‘Social Cohesion’ and Unemployment Exit Rates

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Beyond Networks:

Social Cohesion and Unemployment Exit Rates*

Carmel Hannan

Institute for Labour Research

University of Essex

*Contact address: Carmel Hannan, Institute for Social and Economic Research,

(incorporating the ESRC Research Centre on Micro-social Change), University of

Essex, Wivenhoe Park, Colchester C04 3SQ. UK.

E-mail: [email protected], Fax: 01206 873151, Phone: 01206 872588

Acknowledgements

The support of the Leverhulme Trust, the Economic and Social Research Council

and the University of Essex is gratefully acknowledged. The author would especially

like to thank Marco francesconi for his numerous helpful comments. An earlier

version of this paper was presented at the European Social Fund conference

European Societies or European Society? Inequality and Social Exclusion in

Europe: The Role of Family and Social Networks, Castelvecchio di Pascoli, Italy,

3-7 April 1998 and the Work, Employment and Society conference, Cambridge, UK,

14-16 September 1998. All comments appreciated.


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Beyond Networks:

Social Cohesion and Unemployment Exit Rates

ABSTRACT

This paper provides convincing new evidence on the role of social resource patterns

in shaping an individuals chances of entry to the labour market. It links movements

out of unemployment into employment to constructed indicators of social

cohesion. These are social participation, social support and the social network. It

was found that the current duration in a state has an influence on the probability of

exit from that state. However, even after controlling for this and many other

demographic and economic factors, the social network measure remained a

significance influence on whether the unemployed found a job. Respondents who

have close employed friends are significantly more likely than those who do not to

exit unemployment. Why is this the case? Previous research has shown that the more

socially integrated individuals have greater access to useful job information flows. In

addition, this study has found that the unemployed who have close employed friends

are significantly less likely to suffer psychological distress. In this sense, policies

which isolate the unemployed into ghettos (for example, council housing schemes)

do much harm and may play a large role in keeping the unemployed, unemployed.


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Non-technical summary

Flagged by C. Jenck (1972) as dealing with luck and later by Granovetter (1973) as

having the right contact in the right place at the right time, unemployment exits rates

have been explained from a number of different standpoints. Economic explanation

is built around notions of state and duration dependencies or the effects of previous

spells of unemployment on the probability of exit from that state. Sociology relies

upon notions of social exclusion and social networking or linkages between actors as

channels for the transfer of resources. Using data from the first six waves of British

Household Panel Study (BHPS), a nationally representative random sample, it is

possible to construct measures for both these type of explanation. It is therefore

possible to examine the role social resource patterns in shaping an individuals

chances of entry to the labour market after controlling for the traditional, and

relatively easy to measure, economic factors. Three limited measures of social

cohesion were constructed; a social participation scale, a social support index, and

most importantly, a social network measure.

Of course, it was found that the current duration in a state has an influence on the

probability of exit from that state. However, even after controlling for this and many

other demographic and economic factors, the social network measure remained a

significance influence on whether the unemployed find a job. Respondents who have

close employed friends are significantly more likely than those who do not to exit

unemployment. It was also found that these people display less psychological

distress than those whose close friends were all unemployed. Future work will


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address the linkages between psychological health and social integration. For the

moment, it seems clear that social resource patterns play a crucial role in the

determination of who finds a job. In particular, the segregation of the unemployed

population in any way renders the maintenance and development of links (formal

and informal) with the working world impossible, thereby worsening the

psychological strain placed on these people and statistically rendering them much

less likely to find a job


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Beyond Networks:

Social Cohesion and Unemployment Exit Rates.

For many years the analysis of unemployment was solely the domain of Economics.

However, in recent decades it has become apparent that who exits unemployment is

fundamentally determined by a social process. Over twenty years ago Mark

Granovetter (1974) found that over 60 percent of the professional, technical and

managerial workers he interviewed reported obtaining their jobs through personal

contacts. A recent British Department of Social Security report (1997) reported that

around 38 percent of job seekers had contacted friends and family as a means of job

search, and numerous US studies have estimated that over 50 percent of the

unemployed who found jobs did so through word of mouth (see Montgomery 1992

for a summary). Yet, large scale quantitative analysis of unemployment exit rates

rarely even alludes to this process. It seems that ultimately who finds a job has much

to do with ones social contacts. Who people know, how they know them and the

consequences of differing social relationships on peoples lives are important

research questions.

The importance of this social being has recently received increased attention due to

the popularity of a rather confused debate on the collapse of community or the

decline of social cohesion in modern society. This concept of social cohesion is

mostly misleading and ambiguous. It is assumed to be some natural good yet

strong cohesion can be disabling and counter productive. Take, for example, a highly


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organised cohesive criminal gang. However, this debate has focused attention on the

differing ways in which individuals are linked to each other and to society. Social

network analysis has chosen to plot such linkages in a mathematical way, as some

sort of aid for getting things done, and the debate on social cohesion seems to view

them as some sort of glue to provide order and meaning to social life (Pahl 1996).

The crux of the issue rests on ones view of social relationships. An increasingly

popular view is to argue that through such relationships people build up a stock of

social capital. This theory presents numerous reasons for why social contacts are

important. What follows is a critical review of the implications of adopting such an

approach.

It is argued that this sociological theory differs from its economic counterpart in that

the ability to obtain social capital does not inhere in the individual, as the possession

of money (material capital) or education (human capital) does. It is instead a product

of the individuals set of relationships with others; a product of embeddedness2.

Such a point has been invaluable in highlighting that individuals are not isolated

beings. However, research has focused on what Granovetter (1985) called structural

embeddedness, that is, the ways in which an actors mutual contacts are connected

to one another. This, Granovetter argues, is the most important type of structure in

which economic transactions are embedded. This is because it easily allows for the

transfer of resources (instrumental aid) within groups. Therefore, research on

networks has been limited to firms, interorganisational ties and the environment of

organisations because the linkages between actors can be easily plotted. Of course,


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concern is often expressed over the generalisability of findings. Yet, people are

connected to and influenced by each other even when these connections are scattered

diffusely through out the population. The intention of this paper is to move social

network concerns beyond instrumental aid and hence organisational ties and, in this

way, test the wider relevance of such concerns.

It seems logical to suppose that we are influenced by our social contacts in a

variety of ways but the concept of social capital itself is misleading and, at best,

vague. It is a potentially powerful concept which is so useful that it is given many

different meanings by many different people who use it in many different ways to

explain many different things (Newton 1996: 1). Let me explain this further. The

definition and measurement of social capital remain unresolved in the literature.

The first thing to note is how this concept echoes the economic version of human

capital. The emphasis being on capital as an investment one makes expecting a

future return. Yet again highlighting the instrumental aspect of human activity. For

some social capital is indeed simply a broader version of human capital but one

which includes a social and cultural dimension and highlights the importance of

informal learning (see Morrow 1998).

For Wall, Ferrazzi and Schryer (1998) the confusion surrounding this term may be

clarified into three separate approaches. Firstly, Colemans (1992) view with an

emphasis on the positive outcomes of social capital transformation. The approach

adopted here is probably closest to this view as the focus is on differing (both

positive and negative) outcomes of, what I prefer to call, social resource patterns.


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Secondly, Bourdieus view (1990) of human activity as primarily aimed at

controlling and accumulating different kinds of capital, with economic capital as

the prime form. This approach is commendable in that his definition of social

capital is part of a more complex and intricate typology rooting social capital in the

practises of everyday life (the habitus). Yet, in practise, this concept of social

capital is vague and immeasurable. Morrow (1998) on this point argues that when

researching such a view, it seems best not to conceptualise social capital as a

measurable thing, but rather as a set of processes and practises that are integral

to various aspects of our lives.

Finally, there is Putnams definition of social capital (1993) which is

fundamentally about civic involvement and revolves around the notion of social

trust, the norms of reciprocity and networks of civic engagement and successful

co-operation. This community based approach highlights the centrality of the

concepts of reciprocity and trust or the subjective dimension of social capital. His

views are also open to criticism. One interesting critique attacks Putnams belief

that people who join are people who trust. When in truth, little is known about this

causality (see Newton 1996: 13 for an in-depth analysis).

The notion of trust must take central place in any discussion on why and how people

become friends. For Bourdieu (1990) actors use cultural capital, prestigious forms

of knowledge and style or distinctive speech forms, as bases for interpreting one

anothers character and intentions. Cultural style therefore signals a probability that


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trusting relations can be constructed. This idea is also evident in Homans (1951)

Homophily Principle where individuals become friends with persons similar to

themselves. For social network theory, the most important characteristic of the

network is the degree to which it is composed of individuals with differing social

status (esp. higher ones). In the case of employment, this is to facilitate movements

up the earnings ladder and for the unemployed, so as to gain useful job information.

This implies that certain people have more culturally diverse and therefore,

according to this approach, more useful relationships than others. But is this really

the case (in particular here, for the unemployed) and if it is so, why so?

All relationships, however, do involve a degree of uncertainty, risk, and vulnerability

and hence, require trust in others (the social cohesion argument). It is argued that

this is because the utilities derived from friendships are not constitutive as in market

relations but rely more on a generalised form of reciprocity where good turns will be

repaid at some unspecified time in the future (Newton 1996). However, yet again,

this raises some important research questions about the degree to which this is

actually the case. Given the complexities of the social process as outlined in this

section of the paper, quantitative research can only provide limited measures of the

effects of differing friendship patterns. It can not provide deep insights into the

importance of reciprocity and trust in the development of friendships.

The preceding review of the social capital literature has provided important insights

into how people become friends and why this process is crucial for their future life


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chances. When combined with social network theory, it provides a useful theoretical

understanding of the importance of social contact for the life of the unemployed. It

can be seen that all three types of definitions of social capital are linked; trust and

norms at the subjective level, networks at the objective level and efficacy/ social

cohesion as a collective good. Hence, social capital refers to both the relations,

networks, and obligations existing in social situations and the product of these

interactions (Wall et al. 1998). That is, social capital is confusingly being viewed as

an individual phenomenon and a community based resource all at the same time. In

addition, politically the term is ill advised in that it focuses blame onto the

community for numerous social problems (in place of the usual blame the victim

strategies). It is for these reasons that I have chosen to avoid the use of this term.

Instead, the research focus is on social resource patterns, in particular measures of

sociability, the social networks, and social support.

What follows is built upon this basic premise, that an unemployed persons sense of

self-efficacy in relation to friends, support structures etc., and to the corresponding

feelings of alienation or engagement (psychological effects), will have some

influence on their life chances. With the dawn of high tech communications, many

social relationships know no geographical boundaries and it has become almost

impossible to collect detailed information on every social tie. But by adopting a

broader view on the issue of social networks and, hence, focusing on a more general

hypothesis, this paper demonstrates why all social relationships are important.


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2. The instrumental approach.

As previously noted, most research in this area has emphasised the instrumental way

in which social relations influence unemployment exit rates. Traditional economic

accounts of this process assumed a simple matching process between labour supply

and demand. At the qualitative levels, sociologists argue that there are multiple

criteria by which employers select workers (for example Tilly and Tilly 1992). For

employers to recruit through their existing workforce seems logical as it provides a

cheap and useful screening devise and a clever method for reducing uncertainty and

avoiding risk. One idea is that workers will tend to refer to others who are similar to

themselves, so that employers will solicit referrals from high-ability employees

(inbreeding bias). This policy is reflected in the employment strategies of many

companies which now award bonus to employees who fill vacancies within the

firm.

From the employee side, giving a referral is not a costless exercise, for if the recruit

proves unsatisfactory the sponsors own reputation will be endangered (Greico 1987).

So, when employees refer friends to their employer they have made an informed

judgement about this persons employment ability. It is evident that among job

seekers asking friends and family is indeed a popular job search method. In wave 6

of the British Household Panel Study respondents were asked about their job search

methods, 69 percent of the unemployed men in this sample reported asking friends

and contacts. Holzer (1987) suggests that job seekers prefer this referral procedure


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because contacting friends and family generates a job offer with relatively high

probability by inexpensive means. Of course, this implies that individuals who are

cut off from the social networks in which job information is diffused may have a

reduced probability of finding a job.


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3. Unemployment and Psychological Well-being.

Individuals are connected to each other and society in numerous ways and to

numerous extents with differing implications. Psychological research has

emphasised the implications on happiness and stress levels. All aspects of social

participation are seen as important means of avoiding loneliness (e.g. Knipscheer

1992). The integration theory (Gove and Hughes 1980) suggests that people need

satisfying, intimate relationships that give them affection, identity, and care. Yet

little is known about the implications of differing levels of social involvement on the

well-being of unemployed individuals.

What is known is that unemployed people have much lower levels of psychological

well-being than those in work and that the long term unemployed show less distress

than those who have recently lost their job (Clark and Oswald 1994). Qualitative

studies have shown that unemployment leads to social withdrawal and social

isolation. This can be attributed to, in part a lack of the financial resources needed to

take part in social activities, and in part it is seen as a result of a loss of self-

confidence and a desire to avoid social contact that may well be damaging to ones

self esteem. Some studies have shown that the unemployed tend to be segregated in

networks in which a far higher proportion of their friends are unemployed than is the

case for employed people (Gallie, Marsh and Yogler 1994). It is argued that these

unemployed friends are less likely to offer strong psychological support or effective

assistance in meeting financial problems or the difficulties of finding a job.


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Therefore, such relationships amongst the unemployed are seen as offering few

opportunities for alleviating the stress of unemployment.

This literature highlights the fact that social networks and social support do more

than provide an individual with practical or instrumental support. At a basic level,

social relations (the combination of the above) seem to help the individual develop

their sense of self and their expectation about the world. Antonucci (1987) has

suggested that supportive others, through the provision of support, enable

individuals to feel efficacious, to have higher levels of self esteem, mastery and

control which, in turn, influences the individuals health and well-being. So, in effect,

the notion of social cohesion captures the idea of a world full of individuals who feel

they are capable and competent and that the world is full of others who love/like

them, believe in them, and can be counted on when needed.


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4. Analysis

The data come from the first six waves of the British Household Panel Study

(BHPS), a nationally representative, random sample of over five thousand

households across England, Wales and Scotland (South of the Caledonian Canal).

Each year respondents are asked to detail their labour market movements over the

preceding twelve months, allowing a continuous labour market history of each

individual to be recorded since September 1990. The BHPS also includes a complete

employment status history for each respondent. This additional information is

susceptible to substantial recall error and is therefore only used as a covariant in the

series of logistic regressions estimated in the next section.

4.2 The dependent variable:

The case for this analysis is each month starting from entry into the survey up to the

end of wave 6 (1997) for all the men in the BHPS dataset (work was carried out for

women but the approach is sufficiently different to warrant separate treatment). The

dependent variable is binary, taking the value of unity if the individual has moved

from unemployment (not working) into employment (working) in the current month,

and zero if the respondent remains in the unemployed state. All other cases were

excluded. The definition of unemployment used here does not restrain the sample to

those actively seeking a job. This would have been an unnecessary constraint and

excluded many unemployment exits.


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4.3 Definitional issues:

In researching the impact of differing levels of social involvement amongst the

unemployed it is important to distinguish between the concepts of social

participation, social support and social networks. Researchers have been unable to

reach definitional agreement about the meaning of these terms. In this paper, social

network refers to the restricted measures of friendship carried in the BHPS, in

specific the number of close employed friends the respondents has. It is impossible

to collect data on the respondents entire network of associations, so data was

collected for a maximum of three close friends about whom numerous questions

were asked (see appendix for exact questions). The restriction to a sample of three

close friends seems adequate giving the House and Kahn (1985) finding that the first

five relationships are the most important and contribute most to the understanding of

an individuals social relations.

It is, of course, possible to describe the structure of the network in a number of ways,

for example we find that male respondents are more likely to have female close

friends. Both men and women are also more likely to have friends of their own age.

The unemployed do have employed friends, with 67% of the unemployed having

some (one or more) employed friends by wave 6. This represents an eleven percent

increase in 4 years and is probably reflecting the declining unemployment rate in the

UK over the period.


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Social networks are usually viewed as a vehicle through which social support can be

provided but, unfortunately in the BHPS, the social support questions were asked in

general and not in relation to the friendship questions. Definitions of social support

echo those of social cohesion, for example it may refer to a process which leads

individuals to feel loved, esteemed and valued (Cobb 1976) or, more specifically, to

the receipt of certain types of aid. In the BHPS it refers to the perceived availability

of five types of support ranging from instrumental aid to emotional support (see

appendix for exact questions). It was found that the unemployed perceive themselves

to face much weaker support networks than the employed, with 10.6 percent of the

unemployed believing they have no-one to help in a crisis in contrast to only 3.8

percent of the employed (see table 1).

(Table 1 about here)

An advantage of using panel data is that it provides a life span orientation to the

analysis, so that we can see an individuals level of support in the past given the

future we know occurred. More generally, the idea is that people move through time

influenced by specific events, circumstances and people which increment over time

and influence their needs and expectations of supportive interactions or networks

(convoy model of social relations1). By focusing on the unemployed men who

entered the survey in year one, and seeing their job status 5 years later revealed that


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most of them (68 percent) were employed. Of those who were unemployed in year 1

and were also unemployed in year 5, 20.3 percent perceived they had no-one (for

example) to help in a crisis in year one. This contrasts to only 9.5% of those who

became employed (see table 2). Therefore, those who exited unemployment were

more likely to have understood themselves to have had someone to help in a crisis

than those who did not.

(Table 2 about here).

In addition, it is interesting to compare the levels of perceived support amongst those

who had no unemployment spell as compared to those who had. It can be seen that

that the figures for those who had become employed in table II are very similar to the

averages reported for the unemployed in table I. This seem to indicate that a spell of

unemployment (even if it was far in the past) has a long-term effect on ones

perception of support. The continuously employed sample reported much higher

perceived support levels across all 5 categories.

The social participation index refers to an individuals activity and membership in

societal groups through which friendships and social support may be activated e.g.

political parties, religious organisations, fitness clubs etc. The intention is to single

out those individuals who may be more sociable. As regards Putnams hypothesis

(1995) on the decline of social capital, the data provides no evidence of overall


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declines in sports and cultural associations. The only significant decline in

organisation activity occurred in attendance at a religious service (20 percent drop

over 5 years).

4.4 Measurement issues:

The first important issue to clarify is the reasoning behind the social support index.

Its justification lies in the belief that the actual help provided is less important than

the individuals perception of the amount and quality of the support available.

However, the perception of support as a psychological variable may be only partially

related to the objective characteristics of the support exchanged. On the other hand,

questions which identify actual particular examples of support run the risk of

missing the actual perceived non-acceptance of this as support. Support may be

given but it could be assessed as misguided, malintentional, or misinformed. There,

thus, can be a mismatch between what is desired or expected and what is actually

experienced.

One argument (Gouldner 1960) is that people disassociate themselves from those

who fail to provide support (relying on the assumption that the norms of reciprocity

are widely accepted). This implies that some people develop a support reserve or a

savings account of support owed to them (Antonucci and Akiyama 1987). Other

psychological studies have shown that illusion is an important element in the

maintenance of well-being (Taylor and Brown 1988). So, in this case, the non


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availability of a social support structure (perceived and/or actual) could lead the

unemployed to believe that they are incapable of work and prone to failure. It

therefore seems that it is the perception of support which is of essential interest here.

There are many different techniques for measuring the social network. My concern is

with measures that attempt to infer the strength of a relationship. Granovetters work

was based around the fundamentally flawed measure of frequency of contact. The

amount of time two people spent together was taken as a crude measure for the

strength of an interpersonal tie. However, he defined the strength of a tie in a more

inclusive manner as a "combination of the amount of time, the emotional intensity,

the intimacy (mutual confiding), and the reciprocal services that characterise the tie"

(Granovetter 1973: 1361). The problem with this measurement in practise is that it

seems likely that some people will have close friends they do not see that often. This

is verified in the BHPS where 1 in 5 people contact their best friend3 only once a

month or less often.

This points to the importance of realising that friendship is judged on criteria

internal to the character of the on-going relationship. It is possible with the BHPS to

select out those friends who live close to the respondent or those the respondent

contacts on a daily basis. But it proved more adequate to allow respondents define

their close relationships themselves. In that sense, the measurement of the network

employed here is far the most satisfactory available in a large scale quantitative

survey. However, it must be noted that we do not know anything about how or why


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the respondents choose these people as their closest friends. Yet, it is hoped that

these quantitative assessments of an individuals social relations do take some

account of the quality of the relationships amongst individuals. They are not based

on counting the number of people one knows, or how often one sees them, or on

how much support is actually received. Yet, as argued earlier, without engaging in

fieldwork and participant observation, there is little one can say about how people

define their close friends or the importance trust and obligation in the development

of friendship and support.


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4.5 The explanatory variables:

Sociological variables:

The social support index runs from 0 to 5 depending on the number of situations in

which the individual feels there is support available to them. Most people (80

percent) perceive the availability of full support. The social participation scale was

simplified into three dummies. 14 percent of the unemployed respondents are

members only in an organisation and 39 percent are active members. Three dummies

were also created based on the social network measure with an average of only 37

percent of the unemployed sample naming all three of their close friends as

employed. The importance of these social resources patterns on ones job chances

was then tested before and after controlling for other factors.

Demographic controls:

Included in the models is the respondents age at the start of the current

unemployment spell. We would expect from previous literature a U-shaped

relationship between age and unemployment proneness. We take the socio-economic

background of the individuals father (Goldthorpe class) as the indicator of the

cultural capital of the household of origin, and the highest educational qualification

in 1991 as the indicator of individuals educational capital.

Socio-demographic controls:


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Included at this point is whether or not the respondents attended a private school as

an indicator of one form of potential social capital (6 percent of the unemployed

sample fell into this category). The fathers Goldthorpe class measure was dropped

for dummies indicating whether the respondents came from a two earner household,

a one breadwinner situation or an unemployed background. A housing tenure

dummy was included to control for any spatial concentration of the unemployed.

Research has shown that there is a tendency for this section of the population to

cluster together in large council housing estates. This, of course, has major

implications on the social network. A health dummy was included to control for any

possible physical impairment preventing the individual from working. Finally,

dummy variables were included to control for domestic cycle effects. Previous

studies (for example, Morris 1990) have shown that ones marital status and the

present of children have an effect on the probability of gaining employment. In

particular, the present of young children is strongly associated with weak male

labour force status.

Employment history:

Using the work history data collected at wave 2 in the BHPS it is possible to control

for previous unemployment experiences. A variable was included measuring, in

months, the length of an individuals previous unemployment spell. In addition,

regional monthly unemployment rates were included to take account of the economic


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environment at that time. These were based on travel to work areas for the first 4

years of the BHPS but, for the final two waves, they were only available at a regional

level.

5 Results

The tables in this paper report the effects (log odds) of the independent variables on

the general probability of entering employment from unemployment in a given

month (estimated from logistic regressions). A model performance statistic is

included, -2 the log of the likelihood, which measures how well the estimated model

fits the data. A model that fits the data well is one that results in a high likelihood of

the observed results. This translates to a small value for -2LL (if a model fits

perfectly, the likelihood is 1, and -2 times the log likelihood is 0).

Model 1 in table 3 enters the social variables one at a time and tests their effect

separately and then together on the probability of exiting unemployment. The social

support scale has a significant positive influence on this probability. This positive

influence increases as one moves from perceiving no available support to perceiving

some social support in all 5 situations.Interestingly, the effect of being a member in

an organisation has a stronger effect on unemployment exits rates than being active.

This may be due to the fact the those who are members in an organisation are more

likely to have all employed close friends (45 percent of members had all employed


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close friends compared to 34 percent of active members). The excluded dummy was

neither being active nor being a member of any organisation.


In the third column, the effect of having employed close friends was examined. The

excluded group are those who have no employed close friends. In relation to this

group, those with some or all close employed friends are significantly more likely to

exit unemployment. Those having all three close friends employed have the highest

probability of exiting. However, -2LL has risen in these two models compared to the

social support model. Finally, when all these variables are entered simultaneously,

the models fit improves but the effect of the social support index is now

insignificant.

As well as these variables being related to each other they may also be capturing the

effects of other more conventional covariates. In model two, controls are added for

some possible demographic influences on unemployment exit rates i.e. age,

education and family background. In all cases the goodness of fit of the models

improved yet with the friendship variable remaining highly significant and

displaying the same association as before on the probability of exit from

unemployment. In addition, the family background control and the

membership/activity in organisations dummies are significant. The other variables

display the expected results e.g. as age increases the likelihood of exit from


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unemployment decreases at an increasing rate. Those in the sample who have a

higher educational qualification are much more likely to exit than those with some

other qualification (excluded group those with no formal qualifications). The effects

of fathers occupations status (as measured by Goldthorpe class when the respondent

was aged 16) shows a significant fall in the probability of exit as the fathers

occupational status increases. One possible explanation is that those from better

social backgrounds have a lower probability of exit due to their higher expectations

which may lead them to refuse the first job on offer.

In model three of table three, controls are added for another set of possible

influences on unemployment exit rates. The first control is the dummy which

highlights a private school education (the old schools ties argument). In addition,

dummies were included to signal the level of employment in the respondents

household of origin and the characteristics of their household of destination. Even

after controlling for all these, the friendship measure remained highly significant.

The models fit did deteriorated but only slightly.

The main argument is, of course, that it is the individual employment history (issues

of state dependency or the influence of past states on the present condition) and the

local employment possibilities that ultimately influence ones chances of finding a

job. Even after controlling for these historical details, the friendship dummies

remain significant (this time at the 0.01 level). The differential effect of having some


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likelihood of becoming employed increases to 18 percent. If some of his close

friends worked, his chance of finding a job increases to 26 percent. The downward

sloping line indicates that the longer the individual has been unemployed the smaller

the effect of these variables.

(Figure 1 about here).

5.2 Implications:

The above graph clearly illustrates the strong effect informal social factors have on

employment chances. However, these social resource measures may be acting as a

proxy for some other characteristic. Maybe all the above states (marriage, group

activity, friendship) are indicative of ones psychological status, sociability level, or

individual motivation to find a job. Obviously the one clear link is between

perceived social support and psychological well-being. But what is the link between,

for example, having employed close friends and psychological well-being and can it

help us explain the relationship between these friends and ones chances of finding a

job?

We can not infer from the above finding that these employed friends actually helped

the unemployed find jobs since the employed sample were not asked how they found

their jobs. In addition, we cant relate the support question to these three friends

because the support questions were not asked in relation to these close friends. It


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29

does seem most likely that the influence of these informal social factors is indicative

of the importance of psychological status. The next section links these differing

sociability levels to psychological health scores.

The BHPS contains the 12-item version of the General Health Questionnaire (GHQ-

12). It is used as a general indicator of psychological well-being. The questions ask

respondents how they have been feeling over the last few weeks. The items concern

concentration, lost sleep, usefulness, decisiveness, strain, overcoming difficulties,

enjoyment, problems, depression, confidence, worthlessness and happiness. What

follows is a brief and simply analysis of the effect of differing social resource

patterns on psychological well-being. For this purpose, the GHQ is scored by rating

each response according to whether each of the symptoms is simply present or

absent, yielding an additive score of the number of symptoms, giving a possible

maximum of 12. This score was then multiplied by -1 so that, the lower the score the

worse an individuals psycho-social well-being.

Table 5 reports the results of multivariate analysis using this score (ordered probits

with the GHQ-12 as the dependent variable). A dummy variable (EMPLOYED) was

entered for those who found a job to test the effect of exiting unemployment on

psychological well-being. As expected, it proved insignificant. Previous research has

highlighted that psychological well-being does not instantly recover after finding a

job. We also see the usually inverted U shape effect with age, so that the middle

aged suffer more psychological distress than either the young or the old. The

unemployed who attended a private school are particularly prone to poor


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psychological well-being as are those ill of health, the widowed, separated and

divorced. The effect of the job history variables are small but significant with the

unemployed who live in a high risk unemployment area showing less distress than

others (probably because the norm is to be unemployed). In addition, the longer term

unemployed seem to find a balance and display, as expected, a higher score.


Finally, all the social variables proved highly significant and contributed most to the

models fit. As expected, a high psychological health score indicates the perception of

strong support networks. Interestingly, membership and activity in an organisation

deteriorates ones well-being. This may be due to the financial pressure exerted on

the unemployed who still participate in these groups. It may also be explained in part

by the suggestion that the unemployed join similar clubs. In addition, the

unemployed who have close employed friends are happier than those who dont.

Therefore, having all unemployed friends implies higher psychological distress

levels in addition to decreasing probabilities of finding employment.

(Table 6 about here)


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5. Conclusions

This paper investigated the effects of differing levels of social involvement amongst

the unemployed (Table 6 provides a summary). It represents the first verification,

using a nationally representative random sample, of the importance of informal

social processes in influencing unemployment exit rates. Unemployed men who

have close employed friends are significantly more likely than those who do not to

find a job. Those who find jobs are also more likely to have perceived the existence

of strong social support networks and be members of some social group. However, it

was noted that there may be some unobserved characteristic which makes these

unemployed individuals (who have employed friends) more predisposed to do well

in the labour market and which also allows them form stronger and more numerous

social relations.

To investigate this further an analysis of psychological distress scores was

undertaken. Indeed, it was found that the unemployed who have all employed close

friends are far most likely to display low psychological stress than either those who

have some or no employed close friends. Therefore, the unemployed whose close

friends are all unemployed are doubly worse off since these individuals are more

likely to have high psychological distress scores and less likely to receive effective

assistance in meeting the difficulties of finding a job.

This work has emphasised the social and psychological aspects of unemployment

and shown the crucial role social resource patterns play, in addition to tradition


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economic accounts, in the determination of who finds a job. The segregation of the

unemployed into networks in which a far higher proportion of people are

unemployed directs these people down a road of depression and isolation. Social

policies must address such problems. The harm caused by council housing schemes

which have produced ghettos of excluded groups is one obvious area in need of

change. This work has explicitly shown that social resource concerns have wider

ranging implications and stronger estimated effects than previously thought.


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End Notes

1

see Antonucci and Akiyama 1987.

2The notion that economics behaviour is embedded in a social context first dates to

Polanyi 1957.

3Respondents were asked in alternative years about their best friend and not their

three closest friends.


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Table 1: Respondents employment status by forms of support.

Employment StatusMen only. Proportion of respondents who claim there was nobody available to

listen help in a crisis relax with really appreciate them

% % % %

Employeda

5.3 3.8 4.6 2.8

Unemployedb

9.9 10.6 8.7 6.6

Number of observationsc

9187 9185 9184 9165

Source: British Household Panel Survey, 1991, 1993, 1995. Average of the three year.

aThe employed are defined as those in part-time, full-time and self-employment, an average of 65% of th

state.

bThis category refers to the self-declared unemployed and those on government training schemes, for the

8% were unemployed.

cIncludes all person-year observations for the three years of the survey when the support questions were a


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Table 2: Employment status of respondents who were unemployed in 1991 by forms of support.

Employment Status 1995

Men only. Proportion of respondents who claim there

listen help in a crisis relax with really appreciate t

% % % %

Employed (68.5%) 10.2 9.5 5.8 8.0

Unemployed (31.5%) 10.9 20.3 14.1 14.1

Number of observationsa

201 201 201 201

Source: British Household Panel Survey, 1991-1995.

aOf the 572 men unemployed in the first year of the BHPS, 407 remained in the survey by year 5.


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Table 3: Effect of measures of social cohesion on the probability of entering employment from unem

Logistic regressions Models :I II III

Social variables control demographic + socio-dem

1. social support index 1.14 ** 1.12 1.11

(4698) (3809) (4163)

2. organisation - member

-active

1.46

1.30

1.55*

1.35*

1.47**

1.30**

(4971) (3956) (4323)

3. employed close friends -some

-all

2.00***

2.38***

1.77***

2.22***

1.89***

2.07***

(4984) (3936) (4302)

4. social support index 1.06 1.04 1.07

member organisation 1.42 1.51** 1.46**

active organisation 1.24 1.33** 1.24*

some employed friends 1.97*** 1.80*** 1.78***

all close friends employed 2.29*** 2.25*** 2.01***

(4698) (3761) (4126)

Note:

-2(Log Likelihood) in brackets.*p


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Table 4 : Effects on the probability of entering employment from unemployment.

FULL MODEL

Exp (B) from logistic regressions

exp(B) S.E.

AGE 1.00 0.002

AGE2

0.99* 0.000

DEGREE 0.68 0.326

OTHQUAL 0.51* 0.309

PRIVATE 1.19 0.207

BOTHW 0.96 0.179

DADW 0.99 0.181

MUMW 0.70 0.347

HEALTH 0.73* 0.149

OWNER 0.97 0.132

LA TENANT 0.50*** 0.162

MARRIED 1.57** 0.163

COHAB 1.07 0.171

SEP/DIV/WID 0.88 0.235

NOKID 0.96 0.054

YOUNG 0.73* 0.147

RATE 0.96** 0.017

UNEM 0.97*** 0.004

SUPPORT 1.08 0.058

MEMBER 1.36* 0.138ACTIVE 1.23* 0.100

SOME 1.58** 0.147

ALL 1.61** 0.153

Chi2imprmt 388

Log likelihood 4230

Note: *p


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Ordered Probits

EMPLOYED -0.056 -0.044 -0.061 -0.023 -0.050

AGE -0.002*** -0.001*** -0.002*** -0.003*** -0.003***AGE

21.5E-6*** 1.2E-6** 2.2E-6*** 2.7E-6*** 3.1E-6***

DEGREE -0.142 -0.121 -0.13 -0.052

OTHQUAL -0.036 -0.003 -0.054 0.045

PRIVATE -0.201*** -0.258*** -0.285*** -0.342***

HEALTH -0.491*** -0.508*** -0.553***MARRIED -0.005 0.028 -0.006

COHAB 0.014 0.021 -0.077

SEP/DIV/WID -0.223*** -0.316*** -0.196***

NOKID 0.022 0.011 0.031*

YOUNG 0.012 -0.045 -0.045

RATE 0.021*** 0.017***UNEM 0.003*** 0.004***

SUPPORT 0.178***

MEMBER -0.145***

ACTIVE -0.146***

SOME 0.139***

ALL 0.184***

cut 1 -2.651 -2.634 -2.765 -2.710 -1.856

cut 2 -2.381 -2.365 -2.501 -2.460 -1.626

cut 3 -2.300 -2.284 -2.420 -2.373 -1.532

Table 5 continued next page.

Table 5 : Unemployed mens psychological well-being


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continued.

cut 4 -2.137 -2.121 -2.255 -2.198 -1.360

cut 5 -1.968 -1.953 -2.085 -2.021 -1.169

cut 6 -1.783 -1.769 -1.900 -1.829 -0.965

cut 7 -1.590 -1.576 -1.703 -1.629 -0.761

cut 8 -1.473 -1.458 -1.583 -1.505 -0.632

cut 9 -1.262 -1.247 -1.366 -1.285 -0.406

cut 10 -1.027 -1.011 -1.124 -1.036 -0.158

cut 11 -0.821 -0.804 -0.912 -0.831 0.053

cut 12 -0.388 -0.369 -0.469 -0.381 0.511

Number

observations

10265 10265 10265 9915 9759

Log likelihood -18660 -18645 -18494 -17879 -17380

Note: *p


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Figure 1: Probability of exit from unemployment, men, aged 25.

0%

5%

10%

15%

20%

25%

30%

12

15

18

21

24

27

30

33

36

39

42

45

48

51

54

prvious unemployment (months)

Probability

offinding

a

job

owner occupier

+ marries

+ member society

+ employed friends


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References:

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Appendix A.

Self completion questionnaire:1. Here are some questions regarding the way you have been feeling over the last

few weeks. For each question please tick the box next to the answer that best

describes the way you felt.

Have you recently ...

a) been able to concentrate on whatever youre doing?

b) lost much sleep over worry?c) felt that youre playing a useful part in things?

d) felt capable of making decisions about things?

e) felt constantly under strain?

f) felt you couldnt overcome your difficulties?

g) been able to enjoy you normal day-to-day activities?

h) been able to face up to problems?

I) been feeling unhappy or depressed?j) been losing confidence in your self?

k) been thinking of yourself as a worthless person?

I) been feeling reasonably happy, all things considered?

(coded)

Better than usual......................................

Same as usual...........................................Less than usual.........................................

Much less than usual................................


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5. Here are a few questions about your friends. Please choose the three people you

consider to be your closest friends. They should not include people who live with

you but they can include relatives.a) Is this friends male or female?

b) Is this person a relative?

c) What is your fiends age?

d) Which of these best describes what your friend does

Full time employed

Part time employedUnemployed

Full time education

Full time housework

Fully retired

e) How often do you see or get in touch with your friend whether by visiting, writing

or by telephone?

3. Here are a few questions about people in your life who can provide you with help

or support (tick one only)

a) Is there anyone who you can really count on to listen to you when you need to

talk?

b) Is there anyone who you can really count on to help you in a crisis?

c) Is there anyone you can totally be yourself with?d) Is there anyone who you feel really appreciates you as a person?

e) Is there anyone who you can really count on to comfort you when you are very

upset?

(coded) Yes, one person

Yes, more than one person

No-one

Appendix B. Variable Names and definitions.


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Variables included in logistic regressions.

Sociological:

SOCIAL SUPPORT INDEX 0 - 5 scale based on 5 social supportquestions asked in waves 1, 3 and 5

SOCIAL PARTICIPATION neither active nor member organisations

member only in organisation

active in organisations (all waves)

SOCIAL NETWORKS no employed close friends

some employed close friends

all close friends employed (wave 2, 4 and 6)

Control variables included in logistic regressions.

Demographic:

AGE age at the beginning of the unemployment spell

AGE2

the above squared

PAGOLD fathers Goldthorpe class.

DEGREE highest educational qualification, degree or equiv.

OTHQUAL some other qualification.

Socio-demo:

PRIVATE grammar fee-paying, public or other private school.

PARGROUP 4 dummies for family employment background

HEALTH health limits amount of work can do.

STATUS dummies for married, cohabit, sdw, and single

NOKID number of kids in household

YOUNG child under 5 yrs.

TENURE dummies for owner, LA tenant and other tenant.

Job history:

RATE monthly unemployment rate

UNEM number of months unemployed in previous spell.

‘Social Cohesion’ and Unemployment Exit Rates

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