8.06 (1.17) -0.969 (0.060)RD FC 79.5 (24.4) -37.3 (13.1) -3.00 (0.472)GDPPC -0.798 (0.065) 0.903 (0.034) 0.062 (0.002)POP -0.197 (0.028) 0.495 (0.015) 0.027 (0.001)TAX -0.301 (0.124) -0.172 (0.064) 0.035 (0.030)# obs. 4,001 5,394 112,860Robust standard errors in parentheses


Robustness


Range and complexity of US parent exports

For the range, let SCOPEk be the share of the 500 six-digit NAICSindustries for which exports between US and their related foreignentities is positive

SCOPEk =1500

500

∑i=1(1jExik > 0)

We compute measures of average complexity of exports

TCPXk =1

SCOPEk

500

∑i=1TCPi (1jExik > 0)

where the complexity of the industry, TCPi , is measured based onI Occupations based (O*NET) data: importance of complex problemsolving skills

I Skill intensity based: ratio of non-production to production worker


Exports range and complexity results

Dep. var.SCOPE

Dep. var.TCPXk (Occptn)

Dep. var.TCPXk (SkillInt.)

FC3.65(1.38)

11.08(4.00)

0.75(0.26)

GDPPC0.03(0.03)

0.01(0.11)

0.01(0.01)

POP0.05(0.01)

0.13(0.05)

0.01(0.003)

TAX0.07(0.06)

0.48(0.18)

0.04(0.02)

Robust standard errors in parentheses; # of obs.: 39


Conclusions

Propose a mechanism in which technology transfer costs and tradecosts interact

Employ rm-level data to show that the model explainsI the choice of trade versus FDII intensive and extensive margin of a¢ liate operationI range and technological complexity of parent exports

remarkably well

Trends in o¤shoring should be understood in terms of changes oftrade versus technology transfer costs, together with wage di¤erences


Future work

Use US inward FDI data to test the models predictions on o¤shoringto the South

Quantify the models prediction on the geography of marginal costsarising from technology transfer costs

Empirical analysis of the gains from trade and FDI in a many-countryversion of the model

Incorporate the decision of integration (FDI) versus outsourcing toquantify the extent of international outsourcing


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