Cities facilitate learning and human capital accumulation. In a dense, local labor market, workers can benefit from knowledge spillovers and therefore enhance their productivity. This is supported by many empirical studies from developed countries. Less is known in cities in developing countries. Using micro data from the 2004 manufacturing census and 2005 population census in China, we find that overall workers benefit from labor market pooling and knowledge spillovers in Chinese cities but rural migrants benefit much less than do local urban residents. This is not because rural migrants are low skilled or work in informal sectors. This may be because they lack social network and suffer “double discrimination” for being “rural” and being “migrant.” Our findings suggest that social interactions in cities provide a channel of learning alternative to formal schooling. Our findings also have policy implications on how Chinese cities can become “skilled” during the rapid urbanization process coupled with global competition.

1. Learning in Chinese Cities:
Do Rural Migrants Benefit from Labor
Market Agglomeration Economies？
Shihe Fu
Fulbright Visiting Scholar at CRE, MIT
Southwestern University of Finance and
Economics
STL China Talk Series
October 17 2016

2. 2
Outline
 Background: Why do cities exist
• business agglomeration economies
• labor market agglomeration economies
 Research questions and motivation
 Data and methodology
 Results
 Policy implications and future research

3. 3
Why Do Cities Exist? An Economics
Approach
 Cities are areas with high-density population
(or concentration of people and firms in limited
geographic areas)
 The benefits of such concentration are called
agglomeration economies
 The reason why cities exist

4. 4
Firm Side: Business agglomeration
economies
 Localization Economies: the benefit from the
concentration of same-industry firms in a city
• Silicon Valley, Route 128, Detroit
 Urbanization Economies: the benefit from
the concentration of different-industry firms in a
city
• New York City
Hoover (1937) (Location Theory and the Shoe and Leather Industries)

5. 5
Micro-foundations of Localization
Economies
 Sharing
• sharing inputs: highways, public utility,
airport
 Pooling
• concentration of firms and workers
facilitates matching and reduces search costs
 Learning
• information or knowledge spillovers
 Specialization; Competition

6. 6
Dynamic Localization Economies
 Industries with strong localization economies
tend to grow fast (Marshall, 1920)
 In the dynamic context, localization economies
is dubbed Marshallian externalities
• Marshallian-Arrow-Romer (MAR) externalities
(Glaeser et al., 1992) (Growth in cities, JPE)

7. 7
Urbanization Economies
 Benefits from the general level of city economy.
Measured by city size (population).
(Hoover, 1937, 1971) , Henderson (1986)
 Benefits from overall local urban scale and
diversity (Henderson et al., 1995)
 Benefits from industrial diversity
 In dynamic context: Jacobs externalities,
• Glaeser et al. (1992)
• Jacobs (1961,1969): The Death and Life of Great
American Cities

8. 8
Micro-foundations of Urbanization
Economies
 Sharing
 Pooling
 Learning
• Jacobs: Cross-industry fertilization
promotes innovation and urban growth
 Economies of scope

9. Worker Side: Labor Market
Agglomeration Economies
 Benefit from the concentration of employment
 Labor market localization economies:
• Benefits from concentration of workers in the
same industry (occupation) in a city.
• In dynamic context, Marshallian externalities
in labor markets
 Labor market urbanization economies:
• Benefits from concentration of workers in
different industries (occupations) in a city.
• In dynamic context, Jacobs externalities in
labor markets.

10. Urban Wage Premium
 Labor market agglomeration economies can
improve workers’ matching and learning, therefore
help enhance skills and accumulate human capital
 Workers’ productivity will be higher in larger
cities
 Wages will be higher in larger cities: urban wage
premium

11. Micro-foundations of Labor Market
Agglomeration Economies
 Labor market pooling:
• Improve matching between workers and firms;
reduce search friction; increase labor mobility
 Knowledge spillovers (human capital
externalities) through social interactions
• Formal communications (Charlot and Duranton, 2004)
• Informal social interaction (social networking)
• Poaching
• Peer effect

12. When an industry has thus chosen a locality for itself, it
is likely to stay there long: so great are the advantages
which people following the same skilled trade get from
near neighbourhood to one another…if one man starts a
new idea, it is taken up by others and combined with
suggestions of their own; and thus it becomes the source
of further new ideas. And presently subsidiary trades
grow up in the neighbourhood, supplying it with
implements and materials, organizing its traffic, and in
many ways conducing to the economy of its material.
Marshall (1920): Principles of Economics, Book IV, Chapter 10 The
Concentration of Specialized Industries in Particular Localities

13. 13
Most of what we know we learn from other people. We
pay tuition to a few of these teachers, either directly or
indirectly by accepting lower pay so we can hand around
them, but most of it we get for free, and often in ways that
are mutual - without a distinction between student and
teacher. … We know this kind of external effect is
common to all the arts and sciences - the 'creative
professions'. All of intellectual history is the history of
such effects.
But, as Jacobs has rightly emphasized and illustrated with
hundreds of concrete examples, much of economic life is
'creative' in much the same way as is 'art' and 'science‘…
What can people be paying Manhattan or downtown
Chicago rents for, if not for being near other people?
Lucas (1988): On the mechanism of economic development

14. Empirical Evidence for Labor Market
Agglomeration Economies
 Extensive empirical evidence on urban wage
premium: Glaeser and Mare (2001), Moretti (2004),
Rosenthal and Strange (2006)
 mostly from developed countries
 mostly on effect of city size (urbanization
economies)
 mostly on urban workers
 Testing whether cities make workers more
productive or productive workers move to cities

15. Research Questions
 Do Marshallian externalities exist in
Chinese cities?
 And if so, how large is the magnitude?
 Do rural migrants benefit from urban
labor market agglomeration?

16. Research Motivation
 Massive rural-urban migration of low-skilled
workers.
 Regulations on urban growth: institutional
barriers preventing free migration (hukou
system); cities are relatively small (Au and
Henderson, 2005)
 Global competition; manufacturing industry
upgrading
 City growth and human capital (Glaeser and
Saiz, 2004)
 How to make Chinese cities become skilled?

17. Why Focus on Labor Market Marshallian
Externalities?
 Mitigate the problem “productive workers
select into cities”
 Agglomeration economies are very
localized—decaying with distance
 Very limited empirical evidence so far

18. Main Findings
 There exist Marshallian externalities in the
urban labor market in China
 Rural migrants also benefit from
Marshallian externalities, but benefit much
less than do local workers, urban workers,
or local workers with an urban hukou
 “Double discrimination” (based on hukou
and migration status)

19. Data
 2004 Manufacturing Census data: total
employment in each firm, by education
 2005 inter-census population survey (one-
fourth of the 1% sample)
 Merge by city-industry link (two-digit
industries) (Moretti, 2004)

20. Key Variables of Agglomeration
 log(Emp): total employment in a city-
industry, measuring labor market pooling
effect
 CollegeShare: number of workers with a
college degree or above in a city-industry
cell divided by total employment in that
city-industry cell (human capital externality)

21. Model
effectfixedindustry:
effectfixedcity:
cityinindustryinsharecollege:
cityinindustryinemploymenttotal:
..)education.age,(gender,attributesindividual:
cityinindustryinworkerofwage:
)log(log
3
21
j
k
jk
jk
i
ijk
ijkjk
jkijkijk
kjreCollegeSha
kjEmp
X
kjiW
reCollegeSha
EmpXW







22. Causal Identification
 Two observationally identical workers (A and B)
working in the same industry in two identical
cities (CA and CB), the only difference is that in
one city (CA) there are more workers and more
highly-educated workers in that industry, does
this increase worker A’s wage?
 How to make two workers observationally
identical? Include many observed worker
characteristics: gender, age, marital status,
education, hukou status, migration year, type of
employers, type of labor contract, industry,
occupation

23. Existence of labor market agglomeration economies
baseline industry occupation occuindu
Urbanhukou 0.0297*** 0.0375*** 0.0166*** 0.0217***
2.51 3.49 2.20 2.93
Highschool 0.1330*** 0.1322*** 0.1008*** 0.1004***
23.57 22.47 26.64 26.91
Associate 0.4284*** 0.4250*** 0.3226*** 0.3200***
31.01 31.02 33.12 33.56
College 0.7560*** 0.7522*** 0.6032*** 0.6005***
26.67 26.81 28.84 29.53
Masterabove 1.3198*** 1.3097*** 1.1195*** 1.1132***
29.55 29.48 31.21 31.45
log(Emp) 0.0052* 0.0015 0.0019 0.0029
1.72 0.36 0.66 0.74
CollegeShare 0.5044*** 0.3431*** 0.4621*** 0.3598***
9.97 5.36 10.03 6.10
R2 0.39 0.40 0.43 0.44
sample size 172,002

24.  Weak evidence from labor market pooling
 Subsamples: sorting bias not serious
 Significant human capital externalities (0.2-0.4 in
USA)
Robustness check
occuindu local migrants <=2.5year >2.5year <=33 >33
Log(Emp) 0.0029 0.0111** 0.0015 -0.0018 0.0147*** 0.0018 0.0071
0.74 1.91 0.47 -0.51 3.40 0.50 1.49
College
Share 0.3598*** 0.3473*** 0.2812*** 0.2285*** 0.3454*** 0.3228*** 0.3847***
6.10 5.06 3.87 3.05 3.22 5.26 5.63
R2 0.44 0.44 0.43 0.39 0.46 0.44 0.45
obs. 172002 97478 74524 34975 39549 91426 80576

25. Rural migrants benefit from Marshallian externalities
baseline
Migrant
year<=2.5
Migrant
year>2.5 Age<=26 Age>26
Log(Emp) 0.0123*** 0.0128** 0.0115*** 0.0181*** 0.0104***
2.70 2.20 2.26 3.02 2.19
CollegeShare 0.2095** 0.3551*** 0.1119 0.2209* 0.2381**
1.93 2.64 0.93 1.67 2.07
R2 0.30 0.25 0.33 0.26 0.35
obs. 49916 23302 26614 25260 24656

26. Rural migrants benefit less from agglomeration economies
1 2 3 4 5 6 7
full
sample
Rural
migrants
Urban
hukou
Local
hukou
Local
urban
Urban
migrants All
Log(Emp) 0.003 0.012*** 0.018*** 0.011** 0.020*** 0.018** 0.012**
log(Emp) *
Migrant*Urban
0.009**
log(Emp) * Local
*Rural
-0.014***
log(Emp) *Rural
*Migrant
-0.024***
CollegeShare 0.360*** 0.210** 0.348*** 0.347*** 0.329*** 0.513*** 0.554***
CollegeShare*
Migrant*Urban
0.037
CollegeShare*
Local*Rural
-0.615***
CollegeShare
*Rural* Migrant
-0.588***

27. Possible Interpretation
 Work in informal job sectors that have fewer
spillovers?
 Low-skilled, low absorptive capacity?
(education categories)
 Rural migrants lack of social network?
(information asymmetry)
 Discrimination?

28. High-skilled workers benefit less if they are rural
1 2 3 4 5 6
Low
skilled
High
skilled
Low
skilled
U/R
High
skilled
U/R
Low skilled
L/M
High
skilled
L/M
Log(Emp) 0.003 0.014** 0.010* 0.017*** 0.005 0.017**
Log(Emp)*Rural -0.013*** -0.038**
Log(Emp)*Migrant -0.009** -0.010
CollegeShare 0.311*** 0.504*** 0.537*** 0.517*** 0.322*** 0.499***
CollegeShare*
Rural -0.556*** -0.577***
CollegeShare*
Migrant -0.074 0.035

29. Low / high-skilled worker sample
Full sample Low-skilled High-skilled
Log(Emp) 0.012* 0.008 0.018***
Log(Emp)*urban*migrant 0.009** 0.002 -0.004
Log(Emp)*local*rural -0.014*** -0.007* -0.019
Log(Emp)*rural*migrant -0.024*** -0.014** -0.046***
CollegeShare 0.554*** 0.538*** 0.509***
CollegeShare*urban*
migrant 0.037 -0.093 0.053
CollegeShare*local*rural -0.615*** -0.580*** -0.584**
CollegeShare*rural*
migrant
-0.588*** -0.500*** -0.503
(-1.49)
 There may exist two types of discrimination: local
bias and urban bias

30. Other Studies Suggest Double
Discrimination
 Zax (2016): returns to education vary
significantly and persistently across
provinces and years, suggesting mobility
barriers across provinces
 Chen et al. (2015): rural migrants are more
likely to search jobs through informal social
network but receive lower wages if they do
so.

31. Other Studies Suggest Double
Discrimination
 Liu et al. (2016): rural migrants are
residentially segregated in Shanghai, based
on Census 2010

32. (.9,1]
(.8,.9]
(.65,.8]
(.5,.65]
(.4,.5]
[0,.4]
Local Ratio in Shanghai(2010)
(0.750,1.000]
(0.550,0.750]
(0.350,0.550]
(0.250,0.350]
(0.200,0.250]
[0.000,0.200]
Migrant Ratio in Shanghai(2010)

34. Conclusion
 Labor market agglomeration economies
exist in Chinese cities
 Rural migrants benefit from labor market
agglomeration economies, but benefit
much less than do local, urban residents
 Double discrimination towards rural
migrants

35. Implications
 What drives rural-urban migration and
urbanization? Cities facilitate learning
 Learning in cities through social
interactions, alternative to school education
 Barriers to learning

36. How Can Chinese Cities Attract Skilled
People?
 Make cities safe
 Make cities clean: air quality
 Make cities accessible: public transit, walkable
streets
 Make cities livable: affordable housing, open
space…
 Make cities open, tolerant: remove mobility
barriers
Fortunately, China is reforming the hukou system.

37. Future Research
 Identify how people socially interact in
cities
 Test how relaxing or removing mobility
barriers enhances social interactions
 Urban public policies that promote social
interactions and learning in cities

38. Thanks for your attention!
Comments are very welcome.
shihefu@mit.edu