The impacts of racial and religious diversity on
union participation in the United Kingdom.
Adam Azraei bin Nadzri
Abstract:
The purpose of this paper is to investigate the correlation between diversity and union participation in the
United Kingdom by using the Quarterly Labour Force survey from the Office of National Statistics. The
measure of diversity used in this paper were race, religion and religiosity. Race, religion and religiosity
had positive effect on union participation at an individual level but only religiosity had a negative effect
in the regional level. There is also a U-shape graph when observing union participation and atheism,
proposing that diversity should not be measured in binary or categorical terms but in ordinal terms with
relation to others. In conclusion, there is a statistically significant relationship between diversity and
union participation.
Introduction
The purpose of this paper is to understand the impacts of diversity on union participation in the United
Kingdom. According to the Calmford-Driffils hypothesis, a fully fragmented labour market or a fully
centralized wage setting environment similar to the Scandinavian Corporatist model would result in stable
macroeconomic labour structures that ensure low unemployment (Layard et. Al., 2005). Ever since
Thatcher’s union busting legislation took its toll on union membership, union density as a percentage of
the workforce in the UK has been progressively decreasing. Visser brought in arguments such as
macroeconomic conditions as the reason for the union membership decrease (Visser, 2002), while Toubøl
and Jensen brought in the idea that workplace union density acts as pressure for people to join unions
(Toubøl and Jensen, 2014).
The purpose of this paper is to investigate whether unions are dependent on issues pertaining to race.
Schnabel and Wagner had analysed that union membership is strongly related to personal characteristics
(Schnabel, 2002; Schnabel and Wagner, 2007) According to the Office for National Statistics, union
participation as a percentage of the labour force has been declining since 1995, as can be seen in Figure 1.
In the recent 2015 report by the ONS, one of the key findings was that non-UK nationals were less likely
to participate in trade unions (ONS, 2016). This is an interesting development as it brings up the question
of whether an increase in diversity brought through immigration results in a negative impact on union
participation, reducing the bargaining power of unions, opening up implications towards inequality and
the wage setting in workplaces that are influenced by collective action.
Figure 1
Olson described union participation and retention using social custom theory in which members
encourage union membership through negative reinforcement and punishment (Olson, 1965). Workers are
compelled to join unions as to comply with norms in the fear of being ostracised in their community.
However, Booth and Chatterji (1993) has shown that there is a minimum level of unionisation in which
the reputation effect will not work. There are two hypotheses that could explain the impacts of diversity in
reducing the reputational effect. Firstly, a more diverse environment would create newer norms in which
the community could not punish collectively. Thus, reducing the cost of non-membership and reducing
union participation. Secondly, an increase in diversity would mean that the share of unionised members
from the total workforce has been diluted by an increase in immigrants who are not unionised. This is a
likely hypothesis as, as can be seen from Figure 1, union membership has remained at a constant level as
the workforce continues to grow in the UK.
Description of variables and data sets
I have used the data sets from the UK Quarterly Labour Force Survey from 2002 to 2014. To measure
union participation, I have used the response to the question ‘Are you a member of a trade union or staff
association?’. As I am not interested in labour participation in general and am only interested in the
proportion of unionisation in the labour force, I have removed cases in which the question does not apply
to the respondents and missing cases. To measure diversity, I have used three different measures which
are race, religion and religiosity. The proxies that I chose are proportion of the majority race, proportion
of majority religion and proportion of atheism. Further calculation method is described in Table 1. The
reason that I am observing just the majority race and not segmenting the nationalities is to test the effects
of physical diversity on union participation. The reason for testing the majority religion was to see if there
is a correlation of identifying with a common religion with identifying with a union. Lastly, the reason for
using atheism is to measure religiosity. The assumption is that being an atheist acts as a dummy proxy for
not participating in a religious community, a more probable and consistent measure of low religiosity.
I am interested in two levels which are the individual level and the regional level.
At an individual level, I used a Probit model to determine the likelihood of being unionised given the
characteristics of the respondent. Table 1 describes all the variables that I have taken account in the Probit
model. The Probit model that I am estimating is given in the equation below:
Pr (UnionParticipation = 1|Race, Religion, Atheist, Public, Manual, Qualifications)
= 𝐺(𝛽0 + 𝛽1 Race + 𝛽2 Religion + 𝛽3 Atheist + 𝛽4 Public + 𝛽5 Manual + 𝛽6 Qualifications + 𝑢)
(1)
At the aggregate level, I am interested in the effects of the environment on union participation. By using
different regions of the United Kingdom outlined by the Labour Force Survey, I have created a Fixed
Effects model to understand the relationship between union participation against the various measures of
diversity. Table 1 describes the variables that I have taken into account. Below shows the equation that I
am modelling:
𝛥UnionRateit = 𝛽1 𝛥Diversity + 𝛽4 𝛥PublicPercent it + 𝛽5 𝛥ManualPercent it + 𝛽5 𝛥QualificationsPercent it + 𝑢it
(2)
‘Diversity’ covers three different measures of diversity which are: proportion of majority race, proportion
of majority religion and proportion of atheism. These measures could not be regressed simultaneously due
to endogeneity between the other regressors. Although including them would hold those characteristics
constant, we would need to understand how one measure of diversity affects the others in order to get the
full effect of the measure of diversity. However, one would argue to just regress it all together but it
would be inaccurate since the variations in race and religion are not enough to do such regression and
would render the effect insignificant when in fact there is a correlation between an increase in diversity
with the union participation rate. It would be more sensible to regress individually and just acknowledge
the biasness that arises when including other forms of measures of diversity until we would obtain a
larger sample with more variations in the data. A sensible decision would be to compare the R2 of each
regression and choose the measure with the highest R2 as the instrument to measure diversity.
TABLE 1
Variables and Measurement
Variable
Label
Measurment (values)
Union
Race
Religion
Atheist
Public
Manual
Qualifications
yes (1); no (0)
white (1); non-white (0)
christian (1); non-christian (0)
yes (1); no (0)
yes (1); no (0)
yes (1); no (0)
yes (1); no (0)
Union participation rate
Union Rate
Proportion of White Workers
Race Percent
Proportion of Christian Workers
Christian Percent
Proportion of Atheist Workers
Atheist Percent
Proportion of Public Sector Workers
Public Percent
Proportion of Manual Workers
Manual Percent
Proportion of Workers with Qualifications Higher than NQF Level 4
Qualifications Percent
Employed members as a share of employed wage and salary
earners
Employed white employee as a share of employed wage and
salary earners
Employed Chrisitan employee as a share of employed wage
and salary earners
Employed Atheist employee as a share of employed wage and
salary earners
Employed public sector employee as a share of employed wage
and salary earners
Employed manual-based employee as a share of employed
wage and salary earners
Employed employee with Level 4 Qualifications or higher as a
share of employed wage and salary earners
A: Individual-level data
Union participation
Race
Religion
Atheist
Public Sector Worker
Manual-based Occupation
Qualifications Higher than NQF Level 4
B: Regional aggregates
There are three things that I have included in the regression to be held constant with union participation.
One of them is the proportion of manual workers, as manual workers tend to be highly unionised. I have
used the NS-SEC measure to obtain the proportion of manual workers. Another variable is proportion of
public workers. Lastly, I have included education level as I presumed that higher educated individuals are
less likely to be unionised. For education, I have obtained the proportion of individuals obtaining an NQF
Level 4 and above qualification as being a dummy variable for having higher education.
The 2015 Data Set
In understanding the current demographic of the UK, I have used the 2015 Quarterly Labour Force
Survey to see if there is any pattern within the UK area.
In 2015, by observing different areas of the UK using the same data set, it is interesting to note that there
is a Northern Bias when it comes to union participation. However, what is interesting inside the data is
that atheism does not have a strong effect in decreasing union participation. Despite having higher levels
of atheism in the West Midlands, union participation was still just as high in West Yorkshire and the Rest
of the Northeast. There are two hypotheses that I would like to propose. Firstly, union participation is not
religion specific. We might expect that being part of a union would mean the person was brought up in a
community of high religiosity that promotes community engagement. But as we can see here, this is not
the case. In places where measures of religiosity were low (higher atheism), the same level of union
membership can be maintained.
Another hypothesis that I would like to propose is that union participation may be U-shaped when
measuring diversity. From the graph, high union participation is observed at the ends, which represents
two type of homogeneity. As religiosity decreases, union participation may begin to decrease, but as the
proportion of those areligious communities increases, a new community develops. If it is rational to be in
a trade union, we would see that despite not being active in a community, the self-encouragement of
people similar to you would encourage union participation within that particular group, in line with
Olson’s theory of social customs.
Figure 2
In the cross-sectional view of Christians and white ethnicity, not much can be said other than a reduction
in the proportion of being white and Christian is correlated with lower union participation. We can use the
ideas brought forward through social customs theory to explain the decrease. Another possibility is that
the number of trade union members has remained constant or rather has not kept up with the increase in
the labour force via market liberation and immigration.
Figure 3
Figure 4
Before running the regression, an important factor to include that differs from one region to another is the
effect of education and manual workers. As can be seen, there is a negative relationship between the
proportion of highly-educated individuals and trade union membership. The ONS reports that the
unionised workforce are less likely to be manual workers and have lower forms of qualifications. Despite
what the ONS reports, I have found that regions with higher proportions of manual workers are more
likely to be unionised. This disparity between the report of the ONS and my study may be a result of the
historical context of those regions. Regions with a higher proportion of manual workers would
historically have higher levels of community-centric behaviour despite the workers not being unionised.
As I am just observing the correlations between averages and the ONS is observing individual data in
joining unions, this disparity may not be contradictory at all, as there may be effects of historical norms
just as proposed by Olson.
Figure 5
There is no clear correlation despite being a negative trend with education. Removing outliers of Central
and inner London, we can see that the effects of education is not really that clear.
Figure 6
A probit regression analysis for individual decision of union
participation
TABLE 2
Determinants of probability of joining unions in 2015 (probit)
No of observations: 35,343
Constant
Diversity Variables
Race
Religion
Atheist
Background Variables
Public Sector Worker
Manual-based Occupation
Qualifications Higher than NQF Level 4
- 1.4044 *
Beta
t-values
Average Marginal Effect
0.07676 *
0.2064 *
0.09446 *
2.46
5.36
2.39
0.01929
0.05188
0.02374
69.78
- 0.95
9.18
0.3055
- 0.004721
0.03974
1.216 *
- 0.1879
0.1581 *
* significant at 0.05 level
Observing at an individual level, all the measures of diversity are statistically significant. However as
described in the previous section in observing atheism on the impacts of union participation, there is a
positive correlation between being an atheist and being part of a union. This would provide some
evidence to reject that union participation is based on religiosity. However, religion is still relevant in
determining the likelihood of union participation with respondents professing Christianity being highly
likely to join unions. It is interesting to note that the effects of being white on union participation are not
as strong as being a Christian, which would mean physical appearance is less likely to be an impediment
to union participation. This hypothesis is supported in the ONS 2015 Trade Unions Report, showing that
those who identify as Black British account for the second largest proportion of union members after
those who identify as White British.
Despite the previous regional diagram showing a correlation between areas with high manual workers and
union participation, the probit analysis of individual decision to join unions shows that there is not a
strong correlation between being in a manual-based occupation and the likelihood of joining unions. We
would argue for the relevance of controlling for manual-based occupation due to the fact that manualbased occupations have different effects at regional and individual levels, therefore it should still be a
relevant variable to be put into the UK context.
A pooled regression analysis of the British Unionization trends
TABLE 3
Impacts of diversity on union density (fixed effects)
No of observations: 20 x years = 280
Dependent Variable
Change in density level
Ethnicity
Coefficients t-values
Intercept
Proportion of White Workers
Proportion of Christian Workers
Proportion of Atheist Workers
Proportion of Public Sector Workers
Proportion of Manual Workers
Proportion of Workers with Qualifications Higher than NQF Level 4
2
- 0.0447
0.2307 *
0.5900 *
0.1449 *
- 0.1874 *
0.6641
- 0.62
3.24
10.80
3.81
- 7.10
Measures of diversity
Religion
Religiosity
Coefficients t-values
Coefficients t-values
0.05926 *
2.14
0.1815 *
0.1231 *
5.58
0.4640 *
0.2045 *
- 0.05466
7.97
5.64
- 1.40
0.6882
- 0.1066 *
0.4847 *
0.2081 *
- 0.09839 *
10.68
-
-
4.81
8.24
5.61
2.73
0.6793
* significant at 0.05 level
From the results of regressing the different measures of diversity respectively, we can see that all the
measures of diversity are statistically significant. At an aggregate level, we can observe that atheism has
the reverse effect when regressing over time. This further complicates things as it may show that union
participation is a function of not only individual rationality but also the characteristics of those around the
individual. At a regional level, religion predicts better the model of diversity with union participation with
an R2 of 0.6882.
However, an interesting fact is that there is a change in the sign of the coefficient for the proportion of
atheism. From the probit model, there is a higher probability for the respondent to join a trade union
compared to if the respondent was not an atheist.
Two factors can help explain this inconsistency. Firstly, it is important to understand what each regression
is measuring. The probit model explains the correlation of the likelihood of being unionised against being
an atheist while the fixed effects model is modelling the regional choice rather than the individual choice.
From Figure 2, we can observe that in regions with higher proportions of atheism, the proportion of those
professing Christianity and the proportion of white ethnicity are lower. However, from the same figure,
the correlation between being in an atheist community and union participation is very near to 0. Thus, just
by observing these two results, we can see that the sign change in coefficients is to be expected.
One thing to note is that being a Christian captures a large portion of the effects of having better
qualifications in the workforce. Again, as shown in the fixed effects model above, there is a statistically
significant positive relationship between manual workers and union participation at a regional level.
Conclusions
In conclusion, there are negative relationships at an individual level and at a regional level in being white
and Christian towards the likelihood of being in a union. However, when observing other forms of
diversity such as religiosity, this relationship slowly breaks down. It is important to note that the measures
of diversity that I have been using are binary. Measuring diversity would be a complex issue to address as
diversity would depend not only on how one views others on a relational basis but also on how others
view one as well. A mathematical solution to this would be to use an index or a vector system to measure
relational individual diversity while adding coefficients to signify certain aversion or preferences in
diversity. A diversity index which incorporates all those measures of diversity would also avoid
collinearity when regressing all the measures of diversity together. The first step in overcoming this
problem is to statistically measure diversity in an ordinal manner instead of the nominal method of
measuring diversity in data collecting. Secondly, research in diversity would need more cross-discipline
integration in order to make decision-making more relevant in the human context. The need to understand
human decision beyond the rational utility-maximising model is pivotal to develop new laws, regulations
and mechanism that would benefit society.
The results I have obtained are limited to the UK. It would be interesting to observe in the European
context especially in Scandinavian countries in which wage centralisation is an integral part of the
economy. One more external factor that I have yet to include is the impact of market liberation. Market
liberation may affect the increase in diversity in the workplace as well as the weakening of trade union
power. It is very difficult to measure openness to trade at a regional level. However, we can observe the
effects of market liberalisation when conducting cross-country studies in the future. However, despite of
these setbacks, the results are still significant and does show some form of correlation that should be
continued and explored to understand the dynamics of union participation. For the purpose of policymaking, immigration affects more than just efficiency and output. It is important to note that there are
evidence to show that trade unions do help in combatting inequality in the economy (Chauvel and
Schröder, 2017). There is much that is needed to be understood on the types of diversity how it impacts
certain labour market structures in order for policy-making to be beneficial towards society.
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