trade liberalization and regional dynamics · contributions i literature nding substantially di...
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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)
Liberaliza6on Post-‐liberaliza6on (chg. from 1991)
Liberaliza6on Post-‐liberaliza6on (chg. from 1991)
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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
Pre-‐liberaliza6on (chg. from 1986)
Liberaliza6on Post-‐liberaliza6on (chg. from 1991)
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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)
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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
.
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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
Pre-‐liberaliza5on (chg. from 1986)
Liberaliza5on Post-‐liberaliza5on (chg. from 1991)
Establishment Size
Establishments
Liberaliza5on Post-‐liberaliza5on (chg. from 1991)
Estab. Size Pretrend
Establishments Pretrend
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Dynamics in Labor DemandEvidence for Slow Capital Adjustment
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
Pre-‐liberaliza5on (chg. from 1986)
Liberaliza5on Post-‐liberaliza5on (chg. from 1991)
Exit Pretrend
Entry Pretrend
Exit
Entry
Liberaliza5on Post-‐liberaliza5on (chg. from 1991)
Exit Pretrend
Entry Pretrend
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Dynamics in Labor DemandEvidence for Slow Capital Adjustment
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
Pre-‐liberaliza5on (chg. from 1986)
Liberaliza5on Post-‐liberaliza5on (chg. from 1991)
Job Crea)on Pretrend
Job Destruc)on Pretrend
Job creation and destruction defined as in Davis and Haltiwanger (1990)
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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
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Dynamics in Labor DemandEvidence for Agglomeration Economies
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
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Dynamics in Labor DemandEvidence for Agglomeration Economies
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
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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
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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
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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