Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Trade, Migration and Regional Income Differences: Evidence from China Trevor Tombe University of Calgary
Xiaodong Zhu University of Toronto and SAIF
Department of Economics, Yale
October 7, 2014
1 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Motivation • Aggregate gains from trade widely studied • What about spatial distribution of gains from trade? • Aggregate and spatial effects of trade liberalization depend on
costs to internal trade and factor movements • How large are internal trade and migration costs? Do they differ across space? ... change through time? .. interact with each other?
• To answer these questions, we develop a model and apply it to
a useful setting (China) • Significant recent liberalizations (internal and external) • Large inter-province worker flows (40M in 2005; 86M in 2010) • Massive internal income differences
1 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Related Literature • International trade with multi-region countries: • Henderson (1982), Rauch (1991), Bond (1993), Courant and Deardorff (1993), Krugman and Livas Elizondo (1996), Matsuyama (1999), and Venables and Limao (2002)
• Costly Internal Trade (no labour frictions): • Ramondo et al. (2011); Allen and Arkolakis (2012); Cosar and Fajgelbaum (2012); Caliendo et. al. (2014); Redding (2014); Fajgelbaum and Redding (2014); Tombe and Winter (2014)
• Trade Induced Labour Reallocation (no internal trade): • Kambourov (2009); Artuc et al. (2010); Menezes-Filho and Muendler (2011); Cosar (2013); Dix-Carneiro (2014)
• Commuting Decisions: • Ahlfeldt, Redding, Sturm, and Wolf (2012)
• Occupational Choice: • Cortes and Gallipoli (2014) 2 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
This Paper • Build unique dataset for China: 2000/02 – 2005/07 • We develop a general equilibrium model of internal and
external trade with goods and factor market frictions • We introduce factor mobility frictions: model migration decisions (Artuc et al., 2008; Ahlfeldt et al., 2012; Redding, 2014; Cortes and Gallipoli, 2014)
• Measure and quantify the effect of (1) international trade
liberalization, (2) internal trade liberalization, (3) factor market liberalization, (4) productivity change on: • Welfare — aggregate and regional • Migration — between provinces • Income Differences — between provinces 3 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Data (in brief) • Migration: 2000 and 2005 census data • From 2005 census, we can identify for each province those who have immigrated between 2000 and 2005 • Individual earnings data (2005 only) will prove important
• Trade Flows: Extended regional I/O tables 2002 and 2007 • Information on international trade for each province and bilateral trade for each pair of provinces (2002) or regions (2007) • Province-level gross output and total expenditures
• Real Income: Price and GDP data • Nominal GDP by provinces • Province-specific price levels • 1990 common basket price levels + provincial CPI changes
4 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Visualizing Key Features of the Data Figure: The Geography of China
Heilongjiang
Inner Mongol
Jilin Liaoning
Xinjiang
Beijing Tianjin Shanxi Hebei
Ningxia Qinghai
Shandong Gansu
Shaanxi
Tibet
Henan Hubei
Sichuan
Jiangsu Anhui Shanghai Zhejiang
Guizhou
Hunan Jiangxi Fujian
Yunnan Guangxi Guangdong
Hainan
Table
5 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Visualizing Key Features of the Data Figure: Output per Capita (90th/10th ∼ 7)
Heilongjiang
Inner Mongol
Jilin Liaoning
Xinjiang
Beijing Tianjin Shanxi Hebei
Ningxia Qinghai
Shandong Gansu
Shaanxi
Tibet
Henan Hubei
Sichuan
Jiangsu Anhui Shanghai Zhejiang
Guizhou
Hunan Jiangxi Fujian
Yunnan Guangxi Guangdong
Hainan
Table
6 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Visualizing Key Features of the Data Figure: Home-Share of Spending (90th=0.86, 10th=0.62 )
Heilongjiang
Inner Mongol
Jilin Liaoning
Xinjiang
Beijing Tianjin Shanxi Hebei
Ningxia Qinghai
Shandong Gansu
Shaanxi
Tibet
Henan Hubei
Sichuan
Jiangsu Anhui Shanghai Zhejiang
Guizhou
Hunan Jiangxi Fujian
Yunnan Guangxi Guangdong
Hainan
Table
7 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Visualizing Key Features of the Data Figure: Migrant Worker Shares (90th=0.2, 10th=0.006)
Heilongjiang
Inner Mongol
Jilin Liaoning
Xinjiang
Beijing Tianjin Shanxi Hebei
Ningxia Qinghai
Shandong Gansu
Shaanxi
Tibet
Henan Hubei
Sichuan
Jiangsu Anhui Shanghai Zhejiang
Guizhou
Hunan Jiangxi Fujian
Yunnan Guangxi Guangdong
Hainan
Table
8 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Table: Migrant Characteristics (from Census Data)
Total Migrants Inter-Provincial Migrants Inter-Provincial Migrant Workers
1990
2000
2005
32.7 M 10.5 M 2M
130.6 M 35.8 M 28 M
165.4 M 53 M 40 M
(a) Migrant Stock All Migrants Number 165.4 M Reason for Migrating Work 45% Family 30% Education 6% Other 18% Other Characteristics With Children 30% Agricultural Hukou 62% Male 50%
Inter-Provincial Migrants
Employed Inter-Provincial Migrants
53 M
40 M
73% 21% 2% 4%
91% 6% 2% 0.3%
28% 83% 53%
27% 86% 57%
(b) Characteristics of Migrant Stock (Census 2005) 9 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Migration Costs Wide variety of very large costs to live outside one’s Hukou region: • Lack of employment contracts (no provision of benets or other
legal rights; reform 2007) • Difficult to find housing (couldn’t rent an apartment in Beijing
until 2005) • Unregistered migrants detained/deported (until 2003,
following a death) • Limited health insurance access • Children attend school barred or expensive fees (can be 20% of
income) • Other (more standard) costs: • communication with and travel to home province • language/ethnic dierences
10 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Internal Trade Barriers Pre-2001: • Strong local protectionism and high internal trade barriers in
the 1980s and 1990s (Young, 2000; Poncet, 2003) • The degree of local market protection is positively associated
with the size of the state sector in the region Post-2001: • Downsizing the state-owned sector • State council’s directive about eliminating local market
protection in 2001
11 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Main Results
• Welfare gains are, by far, largest for domestic reforms
(especially internal trade cost reductions) • Trade flows respond very little to changes in migration costs • Internal migration responds very little to changes in trade costs • Internal (not external) liberalization lowers income differences
12 / 36
Model
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Regions and Preferences • N + 1 regions: N within China + rest of the world • Endowments: • L0n initial Hukou registrants • Each of whom differ in productivity (more on this later) • Sn fixed land used for housing and production
• Representative H.H. Objective: • Maximize utility per effective-worker
un = cnα su1−α n subject to Pn cn + rn sun ≤ vn
13 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Production • Final Good: composite of a continuum of intermediates
ˆ Yn =
1
yn (j)(σ−1)/σ dj
σ/(σ−1)
0
• Elasticity of substitution σ > 1 • Final goods are consumed (C ) and used in production as
inputs (Q); market clearing ⇒ Yn = Cn + Qn • Tradable Intermediates: y produced with CRS technology
using effective-labour (H), land (SY ), and inputs (Q) yn (j) = ϕn (j)Hn (j)β SYn (j)η Qn (j)1−β−η • TFP ϕ differs across firms; as in Eaton and Kortum (2002)
14 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Prices and Trade Patterns • Iceberg trade costs τni + perfect competition ⇒
pni (ϕ) = τni MCi (ϕ) ∝ τni wiβ riη Pi1−β−η /ϕ
15 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Prices and Trade Patterns • Iceberg trade costs τni + perfect competition ⇒
pni (ϕ) = τni MCi (ϕ) ∝ τni wiβ riη Pi1−β−η /ϕ −θ • With TFP ϕ distributed Frechet: Fi (ϕ) = e −Ti ϕ , fraction of
region n spending allocated to goods produced in region i is −θ Ti τni wiβ riη Pi1−β−η πni = −θ PN+1 β η 1−β−η T τ w r P k nk k=1 k k k
15 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Prices and Trade Patterns • Iceberg trade costs τni + perfect competition ⇒
pni (ϕ) = τni MCi (ϕ) ∝ τni wiβ riη Pi1−β−η /ϕ −θ • With TFP ϕ distributed Frechet: Fi (ϕ) = e −Ti ϕ , fraction of
region n spending allocated to goods produced in region i is −θ Ti τni wiβ riη Pi1−β−η πni = −θ PN+1 β η 1−β−η T τ w r P k nk k=1 k k k • Aggregate price index in region n (for tradables)
Pn ∝
"N+1 X
Tk
τnk wkβ rkη Pk1−β−η
−θ
#−1/θ
k=1
• Finally, market clearing for land ⇒ rn ∝ wn Hn /Sn 15 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Regional Income • Nominal Income (Expenditures) per Effective Worker:
w n + ηwn /β + |(1 − α)v{z | {zn } } Labour Income Spending on Land β+η wn = αβ
vn =
• Total expenditures: Xn = vn Hn
16 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Regional Income • Nominal Income (Expenditures) per Effective Worker:
w n + ηwn /β + |(1 − α)v{z | {zn } } Labour Income Spending on Land β+η wn = αβ
vn =
• Total expenditures: Xn = vn Hn • Real Income per Effective Worker (vn /Pnα rn1−α ): α
−
α
η+(1−α)β
(S /H ) β+η Tnθ(β+η) π θ(β+η) · · | {z } | nn{z } | n n{z } Vn ∝ Technology Market Access Land / effective worker 16 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Inter-Provincial Migration • Real Income per Effective Worker: Vi in region i • Worker Productivity: different across region • Denote the effective labour units by z • Effective labour is i.i.d. across individuals and locations
• Real Cost of Migration: share time/income lost, 1 − µni • Rule: Migrate from n to i iff µni zi Vi = maxk=1,...,N {µnk zk Vk } • If z follows a Frechet distribution Fz (x) = e
−κ − γx
, then share of region n registered workers that move to region i is (Vi µni )κ
mni = PN
κ k=1 (Vk µnk )
Gravity Evidence 17 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Expected Income and Aggregate Welfare Proposition 2: If worker productivities zi are distributed Frechet with mean 1 and variance parameter κ, and agents are able to migrate between regions at cost µij , then the expected real income net of migration costs for workers from region i is −1/κ
Vi0 = Vi mii
,
and aggregate average real income (welfare) is therefore W
=
N X
−1/κ
λ0i Vi mii
,
i=1
where λ0i =
L0 PN i
j=1
L0j
is region i’s registration share.
−1/κ Proof: See paper. Intuition: max {µnk zk Vk } ∼ Frechet κ, Vn mnn
18 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Eq’m Effective Labour in Each Region • Workers in Region n: Ln =
PN
0 i=1 min Li
19 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Eq’m Effective Labour in Each Region PN
0 i=1 min Li
• Workers in Region n: Ln =
• Analogous to Eaton-Kortum, where πni is both (1) share of
goods and (2) share of spending, we can show mni is both 1. Share of workers registered in n that work in region i 2. Share of income earned by all workers registered in n from those workers working in region i
• Effective Workers in Region n:
Hn Vn = ⇒ Hn =
N X
−1/κ
min L0i Vi mii
i=1 N X
−1 µin min κ
min L0i
i=1
19 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Eq’m Effective Labour in Each Region PN
0 i=1 min Li
• Workers in Region n: Ln =
• Analogous to Eaton-Kortum, where πni is both (1) share of
goods and (2) share of spending, we can show mni is both 1. Share of workers registered in n that work in region i 2. Share of income earned by all workers registered in n from those workers working in region i
• Effective Workers in Region n:
Hn Vn = ⇒ Hn =
N X
−1/κ
min L0i Vi mii
i=1 N X
−1 µin min κ
min L0i
i=1
• Useful with data on real GDP (Hi Vi ), migration (mni , mnn ),
and hukou registrations (L0n ) → solves for Vi , then Hi 19 / 36
Quantitative Analysis
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
The Equilibrium Conditions • Trade balance: vn Hn =
PN+1 i=1
πin vi Hi
• Trade flows: πni ∝ Pnθ Ti τni wiβ riη Pi1−β−η
−θ
20 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
The Equilibrium Conditions • Trade balance: vn Hn =
PN+1 i=1
πin vi Hi
• Trade flows: πni ∝ Pnθ Ti τni wiβ riη Pi1−β−η • Final good price: Pn−θ ∝
PN+1 i=1
−θ
−θ Ti τni wiβ riη Pi1−β−η
• Land rental price: rn ∝ wn Hn /Sn • Real income: Vn ∝ wn /Pnα rn1−α
20 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
The Equilibrium Conditions • Trade balance: vn Hn =
PN+1 i=1
πin vi Hi
• Trade flows: πni ∝ Pnθ Ti τni wiβ riη Pi1−β−η • Final good price: Pn−θ ∝
PN+1 i=1
−θ
−θ Ti τni wiβ riη Pi1−β−η
• Land rental price: rn ∝ wn Hn /Sn • Real income: Vn ∝ wn /Pnα rn1−α κ
• Migration flows: mni = PN(Vi µni )
κ k=1 (Vk µnk )
20 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
The Equilibrium Conditions • Trade balance: vn Hn =
PN+1 i=1
πin vi Hi
• Trade flows: πni ∝ Pnθ Ti τni wiβ riη Pi1−β−η • Final good price: Pn−θ ∝
PN+1 i=1
−θ
−θ Ti τni wiβ riη Pi1−β−η
• Land rental price: rn ∝ wn Hn /Sn • Real income: Vn ∝ wn /Pnα rn1−α κ
• Migration flows: mni = PN(Vi µni )
κ k=1 (Vk µnk )
• Migrant real incomes: Hn Vn ∝
−1/κ 0 i=1 min Li Vi mii
PN
20 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
The Equilibrium Conditions • Trade balance: vn Hn =
PN+1 i=1
πin vi Hi
• Trade flows: πni ∝ Pnθ Ti τni wiβ riη Pi1−β−η • Final good price: Pn−θ =∝
PN+1 i=1
Ti
−θ
τni wiβ riη Pi1−β−η
−θ
• Land price: rn ∝ wn Hn /Sn • Real income: Vn ∝ wn /Pnα rn1−α • Migration flows: mni = PN(Vi µni )
κ
κ k=1 (Vk µnk )
• Migrant real incomes: Hn Vn ∝
−1/κ 0 i=1 min Li Vi mii
PN
20 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Exact-Hat Algebra (Dekle et al., 2008) • Solving for relative changes eases the analysis
rn ∝ wn Hn /Sn ⇒ rˆn = w ˆn Hˆn • Another (less trivial) example:
PN+1
Pˆn−θ =
=
≡
0
Ti
0
0β 0η
0 1−β−η
−θ
τni wi ri Pi −θ PN+1 β η 1−β−η T τ w r P i ni i=1 i i i −θ −θ PN+1 β η 1−β−η β η ˆ 1−β−η ˆi τˆni w τ w r P ˆ r ˆ P T T i ni i i i i=1 i i i −θ PN+1 β η 1−β−η i=1 Ti τni wi ri Pi i=1
N+1 X
−θ Tˆi τˆni w ˆiβ rˆiη Pˆi1−β−η πni
i=1 21 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Exact-Hat Algebra (Dekle et al., 2008)
Appendix
Data: πni
0 , π 0 , given (π , L , m , X , L0 ) Model mapping F : τˆni , Tˆn , µ ˆni → Vˆn , mni n n ni ni n ni 0 , π0 Our strategy: infer τˆni , Tˆn , µ ˆni from F −1 Vˆn , mni ni
w ˆn Hˆn Xn
=
N+1 X
πin0 w ˆi Hˆi Xi ,
(1)
i=1
πni0
=
Pˆn−θ
=
−θ ˆ ˜η Pˆnθ πni Tˆi τˆni w ˆiβ+η Pˆi1−β−η L , i N+1 X
−θ ˆ ˜η πni Tˆi τˆni w ˆiβ+η Pˆi1−β−η L , i
(2) (3)
i=1
Vˆn
=
0 min
=
Hn0 Vn0
=
w ˆnα w ˆn = , Pˆnα rˆn1−α Pˆnα Hˆn1−α κ min Vˆn µ ˆin κ , PN ˆ ˆik k=1 mik Vk µ N X
0 min L0i Vi0 mii0
−1/κ
(4)
(5)
.
(6)
i=1 22 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Calibrating the Model Parameter
Value
Target
η
0.1 0.6 0.13 Data Data Model-Implied 4
Land’s share of gross output Intermediate’s share of output Housing’s share of expenditure National Employment Level Bilateral Trade Shares Initial Eq’m GDP Elasticity of Trade
1−β−η 1−α Li πij Xn θ
Details to Follow τˆni κ µ ˆni Tˆn
Pair Specific 2.21 Pair Specific Region Specific
Bilateral Trade Shares Ex-Post Income Dispersion Migration and Real Income Gaps Real Income Data
22 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Estimating Trade Costs • Flexible trade costs index (Head and Ries, 2001; Novy, 2013)
• Recall: πni ∝ Pnθ Ti τni wiβ riη Pi1−β−η
• ⇒ ln
πni πnn
= ln
−θ
−θ ! Pnθ Ti τni wiβ riη Pi1−β−η −θ Pnθ Tn wnβ rnη Pn1−β−η
≡ Sn −Si −θln(τni )
23 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Estimating Trade Costs • Flexible trade costs index (Head and Ries, 2001; Novy, 2013)
• Recall: πni ∝ Pnθ Ti τni wiβ riη Pi1−β−η
πni πnn
= ln
• ⇒ ln ππni nn
+ ln
• ⇒ ln
−θ
−θ ! Pnθ Ti τni wiβ riη Pi1−β−η −θ Pnθ Tn wnβ rnη Pn1−β−η
πin πii
≡ Sn −Si −θln(τni )
= −θ [ln (τni ) + ln (τin )]
23 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Estimating Trade Costs • Flexible trade costs index (Head and Ries, 2001; Novy, 2013)
• Recall: πni ∝ Pnθ Ti τni wiβ riη Pi1−β−η
πni πnn
= ln
• ⇒ ln ππni nn
+ ln
• ⇒ ln
−θ
−θ ! Pnθ Ti τni wiβ riη Pi1−β−η −θ Pnθ Tn wnβ rnη Pn1−β−η
πin πii
≡ Sn −Si −θln(τni )
= −θ [ln (τni ) + ln (τin )]
• The Head-Reis Index: τ¯ni ≡
√
τni τin =
πnn πii πni πin
1/2θ
• Notice: it’s symmetric (¯ τni = τ¯in ) • We modify the index to incorporate region-specific costs • i.e. an exporter-specific cost ti implies
τni = τ¯ni
p
ti /tn 23 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Estimating Trade Cost Asymmetries • If asymmetries are export costs, then τni = dni ti • Waugh (2010): asymmetries are exporter-specific • Tombe and Winter (2014) show this is also true within countries
• Models imply ln (πni /πnn ) = Si − Sn − θln (τni ); so, estimate
πni ln = ρni + ιn + ηi + ni , πnn where ρni is a directionless pair-effect such that ρni = ρin , and ιn and ηi are importer- and exporter-effects • As the exporter effect is ηi = Si − θln (ti ) and the importer
effect is ιn = −Sn , we infer export costs as tn = e −(ιn +ηn )/θ
Export Cost Estimates 24 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Relative Change in Trade Costs
Table: % Change in Trade Costs τni2007 /τni2002
Importer n NE B&T N Cst C Cst S Cst Cntrl NW SW WLD Distance, not ρni
NE -14.2 -5.7 -16.4 -18.4 -6.6 -4 -3.8 -3.8
B&T -11.8
N Cst -16.7 -15
-1 -5.2 -4 -5.2 -10.6 -1.2 -0.2
C Cst -23.5 -15.5 -1
-4.5 -15.1 -15.1 -20 -17.5 -6.5
Source i S Cst -24.7 -13.8 -11.2 -11.2
-12 -6.7 -12 -5.4 -1.6
-11.2 -18.6 -13.8 9.7
Cntrl -23 -23.9 -20.7 -15.9 -20.7
NW -18 -25.7 -22.6 -17.9 -24.7 -19.1
-21.9 -19.1 -21
SW -18.5 -18.5 -20.7 -12.4 -20.8 -16.8 -17.8
-17.2 -29.4
-18.5
WLD -27.7 -26.9 -20.3 -19.1 -10.6 -27.9 -37.8 -27.7
By Sector
25 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Calibrating the Model Parameter
Value
Target
η
0.1 0.6 0.13 Data Data Model-Implied 4
Land’s share of gross output Intermediate’s share of output Housing’s share of expenditure National Employment Level Bilateral Trade Shares Initial Eq’m GDP Elasticity of Trade
1−β−η 1−α Li πij Xn θ
Details to Follow τˆni κ µ ˆni Tˆn
Pair Specific 2.21 Pair Specific Region Specific
Bilateral Trade Shares Ex-Post Income Dispersion Migration and Real Income Gaps Real Income Data
25 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Heterogeneity of Labour Productivity, κ • Variation in the ex-post wage distribution given by a simple
function of this paramtere (Cortes and Gallipoli, 2014) • Ex-post income is r.v. Z = max {µnk zk Vk }, which is Frechet
• CDF given by Pr (Z < x) ≡ Fi (x) = e −
x/[
PN
j=1
(cij Vj )κ ]1/κ
−κ
√
• Log income is therefore ∼Gumbel, with s.d. π/ κ 6
• Census 2005 has individual earnings data; the average standard
deviation within origin-destination pairs implies κ ≈ 2.21 • Controlling for age, occupation, hukou location, marital status, industry, gender, education, etc... implies κ ≈ 2.85
26 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Migration Costs • As with trade, µni = (mni /mnn )1/κ (Vn /Vi ) 140
200
120 160
Frequency
100 Frequency
120
80 60
80
40 40
0 0
20
0.05 0.1 0.15 0.2 Disposable Income Net of Migration Costs, in 2000
(a) Histogram of cni
0.25
0 0
1
2
3 4 5 6 "Disposable" Income Share
7
8
(b) Histogram of cni zi
• Average migration cost: 89.6% of income • Average migration costs for migrants: 9.6% of income • Average change in migration costs, 2000-2005: µ ˆni = 1.14 Example: To Beijing 27 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Calibrating the Model Parameter
Value
Target
η
0.1 0.6 0.13 Data Data Model-Implied 4
Land’s share of gross output Intermediate’s share of output Housing’s share of expenditure National Employment Level Bilateral Trade Shares Initial Eq’m GDP Elasticity of Trade
1−β−η 1−α Li πij Xn θ
Details to Follow τˆni κ µ ˆni Tˆn
Pair Specific 2.21 Pair Specific Region Specific
Bilateral Trade Shares Ex-Post Income Dispersion Migration and Real Income Gaps Real Income Data
27 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Infer Productivity Changes from Real Income Growth 1.5
% Change in (Adjusted) Productivity Parameter
120
1.3
1.2
1.1
1
0.9
80 60 40 20 0
0.9 1 1.1 1.2 1.3 Relative Real Income Change, Data from 2002−07
1.4
(c) Real Income, when Tˆn = 1
1.5
er
0.8
Mo Sh ngo an lia do He ng Sh nan Sh anx an i Tia nxi Jia njin n J gsu Sh iangx an i gh He ai Hu bei Sic nan Gu huan a Gu ngx izh i ou Zh Jilin eji a He H ng ilo ub ng ei ji Nin ang gx Fu ia G jian Lia ansu on Qin ing g Gu Yun hai an na gd n o Be ng Xin ijing jia n Ch Anh g on ui gq Ha ing ina n
−20
0.8
0.7 0.7
100
Inn
Relative Real Income Change, Model
1.4
α
(d) Required Change in Tˆnθ(β+η)
Notes: Compares the model-implied change in each province’s real income Vˆn when underlying productivity is constant to real income changes measured in data. Both are expressed relative to the mean. In order for the model implies real income changes to match data, we require changes in underlying productivity draws Tˆn . The implied α/θ(β+η) productivity change in display in the right panel, adjusted as Tˆn . 28 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Counterfactual Exercises • We run a variety of counterfactuals 1. 2. 3. 4. 5. 6.
Internal Trade: τˆni for i, n 6= N + 1 only External Trade: τˆni for i, n = N + 1 only All Trade: τˆni for all pairs Migration: µ ˆni for all pairs All Domestic: Internal Trade + Migration Everything
• We then repeat all of the above with Tˆn changes • Changes in outcomes of interest • • • •
Internal and external trade Stock of migrants Income differences (variance of log-income) Aggregate welfare 29 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Counterfactual Aggregate Outcomes
Measured Cost Reduction of
Change in Trade GDP Ratio (p.p.) Internal External
Migrant Stock
Income Differences
Aggregate Welfare
Internal Trade
38.7
-2.7
-1.8%
-3.6%
7.3%
External Trade
-3.1
17.9
0.8%
2.1%
2.5%
All Trade
34.2
13.7
-0.9%
-1.5%
9.6%
Migration
0.0
0.1
37.1%
-8.9%
0.4%
All Domestic
38.7
-2.6
33.1%
-11.9%
7.7%
Everything
34.1
13.8
34.2%
-10.2%
10.1%
Data (2002-07)
17
12
18.5%
-0.1%
–
30 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Lower Migration Costs: Employment and Real Income 20
25 Beijing 20
15
Shanghai
% Change in Real Income
% Change in Labour Force
15 10
Guangdong
5
0
10
5 Inner Mongolia 0 Guangdong −5 Shanghai
−5 Inner Mongolia
−10
0
0.5
1 1.5 2 Initial Real Income, Relative to Mean
(e) Employment
−10
2.5
3
−15
Beijing
0
0.5
1 1.5 2 Initial Real Income, Relative to Mean
2.5
3
(f) Real Income
ˆn and real income Vˆn by province Notes: Displays the percentage change in employment L in response to lower inter-provincial migration costs.
31 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Lower Migration Costs: Trade Volumes 4
4
3 Beijing
Beijing
% Change in Trade Volume (Imports+Exports)
% Change in Trade Volume (Imports+Exports)
3
2
1 Guangdong
Shanghai
0
−1
−2
−3
0.5
1 1.5 2 Initial Real Income, Relative to Mean
(g) International Trade
1
Guangdong
2.5
3
Shanghai
0
−1
Inner Mongolia
−2
Inner Mongolia
0
2
−3
0
0.5
1 1.5 2 Initial Real Income, Relative to Mean
2.5
3
(h) Internal Trade
Notes: Displays the percentage change in trade volumes, both internationally and internally, for each provinces resulting from lower migration costs. Aggregate trade changes little, but there is substantial variation across provinces. Coastal regions trade more more as a result of lower internal migration costs; interior regions trade less. 32 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Distributional Effects on Real Income Differences 25
25
20
20
Jilin
15 % Change in Real Income
% Change in Real Income
15
10 Beijing Guangdong
Shanghai
5
10 Tianjin Inner Mongolia 5 Beijing Guangdong
0
0
−5
−5
−10
0
0.5
1 1.5 2 Initial Real Income, Relative to Mean
(i) Internal Trade
2.5
3
Shanghai
−10
0
0.5
1 1.5 2 Initial Real Income, Relative to Mean
2.5
3
(j) International Trade
Notes: Displays the percentage change in real incomes for each provinces resulting from selected counterfactual.
33 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Distributional Effects on Real Income Differences 25
25
20
20
Inner Mongolia
15 % Change in Real Income
% Change in Real Income
15 10
5 Inner Mongolia 0 Guangdong
10
Tianjin 5 Guangdong
0
−5
Shanghai Beijing
Shanghai −10
−15
−5
Beijing
0
0.5
1 1.5 2 Initial Real Income, Relative to Mean
(k) Migration Costs
2.5
3
−10
0
0.5
1 1.5 2 Initial Real Income, Relative to Mean
2.5
3
(l) Infernal Reforms
Notes: Displays the percentage change in real incomes for each provinces resulting from selected counterfactual.
34 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
... with Productivity Changes
Change in Productivity and ...
p.p. Change in Trade/GDP Ratio Internal External
Productivity Only
-1.1
Migrant Stock
Regional Income Variance
Aggregate Welfare
Marginal Welfare Change
Prior Welfare Change
-4.6
-9.3%
11.5%
40.3%
–
–
Internal Trade
36.8
-6.9
-12.3%
6.2%
50.2%
7.1%
7.3%
External Trade
-3.8
11.4
-8.3%
13.1%
43.3%
2.2%
2.5%
All Trade
32.9
7.9
-11.2%
8.0%
53.1%
9.2%
9.6%
Migration
-1.1
-4.6
22.4%
3.1%
40.8%
0.4%
0.4%
Internal Reform
36.8
-6.8
17.2%
-1.5%
50.7%
7.5%
7.7%
Everything
32.8
7.9
18.5%
-0.1%
53.7%
9.5%
10.1%
Data (2002-07)
17
12
18.5%
-0.1%
–
–
–
35 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Appendix
Conclusion • We develop a general equilibrium model of internal-external
trade with partial factor mobility • Highly tractable; eas to implement quantitative exercises • Useful for “measure” magnitude of trade and migration costs
• We apply the model to China and quantify the impacts of
trade liberalization and migration on aggregate welfare and regional income differences • Domestic reforms substantially more important than external
liberalization • Lower migration and trade costs are complementary policies
• Opening up is important for China, but not because of goods
trade 36 / 36
Introduction
Model
Quantitative Analysis
Cross-Province Differences
Conclusion
Appendix
Back
Summary Metric Across Province Importer
Mean
Median
p90
p10
90/10 Ratio
Real GDP per Capita Exports per Capita Home Share Migration Share
1 1 0.74 0.06
0.67 0.17 0.76 0.02
2.64 2.08 0.86 0.2
0.37 0.03 0.62 0.006
7.14 69.33 1.39 31.67
37 / 36
Introduction
Model
Migration and Gravity
Quantitative Analysis
Conclusion
Appendix
Back
• Evidence that gravity equations capture commuting decisions (Erlander and Stewart, 1990; Sen and Smith, 1995; Ahlfeldt et al., 2012)
−2 Log(Normalized Migration mij/mii for 2000) −10 −8 −6 −4 −12
−12
Log(Normalized Migration mij/mii for 2000) −10 −8 −6 −4
−2
• Inter-provincial migration also consistent with gravity
9
10 11 12 Log(Driving Time, Between Capitals)
(m) Migration vs. Travel Time
13
−3
−2 −1 0 1 2 Ratio of Real Income per Effective Worker, Log(Vj/Vi)
3
(n) Migration vs. Income Differences 38 / 36
Introduction
Model
Quantitative Analysis
Conclusion
Trade Cost Changes, Using Distance (not ρni )
Appendix
Back
• Capture symmetric effect with bilateral distances dni
ln
πni πnn
= δln(dni ) + ιn + ηi + ni
Table: % Change in Trade Costs
Importer NE B&T N Cst C Cst S Cst Cntrl NW SW WLD
NE -16.2 -13.3 -23.9 -22.7 -12.6 -4.9 -10.6 -13.1
B&T -9.7
N Cst -9.4 -9.7
-6.9 -11.6 -6.8 -9.2 -9.3 -6.0 -7.6
C Cst -16.0 -9.4 -0.1
-5.4 -12.4 -13.6 -13.8 -16.6 -8.1
Source S Cst -20.6 -11.2 -13.9 -14.7
-8.3 -4.2 -4.2 -3.5 -2.3
-12.5 -14.9 -15.5 4.6
Cntrl -17.6 -20.5 -22.0 -18.1 -19.6
NW -17.3 -26.7 -28.2 -24.5 -27.9 -23.6
-17.2 -19.6 -23.6
SW -12.3 -14.3 -21.6 -14.2 -19.2 -16.3 -12.3
-22.3 -35.6
-20.7
WLD -19.9 -21.0 -19.0 -18.5 -6.2 -25.4 -31.8 -25.6
39 / 36
Quantitative Analysis
Back
n io
st
eg lR
lC
ea
tra en
N
or
th
an Ti g/
oa
st
jin
2007
st ijin Be
ut
h
C So
N
or
th
th or N
C oa
oa
es t w
hw es t ut
st
2002
So
Appendix
C
Province−Specific Export Cost, Tariff−Equivalent % −40 −20 0 20 40
Provincial Export-Cost Estimates
Conclusion
tra
Model
C en
Introduction
Notes: Displays the tariff-equivalent (in percentage points) region-specific export costs. All expressed relative to the average for the year. A value of 30 for a certain region implies it is 30 percent more costly to export from that region to any other, relative to 40 / 36 the export costs for the average region.
Introduction
Model
Migration Costs
Quantitative Analysis
Conclusion
Appendix
Back
• As with trade, µni = (mni /mnn )1/κ (Vn /Vi ) Figure: Costs of Migrating Into Beijing
Heilongjiang
Inner Mongol
Jilin Liaoning
Xinjiang
Beijing Tianjin Shanxi Hebei
Ningxia Qinghai
Shandong Gansu
Shaanxi
Tibet
Henan Hubei
Sichuan
Jiangsu Anhui Shanghai Zhejiang
Guizhou
Hunan Jiangxi Fujian
Yunnan Guangxi Guangdong
Hainan
41 / 36
Introduction
Model
Quantitative Analysis
Trade Patterns, by Region
Conclusion
Appendix
Back
Table: Expenditure Shares πni , Year 2002
Source Importer
NE
B&T
N Cst
C Cst
S Cst
Cntrl
NW
SW
WLD
NE
0.879
0.007
0.010
0.008
0.013
0.011
0.008
0.009
0.055
B&T
0.039
0.634
0.094
0.030
0.026
0.033
0.014
0.012
0.119
N Cst
0.018
0.033
0.798
0.034
0.018
0.038
0.009
0.008
0.044
C Cst
0.002
0.002
0.006
0.810
0.015
0.024
0.005
0.005
0.133
S Cst
0.005
0.004
0.005
0.026
0.723
0.019
0.004
0.015
0.198
Cntrl
0.006
0.003
0.011
0.048
0.023
0.878
0.007
0.007
0.018
NW
0.020
0.008
0.021
0.033
0.045
0.036
0.774
0.038
0.026
SW
0.009
0.003
0.004
0.018
0.043
0.014
0.009
0.880
0.020
WLD
0.000
0.000
0.000
0.001
0.002
0.000
0.000
0.000
0.996 42 / 36
Introduction
Model
Quantitative Analysis
Conclusion
% Change in Internal Bilateral Costs (2002-07)
Appendix
Back
Summary Metric Across Pairs Importer
Mean
Median
Min
Max
Agriculture Mining Food and Tobacco Textiles Wood & Furniture Paper & Printing Chemicals Non-Metallic Min Metal Products Machinery Transport Equip. Electrical Machi Other Utilities Construction Transportation Other Services
-7.33 -8.92 -9.99 -6.51 -14.00 3.09 -6.64 -17.54 -10.59 -14.99 2.29 -1.74 -3.67 -0.35 -16.78 -11.86 -10.25
-6.96 -8.29 -13.14 -4.53 -14.82 1.88 -6.96 -19.89 -9.89 -17.65 -7.58 -6.59 -0.55 -16.29 -36.75 -17.64 -12.88
-37.63 -36.95 -29.52 -45.49 -48.26 -21.93 -19.56 -36.80 -27.73 -33.71 -34.18 -24.40 -49.32 -52.22 -73.30 -42.91 -30.60
31.07 29.35 7.43 56.12 37.93 29.40 10.16 4.61 5.53 33.64 76.13 60.12 50.53 101.42 111.76 26.58 19.37 43 / 36