Firms and International Trade: Evidence, Theory, and Policy Implications

Marc J. MelitzDepartment of Economics and Woodrow Wilson School

Princeton University

Review of Empirical Evidence from Micro-Level Studies of Trade

1

Extent of Firm/Plant Heterogeneity Within Sectors

Distribution of �rm size: overall and within sector� Standard deviation of log sales

Country # of producers Overall Within Sector (52 Manufacturing Sectors)France 76,456 1.82 1.70Italy 39,704 1.33 1.29Spain 31,446 1.26 1.18

U.S. (plants) 224,009 1.67

Large levels of heterogeneity in other key performance measures� Productivity� Standard deviation of log value added per worker for U.S. plants:Overall: .75 Within 4-digit sectors (450 sectors): .66

� Heterogeneity in other key measures: capital/labor ratio, investment, R&D, ...

�! Does static heterogeneity matter for aggregate cross-sector effects (i.e. for `GE' �elds)?Maybe �rms in a sector tend to change in the same way over time, so can think of an `average�rm' response for the sector?

2

Extent of Firm/Plant Heterogeneity Within Sectors: Dynamics

� Evidence on job �ows:� In the U.S., on average each year, 1 in every 10 jobs are created and destroyed byentering, exiting, expanding, contracting �rms

� Less than 10% of these job �reallocations� re�ect shifts across 4-digit sectors� This pattern holds for almost all countries for which such jobs data is available

� Other plant performance measures:

3

Extent of Firm/Plant Heterogeneity Within Sectors: Dynamics

� Do these within-sector �rm �uctuations represent �white noise� that is irrelevant for generalequilibrium analysis?

� Should one still focus on the �average� �rm response in a sector (even though this representsless than 10% of the �rm-level variance)?

� Evidence on U.S. plant-level heterogeneity and business cycles:� Davis & Haltiwanger (QJE 1992) show that U.S. business cycle �uctuations can not beexplained by �average� �rm response

� Next: Evidence for trade

4

Trade and Plant-Level Performance

� Very few plants/�rms export:� 21% of U.S. �rms plants� 14.6% of U.S. �rms (exporting plants are more likely to be owned by multi-plant �rm)� 17.4% of French �rms� Same pattern holds for both developed and developing countries

� Partitioning of �rms by export status occurs within narrowly de�ned sectors:

5

Trade and Plant-Level Performance (Cont.)

� Export intensity among exporting plants/�rms is typically very low:

6

Trade and Plant-Level Performance (Cont.)Are exporters different than non-exporters in the same sector?

All columns include 4-digit sector and state controls. Columns (d)-(f) add control for plant size (total employment)7

Trade and Plant-Level Performance (Cont.)Are exporters different than non-exporters in the same sector?

Ratio of productivity to mean within 4-digit sector 8

Trade and Plant-Level Performance (Cont.)

Causality of link between export status and productivity� Strong evidence for self-selection of more productive �rms into exporting� Colombia, Mexico, and Morocco: Clerides, Lach, and Tybout (1998, QJE)� U.S.: Bernard and Jensen (1999, JIE)� Taiwan: Aw, Chen, and Roberts (2001, JDE)

� Mixed evidence for �learning-by-exporting�� Some evidence in growing, developing countries (India, Sloevenia)

� However, exogenous causality from either export status or productivity is suspect:� New evidence shows that �rms make joint decisions concerning both export participationand technology use:� Bustos (2006 WP): Adoption of new technology & spending on new technology(Argentina)� Verhoogen (2006 WP): ISO 9000 certi�cation (Mexico)� Tre�er (2007 WP): One time productivity improvement (Canada)

9

Trade and Plant-Level Performance (Cont.)

Evidence on determinants of plant death (U.S. plants, over 5 year period)From Bernard & Jensen (ReStat, forthcoming):� Unconditionally, export status is associated with 12.6% reduction in probability of death� This is a very large number: Overall probability of death is 27%

� This is not driven only by higher productivity of exporters (low productivity is an importantsigni�cant predictor of exit):� Conditional on a full set of industry and �rm controls (productivity, size, capital-laborratio, ...), export status is still associated with a signi�cant 5-6% reduction in probabilityof death.

� Strong suggestive evidence for sunk costs of exporting

� Other effects of plant structure on probability of death:� Multi-product plants (lower conditional probability of death)� Ownership Structure also matters:

� Multi-plant �rm� Multinational �rm� Recent takeover� ... are associated with a higher conditional probability of death� (though lower overall death probability due to other observable characteristics)

10

Trade and Plant-Level Performance: Reallocations

Evidence for U.S. (Bernard & Jensen, 2002 WP):� Although exporter productivity does not grow faster than non-exporters

� Exporters grow faster than non-exporters (in terms of both shipments and employment)

� �! Explains 40% of U.S. manufacturing TFP growth� Half of this reallocation occurs within sectors

� Other suggestive evidence linking trade liberalization and productivity growth driven byreallocations:� Mexico: Tybout & Westbrook (1995 JIE)� Taiwan: Aw, Chen, & Roberts (2000 WBER)� Chile: Pavcnik (2002 ReStud)

� 19.3% productivity growth in manufacturing during 1979-1986� Contribution of 6.6% from increased productivity within plants� Contribution of 12.7% from reallocation towards more ef�cient producers

11

Direct Evidence for Effects of Trade Liberalization

Evidence for U.S. Manufacturing (Bernard, Jensen, & Schott, JME 2006)� Construct measure of U.S. trade costs by 4-digit sector over time (on import side)� Captures both �transport costs� (freight and insurance) and �policy barriers� (dutiesimposed)

� Enough variation over time and sectors to control for both 4-digit sector effects and yeareffects

� Test for effect of changing trade costs on industry productivity (within sector)

12

Trade Liberalization and Industry ProductivityEvidence for U.S. Manufacturing (Bernard, Jensen, & Schott, JME 2006):

13

Trade Liberalization and Reallocations: Market Entry and Exit

Plant-level estimations for high intra-industry trade sectors:� Effect on plant death:� Lower trade costs substantially increases the death probability for non-exporting plants:� A .9% trade cost decrease per year (a one standard deviation change) leads to a 3.7%increase in the probability of death. (Average probability of death in the sample is 26.8%)

� Probability of death for exporters increases by .2%

� Effect on export market entry:� Lower trade costs substantially increases the probability of export market entry fornon-exporters

� A .9% trade cost decrease per year (a one standard deviation change) leads to a 5.8%increase in the probability of exporting. (Average probability of becoming an exporter inthe sample is 27%)

�!These reallocations are driving an important part of the previously measured industryproductivity gains

14

Transitions Into and Out-of Exporting� Export market entry by existing non-exporters have important macroeconomic conse-quences� 40% (U.S.) to more than 50% (Colombia, Mexico) of export increases are driven by theentry of plants into the export market

� In an average year, 13.9% of U.S. plants begin exporting and 12.6% of exporters dropout of the export market

� Kehoe and Ruhl (2003 WP) �nd that newly traded goods account for a substantialamount of the increased trade following trade liberalization

1820

2224

2628

Log 

Impo

rts

7 8 9 10 11 12Log Number of Imported Varieties

­1­.5

0.5

1Im

ports

 Ann

ual G

row

th (d

etre

nded

)

­.4 ­.2 0 .2 .4Imported Varieties Annual Growth (detrended)

15

Export Destinations� Exporting is not just a binary decision: A �rm decides where to export and how many exportdestinations to serve:

AFG ALB

ALG

ANG

ARG

AUL

AUT

BAN

BEL

BEN

BOL

BRA

BUL

BUK

BUR

CAM CAN

CEN

CHACHI CHNCOL

COS

COT

CUB

CZE

DEN

DOMECU

EGY

ELS

ETH

FIN

FRA

GEE

GER

GHA

GRE

GUAHON

HOK

HUNIND

INO

IRN

IRQ

IREISR

ITA

JAM

JAP

JOR

KEN

KORKUW

LIB

LIY

MAD

MAW

MAYMAL

MAUMAS MEX

MOR

MOZ

NEP

NET

NZE

NIC

NIGNIA

NOR

OMA PAKPAN

PAP

PAR

PERPHI

POR

ROMRWA

SAUSEN

SIE

SIN

SOM

SOU

SPA

SRI SUD

SWE

SWI

SYRTAI

TAN

THA

TOG

TRI

TUN

TUR

UGA

UNKUSA

URUUSR

VEN

VIE

YUGZAI

ZAMZIM

1010

010

0010

000

1000

00N

 exp

orte

rs

1 10 100 1000 10000Market Size ($ billions)

Source: Eaton, Kortum, and Kramarz (AER 2004, P&P)

16

Export Destinations � with Control for Geography and Demand Conditions

AFGALB

ALG

ANG

ARG

AUL

AUT

BAN

BEL

BEN

BOL

BRA

BUL

BUK

BUR

CAM CAN

CEN

CHACHI CHNCOL

COS

COT

CUB

CZE

DEN

DOMECU

EGY

ELS

ETH

FIN

FRA

GEE

GER

GHA

GRE

GUAHON

HOK

HUNIND

INO

IRN

IRQ

IREISR

ITA

JAM

JAP

JOR

KEN

KORKUW

LIB

LIY

MAD

MAW

MAYMAL

MAUMAS MEX

MOR

MOZ

NEP

NET

NZE

NIC

NIGNIA

NOR

OMA PAKPAN

PAP

PAR

PERPHI

POR

ROMRWA

SAUSEN

SIE

SIN

SOM

SOU

SPA

SRISUD

SWE

SWI

SYRTAI

TAN

THA

TOG

TRI

TUN

TUR

UGA

UNKUSA

URUUSR

VEN

VIE

YUGZAI

ZAMZIM

1010

010

0010

000

1000

00N

 exp

orte

rs

1 10 100 1000French Firms Market Size ($ billions)

Source: Eaton, Kortum, and Kramarz (AER 2004, P&P)17

Number of Export Destinations

18

Multiple Export Destinations: Firm Characteristics

Are �rms serving multiple export markets different?

19

Multiple Export Destinations: Firm Characteristics

Are �rms serving multiple export markets different?

20

Review of Some Theoretical Models

21

Ricardian Models: Cross-Country Differences in Technology

Eaton-Kortum Model: Multi-Country Extension of DFS (AER 1977) with StochasticTechnology Draws (Ecma 2002; AER 2003 with Bernard & Jensen)� Fixed set of goods that can be produced in any country

� Production technology:� Aggregate differences across countries combined with idiosyncratic advantage/disadvantagefor particular goods (stochastic draw)

� Equilibrium:� Goods with bad technology draws are not produced and imported� Goods with good technology draws are produced and exported� Goods with intermediate draws are produced but not exported

� They are sheltered from import competition by trade costs� Model allows for a very �exible pattern of bilateral trade costs (requiring only atransitivity rule)

� Factor prices adjust to compensate for aggregate technology differences

� Model therefore explains why goods produced with better technologies are exportedwhereas goods with inferior technology may be produced but not exported

� Model emphasizes competition to produce a given good across countries and the effects oftrade costs (along with the key stochastic technology differences)

22

Monopolistic Competition Models with Firm-Level Fixed Costs and EndogenousEntry

� These models neglects competition to produce an individual variety

� Instead, models emphasize:� Firm/product level costs that determine �rm size� Key endogenous entry mechanism of monopolistic competition

� These models can be extended to incorporate additional �rm-level decisions:� Multinationals: horizontal and vertical FDI� Choice of technology and innovation� Expansion of product line

23

Firm Heterogeneity and Trade Induced Reallocations

The Impact of Trade on Intra-Industry Reallocations and Aggregate IndustryProductivity by Melitz (Ecma 2003)� Each �rm produces its own �variety� of a manufactured good.

� Developing this variety and one time production setup costs entail a sunk entry cost

� Following entry, �rms observe their productivity level� Prior to entry, only distribution of potential productivity levels is known (and commonacross �rms)

� Firms also face a �xed overhead production cost

� Exporting involves both a standard �per-unit� trade cost as well as a �xed export cost

� An entering �rm decides whether to produce (or exit) and then whether to export (or onlyserve its domestic market)

24

Equilibrium

0 Φ

Dπ

Xπ

Xf−Df−

(productivity)XΦDΦ

π

25

Equilibrium

0 Φ

Dπ

Xπ

Xf−Df−

(productivity)XΦDΦ

π π

26

Equilibrium: Inter-Firm Reallocations

0 Φ

Dπ

Xπ

Xf−Df−

(productivity)XΦDΦ

πAπ

ADΦ

π

27

Trade Liberalization

� Forces least productive �rms to exit

� Re-allocates market shares towards more productive �rms� Resulting in higher average productivity

� Welfare gains� Combination of higher average productive and an ambiguous effect of product variety

28

Policy Implications

29

Policy Implications

� Policies generate substantial inter-�rm reallocations � even within sectors� ... as �rms respond differently to same policy

Trade Liberalization� Induces substantial re-allocations that are not re�ected in sector-wide statistics� Short run transition costs may thus be under-estimated� Resistance to trade liberalization may be linked in part to greater uncertainty concerningjob tenure

� Challenge for trade policy associated with trade liberalization:� Want to cushion harshest shocks along transition� ... yet also need to allow re-allocations to proceed� �! This is what delivers long run gains to trade� ... and these gains can be more than just a more ef�cient allocation of market sharesacross �rms�

30

Policy Implications

� Firm-level trade barriers are substantial

� Need to understand how trade barriers affect �rm/product level export decision

� Sunk export market entry costs are substantial:� US $350K-$430K for Colombian manufacturing plants� Uncertainty greatly magni�es the effects of such sunk costs� Induces long transition dynamics

� Over 10 years, even for correctly perceived permanent changes in policy

� Information is an important component of trade barriers� Only way to explain large and persistent effect of distance on trade� Also explains large common language effect on trade

� Regulation costs substantially affect the extensive margin of trade� Time to process through customs� # of documents and signatures required� The effects of such costs are magni�ed when they occur at both ends of a tradingrelationship

31

Policy Implications: Regulation Costs of Trade

Relationship Between Unexplained Propensity to Trade (Import) and Regulation Costs

AFG

ALB

DZA

AGO

ARG

AUSAUT

BGD

BEL

BTN

BOL

BRA

SLB

BGR

BDI

KHM

CMR

CAN

CAF

LKA

TCD

CHLCHN COL

COG

CRI

BEN

DNK

DOM

ECU

SLV

FJI

FIN

FRA

GHA

KIR

GRC

GTM

GINGUY

HTIHND

HKG

HUN

ISL

IND

IDN

IRN IRQ

IRL

ISR

ITA

CIV

JAM

JPN

JOR KEN

KOR

KWT

LAO

LBN

MDG

MWI

MYS

MDVMLI

MRT

MUS

MEX

MNG

MAR

MOZ

OMN

NPL

NLD

NZL

NIC

NER

NGA

NORPAK

PNGPRY

PER

PHL

POL

PRT

ROU

RWA

SAU

SEN

SLE

SGP

VNM

ZAF

ZWE

ESP

SDN

SWECHE

SYR

THA

TGO

ARE TUNTUR

UGA

EGY

GBR

TZA

USA

BFA

URY VEN

YEM ZMB

­20

24

6Im

porte

r Fix

ed E

ffect

50 100 150# days to import

Note: 1 unit of �xed effect represents an average 15% probability of trade with a given trade partner

32

Policy Implications: Regulation Costs of Trade

Relationship Between Unexplained Propensity to Trade (Import) and Regulation Costs:Controlling for real GDP and GDP per capita

DNK

SWE

DOM

SGP

SEN

FINNOR

CHN

MOZ

KOR

NLD

NPL

PHL

ESP

TZA

AUT

SLE

BEL

LKA

MRT

MUS

FJI

TGO

MWIJAM

ISR

THAIDNBEN

PAK

MLIIRL

EGY

USA

MYS

JPN

NGA

HTI

NZLUGAPNG

MDG

IND

CHLGHA

PRT

BFA

JOR

TUR

ZMB

CAN

MAR

PRY

BGD

NIC

URY

ISL

HND

KEN

GTM

HKG

PER

ROU

CIV

POL

TUN

GBR

BOL

AUSGUY

MEX

HUN

NER

GIN

ECU

AGOCOG

CRI

RWA

CMR

ARG

SLV

ZAF

BDI

TCDCOL

ZWE

FRA

IRN

SYR

CHE

VENBRA

GRC

DZA

CAF

ITA

­2­1

01

2e(

 imp_

fe | 

X )

­1 ­.5 0 .5 1e( limp_time | X )

coef = ­.61246452, se = .14787213, t = ­4.14

Note: 1 unit of �xed effect represents an average 15% probability of trade with a given trade partner 33

Policy Implications

Interaction between trade and other policies with heterogeneous effects across �rms� Credit market imperfections� Affects smaller �rms � and generates signi�cant changes in trade patterns across sectorswith different levels of external �nance dependence

� This shows up in sectoral trade patterns (both extensive and intensive margins) and inproduct churning rates

� Labor market �exibility� Affects link between trade liberalization and unemployment in non-monotonic ways� Differences in labor market �exibility become a source of comparative advantage whensectors exhibit different intrinsic levels of �rm-level volatility

34

Policy Implications: Labor Market Flexibility and Comparative Advantage

ARG

AUS

AUT BEL

CAN

CHECZE

DEU

DNK

ESP

FINFRAGBR

GRC

HKG

IRL

ISR

ITA

JPNKOR

KWT

NLD

NOR

NZL

OMN

PRT

SAU

SGP

SVN

SWE

USA

0.0

1.0

2.0

3.0

4.0

5A

vera

ge P

urge

d C

ount

ry V

olat

ility

20 40 60 80 100Labor Market Flexibility

35

Policy Implications: Labor Market Flexibility and Comparative Advantage

AUS

AUT BEL

CANDEU

DNK

ESP

FINFRA

GBR

GRC

IRL

ITA

JPN

NLD

NOR

NZL

PRTSWE

TUR

USA

­.01

0.0

1.0

2.0

3A

vera

ge P

urge

d C

ount

ry V

olat

ility

20 40 60 80 100Labor Market Flexibility

36