Research in sociology and economics point to important role for social networks in labor markets. Social contacts mediate propagation of rich and reliable information among indi- viduals and thus help workers find jobs and employers find employees. Recent theoretical advances show that for agents connected through networks employment is positively cor- related across time and agents, unemployment exhibits duration dependence, and inequal- ity can persist. Recent empirical findings underscore nonlinearities in social interactions and potentially important effects of self-selection. Socioeconomic characteristics can explain substantial spatial dependence in unemployment.networks, labor markets, social connections, unemployment, proximity, spatial dependence, information networks, neighborhoods and jobs

Antoni Calvo-Armengol

Yannis M. Ioannides

English

Research Papers in Economics

 
 
DEPARTMENT OF ECONOMICS 
WORKING PAPER 
2005 
 
 
 
 
 
 
 
 
 
 
 
Department of Economics 
Tufts University 
Medford, MA 02155 
(617) 627 – 3560 
http://ase.tufts.edu/econ Social Networks in Labor Markets
Written for the New Palgrave Dictionary of Economics, 2nd Edition, Palgrave MacMillan.
Abstract
Research in sociology and economics point to important role for social networks in labor
markets. Social contacts mediate propagation of rich and reliable information among indi-
viduals and thus help workers ¯nd jobs and employers ¯nd employees. Recent theoretical
advances show that for agents connected through networks employment is positively cor-
related across time and agents, unemployment exhibits duration dependence, and inequal-
ity can persist. Recent empirical ¯ndings underscore nonlinearities in social interactions
and potentially important e®ects of self-selection. Socioeconomic characteristics can explain
substantial spatial dependence in unemployment.
JEL classi¯cation codes: D85, A14, J64, J31, J70, L14
Keywords: networks, labor markets, social connections, unemployment, proximity, spatial
dependence, information networks, neighborhoods and jobs.
The use of social networks is widespread both in employers' recruiting and workers'
job-seeking. Social contacts help workers to ¯nd jobs, and employers to ¯nd employees.
Indeed, social contacts convey rich and reliable information, which they spread widely and
fast throughout the labor market. They thus constitute cost-e®ective search channels that
both enrich the information available to both ¯rms and workers, and enhance its quality.
The study of social networks in labor markets highlights the nature of labor market trans-
actions as very di®erent from trading in goods and re°ects the importance of idiosyncrasies.
The role of job market search and its dealing with frictions goes at least as far back as Stigler
(1962). Everyday experience indicates that access to information is heavily in°uenced by
social structure. Individuals use connections with others, such as friends, and social and
professional acquaintances, to maintain information networks. Rees (1966) ¯rst drew at-
tention to di®erences among workers in their use of the variety of available informational
outlets. In this context, formal sources of information include state and private employ-
ment agencies, newspaper advertisements, union hiring halls, school and college placement
services and, more recently, the Internet [Kuhn and Skuterud (2000)]. Informal sources
include referrals from employees and other employers, direct inquiries by job seekers and
indirect ones through social connections. A recent literature in economics has developed
about the details of social interactions that a®ect the job search process. This literature is
1complemented by the more extensive sociological analysis of networks. Several sociological
works, including notably Granovetter (1974) and Boorman (1975) have been very in°uential
within the economics literature. This entry explores the salience within both theoretical and
empirical economics research of a social networks approach in the study of labor markets.
Several stylized facts about labor market networks have been established by empirical
work on job information networks [Ioannides and Loury (2004)]. The ¯rst stylized fact is
that there is widespread use of friends, relatives, and other acquaintances to search for jobs
and it has increased over time. The second stylized fact about job information networks
is that the use of friends and relatives to search for jobs often varies by location and by
demographic characteristics. Di®erences in using informal contacts by age, race and ethnicity
show con°icting patterns that suggest important subtleties associated with the operation
of social networks are at work. This is con¯rmed by international comparative evidence.
Pellizzari (2004) explores the empirical evidence for the countries of the European Union
as of 2003, using the European Community Household Panel, and compares with the US,
using the National Longitudinal Survey of Youth (NLSY). Pellizzari documents large cross-
country and cross-industry variation in the wage di®erentials between jobs found through
formal and informal methods. Across countries and industries, premiums and penalties are
equally frequent. Such di®erences may be attributed to di®erent recruitment strategies by
¯rms and to di®erent institutional and social practices which may compound the impact
of di®erences in industrial compositions of economies. The third stylized fact about job
information networks is that job search through friends and relatives is generally productive.
Both employed and unemployed workers who used friends to search for jobs received more
o®ers per contact and accepted more o®ers per contact than did workers who used other
sources of information about job openings. The fourth stylized fact about job information
networks is that part of the variation in the productivity of job search through networks by
demographic group simply re°ects di®erences in usage. In particular, US data suggest that
almost one-¯fth of the total di®erence in probability of gaining employment between black
and white youth resulted from racial di®erences in the use of social contacts.
We crudely distinguish two mechanisms through which social contacts impact on the
functioning of the labor market. First, referrals relay information across the two sides of the
labor market, ¯rms and workers. Second, workers' connections disseminate job information
within the supply-side of the labor market through word-of-mouth communication.
Hires mediated by referrals reduce employer uncertainty about prospective workers' pro-
ductivity for a number of reasons [Montgomery (1991)]. One is that incumbent workers are
likely to refer their trusted acquaintances and help them be better informed about their
prospective employers. A second reason is that the long-term nature of the relationship
2between incumbent employees and their employers provides the latter with superior infor-
mation on the incumbents' productivity-related traits. It is thus not surprising that evidence
shows that referral bonuses bring high returns to ¯rms. Yet, excessive reliance on referrals
deprives ¯rms and individuals who happen to be outside the social networks of ¯rms' workers
of mutually bene¯cial matches.
Recent ¯ndings have improved our understanding of the supply side e®ects of social
networks [Calv¶ o-Armengol and Jackson (2004, 2005)]. In their models, workers rely both
on own search e®ort, and on information exchange with their social circles to ¯nd jobs.
Information passing across acquaintances can display a variety of real-life features, e.g.,
when connections di®er in terms of intensities, information recipients can be ranked so as to
re°ect these relational preferences. Their models are the ¯rst to explain several important
stylized facts about labor markets, which are hard to explain altogether without an explicit
social network model. We turn to those next.
First, information passed from employed individuals to their unemployed acquaintances
makes it more likely that these acquaintances will become employed. This generates posi-
tive correlation between employment and wages of networked individuals within and across
periods. Such positive long-run correlation arises despite the short-run rival nature of job
information in the following sense: indirect contacts who are two links away in a network are
potential competitors for any job held by any common friend. Second, duration dependence
and persistence in unemployment, both of which are well documented, can be understood as
social e®ects: the longer an individual is unemployed the more likely it is that her social en-
vironment is associated with unfavorable future unemployment prospects. This explanation
for duration dependence complements more common ones, such as unobserved heterogeneity.
This e®ect resembles an externality and is also responsible for stickiness in aggregate em-
ployment dynamics. The closer the economy is to very high employment (or unemployment),
the harder it is to leave that state. For similar reasons, parts of the economy can experience
a boom while simultaneously other parts of the economy are experiencing a bust.
These are implications of exogenous information networks. With an endogenous network
that results from agents' participation decisions, the model's predictions are the following.
Third, the likelihood of dropping out of the labor force is higher for an individual whose social
contacts have poor employment experience, or for an individual with few acquaintances.
Fourth, small di®erences in initial conditions of di®erent individuals and of network structure
can lead to large di®erences in drop-out rates. Indeed, when an individual drops out, the
prospects worsen for all those who remain, and this generates spillover e®ects in others'
decisions to participate or to drop out. Di®erences in collective employment histories combine
with di®erences in network structure to produce sustained inequality of wages and drop-out
3rates that feed on each other. So, history matters and is responsible for producing persistent
income inequality for reasons that are very di®erent from those due to inequalities in human
capital investments. Because spillover e®ects work in reverse, selective and targeted (rather
than separate) interventions in the labor market that provide incentives for individuals not
to drop out are likely to have ampli¯ed e®ects.
Empirical research has yet to employ fully formal network concepts. It relies typically on
concepts of association because of geographic or cultural proximity. There is evidence of per-
sistent correlations in patterns of unemployment in US cities. Socioeconomic characteristics,
and in particular ethnic and occupational distance, seem to explain a substantial component
of the spatial dependence in unemployment. Topa (2001) and Conley and Topa (2002) ar-
gue that social interactions can indeed explain the spatial correlation patterns present in the
data. Weinberg, Reagan, and Yankow (2004) show that one standard deviation improvement
in neighborhood social characteristics and in job proximity raises individuals' hours worked
by 6% and 4% in the average, respectively. Such social interactions have nonlinear e®ects.
The greatest impact is in the worst neighborhoods. Being in a disadvantaged neighborhood
is more important rather than the labor activity of one's neighbors per se. Bayer et al. (2004)
document that people who live close to each other, de¯ned as being in the same census block
| a US census block encompasses 3,500 to 5,000 residents of a contiguous geographical area
| also tend to work together, that is in the same census block. Using Dartmouth College
(where roommates are assigned randomly) data, Marmaros and Sacerdote (2002) ¯nd large
positive correlations between getting help from fraternity/sorority contacts and obtaining
prestigious, high-paying jobs. Still, other research points to self-selection as the likely origin
of such e®ects: Oreopoulos (2003) ¯nds that when neighborhoods are not selected, neigh-
borhood quality plays little role in determining a youth's eventual earnings, likelihood of
unemployment, and welfare participation, while correlations among outcomes for siblings
are much higher.
As richer network data become available, further empirical tests of the implications of
labor market networks should be developed, which ultimately may call for more elaborate
network modelling tools in labor economics. Such research deserves attention.
Antoni Calv¶ o-Armengol, ICREA, Universitat Autµ onoma de Barcelona, and CEPR.
Yannis M. Ioannides, Tufts University.
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6 
 
 
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A Combinatorial Optimization Model for Transmission of Job Information through Contact Networks,&quot;

and Mikal Skuterud (2000), \Job Search Methods: Internet versus Traditional,&quot; Monthly Labor Review,

Do Friends and Relatives Really Help in Getting a Good Job?&quot; CEP discussion paper no 623, London School of Economics,

Do Neighborhoods A®ect Work Behavior? Evidence from the NLSY79,&quot;

Getting a Job: A Study of Contacts and Careers, ¯rst edition,

Information in the Labor Market.&quot;

Information Networks in Labor Markets,&quot;

Job Information Networks, Neighborhood E®ects, and Inequality,&quot;

Networks in Labor Markets: Wages and Employment Dynamics and Inequality,&quot; mimeo,

Peer and Social Networks in Job Search,&quot;

Place of Work and Place of Residence: Informal Hiring Networks and Labor Market Outcomes,&quot; working paper, 4Yale

Social Networks in Labor Markets

Abstract

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