The Economic Impact of Special Economic Zones: Evidence ......uotaIntro Roadmap Reform Review A Conceptual Framework Data and Identi–cation Results Conclusion The Economic Impact

uotaIntro Roadmap Reform Review A Conceptual Framework Data and Identi�cation Results Conclusion

The Economic Impact of Special Economic Zones:Evidence from Chinese Municipalities

Jin WangLondon School of Economics

January 16th, 2009

Jin Wang Special Economic Zone

uotaIntro Roadmap Reform Review A Conceptual Framework Data and Identi�cation Results ConclusionMotivation Research Question Main Results

Motivation

What are Special Economic Zones (SEZ)s?A demarcated area of land within a country to encourage foreigninvested industry and services for exports using special laws andpolicies.In Chinese context, SEZ means a land using property rightsprotection, tax breaks and a preferential land policy for foreigninvestors.



Why study Chinese Special Economic Zones (SEZ)s?

During the last 30 years, China has been greatly integrated into the

world in terms of its FDI, exports and foreign exchange reserve.

SEZs are very important institutional foundations which drove the

phenomenon and have been underexplored.

World Bank (2008),

3000 zones in 135 countries today, accounting for over 68 million

direct jobs and over $500 billion of direct trade-related value added.

The exact economic impact of SEZs is empirically understudied.



Research Question

From 1979, China has gradually created SEZs in its municipalities.

I collect a unique and comprehensive municipality level dataset from

1978 to 2007 to study:

Is SEZ e¤ective in boosting FDI related outcome?

Does SEZ come in the price of crowding out domestic investment?

Does SEZ bring higher total factor productivity growth?



Research Question









Research Question









Main results

Strategy to tackle the endogeneity of SEZ granting sequence:

1 Dif-in-Dif with municipalitiy speci�c trend and �xed e¤ects

2 Dif-in-Dif combined with propensity score matching

3 Restrict sample to later SEZs only

4 Placebo test for pre-SEZ period and diversion e¤ect

Preview of the results

1 SEZs attract municipality FDI, mainly in the form of export-orientedand foreign-invested industrial enterprises, by 58%;

2 SEZs do not crowd out domestically owned investment and capital;

3 SEZs increase municipality TFP growth rate by 0.6 percentagepoints.



Main results

Strategy to tackle the endogeneity of SEZ granting sequence:

1 Dif-in-Dif with municipalitiy speci�c trend and �xed e¤ects

2 Dif-in-Dif combined with propensity score matching

3 Restrict sample to later SEZs only

4 Placebo test for pre-SEZ period and diversion e¤ect

Preview of the results

1 SEZs attract municipality FDI, mainly in the form of export-orientedand foreign-invested industrial enterprises, by 58%;

2 SEZs do not crowd out domestically owned investment and capital;

3 SEZs increase municipality TFP growth rate by 0.6 percentagepoints.



Related Literature

1 Research on SEZs:Case studies: Kung(1985), Willmore(1996), Ge(1999), Park(1997), Rolfe(2004),

Aggarwal(2005).

Theoretical studies: Litwack and Qian(1998), Xu(2009)

2 Economic Incentives of FDI Location Decision:Devereux et al (2006), Razin and Sadka (2006), Wang(2008), Du et. al(2009)

3 The Economic Bene�ts of FDI:As a source of capital: Whalley & Xin(2006), McGrattan & Prescott (2007),

Desai, Foley & Hines(2009);

As a channel of technology spillover: Coe, Helpman & Ho¤maister(2008);

Liu(2008), Hale & Long(2007), Abraham et al(2009).



Roadmap

Special Economic Zone Experiment Review

A Conceptual Framework

Data and Identi�cation Strategy

Regression Results

Conclusion


uotaIntro Roadmap Reform Review A Conceptual Framework Data and Identi�cation Results ConclusionMap Privilege

Expansion of SEZs



SEZs Granting Sequence

Variables 1978 1979-1985 1986-1990 1991-1995 1996-2007

1.Number of municipalitiesnewly granted SEZs 0 30 49 145 76

2. Number of municipalitieswith SEZs 0 30 79 224 300

3. Total Number ofmunicipalities 326 326 326 326 326

4. Ratio of municipalitieswith SEZs 0.0 0.09 0.24 0.69 0.92

5. Average Distanceto the coast(100miles) - 0.15 1.34 3.75 6.26

6. Average per capitaindustry output in 1978 - 806 611 429 263

7. Average per capitanumber of secondary students 1978 - 0.064 0.060 0.066 0.057



Packages o¤ered to foreign investors within SEZs

Property Rights Protection:Protect the foreign investors�property when the constitution of China is not

amended until 2004.

Tax incentive:Reduced rate (15-24%) of corporate income tax. Virtually zero custom

duties. Income tax exemptions for foreigners working in SEZs

Land and utility bill:>15 years investment free land use fee; or ��ve years free, �ve years half�.

20% o¤ in electricity, water bill, & exemption from local levies.

Liberal economic and labor laws:Limited restrictions on foreign ownerships. Power to hire and �re. Working

permit for foreigners who work in the zones.



A Conceptual Framework

Foreign Firm Decision: SEZ by in�uencing property rights

protection, corporate tax rate and land rental rate will attract FDI.

Hypothesis 1 LnFDIit= α+ η � SEZdummyit+Xitβ+ ξit

Capital Formation: SEZ by attracting FDI, may crowd out or not

of domestic investment & capital depending on the interaction

between FDI and domestic economy.

Hypothesis 2 LnDomIit=φ+ γ � SEZdummyit+Xitβ+ ξitLnDomKit=φ+ γ � SEZdummyit+Xitβ+ ξit

Technology Progress: If SEZ brings not only foreign capital, but

also more advanced technology, it will increase TFP growth.

Hypothesis 3 ∆TFPTFP = λi+γ � SEZdummyit+εit


uotaIntro Roadmap Reform Review A Conceptual Framework Data and Identi�cation Results ConclusionData Identi�cation

Data

326 Municipalities from 1978 to 2007.

1 Special Economic Zone IndexSEZdummy = 1, if the municipality is exposed to the SEZexperiment;SEZdummy = 0, if otherwise.

2 FDI Related OutcomeUtilized foreign direct investment; Exports; Industrial output byforeign invested enterprises

3 Growth Accounting DataGross Domestic Output (Y ) & De�ator for GDP and InvestmentReal Physical Capital Stock(Kf +Kd )Labor(L) and Human Capital (H)Labor and Capital Share



Identi�cation: Di¤erence in Di¤erence speci�cation

Yipt = α+ β � SEZdummyipt + δi + γt + εipt (1)

Yipt = α+ β � SEZdummyipt + δi + δp � (t � 1977) + γt + εipt (2)

Yipt = α+ β � SEZdummyipt + δi + δi � (t � 1977) + γt + εipt (3)

i , Municipality; p, Province; t, Year.

Endogeneity of selection:

Time varying factors �municipality speci�c trend;

Time invariant factors �municipality �xed e¤ect.Other Chinese macro events/reforms - year �xed e¤ect.



Identi�cation: Dif-in-Dif with Matching

For dif-in-dif estimates to be unbiased, the timing of the SEZ experimentshould be random. Then late treated municipalities are valid controlgroups for early ones. But is the timing of SEZ granting random? No.A possible identi�cation strategy is to assume that given a score ofrelevant selection criteria X , outcomes are independent of treatmentassignment, i.e. SEZ timing is random conditional on P(X ).

I use nearest neighbor approach to match early treatedmunicipalities with the closest counterparts that had SEZs later.

Propensity score estimation using a probit model PrfD = 1jXgX = (industrial output, education, geographical location)D = 1 is de�ned as being granted SEZs by 1992; D = 0 otherwise.

Restrict sample to matched 247 municipalities.



a. Probit Regression ResultsVariable Coe¢ cient (std. error)Industry output78 0.0006***

(0.0002)Secondarystudent78 -3.0710

(3.3481)Distance -0.0930***

(0.0197)Log Likelihood -204.11Pseudo R-squared 0.096Number of Obs. 326

b. Comparison Before and After MatchingMean Percent Reduction t-test

Variable Sample Treated Control Bias in |bias| t p>|t|Industry78 Unmatched 565.26 307.43 46.0 4.13 0.000

Matched 565.26 595.22 -5.3 88.4 -0.42 0.672Secondarystudent78 Unmatched 0.064 0.060 15.8 1.43 0.153

Matched 0.064 0.065 -3.8 76.0 -0.34 0.734Distance Unmatched 2.69 5.06 -60.1 -5.44 0.000

Matched 2.69 2.91 -5.7 90.4 -0.64 0.526



Identi�cation: Later SEZs only Speci�cation

Is the result mainly driven by the potential "Special" group which were

granted SEZs earlier?

After 1990s, big wave in granting, less concern on selection.

Restrict sample to municipalities having SEZs post 1990.


uotaIntro Roadmap Reform Review A Conceptual Framework Data and Identi�cation Results ConclusionStep One: SEZ Experiment on FDI Outcome Step Two: SEZ on Domestic Capital Formation Step Three: SEZ on TFP growth

SEZs on FDI

Ln(Per capita Foreign Direct Investment)Full Sample Matched Later SEZ

(1) (2) (3) Sample Sample

SEZdummy 0.723*** 0.478*** 0.460*** 0.434*** 0.355***(0.079) (0.056) (0.053) (0.061) (0.061)

Municipality FE Yes Yes Yes Yes YesYear FE Yes Yes Yes Yes Yes

Province Trend - Yes - - -Municipality Trend - - Yes Yes YesObservations 9772 9772 9772 7405 7404Adj R-squared 0.761 0.845 0.891 0.898 0.845



SEZs on Exports

Ln(Per capita Exports)

Full Sample Matched Later SEZ


SEZdummy 0.871*** 0.719*** 0.608*** 0.595*** 0.531***

(0.098) (0.080) (0.082) (0.096) (0.092)

Municipality FE Yes Yes Yes Yes Yes

Year FE Yes Yes Yes Yes Yes

Province Trend - Yes - - -

Municipality Trend - - Yes Yes Yes

Observations 9733 9733 9733 7391 7376

Adj R-squared 0.833 0.877 0.922 0.927 0.898



SEZs on Industrial Output by Foreign Invested Firms

Ln(Per capita Industrial Output of FIEs)



SEZdummy 0.307*** 0.275** 0.487*** 0.525*** 0.375**

(0.137) (0.124) (0.128) (0.130) (0.184)





Observations 3667 3667 3667 3055 2604

Adj R-squared 0.906 0.922 0.943 0.946 0.935



Placebo Test

Panel A Panel B Panel CLn(Per capita FDI) Ln(Per capita exports) Ln(Per capita FIE output)

SEZ(-2) -0.006 0.040 -0.123(0.040) (0.059) (0.108)

SEZ(-1) 0.046 0.125* 0.022(0.047) (0.070) (0.163)

SEZ(+0) 0.150*** 0.354*** 0.205(0.056) (0.087) (0.210)

SEZ(+1) 0.376*** 0.507*** 0.631***(0.068) (0.101) (0.201)

SEZ(+2) 0.445*** 0.630*** 0.466*(0.073) (0.112) (0.250)

SEZ(3+) 0.880*** 1.024*** 0.765***(0.083) (0.123) (0.254)

Municipality FE YES YES YESYear FE YES YES YESMunicipality Trend YES YES YESObservations 9772 9733 3667Adj R-squared 0.897 0.925 0.944



Test for Diversion E¤ect Within Province



Test for Diversion E¤ect Cross Province



SEZs on Domestic Investment

Ln(Real Domestic lnvestment)



SEZdummy 0.044 0.007 0.067** 0.087** -0.017

(0.044) (0.039) (0.033) (0.037) (0.040)





Observations 9732 9732 9732 7364 7399

Adj R-squared 0.931 0.942 0.960 0.961 0.960



SEZs on Domestic Capital Formation

Ln(Real Domestic Capital)



SEZdummy 0.027 0.012 0.067*** 0.078*** 0.023

(0.038) (0.033) (0.022) (0.025) (0.025)





Observations 9669 9669 9669 7301 7379

Adj R-squared 0.958 0.967 0.986 0.986 0.986



SEZs on TFP Growth

Let gross domestic output be a constant returns to scale function ofcapital and labor inputs(human capital augmented)

Y = F (K ,H � L, t)

where the appearance of t, time, denotes the fact that the productionfunction evolves over time due to technology progress.

∆TFPTFP

=∆YY� θk

∆KK� (1� θk )

∆(H � L)(H � L)

To recall Hypothesis 3:

∆TFPTFP

= λi+γ � SEZdummyit+εit

The e¤ect of SEZs on TFP growth will be identi�ed by the deviationfrom each municipality�s own growth rate level λi .



SEZs on TFP Growth Cont�d

TFP Growth

Capital share Capital share Capital share

Using Province average Using National average Using 1/3

(1) (2) (1) (2) (1) (2)

SEZdummy 0.035*** 0.006** 0.034*** 0.006* 0.035*** 0.007**

(0.002) (0.003) (0.002) (0.003) (0.002) (0.003)

Municipality FE Yes Yes Yes Yes Yes Yes

Year FE - Yes - Yes - Yes

Observations 9440 9440 9440 9440 9440 9440

R-squared 0.071 0.132 0.072 0.132 0.074 0.136



Conclusion

Special Economic Zone, by providing property right protection and

economic incentives to foreign investors, attracts foreign direct

investment in the form of export oriented industrial enterprises.

Special Economic Zone, by bringing FDI, does not crowd out

domestic investment and capital stock.

SEZ, bringing more advanced FDI, increase municipality TFP

growth by 0.6 percentage points.


Documents

The Economic Impact of Special Economic Zones: Evidence ......uotaIntro Roadmap Reform Review A Conceptual Framework Data and Identi–cation Results Conclusion The Economic Impact