Trade Liberalization and Regional Dynamics · Contributions I Literature nding substantially di...

Trade Liberalization and Regional Dynamics

Rafael Dix-Carneiro1 Brian K. Kovak2

1Duke UniversityNBER and BREAD

2Carnegie Mellon University - Heinz CollegeNBER and IZA

Conference on Inequality, Globalization and MacroeconomicsUniversity of Southern California

April 29, 2017

Regional Effects of Trade

I Freer trade generates overall economic gains but is also likelyto create winners and losers (Stolper and Samuelson 1941)

I 60 years of work examining trade’s effects on workers withdifferent skills or in different industries

I Starting late 2000s: trade has vastly different effects onworkers in different local labor markets

I Effects determined by regional industry mix

I Trade’s costs and benefits are unevenly distributedgeographically, not just across industries or skills

Slow Adjustment to Trade

I No / Perfect mobility in trade theory: short- / long-runmodels

I Policy makers: what happens in the short- to medium-run?How do we get to the long run?

I Recent work on transitional dynamics of trade liberalizationI Kambourov (2009), Artuc, Chaudhuri and Mclaren (2010), Cosar

(2013), Dix-Carneiro (2014), Caliendo, Dvorkin and Parro (2015),

Helpman and Itskhoki (2015), Traiberman (2016), Bellon (2016),

and many others.I Structural estimation/calibration followed by simulation

I We document observed dynamics of adjustment followingreal-world trade liberalization

Contributions

I Literature finding substantially different effects of tradeshocks across local labor markets

I Topalova (2007), Kovak (2013), Autor, Dorn and Hanson (2013),and many others

I Effects estimated over windows of 7/10 years.

I We estimate the evolution of the local effects of the early1990s Brazilian trade liberalization

I Discrete liberalization shock → empirical labor market dynamicsI Compare existing medium-run estimates to short- and long-run

Brazilian Trade Liberalization

Tariff Changes 1990-1995

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

Chan

ge in

ln(1

+tar

iff),

1990

-95

Agric

ultu

re

Met

als

Appa

rel

Food

Pro

cess

ing

Woo

d, F

urni

ture

, Pea

t

Text

iles

Nonm

etal

lic M

iner

al M

anuf

Pape

r, Pu

blish

ing,

Prin

ting

Min

eral

Min

ing

Foot

wear

, Lea

ther

Chem

icals

Auto

, Tra

nspo

rt, V

ehicl

es

Elec

tric,

Ele

ctro

nic

Equi

p.

Mac

hine

ry, E

quip

men

t

Plas

tics

Oth

er M

anuf

.

Phar

ma.

, Per

fum

es, D

eter

gent

s

Petro

leum

Refi

ning

Rubb

er

Petro

leum

, Gas

, Coa

l

Empirical Approach

I Follow Kovak (2013): trade-induced labor demand shocks

Regional Tariff Reductions

RTRr = −∑i

βrid ln(1 + τi )

βri ≡λri

1ϕi∑

j λrj1ϕj

I i : industryI τi : tariff rate in industry iI d : long difference from 1990-1995I λri : share of regional employment in industry iI ϕi : 1 minus labor share of value added

Regional Tariff Reductions

BelémBelém

RecifeRecife

ManausManaus

CuritibaCuritiba

BrasíliaBrasília

SalvadorSalvador

FortalezaFortaleza

São PauloSão Paulo

Porto AlegrePorto Alegre

Belo HorizonteBelo Horizonte

8% to 15%4% to 8%3% to 4%1% to 3%-1% to 1%

90-10 gap ≈ 0.10

Data Description

Administrative Data: RAIS

I Census of Brazilian formal labor market

I Establishment-level informationI geographic location (municipality), industry, employment

I Worker-level informationI gender, age, education (9 categories), earnings

I Years: 1986-2010

Empirical Approach

Compare evolution of outcomes across regions facing larger vs.smaller tariff cuts

yrt − yr ,1991 = θtRTRr + αst + γt(yr ,1990 − yr ,1986) + εrt ,

I yrt : value of region r outcome in post-lib year t

I αst : state fixed effects

I θt : effect of liberalization on change in outcome by year t.

I RAIS analysis also includes pre-liberalization outcome trend control,(yr,1990 − yr,1986)

I OutcomesI formal employment

I formal earnings premium: µrt from ln(earnjri ) = µrt + φit + Xjtβt + ejrit

ResultsEmployment

-‐6.5

-‐5.5

-‐4.5

-‐3.5

-‐2.5

-‐1.5

-‐0.5

0.5

1.5

1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Pre-‐liberaliza6on (chg. from 1986)

Liberaliza6on Post-‐liberaliza6on (chg. from 1991)



ResultsEarnings

-‐2.0

-‐1.5

-‐1.0

-‐0.5

0.0

0.5

1.0

1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010



Dynamics in Labor Demand

I r = 1, ...,R regions and i = 1, ..., I industries

I CRS Cobb-Douglas production (shares may vary by i)

Yri = AriL1−ϕiri

(T ζi

ri K1−ζiri

)ϕi

where ϕi , ζi ∈ (0, 1)

I Lr labor, perfectly mobile between industries within regionsI Tri fixed factor (e.g., resources), specific to region and industryI Kri capital, specific to region and industry, may change through

depreciation and investment

I Ari region-industry Cobb-Douglas productivity shifter

I Competitive markets. Exogenous output price Pi

I Examine effects of changing vector of output prices (liberalization)

Dynamics in Labor Demand

I Factor market clearing, zero profits, and cost minimizationimply equilibrium relation

wr =∑i

βri Pi +∑i

βri Ari − δr

(Lr −

∑i

λri (1− ζi )Kri

)

where βri ≡λri

1ϕi∑

j λrj1ϕj

and δr ≡1∑

k λrk1ϕk

.

Dynamics in Labor DemandEvidence for Slow Capital Adjustment

Number of formal establishments proxy for regional capital stock

-‐5

-‐4

-‐3

-‐2

-‐1

0

1

2

1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010



Establishment Size

Establishments


Estab. Size Pretrend

Establishments Pretrend


Immediate investment response, slow depreciation response

-‐3

-‐2

-‐1

0

1

2

3

4

5

1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Exit

Entry



Exit Pretrend

Entry Pretrend

Exit

Entry


Exit Pretrend

Entry Pretrend


Immediate investment response, slow depreciation response

-‐4

-‐3

-‐2

-‐1

0

1

2

3

4

5

1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Job Crea)on

Job Destruc)on



Job Crea)on Pretrend

Job Destruc)on Pretrend

Job creation and destruction defined as in Davis and Haltiwanger (1990)

Dynamics in Labor DemandEvidence for Agglomeration Economies

I Assume in the long run...I Constant elasticity agglomeration function

(Glaeser Gottlieb 2008, Kline Moretti 2014):

Ari = κLr

I Constant elasticity labor supply:

Lr =1

ηwr

I Perfectly mobile capital

Rr = R, ∀r


I Imposing these assumptions yields the following expressions

wr =η

η[1 − ϕ(1 − ζ)] − κ+ ϕζ

∑i

βri Pi −ϕ(1 − ζ)η

η[1 − ϕ(1 − ζ)] − κ+ ϕζR

Lri =1

ϕζPi−

1

ϕζ·

η[1 − ϕ(1 − ζ)] − κ

η[1 − ϕ(1 − ζ)] − κ+ ϕζ

∑i

βri Pi−ϕ(1 − ζ)

η[1 − ϕ(1 − ζ)] − κ+ ϕζR

I Test for agglomeration economies

Lri = γ0 + γ1Pi + γ2RTRr + εri

γ2 < 0 ⇒ κ > 0


Test for agglomeration economies

Change in log Region x Industry Employment: All industries Tradable industries Tradable industries(1) (2) (3)

Regional tariff reduction (RTR) -‐6.183*** -‐6.708*** -‐6.704***(0.631) (0.675) (0.694)

Industry price change controls ✓ ✓Industry fixed effects (20) ✓

Observations 4,648 4,174 4,174R-‐squared 0.119 0.120 0.222

γ2 < 0⇒ κ > 0, i.e. agglomeration economies are present

Dynamics in Labor DemandQuantification

I Estimating agglomeration elasticity, κ

I Estimate 1/η from Lr = (1/η)wr , with RTR as IV for wr

I Estimate κ using non-linear least squares from each of

wr =η

η[1 − ϕ(1 − ζ)] − κ+ ϕζ

∑i

βri Pi −ϕ(1 − ζ)η

η[1 − ϕ(1 − ζ)] − κ+ ϕζR

Lri =1

ϕζPi −

1

ϕζ·

η[1 − ϕ(1 − ζ)] − κ

η[1 − ϕ(1 − ζ)] − κ+ ϕζ

∑i

βri Pi −ϕ(1 − ζ)

η[1 − ϕ(1 − ζ)] − κ+ ϕζR

Bootstrap entire procedure to account for correlation between η and κ

Dynamics in Labor DemandQuantification

Agglomeration elasticity estimates

Panel A: Inverse labor supply elasticity (η) 0.363***(0.060)

Panel B: Agglomeration elasticity (κ)(1) (2) (3)

Specific factors' share of non-labor inputs (ζ): low (0.152) mid (0.349) high (0.545)

Wage-based agglomeration elasticity (κ) 0.042* 0.188*** 0.333***(0.023) (0.023) (0.025)

Employment-based agglomeration elasticity (κ) 0.215*** 0.330*** 0.461***(0.032) (0.038) (0.043)

I Estimates within range of prior literature (Melo et al. 2009)

I Kline and Moretti (2014) find 0.2

Summary

ContributionsI Empirically describe the dynamics of labor market transition in

response to trade liberalizationI Dynamic context for existing static regional resultsI Challenge conventional wisdom on equalizing migration

I Mechanism that qualitatively and quantitatively explainsgrowing effects

I Finite elasticity of regional labor supplyI Agglomeration economiesI Slow adjustment of complementary factors

I Benefits and costs from trade liberalization unevenlydistributed across space for years after liberalization

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