Is There a Pollution Haven E⁄ect? Evidence from a Natural ...

Is There a Pollution Haven E¤ect? Evidence from aNatural Experiment in China

Yi Lua, Mingqin Wub, and Linhui Yuc

aNational University of Singapore, bSouth China Normal University, cUniversity of HongKong

June 2012

Lu, Wu, and Yu (NUS, SCNU, HKU) Pollution Haven E¤ect? June 2012 1 / 41

IntroductionMotivation

Extreme weather in the world

concerns about environmental protectiontougher regulations on pollutionpush for development of greener technologies

An unintended consequence

plant reallocation to regions with less stringent regulationspotential increase in the overall pollutant emissionsPollution Haven E¤ect



Academic evidence is far from conclusive

no e¤ect

e.g., Friedman, Gerlowski, and Silberman (1992); Levinson (1996a);Eskeland and Harrison (2003); Javorcik and Wei (2004)surveys: Dean (1992); Ja¤e, Peterson, Portney, and Stavins (1995);Levinson (1996b)

negative e¤ect (PHE)

e.g., Henderson (1996); Becker and Henderson (2000); List and Co(2000); Keller and Levinson (2002); List, Millimet, Gredriksson, andMcHone (2003); Dean, Lovely and Wang (2009)

One of the most contentious issues in the international economicsliterature (Kellenberg, 2009)

Insu¢ cient academic evidence, especially in developing countries(Taylor, 2004)



An inherent challenge � - endogeneity of environmental regulation

exogenousendogenous

instrumental variable approach: Millimet and Roy (2011) for a surveypropensity score matching: List, Millimet, Gredriksson, and McHone(2003)


IntroductionContribution

Use a change in the environmental regulation in 1998 in China, TwoControl Zone (TCZ), as a natural experiment

Di¤erence-in-di¤erences estimation

time variation: before and after 1998cross-sectional variation: cities in the TCZ list and those not in theTCZ list


IntroductionContribution

Hanna (2011)

DID estimationout�ow FDI in the U.S.�rm-level analysis

Departure of our study

Developed country (the U.S.) versus developing country (China)FDI sourcing country versus FDI recipient country


Background on the National Environmental Policies

Fast increase in sulfur dioxide (SO2) emissions

1.05 billion tons in 1990 to 1.28 billion tons in 199562.3% cities exceeded the national Class II standard

Regulation before 1995

the Air Pollution Prevention and Control Law (APPCL) enacted in1987 and executed in 1988general principles of supervision on air pollution for the governmentinstitutions and related enterprisesno comprehensive system including all contributors of SO2 emissionsno e¤ective regulations to limit the SO2 emissions



Regulation 1995-1998

the 1987 APPCL was amendedone chapter for air pollution caused by coal combustion and SO2emissionsregional strategy to control for pollution, TCZ

SO2 pollution control zone and acid rain control zone



Criteria for TCZs

SO2 pollution control zone

average annual ambient SO2 concentration above the national Class IIstandard (0.06 mg/m3) in recent yearsdaily average ambient SO2 concentration above the national Class IIIstandard (0.25 mg/m3)SO2 emission is large

acid rain control zone

average PH value of precipitation below 4.5sulfate deposition above the critical loadSO2 emission is large



New regulations in TCZs

desulfurization, dust-collecting facilities and other required equipmentinstalled for new thermal power plants, medium or large �rms withserious SO2 emissionsdesulfurization and dust-collecting measures taken for existingSO2-emitting plants

Timeline

National Environmental Protection Bureau (NEPB) started todesignate TCZ cities in late 1995NEPB sent the list to the State Council for approval in 1997The proposal was approved and put into e¤ective in 1998A total of 175 cities was listed as TCZ cities, 11.4% of the nationalterritory



E¤ects of the new regulation

in 2000, 102 cities in the TCZ achieved the national class II standard84.3% �rms designated as severely polluted �rms achieved theregulated level of SO2 emissionsaverage growth rate of SO2 emissions in TCZ between 2001-2006 was-6.5%till 2010, 94.9% cities achieved the national class II standard; no cityworse than the national class III standard


Empirical Strategy

Assume for a city c at year t, we can observe two outcome values,Yct (1) and Yct (0)

Yct (.) the logarithm of FDIYct (1) the value when there is stringent environment regulation,determined by economic factors Xct

Yct (1) = αc + λt +X0ctβ (1)

Yct (0) the value when there is no environmental regulation

Yct (0) = Yct (1) + γ (2)

where γ > 0 for any PHE

The PHE is identi�ed as

�γct = E [Yct (1)� Yct (0)] (3)

average e¤ect γct = γ


Empirical Strategy

In the observational data, only one of fYct (0),Yct (1)g is observedUse TCZ policy as a natural experiment to conduct a DID analysis

De�ne the treatment status indicator TCZ as

TCZc =�1 if city c is a TCZ city0 otherwise

(4)


Empirical Strategy

DID estimation

�γDID = E [Yc1998 � Yc1997jTCZc = 1]�E [Yc1998 � Yc1997jTCZc = 0]

= E [Yc1998(1)� Yc1998(0)jTCZc = 1]

+

�E [Yc1998(0)� Yc1997(0)jTCZc = 1]�E [Yc1998(0)� Yc1997(0)jTCZc = 0]

�= �γ+

�E [Yc1998(0)� Yc1997(0)jTCZc = 1]�E [Yc1998(0)� Yc1997(0)jTCZc = 0]

�(5)


Empirical Strategy

DID estimation

the identi�cation assumption

E [Yc1998(0)� Yc1997(0)jTCZc = 1]= E [Yc1998(0)� Yc1997(0)jTCZc = 0] (6)

the treatment and control groups are comparablethe treatment status may be endogenous, i.e.,

E [Yc1997(0)jTCZc = 1] 6= E [Yc1997(0)jTCZc = 0]


Empirical Strategy

DID estimation in regression form

Yct = αc + λt + γ � TCZc � Postt +X0ctβ+εct (7)

where

Postt =�1 if t � 19980 otherwise

(8)

Identi�cation assumption

E [∆εc1998jTCZc = 1,∆Xc1998,∆λ1998]

= E [∆εc1998jTCZc = 0,∆Xc1998,∆λ1998] (9)


Data

China City Statistical Yearbook, 1992-2009

Yct (logarithm): amount of realized FDIXct (logarithm): college students, high school students, telephone,GDP growth rate, taxi, road per capita, industrial production, retailingconsumption

O¢ cial document, "The o¢ cial reply of the State Council concerningacid rain control areas and SO2 pollution control areas"

list of TCZ cities

China Environmental Yearbook

SO2


Empirical FindingsTime Trends


Empirical FindingsBaseline


Empirical FindingsValidity Check on DID Estimation I, Di¤erential Time Trends Before the Policy Change

Check on whether the treatment and control groups are comparablebefore the policy change

E [∆εc1998�s jTCZc = 1,∆Xc1998�s ,∆λ1998�s ]

= E [∆εc1998�s jTCZc = 0,∆Xc1998�s ,∆λ1998�s ] (10)

for s � 1The corresponding regression speci�cation is

Yct = αc + λt + γ � TCZc � Postt+∑s�1 δs � TCZc � λ1998�s +X0ctβ+εct (11)

where

δs � δs+1 = E [∆Yc1998�s (0)jTCZc = 1]�E [∆Yc1998�s (0)jTCZc = 0] (12)


Empirical FindingsValidity Check on DID Estimation I, Di¤erential Time Trends Before the Policy Change


Empirical FindingsValidity Check on DID Estimation II, City-speci�c Time Trend

Cities in the treatment and control groups may follow di¤erent timetrends

decompose the �rst-di¤erenced error term into two parts,

∆εct = αc + ∆ε̃ct

the new identi�cation assumption is

E [∆ε̃c1998 jTCZc = 1,∆Xc1998,∆λ1998, αc ]

= E [∆ε̃c1998 jTCZc = 0,∆Xc1998,∆λ1998, αc ] (13)

The corresponding regression speci�cation is

Yct = αc + λt + γ � TCZc � Postt+αc � t +X0ctβ+εct (14)


Empirical FindingsValidity Check on DID Estimation II, City-speci�c Time Trend


Empirical FindingsValidity Check on DID Estimation III, Matched Control Group

Match each city in the treatment group with one in the control groupbased on

Wc92�97 (logarithm, 92-97 average): wage, population, GDP growthrate, college students, high school students, telephone, road per capita,valued added tax, industrial productionthe regression for the matching

ρc = Pr (TCZc = 1jWc92�97) = F (Wc92�97)


E [∆εc1998 jTCZc = 1,∆Xc1998,∆λ1998, ρ̂c ]

= E [∆εc1998 jTCZc = 0,∆Xc1998,∆λ1998, ρ̂c ] (15)


Empirical FindingsValidity Check on DID Estimation III, Matched Control Group


Empirical FindingsValidity Check on DID Estimation IV, Surrounding Cities

Use a TCZ citie�s all surrounding non-TCZ cities as the control group

similar conditions, like economic, climate, etcimprove the comparability between the treatment and control groups


Empirical FindingsValidity Check on DID Estimation IV, Surrounding Cities


Empirical FindingsValidity Check on DID Estimation V, Province-time E¤ect and Spatial Correlation

Allow for any arbitrary time-varying provincial compounding factorsand also spatial correlation


E�

∆εc1998 jTCZc = 1,∆Xc1998,∆λ1998,∆λp1998�

= E�

∆εc1998 jTCZc = 0,∆Xc1998,∆λ1998,∆λp1998�(16)

the corresponding regression speci�cation is

Yct = λc + λt + γ � TCZc � Postt+λpt +X0ctβ+εct (17)


Empirical FindingsValidity Check on DID Estimation V, Province-time E¤ect and Spatial Correlation


Empirical FindingsValidity Check on DID Estimation VI, A Placebo Test: 1996 as the Year of Policy Change

The preparation of TCZ lists took more than 2 years since late 1995

potential expectation e¤ect

Check on the expectation e¤ect

re-de�ne 1996 (instead of 1998) as the year of policy changethe DID estimator is

�γ̄DID = E [Yc1996(0)� Yc1995(0)jTCZc = 1]�E [Yc1996(0)� Yc1995(0)jTCZc = 0] (18)

γ̄DID is expected to be zero


Empirical FindingsValidity Check on DID Estimation VI, A Placebo Test: 1996 as the Year of Policy Change


Empirical FindingsFalsi�cation Test, Other Una¤ected Outcome Variables

Look at some other outcome variables that are supposed to be nota¤ected by the policy change

Zct (logarithm): bus, bus passenger, middle school, primary school,primary school students, total road areathe DID estimator is

�γzk

DID = EhZ kc1998(1)� Z kc1997(0)

��TCZc = 1i�E

hZ kc1998(1)� Z kc1997(0)

��TCZc = 0i= E

h∆εz

k

c1998

��TCZc = 1i� E h∆εzk

c1998

��TCZc = 0i(19)

given γ̂zk

DID = 08zk , we have

Eh

∆εzk

c1998

��TCZc = 1i = E h∆εzk

c1998

��TCZc = 0i 8zk (20)


Empirical FindingsFalsi�cation Test, Other Una¤ected Outcome Variables


Empirical FindingsInstrumental Variable Estimation

The selection of TCZ is based on some criteria

SO2 � 60 for northern cities; PH � 4.5 for southern citiesinstrumental variable

TCZIV = I [Mc95 � m0 ] (21)

New identi�cation assumption is

E [∆εc1998j I [Mc95 � m0] = 1,∆Xc1998,∆λ1998,Mc95]

= E [∆εc1998j I [Mc95 � m0] = 0,∆Xc1998,∆λ1998,Mc95] (22)

based on past valuesspeci�c threshold



Implementation issues

no PH informationonly 80 cities (about 30% of the total observations): capital cities,large and industrial cities

Remedies

use SO2 to replace PH (so2 dissolved in the water and precipitationbecomes acid rain)

Costs

low predicatory power of the instrument (irrelevance) and weakinstrumentseveral econometric tests on the relevance and weak instrumentDurbin-Wu-Hausman test on the comparison of OLS and IV estimators


Empirical FindingsOther Robustness Checks

Use 1992-1995 as the Pre-treatment Period

Excluding four municipalities (Beijing, Chongqin, Tianjin, Shanghai)

municipalities have higher administrative levels than other cities

Excluding cities without information of FDI in year 1998

no post-treatment outcome value

Excluding cities without information FDI in the period of 1995-1997

no enough pre-treatment outcome value


Empirical FindingsOther Robustness Checks


Conclusion

Investigate whether there is a Pollution Haven E¤ect

Use a change in the environment regulation in China in 1998 as anatural experiment

DID estimation �nds signi�cant, negative PHE

the stringent regulation on SO2 emissions causes the amount of FDI todrop by 41%

Robust to a series of checks on the validity on DID estimation andother econometric concerns


Is There a Pollution Haven E⁄ect? Evidence from a Natural ...

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