Why so unhappy? The effects of unionization on job satisfaction
Alex Bryson§, Lorenzo Cappellari°* and Claudio Lucifora°
# March 2007
§
Policy Studies Institute, London
° Istituto di Economia dell’Impresa e del Lavoro, Università Cattolica, Milano.
Word count [#####]
*
Corresponding author, Istituto di Economia dell’Impresa e del Lavoro, Università Cattolica,
Largo Gemelli 1,20123, Milano, Italy. Email: [email protected], tel
+390272343010, fax +390272342781. The authors thank the Department of Trade and
Industry, the Economic and Social Research Council, the Advisory, Conciliation and
Arbitration Service and the Policy Studies Institute who co-sponsor the Workplace
Employment Relations Surveys, and acknowledge the UK Data Archive as the distributor of
the data.
i
Why so unhappy? The effects of unionization on job satisfaction
Abstract
We use linked employer-employee data to investigate the job satisfaction effect of union
membership in Britain. We depart from previous studies by developing a model that
simultaneously controls for the determinants of individual membership status and for the
selection of employees into occupations according to union coverage. We find that a negative
association between membership and satisfaction typically found in previous studies is
confined to non-covered employees. We interpret this as a union voice effect. In covered
occupations the negative association between membership and satisfaction disappears having
accounted for selection effects, suggesting that less satisfied individuals are more likely to be
union members, but only when the occupation is covered by collective bargaining. Our
results are also consistent with the existence of queues for union covered jobs.
JEL classification: J28, J51
Keywords: Job satisfaction, Union membership, Union coverage, Endogeneity
ii
I. Introduction
Surveys of employees’ opinions typically reveal that union members’ reported job satisfaction
is lower than non-members’. Taken at face value this is puzzling since unions should improve
working conditions, this being among the reasons for joining a union. Freeman and Medoff
(1984) and Borjas (1979) explain this finding arguing that members ‘voice’ their
dissatisfaction to improve the bargaining power of the trade union. Bender and Sloane (1995),
on the other hand, emphasise that unions organise where working conditions are poor:
according to this view, workplace characteristics determine both union membership and
dissatisfaction, so that the observed differential might reflect spurious correlation. Others
stress the role of unobserved individual characteristics in the sorting of dissatisfied individuals
into membership as the basis for a spurious correlation between membership and satisfaction
(Heywood et al., 2002; Bryson et al., 2004.
This paper is the first to consider the interplay between individual union membership
and bargaining coverage in explaining the link between membership and satisfaction. There
are several reasons why failure to account for coverage may bias estimates of union
membership effects on job satisfaction. First, union coverage may have its own effect on job
satisfaction, arising from the bargaining and voice effects of union representation which we
discuss below. Hence, where coverage is unobserved estimated membership effects may
suffer from omitted variables bias.1 Second, the incentives to be a union member may not be
the same in covered and uncovered jobs, and this may imply different effects of membership
on satisfaction in the two cases. Third, the selection of workers into covered and uncovered
jobs may itself be non-random, implying that coverage status, like membership, may also be
endogenous. This multifaceted interaction between membership and coverage suggests that it
1
This has also emerged as an issue in the union wage premium literature (Andrews et al., 1998).
1
is important to account for both when looking at union membership effects on job
satisfaction.
We use linked employer-employee data representative of the British workforce to
analyze job satisfaction while simultaneously addressing employees’ selection into both union
membership and covered jobs within workplaces. We exploit the linked nature of the data and
use variation of workplace attributes within cells defined by workplace industry, size, region
and workforce structure to estimate the impacts of unionization on satisfaction. Our results
indicate that the membership-satisfaction puzzle depends crucially upon bargaining coverage.
Among workers not covered by collective bargaining, union membership is found to increase
dissatisfaction with the job, consistent with members using their status to voice discontent
with the aim of increasing bargaining power or with a view to organizing the union. These
uncovered members appear to behave like union activists in the absence of bargaining
coverage. Conversely, among covered workers we find no differences in satisfaction between
members and non-members having accounted for selection effects. We also find that covered
workers are intrinsically satisfied with their job, a result consistent with the existence of
queues for union covered jobs as proposed by Abowd and Farber (1983).
II. Job satisfaction, union membership, and union bargaining coverage
To date none of the studies of union membership effects on job satisfaction have considered
the role played by union bargaining coverage. This might not matter where, as in the United
States, membership and coverage are virtually synonymous. But, as the data in this paper
show, this is not the case in Britain (see the first row of the table in the Appendix). Indeed, 26
percent of employees not covered by union bargaining are members of the union, and almost
40 percent of employees covered by bargaining are not members of the union. Employees in
the latter category are ‘free-riders’ in that they may benefit from collective bargaining
2
coverage without becoming union members. This ‘free-riding’ rate is considerably higher
than that in the United States (Bryson and Freeman, 2006), in spite of the fact that in both
countries most collective bargaining occurs at workplace-level, rather than sectorally or
nationally (Kersley et al., 2006). This is because the union membership decision has been a
genuinely free one in Britain since the closed shop was outlawed in the early 1990s. What is
more, the incentive to free-ride is bolstered by the fact that British unions are unable to levy
an agency fee on non-members to cover the union agency costs in bargaining on their behalf.
In these circumstances, it seems natural to enquire as to why anybody would pay union
dues to be a union member. Part of the answer appears to be that it is the employees facing
the greatest number of problems at work – and therefore with the greatest potential for job
dissatisfaction – who are most desirous of union membership (Charlwood, 2003; Bryson and
Freeman, 2006; Bryson, 2007a).2 Among covered workers, one might therefore observe
greater job dissatisfaction among members than non-members. This dissatisfaction may arise
from their job circumstances, which generate problems leading to dissatisfaction.
Alternatively, when faced with similar job circumstances to others, these workers perceive
more problems than others, perhaps because their aspirations from work are higher than nonmembers’, or else they are inherently more dissatisfied with things in life.3 If any negative
correlation between membership and satisfaction among covered workers arises for these
reasons, one would expect it to disappear having controlled adequately for job conditions and
workers’ traits
One may also wonder why non covered employees unionize, given that they do not
benefit from the union representation at the workplace, which would bargain on their behalf
2
There are other reasons why covered workers may choose not to free-ride. First, there is evidence that the
returns to union coverage are greater in workplaces with higher union density, perhaps because higher
membership strengthens the union’s bargaining hand (Stewart, 1987). Second, there are union benefits
unconnected with bargaining coverage which are confined to members. These include access to union
representation in grievance cases. Third, there are reputational pay-offs to becoming a union member where it is
the social custom to do so (Booth, 1995).
3
A further possible reason for membership dissatisfaction in the covered sector is resentment at paying union
dues in the presence of free-riders.
3
and help voice their concerns to management. One interpretation might be that these
uncovered members are characterized by strong collectivist attitudes or act as union activists
in the early stages of organizing a workplace with a view to obtaining union bargaining rights.
At the time of the survey workers had no legal right to coverage at the workplace, even if a
majority of workers would have voted for it. Rather, coverage was at the discretion of the
employer, a concession that was more likely to be granted where a substantial proportion of
workers were union members.4 Thus, it is possible that uncovered members will emphasize
their job dissatisfaction and voice it to others in the hope of ‘drumming up’ support for
bargaining coverage, an effect that is consistent with predictions from Freeman and Medoff’s
(1984) theory, i.e. unionized workers use their voice as a strategic device.
In reality, it often takes a long time for workplaces with minority union membership to
achieve union recognition from an employer (Kersley et al., 2006). Under these
circumstances, uncovered members’ primary objective may be the improvement of their own
terms and conditions, effectively taking on the role that, in the covered sector, would be
undertaken by the recognized trade union. In a sense, these members are substitutes for the
union. Being in the non-covered sector may induce them to report job dissatisfaction, since
there are no union representatives to ‘voice’ discontent. If this was the case, any negative
correlation between membership and satisfaction would be the consequence of their
membership status rather than a selection effect.
Even in the absence of coverage, workers may benefit from union membership. For
instance, they may be using their membership as an insurance policy in the sense that, even
though the union may not be recognized for bargaining, the individual can call on the union
for protection against unfair employer behaviour (Bryson and Freeman, 2006). Other benefits
4
The 1999 Employment Relations Act introduced a Wagner-like legal right to union bargaining coverage where
a majority of workers in a bargaining unit wished for it. However, the vast majority of new union recognitions
continue to be voluntary and do not involve the legal procedures laid down in the act.
4
of union membership include professional indemnity insurance.5 Alternatively, as previously
discussed, uncovered workers may become members when the individual is ideologically
attached to union membership and sees it as an expression of personal values (see Bryson,
2007b; for empirical evidence on the role of political and social values in explaining union
membership status in Britain).
Their membership may be part of their occupational
identification, as is the case with many health professionals whose pay is nevertheless set by
public sector Pay Review Bodies rather than through collective bargaining (Bach and Givan,
2004).
Confronted with the negative association between membership and job satisfaction that
typically emerges from the data, previous research has clarified that members’ dissatisfaction
could either reflect a causal effect, consistent with the ‘voice’ hypothesis, or be the symptom
of spurious correlation induced by unobservable individual characteristics or working
conditions that co-determine satisfaction and unionisation.6 The discussion in this Section
indicates how these arguments specialise when union coverage is added to the picture, but an
explicit assessment of the role of bargaining coverage is missing from the literature. Most of
the studies in the literature have not controlled for coverage, while others have conflated
coverage and membership (Bender and Sloane, 1998; Heywood et al., 2002). To fill this gap
of knowledge, we use linked employer-employee data and develop a sufficiently flexible
model that estimates employees job satisfaction while controlling for endogenous selection
along the two relevant dimensions of unionization, coverage and membership.
III. Data and preliminary analysis of the membership/satisfaction link
5
For an example of just how substantial this benefit might be see
http://www.unison.org.uk/healthcare/pages_view.asp?did=1183 which outlines to insurance offered by
UNISON, the largest public sector union in Britain.
6
Besides those cited in the Introduction, studies on this issue also include Schwochau (1987); Hersch and Stone
(1990); Gordon and Denisi (1995).
5
Our data are the linked employer-employee British Workplace Employee Relations Survey
1998 (WERS). With appropriate weighting, it is nationally representative of British
employees working in workplaces with 10 or more employees covering all sectors of the
economy except agriculture (Airey et. al, 1999). The survey covers a wide range of issues and
contains controls for a large set of individual-level and workplace-level attributes. We use two
elements of the survey. The first is the management interview, conducted face-to-face with
the most senior workplace manager responsible for employee relations. The second element is
the survey of employees where a management interview was obtained. 7
Two aspects of the data make them particularly suited for analyzing the interplay
between union membership and union coverage in affecting employees’ satisfaction. First, the
management interview contains a bargaining coverage indicator for each occupational group
in the workplace, providing a precise measure of coverage that is difficult to obtain from
surveys exclusively based on interviews with employees. Second, the available information
on workplace attributes is very detailed, providing variability even within cells defined by
industry, size and region, i.e. the set of workplace controls typically deemed to affect job
satisfaction in the literature. To the extent that such variability has an impact on unionization
and not on satisfaction, then linked employer employee data offer a rich source of variation
that is useful for estimating the impact of unionization on satisfaction. In this respect, linked
data may be seen as a complement to longitudinal surveys that use changes in individual
union status over time for estimating the impact of membership on satisfaction (see e.g.
Heywood et al 2002).
The survey asked each employee to provide a rating, on a five-point scale from ‘very
satisfied’ to ‘very dissatisfied’, concerning how satisfied they were on four aspects of their
job: (i) the amount of influence they had over their job; (ii) the pay they received; (iii) the
7
Response rates were 80 percent and 64 percent for the management and employee questionnaires respectively.
6
sense of achievement they got from their work; and (iv) the respect they got from supervisors
and line managers. We conduct our initial analysis on each of the four facets. Later we
concentrate on the three non-pecuniary job satisfaction items, where we find the puzzling
negative association with union membership to be more evident.8 Information on individual
membership is derived from a question in the employee questionnaire. We match the
information on union coverage from the manager questionnaire to individuals using their
occupational category recorded in the employee questionnaire.
The Appendix provides some descriptive statistics for the estimation sample, which is
derived from the original WERS sample after deletion of cases with missing information on
variables required for the econometric analysis (approximately 4,000 cases were deleted in
this way). Employees exhibit greater dissatisfaction with pay than with non-pecuniary facets
of their jobs. There are differences in non-pecuniary job satisfaction between employees in
covered and non-covered occupations with those in non-covered occupations expressing
greater satisfaction.
Breaking the data down by union membership and coverage reveals
notable differences in personal attributes. In particular, the profile of union members differs
across covered and non-covered occupations. For example, the proportion of highly educated
individuals is larger among non-covered members compared with covered members, by
approximately fifty percent. Conversely, the distribution of educational attainment does not
differ much if one compares non-members in covered and non-covered occupations. Noncovered members also tend to be concentrated in professional and technical occupations,
whereas the occupational distribution of covered members is skewed towards manual jobs.
Finally, while most non-covered members can be found in Health and Education, covered
union members are concentrated in Manufacturing.
<TABLE 1>
8
Bryson et al. (2004) analyse the determinants of satisfaction with pay and find that there is no statistically
significant difference between union members and non-members.
7
We describe the relationship between job satisfaction and membership by means of an
ordered probit regression of each satisfaction indicator on a membership dummy and a set of
controls that include personal characteristics, job and workplace attributes. Regressions are
estimated on the whole sample and the sub-samples of covered and non-covered employees.9
Table 1 focuses on the marginal effects associated with the membership coefficient, using the
probability of being ‘Satisfied’ or ‘Very Satisfied’ as the outcome of interest.10 (The full set of
ordered probit coefficients is reported in a table available from the authors upon request,
while the choice of the regressors entering the satisfaction equation is discussed in the next
section). Considering pay satisfaction first, Table 1 shows that there is no significant
association between union membership and job satisfaction: the puzzling negative effect
apparent in much of the previous literature does not seem to apply to pecuniary facets of
satisfaction. This may reflect the union membership pay premium documented, among others,
by Blanchflower and Bryson (2004) using WERS data, which may compensate for the
member/non-member dissatisfaction differential. The satisfaction “penalty” associated with
membership is statistically significant for the other satisfaction items, and ranges between 6
and 8 percentage points on the probability of being ’Very satisfied’ or ‘Satisfied’. Since the
sample frequencies of workers who were ‘Very satisfied’ or ‘Satisfied’ reported in the
Appendix range between 57 and 63 percent in the overall estimation sample, holding personal
attributes fixed union membership shifts the satisfaction probability by roughly one tenth of
the aggregate probability in the sample. Table 1 also shows that quantitatively these
differentials are very similar in sub-samples defined by union coverage status.
<TABLE 2>
9
The regressions are weighted to account for sampling probabilities and a robust variance estimator corrects for
the presence of repeated observations on the same establishment.
10
Marginal effects are computed from ordered probit coefficients by considering the shift in the probability of
the outcome of interest (i.e. being ‘very satisfied’ or ‘satisfied’ on a given job satisfaction facet) induced by a
switch in union membership status, and are evaluated at the constant of the regression model.
8
Table 2 reports union membership satisfaction differentials using propensity score
matching (PSM). As in the case of the regression estimates shown above, interpretation of the
member/non-member differential as the causal effect of union membership relies on the
assumption that selection into union membership is captured by observables. However, unlike
regression, PSM is a semi-parametric technique and does not require assumptions to be made
about the functional form of the satisfaction equation. Rather it compares the satisfaction
differential between members and non-members who are similar with respect to observable
attributes. The maintained assumption in regression and PSM when estimating treatment-onthe-treated is that counterfactuals for members can be found among non-members who are
observationally equivalent as indicated by their propensity for union membership. In our
analysis, this propensity is estimated as the probability of membership based on a probit
estimator. The independent variables entering the probit are identical to those used in the
regression analyses. Where members are adjudged to be too far from their non-member
counterparts they have no counterfactuals against which to estimate the union membership
effect and are therefore dropped from the analysis.11
The figures in Table 2 are the mean differences in satisfaction across members and their
matched non-member counterparts where satisfaction is measured as being ‘Very satisfied’ or
‘Satisfied’. As in the case of the regression analyses, results are presented separately for the
whole economy, covered employees and uncovered employees. The results are qualitatively
similar to those obtained from regressions presented above. The membership/satisfaction
differential is the smallest with respect to pay. Indeed, in the covered and uncovered subsamples the differential is not statistically significant. On all three non-pecuniary aspects of
11
The matching method deployed is nearest neighbour matching. Matches for members were those nonmembers whose estimated probability of membership was up to 0.002 above or below the estimated probability
for the member. Matching is undertaken separately for all employees, covered employees and uncovered
employees. The number of members lost through enforcement of this support requirement was 44 in the case of
the whole economy estimates, 125 among covered employees, and 56 among non-covered employees. Full
details of the probit estimation and diagnostic tests for the matching are available from the authors on request.
9
satisfaction members were significantly less satisfied than their non-member counterparts, the
differential being in the range of 6-10 per cent. The effects did not differ greatly across
covered and uncovered employees nor across the different aspects of non-pecuniary
satisfaction.
The results presented thus far indicate that the union membership/satisfaction
differential persists having controlled for differences in the characteristics of members and
non-members, except in the case of pay satisfaction. Furthermore, these effects are apparent
in the covered and uncovered sectors. The discussion of the previous Section indicates that
the reason for members’ dissatisfaction may be different in covered and non-covered
occupations. Moreover, descriptive statistics show that members’ profile is different in
covered and non-covered occupations. We therefore pursue further analyses that account for
the interplay between union membership and union coverage in shaping members’
satisfaction with their job .
IV. An econometric model of job satisfaction, union membership and union coverage
In order to estimate the effect of membership on satisfaction, we extend the instrumental
variables framework used in several previous studies to encompass selection into different
bargaining regimes, i.e. jobs covered by collective agreements and those that are not covered.
We do so by allowing for the possibility that unobserved heterogeneity in job satisfaction may
be correlated with the process assigning individuals to covered and non-covered jobs. In
tackling this issue we exploit the linked employer-employee structure of the WERS data
which permits us to match information on union coverage for each occupational group in the
workplace, derived from the manager questionnaire, with individual-level information on
employees. Unlike the methods applied in the previous section, the model in this section
explicitly assesses the role of unobserved heterogeneity.
10
Let c*i denote the propensity of being employed in a covered job for individual i,
i=1…n. This propensity depends upon two components: the net benefit derived from covered
employment and the employer’s hiring decision. Both components are functions of personal
and workplace characteristics, observed (xi) and unobserved (εi). If there are queues for
covered jobs, individuals’ observable and unobservable (to the analyst) personal attributes can
play a role in affecting employers’ hiring decisions.12 The vector of observables xi includes
personal attributes (gender, age, education, disability status, marital and parental status,
ethnicity) and workplace attributes (industry, size, region, workforce composition, age,
whether the workplace is a stand-alone workplace or part of a larger organization, and
whether it is publicly or privately owned) plus an indicator of local labour market conditions
(the travel-to-work area unemployment rate). Individual wages (a job satisfaction shifter in
most of the literature) are not included in xi since they are one of the bargaining outcomes and
therefore endogenous to coverage. We specify c*i as a linear function of its determinants:
c*i = β’xi+εi
(1)
where β is a coefficient to be estimated. We do not observe c*i; rather, we observe whether
individual i is covered by union bargaining, an event that signals that c*i exceeds some latent
threshold, which can be set to zero without loss of generality. Let Ci =I(c*i >0) indicate the
event, where I( ) is an indicator function.
Next, let the net benefit derived from membership, m*i, be a function of the same set of
personal and workplace attributes used in the coverage equation, plus an unobserved
component:
m*i=γ’xi+vi
(2)
where symbols have a meaning analogous to that in equation (1). Although the individual
membership decision is possibly less influenced by employer behaviour than coverage is, the
12
Evidence of job queues for union jobs in the US is discussed by Abowd and Farber (1983), Farber (2001) and
Freeman and Rogers (1999).
11
set of workplace characteristics included in xi may capture factors that are relevant to
individual membership, such as industry-specific attitudes towards the union, and therefore
we use in (2) the control factors used in the coverage equation. When the net benefit is
positive, we observe individual i to be a union member; let Mi = I(m*i >0) index that event.
Taken together, equations (1) and (2) fully represent the ‘choice set’ resulting from the
combination of the membership and coverage choices. Note that the two processes are
unconditional one upon the other. That is, since we are not interested in the effect of coverage
on membership, for instance, we model the two processes in a reduced form fashion, and
control for their interrelationship by estimating the cross-process correlation, as discussed
below.
In order to estimate the effect of membership on satisfaction while accounting for
employees’ union coverage status, we adopt an endogenous switching framework and allow
the impact of (observed and unobserved) job satisfaction determinants to be different in the
two bargaining regimes:
s*i=(δC’zi+λCMi+uCi)Ci + (δΝC’zi+λΝCMi+uΝCi)(1-Ci)
(3)
where s*i is the individual propensity to be satisfied with the job and the C and NC subscripts
refer to quantities relevant for workers in jobs that are covered or non covered by union
bargaining. Following Clark and Oswald (1996), s*i may be thought of as the utility derived
from working, itself an argument for an overall individual welfare function. The data do not
allow direct observation of s*i, but provide information on the satisfaction rank reported by
employees (Si). We let the observed satisfaction rank depend on the underlying satisfaction
propensity through the mapping τ, Si=τ(s*i), which is a step function that takes on a set of
ordered values (from ‘very dissatisfied’ to ‘very satisfied’) depending upon s*i crossing a set
of threshold levels. The unknown coefficients λC and λΝC index the effect of union
membership on job satisfaction after taking account of endogenous selection into union
12
coverage. The vector of observables zi includes all the variables that affect unionization (but
with some exceptions, see below), plus pecuniary (weekly earnings, hours of work and
whether overtime hours are always paid) and non pecuniary job attributes that may influence
job satisfaction and may to some extent be correlated with unionization. Specifically, non
pecuniary attributes include training, gender segregation in the job, whether the employment
relationship is fixed term, , the availability of family friendly policies and the possibility to
take days off when needed.
Estimating equations (2) and (3) ignoring equation (1) is subject to an endogenous
sample selection issue, as long as the unobserved individual determinants of union coverage
are correlated with unobservables in the membership and satisfaction equations. For example,
unobservable determinants of membership and coverage are likely to be positively correlated,
if individuals who care about representation are more likely to work in covered workplaces
and be union members. Alternatively if there are queues for job positions covered by union
bargaining and the individual attitude toward working (the innate propensity to be satisfied
with the job) is valued and somehow observed by employers, then we should expect the
unobserved (by the researcher) determinants of coverage and satisfaction to positively covary.
Besides endogenous selection into coverage, the other source of spurious correlation is
the endogeneity of membership, the only one that has been addressed by the literature thus
far. As discussed there, such a correlation might be negative if members are ‘genuinely’
dissatisfied, say because they have higher aspirations towards the work environment
compared to non-members, which can be more easily frustrated. Or it can be positive, if
members are more motivated towards the job compared to non-members.
We tackle both forms of endogeneity by allowing the unobserved individual
components of equations (1), (2) and (3) to be jointly distributed according to a four-variate
normal distribution with zero means, unit variances and free correlations:
13
(εi,vi,uCi,uNCi)~N4(0,Ω)
(4)
By specifying the extra-diagonal elements of the correlation matrix Ω we introduce
unobserved heterogeneity into the model, thereby accounting for the endogeneity issues
outlined above.13
In order to aid identification of the effects of interest we formulate a set of exclusion
restrictions. In particular, we need to make assumptions about variables that affect coverage
and/or membership but, conditional on these, have no residual impact on job satisfaction. To
this end, we assume that after controlling for factors such as the establishment’s industry,
size, region and workforce composition throughout the model’s equations, some of the
workplace characteristics included in xi have no independent effect on job satisfaction. In
doing so, we exploit our linked employer-employee data to provide identification of the
model. Since the two union equations are unconditional one upon the other and their
(observable) determinants are likely to be similar, we use the same set of ‘instruments’ in the
two equations. The first variable in this group is establishment age. We hypothesize that in
older (more than twenty years) workplaces the chance of union bargaining coverage is larger
than in otherwise comparable establishments and this may also have a bearing on membership
decisions. There is considerable empirical support for this hypothesis in Britain. Earlier
cohorts of workplaces were more likely to recognize unions for pay bargaining than those
‘born’ after 1980 (Machin, 2000; Millward et al., 2000). We assume that after controlling for
establishment characteristics such as industry and size (that may depend upon establishment
age) there is no residual impact of workplace age on job satisfaction. Second, we assume that
whether a workplace belongs to a multi-establishment firm or is a stand-alone workplace has
no independent impact on job satisfaction, net of union coverage, while it matters for
13
We estimate the model by maximum simulated likelihood, using the GHK simulator and 50 Halton draws. As
in the previous section, we use sample weights and a robust variance estimator. The correlation coefficient
between uCi and uNCi is not identified, since it would require individuals simultaneously observed in covered and
non-covered jobs, and does not enter the likelihood function.
14
workplace unionization. Union coverage has fixed costs for employers (such as the
transaction costs in engaging in negotiation and consultation with worker representatives)
which can be better accommodated in the presence of multiple establishments (Bryson et al.,
2004), while employees’ satisfaction is more likely related to characteristics of the
establishment where they are located. Finally we assume that public, as opposed to private,
ownership affects a workplace’s propensity for union coverage, in part because wage setting
is not subject to the same market pressures in the public sector, and also because negotiation
with workers over wages has been part of the traditional ‘good employer’ model for the
public sector in Britain. For these reasons collective bargaining coverage remains very high
in the public sector but continues to decline in the private sector (Kersley et al., 2006).
However, conditioning on individual and workplace characteristics, including industry, there
is no reason to suspect that public ownership per se should affect employee job satisfaction.
V. Results
This section discusses the results obtained by estimating the econometric model of the
previous section on the WERS sample. Since Tables 1 and 2 showed that the membership –
satisfaction puzzle does not emerge when considering satisfaction with pay, in this Section we
concentrate on non-pecuniary job facets. To gauge the distinctive contribution of accounting
for endogenous coverage in addition to endogenous membership, we start by considering
results from restricted versions of the model of interest in which only membership is treated
as endogenous, i.e. as in the existing literature on union membership and job satisfaction. We
then move to the results of the model presented in the previous section, which also controls
for the (observed and unobserved) determinants of coverage.
Table 3 presents the estimates of the effect of union membership on the non-pecuniary
facets of job satisfaction and of the correlations of unobservables between the membership
15
and satisfaction equations (the full set of estimated coefficients is available from the authors
upon request).
<TABLE 3>
Estimates are presented for the whole estimation sample and by (exogenously) splitting
observations according to individual coverage status. Considering the whole sample first, the
negative satisfaction differential distinguishing members from non-members is magnified by
endogenisation of membership status, its absolute value doubling (from 7 to 15 percentage
points) in comparison with the estimates of Table 1 where membership was treated as
exogenous. The estimated membership differential is similar across satisfaction facets. The
increase in the absolute value of the effects is suggestive of a positive selection effect of
intrinsically more satisfied individuals into union membership, which is confirmed by the
positive signs on the estimated correlation of error terms between the membership and
satisfaction equations. In other words, in this framework where coverage is assumed
exogenous, it seems that it is not inherent dissatisfaction per se that motivates workers to be
part of the union: if anything the opposite seems to be true, i.e. it is workers’ union status that
induces the voicing of dissatisfaction.
Splitting the sample by bargaining coverage reveals remarkable differences in members’
satisfaction relative to non-members’. The membership dissatisfaction differential persists
among non-covered employees, and is apparent for all three non-pecuniary job facets. Among
covered employees the differential is no longer significant in the case of satisfaction with
influence over work and with sense of achievement, while it is still evident in the case of
satisfaction with respect from supervisors. Moreover, the positive selection effect of
intrinsically satisfied individuals into membership is not found among covered employees, the
correlations of the unobservables dwindling to insignificance for all three facets of
satisfaction. In contrast, the selection effect remains positive and significant among non-
16
covered employees, indicating that the unobservable characteristics of non-covered members
are associated with higher job satisfaction relative to otherwise identical non-covered
employees. It seems, therefore, that the nature of members’ dissatisfaction differs depending
upon whether their occupation is covered by collective bargaining. In occupations in which
there is no union representation in bargaining, the fact of being a member increases
dissatisfaction. This effect can be deemed causal, since we have accounted for observed and
unobservable selection into membership. This result is consistent with the voice effect
previously discussed: in the absence of formal union representation members substitute
themselves for the union, voicing out discontent as a way to increase bargaining power or to
motivate other workers to organize in the hope of obtaining union coverage. Conversely, for
covered workers, dissatisfaction is more apparent than real, and disappears once the
determinants of the membership status are taken into account.14
We now discuss the results obtained from estimating the model presented in the
previous section, in which the satisfaction-membership relationship is allowed to change
according to coverage while accounting for the observed and unobserved factors that
determine assignment to covered occupations . By doing so, we are able to assess the role
played by selection into occupations and to establish the extent to which the membershipsatisfaction differential in covered and non-covered occupations is due to differences in the
(unobserved) propensities to be satisfied across covered and uncovered occupations.
<TABLE 4>
The main coefficients of interest are reported in Table 4. The table presents marginal
effects of union membership on job satisfaction and the cross-equation correlations of the
error terms in the coverage, membership and satisfaction equations. Although the whole set of
14
Using an overall job satisfaction indicator and pooling covered and non covered employees from WERS98,
Bryson et al. (2004) also found that the negative satisfaction/membership link was the result of self-selection
into membership. Their analysis was conditional on a battery of indicators of individuals’ opinions on the
climate of industrial relations. The fact that these opinions may be correlated with union coverage can explain
why we are able to find results consistent with theirs after splitting the sample according to coverage status.
17
estimates is not reported for lack of space (it is available upon request), it is worth briefly
discussing the estimates of the coefficients associated with the instruments in the membership
and coverage equations. The instruments (i.e. workplace age, single-establishment
organization and public ownership) are always statistically significant in shifting membership
and coverage and bear the ‘expected’ signs, indicating that union members and occupations
covered by collective agreements are more likely to prevail in workplaces that are older, are
publicly owned, and belong to multi-plant organisations. Using normality as the identifying
restriction, we also tested that the ‘instruments’ were not significant in the satisfaction
equations at conventional levels of confidence, and in all but one of the six satisfaction
equations estimated (satisfaction with influence in non-covered occupations) we found
support for their exclusion, since the null hypothesis of joint non significance could never be
rejected, with p-values in the order of 0.3 or larger.
In Table 4 the effect of membership on satisfaction is never statistically significant for
employees in covered occupations. In the case of satisfaction with respect from supervisors,
the significant negative effect of membership obtained when treating coverage as exogenous
switches sign and becomes statistically non-significant when treating coverage as
endogenous. The result emphatically confirms our previous finding that in these covered
occupations the negative impact of membership is not causal but spurious. Further support for
this interpretation comes from the estimated correlations of the errors for the satisfaction and
membership equations. These are now negatively signed and, whilst still not statistically
significant at conventional levels, they are more precisely estimated than those reported in
Table 3. Taken together these correlations suggest that inherently dissatisfied workers select
into union membership when the occupation is covered by union bargaining. Employees in
covered occupations in Britain are not required to join the union or pay it an agency fee for its
bargaining services, so that it is easy to ‘free-ride’ on the benefits of coverage. Our results
18
suggest that where the job is covered by collective bargaining individuals who are members
have to be inherently very dissatisfied about their job. The fact that dissatisfaction disappears
having accounted for unobservable differences between members and non-members suggests
that the unionized environment in which they work is capable of internalizing and conveying
their discontent through bargaining activity (i.e. give voice) thus reducing the dissatisfaction
differential.
When non-covered occupations are considered, we find a negative effect of membership
on satisfaction (albeit imprecisely estimated in the case of satisfaction with respect from
supervisors). When workers are not covered by a collective agreement being a union member
raises reported dissatisfaction vis-à-vis non-union members. This is consistent with the voice
interpretation: in the absence of formal representation, members substitute themselves for the
union and voice their dissatisfaction to strengthen workers’ bargaining power and encourage
others to organize. The correlations between unobservables in the membership and
satisfaction equations for non-covered employees indicate positive selection of intrinsically
satisfied individuals into membership (again, with a loss of precision for the coefficient
referring to satisfaction with respect from managers). That is, when there is no union
recognised for bargaining, it is those who are intrinsically more satisfied that are found among
union members. This effect may be interpreted in terms of employees’ underlying motivation
towards their job. For example, in the absence of pecuniary rewards through bargaining
coverage, the returns to membership may come in the form of things like greater information
flows from management, which are prized more highly by those who are particularly attached
to their jobs. The positive coefficient could also be capturing some underlying features of
specific jobs where membership is an important part of employees’ occupational
identification, or where particular job attributes make it advantageous for employees to join
the union and pool professional risks. In Britain, these professions include teachers and
19
medical professionals whose pay is set by government Pay Review Bodies rather than through
collective bargaining. The evidence provided in the Appendix Table about the characteristics
of non-covered members supports these interpretations.
Results from the model with endogenous coverage indicate that differences in members’
job satisfaction across covered and non-covered jobs are not driven by selection effects. By
endogenising coverage, one also gains insights into the correlations of unobservables
affecting membership and coverage, on the one hand, and satisfaction and coverage on the
other. The correlation of the unobserved determinants of union membership and union
coverage is relatively large and precisely estimated which suggests that the reduced form
approach to their joint estimation is not unduly restrictive in assuming that the same set of
factors are relevant in explaining both dimensions of unionism. The coefficients capturing
correlations between the error terms in the propensity to be satisfied and the probability to be
employed in a covered occupation are always positive and tend to be precisely estimated.
Therefore, as one might expect, individuals in jobs covered by union bargaining are found to
be always (inherently) more satisfied than individuals in non-covered jobs. This finding is
supportive of the hypothesis that covered jobs are rationed and prospective employers are able
to select from the queue of job applicants selecting individuals according to some traits that
are likely to be correlated with productivity, like job satisfaction.
VI. Conclusion
In this paper we contributed to the literature on union membership and job satisfaction
showing that the union membership effect on job satisfaction crucially depend upon whether
members are covered by union bargaining. We used linked employer-employee data to
investigate the job satisfaction effect of unionisation in Britain while also accounting for the
process that assigns workers to covered and non-covered occupations. For covered members,
our results support explanations based on the spurious correlation argument, i.e. members are
20
inherently more dissatisfied with their jobs than their non-member counterparts. This is what
one could expect given the British context in which covered workers do not need to be union
members to benefit from union bargaining so that individual membership in covered
environments is driven by inherent dissatisfaction with the job. In these circumstances
membership has no negative effect on satisfaction. Rather, the unionised environment seems
capable of internalising and conveying members’ discontent through bargaining activity.
The results for employees in non-covered occupations are very different. We find that
membership reduces satisfaction, in line with the ‘union voice’ hypothesis. Our result
suggests that in the absence of formal representation in bargaining, members substitute for the
union, voicing their dissatisfaction so as to increase workers’ bargaining power and encourage
organization among co-workers.
Finally, we show that the individual propensity to be satisfied with the job is larger in
covered than in non-covered occupations. Where covered jobs are perceived by employees as
better jobs, and (as shown by some studies reviewed in this paper) workers’ demand for union
representation exceeds the supply, there will be queues for such jobs. Unionised employers
will be able to pick the ‘best’ workers from this queue. To the extent that job satisfaction is
positively associated with traits such as motivation and ability that are at least partly
observable by employers, we should indeed expect to find the more satisfied among covered
workers. Our results are therefore consistent with an open-shop environment such as Britain,
where workers are free to choose whether to unionize or not, jobs covered by collective
agreements are rationed and workers queue for union jobs.
21
Appendix: Descriptive statistics of the WERS98 sample
Number of observations
Satisfaction with pay
Very dissatisfied
Dissatisfied
Neither satisfied nor
dissatisfied
Satisfied
Very satisfied
Satisfaction with sense of
achievement
Very dissatisfied
Dissatisfied
Neither satisfied nor
dissatisfied
Satisfied
Very satisfied
Satisfaction with respect from
supervisors
Very dissatisfied
Dissatisfied
Neither satisfied nor
dissatisfied
Satisfied
Very satisfied
Satisfaction with influence over
work
Very dissatisfied
Dissatisfied
Neither satisfied nor
dissatisfied
Satisfied
Very satisfied
Female
Aged less than 20
Aged 20-24
Aged 25-29
Aged 30-39
Aged 40-49
Aged 50-59
Aged 60 or more
No educational qualification
Has at most O levels
Has at least A-levels
Disabled
Whole
sample
Covered
Members
Covered
NonMembers
Non
Covered
Members
23,601
5721
3,487
3,854
Non
Covered
Non
Members
10539
12.12
28.42
23.74
13.54
29.99
22.24
10.22
27.45
25.2
13.1
29.42
23.04
11.63
27.56
24.31
32.11
3.61
31
3.24
34.1
3.03
30.19
4.25
32.72
3.78
4.65
10.52
21.64
6.64
13.18
24
4
9.76
20.06
5.16
11.54
19.28
3.64
9.04
21.75
48.84
14.34
45
11
51.53
14.64
48.29
15.73
50.03
15.53
8.59
12.86
20.55
11.9
15.94
21.65
6.04
11.08
20.03
10.7
14.41
22.19
6.94
11.3
19.6
44.16
13.83
40.17
10.34
46.45
16.41
40.34
12.36
46.81
15.36
3.23
12.12
25.97
4.91
16.03
26.13
1.95
9.98
27.52
4.58
13.81
27.24
1.95
9.98
27.52
47.49
11.19
47.99
4.74
7.39
12.66
28.24
24.78
18.01
4.20
24.80
26.86
36.34
5.95
44.45
8.48
34.97
1.17
2.93
10.17
30.96
30.58
20.77
3.42
30.59
26.67
29.02
8.40
49.94
10.6
60.57
5.03
7.66
13.40
26.55
24.50
18.30
4.56
22.31
30.37
36.90
4.50
44.53
9.83
49.49
0.85
3.66
11.35
30.77
30.60
19.33
3.43
23.28
21.19
45.67
5.98
49.94
10.6
50.50
7.78
10.84
14.15
26.50
19.94
16.05
4.74
23.01
27.75
36.96
5.10
22
Nonwhite
Has children
Married
Manager
Professional
Associate professional and
technical
Clerical and secretarial
Craft and skilled service
Personal and protective service
Sales
Operative and assembly
Other occupations
Job equally done by men and
women
Availability of family friendly
policies
Can take day off if needed
Overtime always paid
Open ended contract
At leats 10 days of training in the
past year
Paid less than £50 per week
Paid £51-£80 per week
Paid £81-£140 per week
Paid £141-£180 per week
Paid £181-£220 per week
Paid £221-£260 per week
Paid £261-£310 per week
Paid £311-£360 per week
Paid £361-£430 per week
Paid £431-£540 per week
Paid £541-£680 per week
Paid more than £681 per week
Total hours worked on average
week
10 thru 24 employees
25 to 49 employees
50 to 99 employees
100 to 199 employees
200 to 499 employees
500 or more employees
East Anglia
East Midlands
London
North
North West
Scotland
3.54
53.24
69.93
9.18
11.25
8.13
3.39
59.90
77.02
5.50
8.50
7.77
3.64
55.08
69.04
6.93
9.79
6.02
3.86
60.24
76.91
7.14
23.49
15.10
3.48
46.92
64.23
12.44
9.14
6.69
17.80
10.77
11.20
9.24
12.96
9.48
29.77
17.70
16.03
8.99
4.02
22.08
9.41
26.64
31.21
7.22
12.15
8.88
7.15
10.65
30.70
7.90
10.63
12.78
4.63
12.59
5.75
31.53
17.04
9.14
11.55
13.58
10.06
10.37
30.55
51.63
52.71
59.59
54.15
47.85
97.13
45.82
92.87
8.79
97.40
54.76
96.88
9.92
98.24
39.59
86.00
7.87
94.07
42.08
94.11
12.30
97.65
44.24
92.45
7.35
6.90
6.99
12.28
8.90
11.42
10.56
10.03
8.35
9.93
7.53
3.77
3.36
36.01
1.77
2.89
8.02
6.20
13.26
13.17
13.71
12.72
13.94
8.43
3.64
2.25
38.43
10.17
10.67
16.86
8.93
11.89
10.30
8.06
6.57
6.90
5.32
2.30
2.03
31.74
1.81
3.36
8.09
8.57
10.08
10.18
11.32
9.55
17.00
12.12
5.10
2.81
38.29
10.25
9.21
14.48
10.41
10.74
9.39
8.27
6.21
6.44
6.23
3.85
4.52
35.29
4.58
8.66
9.83
7.00
9.99
10.40
18.54
8.45
4.35
9.86
8.35
14.14
3.32
8.19
7.81
12.67
11.93
14.38
10.64
9.16
4.35
8.96
8.58
6.42
6.27
11.17
8.69
6.82
7.89
12.04
19.13
8.23
3.00
10.11
6.66
11.62
3.78
7.89
10.62
6.91
12.30
10.00
14.89
6.38
6.58
13.33
7.31
10.89
4.99
8.40
10.96
4.12
8.86
7.96
23.67
8.82
4.02
9.12
9.09
19.98
23
Rest of the South East
South West
Wales
West Midlands
Yorkshire & Humberside
Manufacturing
Electricity, gas water
Construction
Wholesales and retail
Hotels and restaurants
Transports and communication
Financial services
Other business and services
Public administration
Education
Health
Other community services
Share female employees
Share part time employees
Share high skilled employees
Share medium skilled employees
Share low skilled employees
TTWA unemployment rate > 5
percent
Single establishment
Publicly owned establishment
Establishment older than 20 years
14.95
14.61
20.32
23.65
12.33
24.16
0.64
3.09
14.83
4.09
6.00
4.16
8.38
8.77
10.25
12.42
3.20
48.31
25.35
8.36
31.75
59.89
50.28
9.27
14.08
25.11
38.70
6.41
32.18
1.53
2.37
6.29
0.95
12.32
4.42
2.15
17.78
7.18
10.23
2.59
37.62
17.07
6.85
31.89
61.27
57.87
12.10
15.97
20.68
31.35
8.27
15.92
0.92
2.32
13.22
2.40
4.55
7.28
3.20
14.56
18.07
14.14
3.43
55.63
29.71
7.76
31.27
60.97
44.57
14.75
14.65
22.58
28.90
8.24
21.29
0.63
3.08
6.41
1.40
4.91
3.55
2.77
11.53
19.43
23.21
1.79
52.76
26.72
6.60
43.06
50.34
57.42
18.83
14.47
16.98
11.75
17.98
23.38
0.10
3.70
22.52
7.11
3.49
3.28
15.03
1.42
6.52
9.54
3.91
50.24
27.91
9.91
28.14
61.95
45.72
23.80
30.55
51.14
10.23
45.89
65.40
17.08
52.70
57.19
16.46
52.79
61.74
35.30
8.63
38.43
24
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Table 1: The effect of union membership on job satisfaction: estimates from models that treat both membership and coverage as exogenous
Satisfaction with Pay
Satisfaction with
Satisfaction with
Satisfaction with sense
influence over work
respect from managers
of achievement
Whole sample
Union coverage
No union coverage
-0.003
-0.003
-0.003
(0.003)
(0.003)
(0.004)
-0.073
-0.061
-0.078
*** (0.010)
*** (0.015)
*** (0.014)
-0.075
-0.065
-0.076
*** (0.010)
*** (0.014)
*** (0.014)
-0.071
-0.073
-0.063
*** (0.010)
*** (0.014)
*** (0.013)
Notes: Reported are marginal effects associated with the union member dummy variable in ordered probit regressions of job satisfaction. The effect refers to the
shift in the probability of being ‘Very satisfied’ or ‘Satisfied’ associated with a change in the membership indicator from 0 to 1. The number of observation is
23,601 in the whole sample , of which 9,208 in the sample of occupations covered by union bargaining and 14,393 in other occupations Robust standard errors in
parentheses; ***, **, and * denote statistical significance at the 1, 5 and 10 percent confidence level. Regression uses survey weights. For each of the models
estimated, the hypothesis that regressors have no explanatory power is rejected with a p-value of 0.0000. The variables used as regressors are: gender, age
dummies, education dummy, ethnicity, marital and parental status, disability status, occupational dummies, indicators for training, gender segregation in the job,
whether the employment relationship is fixed term, whether overtime hours are always paid, the availability of family friendly policies and the possibility to take
days off when needed, weekly pay and weekly hours, industry, establishment size, region, workforce composition and the unemployment rate in the relevant
travel to work area.
Table 2: Propensity score estimates of the membership/satisfaction differential
Satisfaction with Pay
Satisfaction with
influence over work
Whole sample
Union coverage
No union coverage
-0.032
-0.034
-0.035
*
(0.064)
(0.178)
(0.185)
-0.078
-0.088
-0.098
*** (0.000)
*** (0.000)
*** (0.000)
Satisfaction with
respect from managers
-.087
-.056
-.079
*** (0.000)
** (0.030)
*** (0.001)
Satisfaction with sense
of achievement
-0.081
-0.071
-0.046
*** (0.000)
*** (0.003)
** (0.021)
Notes: mean differences in satisfaction across members and their matched non-member counterparts where satisfaction is measured as being ‘Very satisfied’ or
‘Satisfied’. Asymptotically robust p-values in parentheses; ***, **, and * denote statistical significance at the 1, 5 and 10 percent confidence level. Matching
uses survey weights. Whole sample N=13,741 (9422 members and 4319 non-members). Covered employees N=7422 (5522 members and 1900 non-members).
Uncovered employees N=5685 (3746 members and 1939 non-members). The reason why the sums of uncovered employees and covered employees does not
equal the base for the whole economy is that matching is undertaken for each of the three samples – whole economy, covered employees and uncovered
employees – producing different matched samples.
28
Table 3: The effect of union membership on job satisfaction: estimates from models with endogenous union membership
and exogenous union coverage
Whole sample
Union coverage
No union coverage
Marginal effect of union membership
dummy in equation for job satisfaction
with
Influence over work
-0.156 *** (0.029)
-0.065
(0.149)
-0.159 *** (0.037)
Respect from supervisors
-0.163 *** (0.031)
-0.142 ** (0.065)
-0.163 *** (0.041)
Sense of achievement derived from
work
-0.145 *** (0.030)
-0.046
(0.215)
-0.160 *** (0.036)
Correlation of unobservables across
equations for union membership and
job satisfaction with
Influence over work
Respect from supervisors
Sense of achievement derived from
work
0.156
0.151
***
***
(0.044)
(0.050)
0.006
0.181
(0.298)
(0.183)
0.139
0.140
**
**
(0.054)
(0.061)
0.123
***
(0.045)
-0.040
(0.326)
0.156
***
(0.052)
Notes: Results are derived from a simultaneous equations model for job satisfaction and union membership. Reported are marginal effects
associated with the union member dummy variable in job satisfaction equations, and the cross-equations correlations of the errors. The effect
refers to the shift in the probability of being ‘Very satisfied’ or ‘Satisfied’ associated with a change in the membership indicator from 0 to 1. The
number of observation is 23,601 in the whole sample , of which 9,208 in the sample of occupations covered by union bargaining and 14,393 in
other occupations Robust standard errors in parentheses; ***, **, and * denote statistical significance at the 1, 5 and 10 percent confidence level.
Regression uses survey weights. For each of the models estimated, the hypothesis that regressors have no explanatory power is rejected with a pvalue of 0.0000. The variables used as regressors for job satisfaction are the ones indicated in Table 1. Regressors for the union membership
equation are: gender, age dummies, education dummy, ethnicity, marital and parental status, disability status, occupational dummies, industry,
establishment size, region, workforce composition and the unemployment rate in the relevant travel to work area, a dummy for establishment age
larger that 20 years, and indicators for whether the establishment is stand-alone or publicly owned.
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Table 4: The effect of union membership on job satisfaction : estimates from models that treat both
membership and coverage as endogenous.
(1) Model for job satisfaction with influence over work
Effect of union membership dummy on job satisfaction
If union coverage
If no union coverage
Correlations of unobservables in model of satisfaction with
influence over work across equations for
Membership and Coverage
Coverage and satisfaction if union coverage
Membership and satisfaction if union coverage
Coverage and satisfaction if no union coverage
Membership and satisfaction if no union coverage
(2) Model for job satisfaction with respect from supervisors
Effect of union membership dummy on job satisfaction
If union coverage
If no union coverage
Correlations of unobservables in model of satisfaction with respect
from supervisors across equations for
Membership and Coverage
Coverage and satisfaction if union coverage
Membership and satisfaction if union coverage
Coverage and satisfaction if no union coverage
Membership and satisfaction if no union coverage
(3) Model for job satisfaction with sense of achievement from work
Effect of union membership dummy on job satisfaction
If union coverage
If no union coverage
Correlations of unobservables in model of satisfaction with across
equations for
Membership and Coverage
Coverage and satisfaction if union coverage
Membership and satisfaction if union coverage
Coverage and satisfaction if no union coverage
Membership and satisfaction if no union coverage
0.058
-0.132
(0.094)
*** (0.040)
0.343
0.204
-0.143
0.110
0.119
*** (0.027)
** (0.090)
(0.120)
* (0.064)
** (0.055)
0.031
-0.066
(0.087)
(0.050)
0.343
0.176
-0.112
0.211
0.042
*** (0.027)
** (0.076)
(0.111)
*** (0.072)
(0.064)
-0.002
-0.096
(0.0875)
** (0.041)
0.343
0.106
-0.078
0.134
0.087
*** (0.027)
(0.085)
(0.112)
** (0.065)
* (0.050)
Notes: Results are derived from the simultaneous equations model for job satisfaction, union membership and union
coverage. Models estimated by maximum simulated likelihood, using a GHK simulator with 50 Halton draws.
Reported are marginal effects associated with the union member dummy variable in job satisfaction equations that
switch according to coverage, and the cross-equations correlations of the errors. The effect refers to the shift in the
probability of being ‘Very satisfied’ or ‘Satisfied’ associated with a change in the membership indicator from 0 to 1.
The number of observation is 23,601. Robust standard errors in parentheses; ***, **, and * denote statistical
significance at the 1, 5 and 10 percent confidence level. Regression uses survey weights. For each of the models
estimated, the hypothesis that regressors have no explanatory power is rejected with a p-value of 0.0000. The
variables used as regressors for job satisfaction are the ones indicated in Table 1, those for the membership equation
are indicated in Table 3, and the coverage equation uses the same set of regressors as the membership one.
30