By province - Institute for China and Global Development

Albert Park, University of Oxford, CEPR, and IZA

• Since 2008, China’s labor markets were
greatly influenced by two major events
• New Labor Contract Law ‐‐ beginning of 2008
• Global economic crisis ‐‐ October 2008
• Evidence of robust employment recovery
• Relative lack of information on how well the
new Labor Law has been enforced, including
• Employment impacts
• Affect of crisis on implementation

• How did the crisis affect employment
• How well has the Labor Law been enforced in
different cities
• Did the crisis affect enforcement
• How did city variation in enforcement affect
the impact of the Labor Law on employment
changes
• Did the crisis reduce these impacts

• 8 provinces: 4 coastal provinces (Shandong, Jiangsu,
Zhejiang, and Guangdong), one northeast province
(Jilin), one central province (Hubei), one northwest
province (Shaanxi), and one southwest province
(Sichuan).
• Representative sample of >2000 manufacturing firms
in 25 municipalities
• Focus on employment at 4 points in time: end‐2007,
mid‐2008, end‐2008, mid‐2009
• Sampling frame: all firms who ever had credit
relationship with any financial institution
• Key collaborators: People’s Bank of China Research
Department, Peking University, CASS

• In each of 6 cities, survey 700 local resident
households and 600 migrant households
• Surveyed >15,000 adults, including 6000
migrants
• 3‐stage PPS sampling of urban sub‐districts,
neighborhoods, and households
• Detailed enumeration of all dwellings in each
neighborhood
• Surveys directed by CASS, working closely with
city Statistical Bureaus

Growth was slowing prior to the crisis and rebounded quickly

• Massive $560 billion economic stimulus package
• Support to enterprises:
• suspend tax payments
• social insurance contributions delayed and/or reduced
• credit expansion
• wage subsidies
• Expansion of labor training programs
• Expansion of safety net programs (esp. rural minimum
living standards subsidies)
• Expanded social insurance coverage (including
portable pension and unemployment insurance for
migrants)

• Job vacancy rates fell but bounced back quickly
• Up to 20 million migrant workers lost jobs
temporarily (MOA, NBS surveys)
• 2/3 of those losing jobs reemployed by summer
2009 (Rozelle et al., 2009)
• Migrant employment in cities increased by 2.9%
from 2008 to 2009 (to 145 million) (NBS)
• By 2010, very low urban unemployment rates
(China Urban Labor Survey in 6 cities)
• Migrant wages continued to increase on average
through the crisis

CULS2 (2005) CULS3 (2010)
Local Migrants Local Migrants
All 5.34 1.39 2.36 0.66
By gender:
Male 5.97 1.06 2.88 0.54
Female 4.74 1.75 1.88 0.78
By age:
16~29 9.60 2.14 8.24 1.15
30~39 7.60 0.91 1.74 0.20
40~49 7.23 0.68 2.35 0.52
50~59 3.10 1.91 1.84 0.68
60+ 0.07 0 - 0
By education:
0~6 0.90 1.27 0.33 1.17
7~9 7.00 1.48 2.52 0.53
10~12 6.41 1.46 2.29 0.92
13+ 2.19 0.70 2.89 0.97

NBS=National Bureau of Statistics
RCRE=Research Center for Rural Economy (Ministry of Agriculture)
PBC=People’s Bank of China

2008 2009
Manufacturing 42.0 39.1
Construction 16.3 17.3
Hotels and 7.6 7.8
catering
Wholesale and 7.0 7.8
retail trade
Transport 5.6 5.9
Other 21.5 22.1
Units: %. Source: Sheng Laiyun of NBS (2009)

Jun‐08 Dec‐08 Jun‐09
All firms 3.03 ‐0.53 2.87
Non‐exporters 3.27 0.68 3.20
Exporters 2.76 ‐1.92 2.48
By ownership:
State/collective ‐6.05 ‐0.83 1.78
Private 2.61 0.99 5.40
Joint/Ltd/Other 3.70 0.65 1.70
Foreign 3.84 ‐4.55 4.30
By size (#employees)
Smallest quartile 2.11 0.48 3.41
Second quartile 3.00 0.28 3.20
Third quartile 3.00 0.16 4.16
Largest quartile 3.05 ‐0.72 2.63
Crisis hit exporters, foreign‐invested firms, and larger firms the hardest.

Surplus Appropriate Deficit
All firms 5.05 59.86 35.09
By ownership:
State/collective 35.15 53.26 11.59
Private 4.55 57.33 38.12
Joint/Ltd/Other 2.55 69.90 27.55
Foreign 1.65 45.36 52.99
Still very high labor demand, despite regulations and recent negative shocks.
State/collective sector still plagued by surplus labor.

• Labor Contracts
• After 2 fixed‐term contracts, or 10 years of employment,
contract must be open‐ended
• Limits on probationary period (1‐3 months depending on
contract length)
• Regulations on temporary work agencies (labor service
companies)
• Severance conditions
• 30‐day written notice
• Severance pay: one month’s pay for each year of service (half
month’s pay if less than 6 months), double severance pay for
unfair dismissal
• Internationally, law considered highly protective of
workers

100%
80%
Very poor
60%
Somewhat
poor
40%
So so
20%
Satisfied
Very good
0%
Local residents
before crisis
Local residents
after crisis
Migrants before
crisis
Migrants after
crisis
• There is no significant difference between local residents and migrants.
• There is no significant change in enforcement before and after crisis for both local
residents and migrants.

Notable reduction in informality of migrant employment

Very strict Strict Not strict
By period:
2007 21.57 71.12 7.31
Jan‐Jun 2008 22.46 72.61 4.93
Jul‐Dec 2008 23.47 72.33 4.19
Jan‐Jun 2009 24.61 71.34 4.04
By size:
Smallest 18.32 73.21 8.47
2nd quartile 25.02 70.38 4.60
3rd quartile 22.01 73.66 4.33
Largest 26.40 70.27 3.33
Firms report strict enforcement, with no weakening during the crisis.
Smaller firms report less strict enforcement than larger firms.

Have labor regulations
made it more difficult
for your firm to hire and
fire workers (% yes)
Has new Law
reduce hiring
(% yes)
Has new Law
reduce firing
(% yes)
Total 34.5 15.8 30.8
By ownership type:
State/collective 28.1 18.4 27.3
Private 31.6 19.0 33.8
Joint/Ltd/Other 35.4 15.2 32.8
Foreign 38.3 13.5 25.8
By province:
Zhejiang 46.5 17.8 29.7
Jiangsu 31.9 20.3 35.0
Guangdong 45.5 15.8 38.9
Shandong 21.5 13.2 28.7
Jilin 25.4 51.5 34.1
Hubei 21.4 5.3 37.2
Shaanxi 26.0 7.1 27.7
Sichuan 20.4 5.1 13.8
By export status:
0 34.9 16.8 27.2
1 33.5 14.8 35.7

Province
significant
increase
some
increase
no
increase
Zhejiang 12.74 60.28 26.98
Jiangsu 15.97 67.46 16.57
Guangdong 15.65 75.97 8.38
Shandong 6.14 70.81 23.05
Jilin 8.29 67.67 24.04
Hubei 21.34 42.57 36.09
Shaanxi 10.98 64.09 24.93
Sichuan 5.04 86.68 8.28
Total 11.21 68.16 20.63

Days yuan
Total 6.43 12850
By ownership:
State/col 10.65 21189
Private 6.36 9391
Joint/Ltd 6.49 14319
Foreign 5.24 12166
By province:
Zhejiang 4.62 10401
Jiangsu 5.89 7135
Guangdong 6.37 18949
Shandong 8.25 17483
Jilin 9.20 7837
Hubei 7.51 10412
Shaanxi 9.24 15571
Sichuan 5.65 11981

Albert Park, University of Oxford
John Giles, World Bank
Du Yang, Chinese Academy of Social Sciences
Preliminary, please do not cite

• A number of previous papers have found a negative
(positive) relationship between the flexibility of labor
regulations and employment (unemployment) (Besley and
Burgess, 2004; Ahsan and Pages, 2009; Fledmann, 2009;
Djankov and Ramalho, 2009; Kaplan, 2009)
• Few studies analyze firm‐level data
• Almeido and Carneiro (2005) find stricter enforcement (higher
fine) has no effect on total employment, but increases informal
employment in Brazil
• Amin (2007) finds negative effect of stricter regulation (mean
perception by state) on employment in Indian retail outlets
• Fallon and Lucas (1993) find a negative employment effect of
new legislation to increase job security in India and Zimbabwe
*only latter study uses panel data, aggregated to industry level

• Positives:
• Essential for constructing aggregate measures of
enforcement and implementation
• Enables examination of heterogeneity in impacts
for different types of firms
• Negatives:
• Selectivity bias if exited firms not surveyed
• Captures employment only in sampled firms (may
exclude small firms, informal sector, nonmanufacturing
sector)

Firm static model:
L ijc,t = α 1 X c,2007 + α 2 X ijc + α 3 Exporter ijc,2007 *S jc,t + λ t + ε ijc,t
Dynamic model:
L ijc,t = δ 1 L ijc,2007 + δ 2 X c,2007 + δ 3 X ijc + δ 4 Exporter ijc,2007 *S jc,t + λ t + u ijc,t
Note: models can be estimated at firm or city level
• Subscripts i=firm, j=sector, c=city, t=year
• X ijc includes firm time‐invariant characteristics (including 2007
characteristics, e.g., size, exporter)
• X c,2007 are city characteristics before Labor Law implemented
• λ t are time period fixed effects
• Notes: interacted terms also included independently as regressors,
constant term omitted

• Quarterly export data from first quarter of
2007 through second quarter of 2009
• Data on export volume by city‐sectordestination
• Used to construct export shock variable (S) by
sector (s) in each city (c):
Δexports cst = exports cst –exports cst‐1 ,
where exports ct = exports in previous 6 months (12
months for 2007)

National Data
25 sample cities

Dependent variable (ordered probit):
Enforcement
(3=very strict, 2=strict, 1=not strict)
Reference categories:
food and beverage
state sector
Zhejiang
Size quartile 4 (smallest size)
2007
Findings: enforcement stricter for:
‐ capital producers
‐ state sector (not foreign)
‐ Sichuan, Jiangsu, Jilin (no strong
pattern)
‐ exporters
‐ large firms
‐ most recent period
Coef. Std. Err. t P>|t|
Sector consumer products ‐0.0171 0.0689 ‐0.25 0.804
Sector raw material 0.0552 0.0665 0.83 0.406
Sector capital and equipment 0.1761 0.0722 2.44 0.015
Sector other 0.2774 0.0927 2.99 0.003
Ownership private ‐0.0669 0.1036 ‐0.65 0.519
Ownership joint ‐0.0373 0.0996 ‐0.37 0.708
Ownership foreign ‐0.2348 0.1136 ‐2.07 0.039
Jiangsu 0.2459 0.0626 3.93 0.000
Guangdong 0.0556 0.0667 0.83 0.404
Shandong 0.0303 0.0603 0.50 0.615
Jilin 0.1213 0.0867 1.40 0.162
Hubei ‐0.1217 0.1328 ‐0.92 0.360
Shaanxi 0.0514 0.0826 0.62 0.534
Sichuan 0.5851 0.0863 6.78 0.000
Size‐3 rd quartile 0.4032 0.0585 6.89 0.000
Size‐2 nd quartile 0.4289 0.0595 7.20 0.000
Size‐largest quartile 0.5440 0.0624 8.71 0.000
Exporter 0.1090 0.0508 2.15 0.032
End‐2008 0.0164 0.0473 0.35 0.728
Mid‐2009 0.0950 0.0472 2.01 0.044

Coef. Std. Err. t P>|t|
2007 city enforcement ‐0.13771 0.005644 ‐24.4 0
Sector consumer products ‐0.00472 0.001952 ‐2.42 0.016
Sector raw material ‐0.00355 0.001893 ‐1.87 0.061
Sector capital and equipment ‐0.01039 0.002032 ‐5.11 0
Sector other ‐0.00256 0.00257 ‐0.99 0.32
Ownership private 0.005141 0.002896 1.78 0.076
Ownership joint 0.001413 0.002802 0.5 0.614
Ownership foreign 0.011397 0.003129 3.64 0
Jiangsu ‐0.01689 0.001907 ‐8.86 0
Guangdong ‐0.04176 0.002599 ‐16.07 0
Shandong 0.011121 0.003057 3.64 0
Jilin ‐0.06418 0.004317 ‐14.87 0
Hubei ‐0.01749 0.004375 ‐4 0
Shaanxi 0.098844 0.003127 31.61 0
Sichuan 0.137756 0.003589 38.38 0
Size‐3 rd quartile 0.001194 0.001586 0.75 0.452
Size‐2 nd quartile 0.003146 0.001592 1.98 0.048
Size‐largest quartile 0.00627 0.001686 3.72 0
Exporter 0.004404 0.001364 3.23 0.001
Export shock ‐0.0023 0.00103 ‐2.23 0.026
Exporter*export shock 0.002957 0.002133 1.39 0.166
End‐2008 0.017288 0.001264 13.68 0
Mid‐2009 0.029576 0.001306 22.64 0
Log 2007 city population ‐0.01828 0.001362 ‐13.43 0
Log 2007 city GDP p.c. 0.056516 0.003863 14.63 0
Log 2007 city GDP growth ‐0.0078 0.000452 ‐17.25 0
Log 2006‐7 city budget expend p.c. 0.085827 0.002624 32.71 0
Log 2007 city wage ‐0.10943 0.007819 ‐14 0
2007 city secondary sector share ‐0.00286 0.000113 ‐25.31 0
Constant 0.489621 0.056978 8.59 0
Enforcement increased more for
cities with:
1) Less initial enforcement
2) Smaller population
3) Higher GDP p.c.
4) Lower prior economic growth
5) More budgetary expend p.c.
6) Lower wage
7) interior provinces
8) Larger firms
9) Exporters
10) City‐sectors less subject to
negative export shocks

• Consider employment (E t ) to be a simple ratio of a firm’s
optimal employment given perfect enforcement of the
Labor Law (L t ) and the actual strictness of Labor Law
enforcement (s t ):
E t = L t /s t
Here, 0

• Consider two possible impacts of Law on strictness of
enforcement:
• Brings strictness of all cities closer to being perfect
(s 2 =1), then ΔlnE = ΔlnL + lns 1
> initial strictness is associated with increases in
employment
• No change in strictness, then ΔlnE = ΔlnL
> strictness has no effect on employment change, but
this is sensitive to assumptions about the
complementarity between strictness and substance of
the law

ΔW ijc,t = β 1 L c,2007 + β 2 X c,2007 + β 3 X ijc + β 4 S jc,t + β 5 Exporter ijc,2007 S jc,t L c,2007 + λ t + u ijc,t
• Key identification issue: endogeneity of enforcement
– Focus on pre‐Labor Law enforcement (predetermined)
– City‐level measures of enforcement
• Measurement
– Which enforcement variables
– Defining shocks:
• City‐sector trade shocks from customs data

• Clustered standard errors
• L c,2007 is city‐level measurement, so should cluster standard
errors at city level
• Small number of clusters (25)
▪ *Bootstrapped standard errors (Cameron, Gelbach, Miller,
2008)
▪ *Define observations at city‐level
• Classical measurement error in L c,2007 due to reporting error and
sampling error
• Attenuation bias toward zero
• *Use IV constructed from alternative enforcement
measurements
*To do!

Coef. Std. Err. t P>|t|
2007 city enforcement 0.090 0.020 4.53 0
Sector consumer products ‐0.018 0.016 ‐1.09 0.285
Sector raw material 0.003 0.014 0.19 0.85
Sector capital and equipment 0.005 0.015 0.33 0.747
Sector other 0.006 0.023 0.27 0.789
Ownership private 0.015 0.015 1.02 0.317
Ownership joint 0.018 0.016 1.1 0.285
Ownership foreign 0.000 0.018 ‐0.01 0.993
Jiangsu 0.000 0.010 0.02 0.985
Guangdong ‐0.015 0.013 ‐1.19 0.248
Shandong 0.009 0.013 0.69 0.497
Jilin ‐0.022 0.016 ‐1.38 0.182
Hubei 0.107 0.013 8.17 0
Shaanxi ‐0.031 0.011 ‐2.89 0.009
Sichuan ‐0.047 0.020 ‐2.42 0.024
Exporter ‐0.021 0.009 ‐2.22 0.037
Export shock 0.010 0.011 0.89 0.385
Exporter*export shock 0.030 0.016 1.79 0.086
Size‐3 rd quartile 0.024 0.010 2.33 0.029
Size‐2 nd quartile 0.025 0.008 3 0.007
Size‐largest quartile 0.032 0.009 3.41 0.003
Firm age ‐0.002 0.001 ‐3.75 0.001
End‐2008 ‐0.032 0.008 ‐3.93 0.001
Mid‐2009 ‐0.015 0.008 ‐1.74 0.096
N=3775
Standard errors
clustered by city‐year

Log 2007 city population 0.017 0.005 3.21 0.004
Log 2007 city GDP p.c. ‐0.031 0.014 ‐2.21 0.038
Log 2007 city GDP growth 0.006 0.002 3.39 0.003
Log 2006‐7 city budget expend p.c. ‐0.040 0.010 ‐4.07 0.001
Log 2007 city wage 0.095 0.034 2.81 0.01
2007 city secondary sector share 0.001 0.000 1.95 0.064
Constant ‐0.679 0.248 ‐2.73 0.012
Note: Controlling for city characteristics increases the coefficient magnitude and
statistical significance of 2007 city enforcement

Without city controls With city controls
2007 city enforcement 0.054*** 0.090***
Ln(mean training cost per firm) 0.021*** 0.028***
Mean training days 0.00433* 0.00682***
Notes: ***significant at 1% level, * significant at 10% level.
Results are from separate regressions using each enforcement measure and
same specification as in previous tables.

• Regressions of change in city enforcement
from 2007 to 2009 on initial city enforcement
level finds a highly significant negative
coefficient of ‐0.12

Coef. Std. Err. t P>|t|
2007 city enforcement ‐0.0037 0.0295 ‐0.13 0.900
Export shock ‐0.0815 0.0363 ‐2.25 0.028
Exporter 0.0027 0.1190 0.02 0.982
Enforcement*Export shock 0.0437 0.0185 2.36 0.021
Enforcement*Exporter ‐0.0116 0.0548 ‐0.21 0.833
Export shock*Exporter 0.1514 0.0826 1.83 0.071
Enforcement*Export
shock*Exporter
‐0.0658 0.0380 ‐1.73 0.088
Dependent variable: change in ln(production workers). Table shows coefficents on
newly added interaction terms. Rest of specification same as above, other coefficients
not reported here.
Firms suffering from adverse export shocks were more sensitive to 2007 enforcement
differences

• Impacts less for materials and capital sectors
• Impacts are greater in Shandong and Hubei
• Impacts less for state firms, larger firms, and
in earlier years, but none of these differences
are statistically significant

• A significant share of managers report that the new
Labor Law is enforced strictly and has affected
employment decisions and increased labor costs
• Enforcement strictness increased more in interior
provinces and with more foreign firms/exporters, but
was less strict in cities exposed to negative export
shocks
• Results suggest that enforcement of the new Labor
Law reduced employment growth more in areas with
previous lax enforcement
• These effects were more apparent for firms exposed
to adverse export shocks

• Crisis had very short‐term impacts on aggregate
employment despite introduction of Labor Law
• This was NOT due to lack of enforcement of the
Labor Law
• Suggests that robust labor demand is facilitating
regulatory reform
• Labor Law reduced employment growth more in
cities with prior lax enforcement
• Labor regulation still may emerge as key constraint
in future