techno-industrial fdi policy and china's export surge
TRANSCRIPT
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Techno-Industrial FDI Policy and China’s Export Surge
Yang Liang1 Mary E. Lovely2 Hongsheng Zhang3
1San Diego State University2Syracuse University & PIIE
3Zhejiang University
NYU Stern CGEB, April 15, 2019
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Motivation
China’s exports surged, rising from $380 B in 2001 to $1.62 T by 2008.for the US: $87 B to $330 B
This one-time ‘China Shock’ has been used to study:The effects of Chinese import competition(Autor, Dorn, and Hanson ’13, ...)
Early studies explained the China’s export surge due toDomestic firms’ productivity shock (Brandt et al ’12...)Importing countries trade policy uncertainty(Handley and Limao ’15, Pierce & Schott ’16, Feng, Li and Swenson ’16,Crowley, Meng and Song ’17)
Missing story: How did Chinese foreign investment policies affect exportgrowth?
Our paper studies the extent to which Chinese FDI policy shapes this exportsurge.
Liang, Lovely, Zhang FDI Policy and Exports Apr 15, 2019 2 / 38
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Motivation
China’s exports surged, rising from $380 B in 2001 to $1.62 T by 2008.for the US: $87 B to $330 B
This one-time ‘China Shock’ has been used to study:The effects of Chinese import competition(Autor, Dorn, and Hanson ’13, ...)
Early studies explained the China’s export surge due toDomestic firms’ productivity shock (Brandt et al ’12...)Importing countries trade policy uncertainty(Handley and Limao ’15, Pierce & Schott ’16, Feng, Li and Swenson ’16,Crowley, Meng and Song ’17)
Missing story: How did Chinese foreign investment policies affect exportgrowth?
Our paper studies the extent to which Chinese FDI policy shapes this exportsurge.
Liang, Lovely, Zhang FDI Policy and Exports Apr 15, 2019 2 / 38
![Page 4: Techno-Industrial FDI Policy and China's Export Surge](https://reader031.vdocuments.site/reader031/viewer/2022012510/61878fa60f303f14db5519ca/html5/thumbnails/4.jpg)
Motivation
China’s exports surged, rising from $380 B in 2001 to $1.62 T by 2008.for the US: $87 B to $330 B
This one-time ‘China Shock’ has been used to study:The effects of Chinese import competition(Autor, Dorn, and Hanson ’13, ...)
Early studies explained the China’s export surge due toDomestic firms’ productivity shock (Brandt et al ’12...)Importing countries trade policy uncertainty(Handley and Limao ’15, Pierce & Schott ’16, Feng, Li and Swenson ’16,Crowley, Meng and Song ’17)
Missing story: How did Chinese foreign investment policies affect exportgrowth?
Our paper studies the extent to which Chinese FDI policy shapes this exportsurge.
Liang, Lovely, Zhang FDI Policy and Exports Apr 15, 2019 2 / 38
![Page 5: Techno-Industrial FDI Policy and China's Export Surge](https://reader031.vdocuments.site/reader031/viewer/2022012510/61878fa60f303f14db5519ca/html5/thumbnails/5.jpg)
Motivation
China’s exports surged, rising from $380 B in 2001 to $1.62 T by 2008.for the US: $87 B to $330 B
This one-time ‘China Shock’ has been used to study:The effects of Chinese import competition(Autor, Dorn, and Hanson ’13, ...)
Early studies explained the China’s export surge due toDomestic firms’ productivity shock (Brandt et al ’12...)Importing countries trade policy uncertainty(Handley and Limao ’15, Pierce & Schott ’16, Feng, Li and Swenson ’16,Crowley, Meng and Song ’17)
Missing story: How did Chinese foreign investment policies affect exportgrowth?
Our paper studies the extent to which Chinese FDI policy shapes this exportsurge.
Liang, Lovely, Zhang FDI Policy and Exports Apr 15, 2019 2 / 38
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Why focus on foreign investment?
Along with Chinese WTO entry, FDI flows to China surged between 2000 and2007.
Source: National Bureau of Statistics of China, data.stats.gov.cn
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Why focus on foreign investment?
Exports from foreign-invested enterprises (FIEs) grew even faster thanexports from domestic firms.
05
00
10
00
15
00
Bill
ion
US
D
2000 2002 2004 2006 2008Year
Foreign−Invested Domestic
Source: China Custom Records by WIND
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This Paper
Question: Does foreign investment activity change when a sector’s FDIregulation is changed?
Outcomes: entry, exporters, export valuesSetting: compare activity patterns over time, using diff-in-diff methods.
How important are foreign-invested enterprises to the growth in Chineseexports following its WTO accession.
counterfactual
Can we account for possible policy endogeneity?event-study analysis
Is activity being driven by other factors?add controlstriple-differencing method
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Background
Guidelines Categorize Sectors by Openness to Investment
Forbidden: no foreign investment permitted.
Restricted: investment by permission and only as minority shareholder in ajoint venture.
Encouraged: preferences available on a deal-by-deal basis.
Investment in all other industries is allowed, with no explicit restrictions onownership, subject to approval.
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Background
What do we expect the policy to do?
Encouraged: policies are deal specific, but they may lower fixed costs of entryand, by lowering corporate tax rate, encourage entry and raise exports.
Restricted: sectors are closed to wholly owned foreign investment, soliberalization should reduce encourage by this mode and raise exports by suchfirms.
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Background
02
04
06
08
01
00
Sh
are
of
ind
ustr
ies
1995 1997 2002 2004 2007 2010
forbidden restrict
restrict + encourage neutral
encourage
Source: Policy designation at SCIC four-digit taken from Sheng and Yang (2016).Grouping and calculations by authors.
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Background
Share of Sectors Designated Encouraged, by Group, 1995-2007
1020
3040
5060
Sha
re o
f Sec
tors
Enc
oura
ged
1995 1997 1999 2001 2003 2005 2007Year
High−Tech Capital Intensive Labor Intensive
(a) Encouraged
Source: Policy designation at SCIC four-digit taken from Sheng and Yang (2016).Grouping and calculations by authors.
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Background
Share of Sectors Designated Restricted, by Group, 1995-2007
05
1015
20S
hare
of S
ecto
rs R
estr
icte
d
1995 1997 1999 2001 2003 2005 2007Year
High−Tech Capital Intensive Labor Intensive
(a) Restricted
Source: Policy designation at SCIC four-digit taken from Sheng and Yang (2016).Grouping and calculations by authors.
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Background
Linear Probability Models of Policy Designations
(1) (2) (3) (4)Encouraged Encouraged Restricted Restricted
Capital-Labor Ratio (1998) 0.000 0.000 0.001∗∗∗ 0.001∗∗∗(0.000) (0.000) (0.000) (0.000)
High-Tech Dummy 0.297∗∗∗ 0.293∗∗∗ 0.046 0.034(0.070) (0.067) (0.029) (0.032)
SOE Output Share 0.055 0.005 0.016 0.009(0.124) (0.134) (0.065) (0.069)
COD Intensity 0.001 -0.000(0.002) (0.001)
SO2 Intensity 0.011 -0.005(0.009) (0.004)
Year FE Yes Yes Yes YesNote: Dependent variables are policy designations for CIC four-digit sectors from Shengand Yang (2016). Other data sources described in text. Pooled observations, 1995-2007.Robustness standard errors in parentheses are two-way clustered at the industry and yearlevel.∗ p < .10, ∗∗ p < .05, ∗∗∗ p < .01
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Background
Which industries are designated as high tech? (some examples)
Chemicals (also capital intensive)
Medical and pharmaceutical products (also cap int)
Special equipment manufacturing (also cap int)
Communications, computers, other electronics
Instruments, meters, office machinery
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Empirical Approach
Empirical Approach
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Empirical Approach
Baseline Specification (Difference-in-Differences)
ln Yjt = α + β1Encouragedjt + β2Restrictedjt + µj + ηt + εjt
j = industry, t = yearEncouraged = 1 if industry j contains encouraged item in the FDI catalogueRestricted = 1 if industry j contains restricted item in the FDI catalogueµj, ηt are industry and year fixed effectsStandard errors are two-way clustered at the industry and year level.
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Empirical Approach
Event Study
ln Yjt = α +4
∑t=−3
β1tEncouragedjt +4
∑t=−3
β2tRestrictedjt + µj + ηt + εjt
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Empirical Approach
Event StudyNumber of FIE firms
Number of FIE Firms
−.1
0.1
.2lo
g di
ffere
nce
in n
umbe
r of
FIE
s
yearl4 yearl3 yearl2 yearl1 year0 yearf1 yearf2 yearf3Years prior/after policy change
(a) Encouraged
−.4
−.2
0.2
log
diffe
renc
e in
num
ber
of F
IEs
yearl4 yearl3 yearl2 yearl1 year0 yearf1 yearf2 yearf3Years prior/after policy change
(b) Restricted
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Empirical Approach
Event StudyNumber of FIE exporters
Number of FIE Exporters
−.1
0.1
.2.3
log
diffe
renc
e in
num
ber
of F
IE e
xpor
ters
yearl4 yearl3 yearl2 yearl1 year0 yearf1 yearf2 yearf3Years prior/after policy change
(a) Encouraged
−.4
−.2
0.2
log
diffe
renc
e in
num
ber
of F
IE e
xpor
ters
yearl4 yearl3 yearl2 yearl1 year0 yearf1 yearf2 yearf3Years prior/after policy change
(b) Restricted
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Empirical Approach
Event StudyExport values for FIEs
Export values for FIEs
−.5
0.5
1lo
g di
ffere
nce
in e
xpor
t val
ue
yearl4 yearl3 yearl2 yearl1 year0 yearf1 yearf2 yearf3Years prior/after policy change
(a) Encouraged
−3
−2
−1
01
log
diffe
renc
e in
exp
ort v
alue
yearl4 yearl3 yearl2 yearl1 year0 yearf1 yearf2 yearf3Years prior/after policy change
(b) Restricted
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Empirical Approach
Other Possible Threats to Identification
reverse causality/simultaneity
concurrent policies (OVB)NTR gapChinese import tariffsNon-tariff barriers
Not enough?
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Empirical Approach
Triple Differencing: Domestic Firms as Controls
ln Yijt = α + β1Encouragedjt × FIEi + β2Restrictedjt × FIEi
+ γjt + FIEi × µj + FIEi × ηt
+ FIEi + µj + ηt + εjt,
γjt= industry-by-year fixed effectsi = 1 if if outcome variable refers to foreign-invested enterprises in industry jj = industry, t = yearEncouraged = 1 if industry j contains encouraged item in the FDI catalogueRestricted = 1 if industry j contains restricted item in the FDI catalogueµj, ηt are industry and year fixed effectsStandard errors are two-way clustered at the industry and year level.
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Data
What Data We Use?
Chinese manufacturing firm census, 1998-2010Omits the smallest firmsProvides number of firms, ownership, export value
Chinese Customs Records, 2000-2013 Universe of exportsProvides information on ownership typeProvides product and destination information
Sheng and Yang (2016) - policy designations
Brandt et al. (2018) - other policy controls
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Results
Results
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Results
Which activities do we expect to be influenced by FDI policy?
Entry of new foreign enterprises into China
Entry of foreign enterprises into exporting
Export volume of foreign firms
Other aspects of export behavior:Intensity of existing relationshipsExport of new products to new destinationsExports to the United States only
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Results
Baseline Results: DID
Regression DD Estimates of FDI Policy Effects
(1) (2) (3) (4)FIE JV WOFE Domestic
(Panel A: Depvar = ln Number of Firms)Encouraged 0.141∗∗∗ 0.142∗∗∗ 0.102∗∗ 0.077
(0.044) (0.042) (0.046) (0.059)Restricted -0.005 0.029 -0.147∗∗ -0.034
(0.045) (0.039) (0.067) (0.062)(Panel B: Depvar = ln Number of Exporters)
Encouraged 0.153∗∗∗ 0.138∗∗∗ 0.101∗ 0.021(0.047) (0.041) (0.055) (0.069)
Restricted -0.047 0.024 -0.197∗∗ 0.000(0.049) (0.042) (0.074) (0.065)
(Panel C: Depvar = ln Export Values)Encouraged 0.357∗∗ 0.382∗ 0.261 -0.171
(0.141) (0.177) (0.185) (0.123)Restricted 0.173 0.207 -0.493 0.195∗
(0.153) (0.195) (0.329) (0.104)Observations 5615 5483 5194 5425
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Results
Baseline Results: DID
Regression DD Estimates of FDI Policy Effects
(1) (2) (3) (4)FIE JV WOFE Domestic
(Panel A: Depvar = ln Number of Firms)Encouraged 0.141∗∗∗ 0.142∗∗∗ 0.102∗∗ 0.077
(0.044) (0.042) (0.046) (0.059)Restricted -0.005 0.029 -0.147∗∗ -0.034
(0.045) (0.039) (0.067) (0.062)(Panel B: Depvar = ln Number of Exporters)
Encouraged 0.153∗∗∗ 0.138∗∗∗ 0.101∗ 0.021(0.047) (0.041) (0.055) (0.069)
Restricted -0.047 0.024 -0.197∗∗ 0.000(0.049) (0.042) (0.074) (0.065)
(Panel C: Depvar = ln Export Values)Encouraged 0.357∗∗ 0.382∗ 0.261 -0.171
(0.141) (0.177) (0.185) (0.123)Restricted 0.173 0.207 -0.493 0.195∗
(0.153) (0.195) (0.329) (0.104)Observations 5615 5483 5194 5425
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Results
Baseline Results: DID
Regression DD Estimates of FDI Policy Effects
(1) (2) (3) (4)FIE JV WOFE Domestic
(Panel A: Depvar = ln Number of Firms)Encouraged 0.141∗∗∗ 0.142∗∗∗ 0.102∗∗ 0.077
(0.044) (0.042) (0.046) (0.059)Restricted -0.005 0.029 -0.147∗∗ -0.034
(0.045) (0.039) (0.067) (0.062)(Panel B: Depvar = ln Number of Exporters)
Encouraged 0.153∗∗∗ 0.138∗∗∗ 0.101∗ 0.021(0.047) (0.041) (0.055) (0.069)
Restricted -0.047 0.024 -0.197∗∗ 0.000(0.049) (0.042) (0.074) (0.065)
(Panel C: Depvar = ln Export Values)Encouraged 0.357∗∗ 0.382∗ 0.261 -0.171
(0.141) (0.177) (0.185) (0.123)Restricted 0.173 0.207 -0.493 0.195∗
(0.153) (0.195) (0.329) (0.104)Observations 5615 5483 5194 5425
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Results
Baseline Results: DID
Regression DD Estimates, with Industry-Specific Year Trends
(1) (2) (3) (4)FIE JV WOFE Domestic
(Panel A: Depvar = ln Number of Firms)Encouraged 0.098∗∗ 0.112∗∗ 0.044 0.013
(0.037) (0.038) (0.038) (0.041)Restricted 0.023 0.039 -0.134∗ -0.044
(0.045) (0.040) (0.073) (0.053)(Panel B: Depvar = ln Number of Exporters)
Encouraged 0.116∗∗ 0.107∗∗ 0.053 -0.081(0.040) (0.039) (0.047) (0.048)
Restricted -0.005 0.049 -0.180∗∗ 0.002(0.050) (0.047) (0.075) (0.059)
(Panel C: Depvar = ln Export Values)Encouraged 0.461∗∗ 0.333 0.425∗∗ -0.354∗∗∗
(0.154) (0.187) (0.175) (0.104)Restricted 0.246 0.211 -0.485 0.265∗∗
(0.157) (0.212) (0.301) (0.095)Industry Specific Year Trends Yes Yes Yes YesObservations 5615 5483 5194 5425
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Results
Adding Controls
DD Regressions with Controls
ln Num of Firms ln Num of Exporters ln Export Values(1) (2) (3) (4) (5) (6) (7) (8) (9)FIE JV WOFE FIE JV WOFE FIE JV WOFE
Encouraged 0.139∗∗ 0.133∗∗∗ 0.099∗ 0.153∗∗ 0.131∗∗∗ 0.098 0.349∗∗ 0.367∗ 0.098(0.047) (0.041) (0.054) (0.051) (0.039) (0.062) (0.125) (0.175) (0.092)
Restricted -0.033 0.004 -0.183∗∗ -0.067 0.013 -0.230∗∗ 0.198 0.229 -0.264∗(0.043) (0.039) (0.070) (0.050) (0.045) (0.082) (0.163) (0.185) (0.137)
NTR Gap 0.007∗∗∗ 0.006∗∗∗ 0.006∗∗∗ 0.009∗∗∗ 0.007∗∗∗ 0.008∗∗∗ -0.005 0.005 0.001(0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.007) (0.007) (0.004)
ln Output Tariff 0.013 0.122∗∗∗ -0.007 -0.016 0.119∗∗ -0.047 -0.239∗ 0.126 -0.239(0.034) (0.033) (0.045) (0.041) (0.049) (0.048) (0.126) (0.268) (0.136)
Non-Tariff Barriers 0.255∗∗ 0.168∗∗ 0.301∗∗ 0.181∗ 0.033 0.270∗ -0.379 -0.421∗ 0.449(0.096) (0.063) (0.125) (0.098) (0.081) (0.146) (0.404) (0.223) (0.337)
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Results
Robustness Check# of Firms
FIE_baseline
FIE_with_controls
FIE_add_trend
JV_baseline
JV_with_control
JV_add_trend
WFOE_baseline
WFOE_with_controls
WFOE_add_trend
-.1 0 .1 .2 .3 -.4 -.2 0 .2
Encouraged Restricted
log
diffe
renc
e in
ln N
um o
f Firm
s
coefficient estimate
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Results
Robustness Check# of Exporters
FIE_baseline
FIE_with_controls
FIE_add_trend
JV_baseline
JV_with_control
JV_add_trend
WFOE_baseline
WFOE_with_controls
WFOE_add_trend
-.1 0 .1 .2 .3 -.4 -.2 0 .2
Encouraged Restricted
log
diffe
renc
e in
ln N
um o
f Exp
orte
rs
coefficient estimate
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Results
Robustness CheckExport Values
FIE_baseline
FIE_with_controls
FIE_add_trend
JV_baseline
JV_with_control
JV_add_trend
WFOE_baseline
WFOE_with_controls
WFOE_add_trend
0 .5 1 -.5 0 .5 1
Encouraged Restricted
log
diffe
renc
e in
ln E
xpor
t Val
ues
coefficient estimate
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Results
Results: Triple-Differencing
Regression DDD Estimates of FDI Policy Effects
(1) (2) (3)FIE JV WOFE
(Panel A: Depvar = ln Number of Firms)DDD Enc 0.115∗∗∗ 0.116∗∗∗ 0.076∗
(0.028) (0.031) (0.036)DDD Res 0.015 0.049 -0.127∗∗
(0.044) (0.045) (0.052)(Panel B: Depvar = ln Number of Exporters)DDD Enc 0.180∗∗∗ 0.165∗∗∗ 0.128∗∗∗
(0.039) (0.040) (0.041)DDD Res -0.024 0.048 -0.173∗∗
(0.056) (0.056) (0.058)(Panel C: Depvar = ln Export Values)
DDD Enc 0.224∗∗ 0.341∗∗∗ 0.323∗∗(0.109) (0.118) (0.130)
DDD Res 0.156 0.241 -0.095(0.159) (0.174) (0.201)
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Results
Extensive Margins
We concord industry-level policies to the product level and estimate a DIDspecification.
We use Chinese Customs Records to capture all exporters and to observeboth products and destinations. Allows us to explore extensive margins.
Extensive margins# of firms exporting to a HS6 product-country cell
ln Ycjt = α + β1Encouragedjt + β2Restrictedjt + µct + δcj + εcjt
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Results
Extensive margins for all countries and US only
DD Estimates of Policy Effects on Extensive Margins, Total Exports and US Only
To All countries To the US(1) (2) (3) (4) (5) (6)FIE WOFE JV FIE WOFE JV
Enc 0.093∗∗∗ 0.096∗∗∗ 0.058∗∗∗ 0.195∗∗∗ 0.195∗∗∗ 0.155∗∗∗(0.019) (0.020) (0.016) (0.052) (0.051) (0.043)
Res 0.032 0.012 0.006 0.040 0.053 0.001(0.048) (0.041) (0.042) (0.050) (0.062) (0.035)
Observations 4262156 4262156 4262156 64030 64030 64030FE HS#C,C#Y HS#C,C#Y HS#C,C#Y HS,Y HS,Y HS,Y
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Results
Magnitudes: Counterfactuals
Use the regression coefficients and actual trade flows to calculate predictedexported values in absence of encouragement.
∆Exportt = ∑j
Xjt · (eβ1·1{Encouragedjt} − 1)
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Results
FIE export counterfactual, actual vs. without encouragement
FIE Export Values, Actual v. Counerfactual, 1998-2010
010
0020
0030
0040
00E
xpor
t Val
ues
(Bill
ion
RM
B)
1998 2000 2002 2004 2006 2008 2010Year
Total FIE Export Counterfactual FIE Export
Source: Source of export data is the ASIP.
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Results
Export composition in 2010, actual and counterfactual
Share of FIE Export Values by Group, Actual v. Counterfactual, 2010
10.57%
66.5%
22.93%
Capital Intensive High Tech Labor Intensive
(a) Actual
11.22%
60.75%
28.02%
Capital Intensive High Tech Labor Intensive
(b) Counterfactual
Source: Source of export data is the ASIP. Grouping and calculations by authors.
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Conclusion
Conclusion
Encouraged investmentRaises the number of foreign enterprises by 14%Raises the number of foreign exporters by 15%Raises the value of exports from foreign-invested enterprises by 36%FDI promotion policies have no effect on domestic enterprises.
Removing RestrictionsRemoving restrictions limiting wholly owned foreign firms raises the number ofsuch firms by 15%.Raises the value of exports from WFOEs.Has no significant effect on activity of joint ventures.Reduces the value of exports from domestic enterprises.
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Conclusion
Conclusion
Encouraging investment increases the number of new products sent to newdestinations.
This outcome is consistent with technology upgrading of FIE firms in theaggregate.
This extensive-margin effect is powerful for the US.
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Conclusion
Thank you!
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