Department for Work and Pensions
Research Report No 483
The business case for
Equal Opportunities: An
econometric investigation
Rebecca Riley, Hilary Metcalf and John Forth
A report of research carried out by the National Institute of Economic and Social
Research on behalf of the Department for Work and Pensions
© Crown Copyright 2007. Published for the Department for Work and Pensions
under licence from the Controller of Her Majesty’s Stationery Office.
Application for reproduction should be made in writing to The Copyright Unit,
Her Majesty’s Stationery Office, St Clements House, 2-16 Colegate, Norwich NR3 1BQ.
First Published 2008.
ISBN
978 1 84712 349 7
Views expressed in this report are not necessarily those of the Department for
Work and Pensions or any other Government Department.
Contents
Contents
Acknowledgements.......................................................................................... vii
The Authors......................................................................................................viii
Abbreviations..................................................................................................... ix
Summary............................................................................................................1
1 Introduction..................................................................................................5
1.1
Background........................................................................................5
1.1.1
Diversity Management versus Equal Opportunities . .............6
1.1.2
Research evidence on the aggregate effects on business .......
performance........................................................................6
1.2
The aims and scope of the study.........................................................8
1.3
Key issues...........................................................................................9
1.4
Limitations of the study....................................................................10
1.5
The structure of the report................................................................11
2 Equal Opportunities policies and practices...................................................13
2.1
Introduction......................................................................................13
2.2
Equal Opportunities policies, practices and effectiveness...................13
2.3
Measures of Equal Opportunities policies and practices.....................15
2.4
2.3.1
Introduction.......................................................................15
2.3.2
Individual and conglomerate variables................................16
2.3.3
Variable choice for the study..............................................17
2.3.4
Selection process................................................................21
Factors affecting the adoption of Equal Opportunities policies .........22
iii
iv
Contents
3 The business benefits of Equal Opportunities policies and practices.............25
3.1
Introduction . ...................................................................................25
3.2
Potential business benefits of Equal Opportunities policies and
practices...........................................................................................26
3.3
3.2.1
Improved recruitment.........................................................28
3.2.2
Enhanced staff utilisation: matching employees and jobs....28
3.2.3
Enhanced staff utilisation: family-friendly working .................
practices.............................................................................29
3.2.4
Morale and employee commitment....................................29
3.2.5
Greater employee diversity.................................................30
3.2.6
Shareholder approval.........................................................31
The costs of implementing Equal Opportunities
policies and practices........................................................................31
4 Identifying the effect of Equal Opportunities on business
outcomes using WERS 2004.......................................................................35
4.1
The basic identification problem.......................................................35
4.2
Identification strategy.......................................................................36
4.3
Modelling business performance.......................................................38
4.4
4.5
4.3.1
Measuring business performance in WERS 2004.................38
4.3.2
Estimating models of business outcomes in WERS 2004.....41
Modelling treatment selection..........................................................46
4.4.1
Models of Equal Opportunities...........................................46
4.4.2
Instrumental variables.........................................................51
Summary..........................................................................................52
5 Estimates of the relationship between Equal Opportunities
and business outcomes using WERS 2004...................................................53
5.1
Sample correlations between Equal Opportunities
and business performance................................................................53
5.2
Estimates of the effects of Equal Opportunities
on business performance..................................................................58
5.2.1
Workplace performance and Equal
Opportunities policies . ......................................................58
Contents
5.2.2
Workplace performance and Equal Opportunities
monitoring and reviewing practices ...................................64
5.2.3
Workplace performance and Equal Opportunities
practices concerning ethnic background . ..........................71
5.2.4
Workplace performance and family-friendly practices ........75
6 Summary and conclusions...........................................................................87
6.1
Introduction......................................................................................87
6.2
Linkages between Equal Opportunities policies
and practices and business performance...........................................87
6.3
Limitations of the evaluation of the impacts of
Equal Opportunities policies and practices on business
performance using WERS 2004.........................................................88
6.4
Evidence of the effects of Equal Opportunities policies and
practices on business performance using WERS 2004.......................89
6.5
Policy implications.............................................................................90
6.6
6.5.1
Regulation..........................................................................90
6.5.2
Changing the net costs: subsidies and penalties..................90
Further research................................................................................91
Appendix A The possible routes to business benefits of Equal
Opportunities policies and practices.............................................93
Appendix B Descriptive statistics on Equal Opportunities policies
and practices...............................................................................95
Appendix C Notes to Tables 5.2-5.8..............................................................103
References......................................................................................................105
List of tables
Table 2.1
Table 4.1
Table 4.2
Table 4.3
Table 5.1
Table 5.2
Equal Opportunities policy and practice variables analysed
and their incidence......................................................................21
The incidence of Equal Opportunities policies and
practices in UK workplaces..........................................................40
Models of business performance.................................................43
Models of Equal Opportunities selection......................................47
Difference in business performance between establishments
with and without Equal Opportunities policies/practices...............55
Estimated workplace performance effects of having a formal
written policy on Equal Opportunities or managing diversity........61
vi
Contents
Table 5.3
Table 5.4
Table 5.5
Table 5.6
Table 5.7
Table 5.8
Table B.1
Table B.2
Table B.3
Table B.4
Estimated workplace performance effects of reviewing
promotion procedures or relative pay rates to identify
indirect discrimination..................................................................65
Estimated workplace performance effects of measuring
the impacts of Equal Opportunities policies in the workplace.......68
Estimated workplace performance effects of reviewing
recruitment or promotion procedures or relative pay rates to
identify indirect discrimination on the grounds of
ethnic background.......................................................................72
Estimated workplace performance effects of working time
arrangements that include working from home in
normal working hours.................................................................76
Estimated workplace performance effects of arrangements
where time off for family emergencies is usually taken
as special paid leave....................................................................80
Estimated workplace performance effects of arrangements
where time off for childcare is usually taken as special
or parental paid leave..................................................................84
Presence of Equal Opportunities policies and/or practices
(percentage of workplaces), by workplace characteristics.............96
Presence of Equal Opportunities policies and/or practices
(percentage of workplaces), by workforce compositions..............98
Presence of Equal Opportunities policies and/or practices
(percentage of workplaces), by workplace
performance outcome.................................................................99
Presence of equal opportunities policies and/or practices
(percentage of workplaces), by workplace
intermediate outcome...............................................................101
List of figures
Figure 2.1
Figure 3.1
Some potential routes to business benefits of
Equal Opportunities policies.........................................................14
Potential business benefits of effective Equal
Opportunities policies .................................................................27
Acknowledgements
Acknowledgements
This research was funded by the Department for Work and Pensions (DWP). We
would like to acknowledge the support of Anthony Johnson and Liz Such who
managed this study for the DWP and of Lucy Stokes and Helen Bewley of the
Workplace Employee Relations Survey (WERS) Information and Advisory Service.
We are also grateful for John Purcell’s comments and helpful discussion with James
Mitchell.
We acknowledge the Department of Trade and Industry, the Economic and Social
Research Council, the Advisory, Conciliation and Arbitration Service and the Policy
Studies Institute as the originators of the 2004 Workplace Employment Relations
Survey data, and the Data Archive at the University of Essex as the distributor of
the data. The National Centre for Social Research was commissioned to conduct
the survey fieldwork on behalf of the sponsors. None of these organisations bears
any responsibility for the analysis and interpretations of the data here.
vii
viii
The Authors
The Authors
Rebecca Riley is a Research Fellow at the National Institute of Economic and Social
Research. Her research covers a variety of topics in applied labour economics. She
has undertaken several policy evaluation studies for government departments.
Hilary Metcalf is a Senior Research Fellow at the National Institute of Economic
and Social Research. She specialises in employment and social policy. Her main
research interests are in employers’ roles in affecting disadvantage in the labour
market and policies to address disadvantage.
John Forth is a Research Fellow at the National Institute of Economic and Social
Research. He works on a range of labour market issues, but has a particular interest
in the study of employment relations, with his work in this area having included
contributions to the design and analysis of the Workplace Employment Relations
Surveys (WERS).
Abbreviations
Abbreviations
ABI Annual Business Inquiry
ATT Average Treatment effect on the Treated
HRM Human Resource Management
WERS 1998
The 1998 Workplace Employee Relations
Survey
WERS 2004
The 2004 Workplace Employment Relations
Survey
ix
Summary
Summary
Aims and objectives
The main aim of the study was to try to identify whether Equal Opportunities
policies and practices affect business performance and, specifically, whether such
policies and practices affect productivity or profits.
The study aimed to:
• map out, conceptually, the relationship between business performance and
Equal Opportunities policies and practices;
• explore how the effects of Equal Opportunities policies and practices on
productivity and profits might be identified;
• evaluate the effects of Equal Opportunities policies and practices on productivity
and profits.
An important aspect of the study was to assess not only the links between Equal
Opportunities policies and practices but to try to assess, as far as possible, the
causal impacts of Equal Opportunities policies and practices.
Methods
The analysis was conducted using the Workplace Employment Relations Survey
2004 (WERS 2004), the latest in a series of matched employer/employee datasets.
The WERS series (and data linked to these) was the only British dataset which
provided the necessary data on Equal Opportunities policies and practices, other
management practices, productivity and profitability. The latest surveys not only
offered the most recent data for investigating the link but also a greater range of
data than previously.
The study examined a range of Equal Opportunities policies and practices: formal,
written Equal Opportunities policies (not informal); monitoring and reviewing
practices; formal assessment and modifications of workplace accessibility for
disabled people; flexible working arrangements; and leave (above the statutory
Summary
minimum) for family responsibilities. Full analysis of the business benefits of Equal
Opportunities policies and practices was confined to seven policies and practices.
The selection meant that the study covered practices directed at race and gender
equality in more detail, although the study does relate to all equality groups.
Two types of productivity and profits measures were examined: objective
(accounts-based) measures of labour productivity and profitability and subjective
measures of productivity and profitability (these were the managerial respondents’
assessments of the establishments’ performance relative to the industry average).
The subjective measures were used because objective data was available for only
a small number of cases in WERS.
A key issue for the analysis was causality. It cannot be assumed that if establishments
with Equal Opportunities policies and practices have higher productivity or profits,
that the former causes the latter. It is feasible that causality goes in the opposite
direction: that higher productivity or profits enable establishments to introduce
Equal Opportunities policies and practices (or increase the likelihood that they
do so). It is also possible that some other factor results in both better business
performance and the take-up of Equal Opportunities policies and practices.
Two main approaches were used to evaluate the effect of Equal Opportunities
policies and practices on productivity and profits: multivariate regression analysis
with instrumental variables and matched comparison analysis.
Understanding the relationship between Equal Opportunities
and business
The relationship between Equal Opportunities policies and practices and business
performance is complex:
• Policies and practices vary in the degree to which they are implemented and
affect equality of opportunity; and so in the extent to which they could affect
business performance (Section 2.2).
• Policies and practices incur costs, as well as benefits; the net benefit to an
organisation may be positive or negative, depending on the Equal Opportunities
practice, the organisation’s characteristics and its circumstances (Chapter 3).
• The route by which an Equal Opportunities policy or practice in an organisation
might affect business performance may be direct or indirect, affecting a set of
intermediate outcomes en route (Chapter 3).
• There is no reason to assume that different types of Equal Opportunities policies
and practices have the same effects on business performance or even that the
same type of Equal Opportunities policy has the same effect in different business
and organisational contexts (Chapter 3).
Thus, some employers may derive business benefits from Equal Opportunities
policies and practices, whilst others may not.
Summary
Main findings
Evidence of the effects of Equal Opportunities policies and
practices on business performance using WERS 2004 (Chapter 5)
It is difficult to argue that the business benefits of Equal Opportunities policies and
practices are large and widespread amongst the establishments who implement
these. However, we cannot rule out that certain Equal Opportunities practices
may be associated with enhanced workplace productivity:
• There are some statistically significant relationships between subjective business
performance and Equal Opportunities policies but these are unlikely to reflect
the causal impacts of policy.
• The evidence in the data for either a large or widespread impact, positive or
negative, of Equal Opportunities monitoring and reviewing practices on business
productivity or profits is not strong.
• To the extent there are any positive effects on business productivity or profits of
Equal Opportunities monitoring and reviewing practices these are more likely to
arise in larger establishments.
• There is some, but limited, evidence to suggest there are positive effects of
some family-friendly practices on business productivity and profits. To the extent
there are positive productivity (profit) effects these are more likely to arise in
smaller (larger) establishments.
• The evidence does not support the notion that Equal Opportunities policies and
practices place disproportionate burdens on business. In other words, Equal
Opportunities policies and practices do not appear to cost the private sector
profits.
• There is no evidence that Equal Opportunities policies and practices result in
a net cost (or benefit) to employers in aggregate (i.e. on average). However, it
is likely that some employers will derive net benefits from implementing Equal
Opportunities policies and practices and others will see a net cost.
Limitations of the evaluation of the impacts of Equal Opportunities
policies and practices on business performance using WERS 2004
The following limitations on the study should be borne in mind:
• The evaluation of policy is restricted to formal, written policies; this is likely
to obscure the effect of Equal Opportunities policies on business performance
(Section 2.3).
• The four outcome measures used (subjective and objective measures for both
productivity and profits) either have small sample sizes (the objective measures)
or are potentially unreliable (the subjective measures). Thus, the objective
measures are less likely to identify performance effects, whilst the subjective
measures suffer from reduced reliability of the findings (Section 4.3.1)
Summary
• The complexities of the linkages between Equal Opportunities policies and
practices and business performance, combined with data limitations, reduced
the likelihood of identifying accurately the effects of these policies and practices
(Chapters 2, 3, 4 and 5).
• Sample sizes in WERS 2004 are relatively small and this problem is accentuated
by the need to look at sub-samples of the data, due to measurement issues and
the correlation of policy with other factors affecting business outcomes. For
example, Equal Opportunities policies and practices are highly coincident with
workplace size and other factors that are correlated with business performance
such that subset analysis is to be preferred (Chapter 5).
Implications for policy and further research (Chapter 6)
Equality of opportunity in the labour market may bring economic and social
benefits. Notably, it can increase the supply of labour and improve the efficiency
with which human resources are used, reducing labour costs and raising aggregate
income. It may also help to reduce social inequalities. Individuals, society at large
and individual businesses may all share in these benefits. At the same time, the
evidence presented in this report suggests that, on average, individual employers
do not necessarily gain (nor lose) from implementing policies and practices to
promote equality of opportunity. The implication is that there is likely to be a
difference between the private (individual business) and public (society) costs and
benefits of Equal Opportunities policies and practices. In this situation, leaving
decisions to implement Equal Opportunities policies and practices entirely to
individual businesses (i.e. to the free market) is liable to result in fewer policies
and practices than would be best for society. Addressing this market failure might
lead to an increase in economic and social well-being. Two standard measures to
address market failure could be useful: regulation and changing the net costs to
employers, either through subsidies or penalties.
Regulation may require employers to undertake certain practices (e.g. equality
training, monitoring and reviewing, equality audits). Subsidies could be given for
specific practices and could be tailored to reach those more likely to encounter
business costs rather than benefits of these practices (although close identification
of this would be difficult). Penalties could be introduced through contract
compliance, although this would only affect employers who supply or contract to
the public sector.
The complexity of the route from Equal Opportunities policies and practices
to business performance made the identification of business benefits difficult.
Understanding of the linkage could be enhanced through research examining
shorter linkages, particularly from Equal Opportunities policies and practices to
the effect on equality in the workplace and the effect of policies and practices on
intermediate business outcomes, for example, morale.
Which includes individual businesses.
Introduction
1 Introduction
1.1
Background
Equality of opportunity in the labour market may have economic, as well as
social, benefits. Notably, it can increase the supply of labour and improve the
efficiency with which human resources are used, reducing labour costs and
raising aggregate income. However, whilst all businesses can benefit from these
macroeconomic effects, this need not mean that any individual employer would
benefit from improving equality in their own organisation: they may benefit from
the wider effects of others increasing equality but the costs of contributing to this
improvement may outweigh the returns to their own actions. This report focuses
on the net change in business performance associated with an employer’s own
actions.
In the early 1990s, there was a shift away from moral and social justice arguments
for Equal Opportunities to an emphasis on business self-interest (Dickens, 1998).
Encouraged by Government policy, a substantial literature has built up extolling
the business benefits of Equal Opportunities. It is claimed, for example, that
greater equality of opportunity within a particular business can reduce labour
shortages, improve employee commitment and morale, reduce turnover and
increase sales. Qualitative research shows that a range of benefits do occur but
the evidence suggests that benefits to a specific organisation are contingent on
that organisation’s characteristics and circumstances. At the same time, providing
equality of opportunity incurs administrative, management and training costs
(for example, costs of enhanced leave arrangements, recruitment process costs,
additional training, increased management and monitoring) and may have other
disbenefits (for example, reduced morale and commitment in the previously
advantaged group). It is, therefore, unclear, a priori, whether an individual
organisation will benefit from providing equality of opportunity. It is also unclear,
Equal Opportunities is used, variously elsewhere, to refer to equality of
opportunity in respect of gender alone or in respect of a range of characteristics
(gender, ethnicity, age, etc.). Throughout this report we use it in its wider
sense.
Introduction
therefore, whether, on average, organisations benefit from their own steps to
improve Equal Opportunities.
1.1.1
Diversity Management versus Equal Opportunities
Before proceeding any further it is helpful to bear in mind that Equal Opportunities
are not synonymous with Diversity Management. Kirton and Greene neatly
juxtapose definitions of Equal Opportunities policies and Diversity Management
to highlight the differences:
‘An Equal Opportunities policy can be defined as “a commitment to engage
in employment practices and procedures which do not discriminate, and
which provide equality between individuals of different groups or sex to
achieve full, productive and freely chosen employment“ (Lean Lim, 1996:
34). Whereas, the concept of ‘managing diversity’ is generally seen as
“proactively capitalizing on the different skills, qualities and viewpoints that
a diverse workforce has to offer“ (EOR, 1999a: 14).’
Kirton and Greene (2000: 178-9)
The essential difference is that Equal Opportunities is, as stated, about treating
people equally, whereas Diversity Management aims for a diverse workforce.
The latter may require treating some groups more favourably, if, for example,
those groups are under-represented in the labour market. (Note that Equal
Opportunities may also lead to differential treatment between groups, but this
reflects differences in needs and previous treatment between groups and is aimed
at levelling the playing field.) Thus, whilst, in practice, Diversity Management will
tend to encompass Equal Opportunities principles and practices (and so stay within
the law), the basic concept differs and, except where the required diversity reflects
the labour market, will conflict.
1.1.2
Research evidence on the aggregate effects on business
performance
A small number of studies have tried to address the question of benefits to business
in aggregate. These have examined the relationship between Equal Opportunities
policies, Equal Opportunities practices and family-friendly practices and various
aspects of business performance. Others have looked at intermediate outcomes
(such as the effects on employee commitment and employees’ perceptions of
fairness of treatment) which may feed in to improved business performance.
Equal Opportunities and business performance
Pérotin and Robinson (2000) found that in workplaces with a formal, written
Equal Opportunities policy, managers tended to perceive their labour productivity
as relatively high compared to similar workplaces without a policy, after controlling
for other factors. But, they also found that perceived levels of relative productivity
This is not to deny that employers may benefit from whole economy
effects.
Introduction
were lower in those establishments with an extensive range of monitoring and
review practices that supported Equal Opportunities. They suggested that this
latter result may illustrate short-term disruption arising from the introduction of
Equal Opportunities practices or adverse reactions from previously-advantaged
groups. Using a composite indicator of the strength of Equal Opportunities policies,
Dex, Smith and Winter (2001) found no association with business performance
measures, apart from with labour turnover which was higher amongst those
workplaces with stronger Equal Opportunities policies. Gray (2002) found negative,
positive and insignificant associations between business performance and a range
of Equal Opportunities practices.
Forth and Rincon-Aznar (2007) focused on Equal Opportunities with respect to
gender and examined links with perceived productivity and profits. Their analysis
had mixed results. They did not identify convincing links between policy and
productivity or profits, but found a negative correlation between productivity and
monitoring, as did Pérotin and Robinson (2000).
Dex, Smith and Winter (2001) and Gray (2002) examined a range of business
performance measures (e.g. productivity, financial performance, quality, sales and
labour turnover). Both found correlations (mainly positive) between a range of
family-friendly practices and performance measures.
Note that in the four studies discussed above, productivity and financial performance
are measured as managers’ subjective view of their establishment’s productivity
or profits compared with similar establishments. It is not clear whether these
findings on the relationship between Equal Opportunities and subjective measures
of business performance extend to the relationship between Equal Opportunities
and objective measures of business performance.
Equal Opportunities and employee commitment
Dex and Smith (2001) found a positive association between access to familyfriendly practices and commitment in the private sector but no association in the
public sector. Forth and Rincon-Aznar (2007) examined the effects of a range of
Equal Opportunities policies and practices on the commitment of each equality
group separately (e.g. women, men, ethnic minorities). They found no relationship
between having a written Equal Opportunities policy and commitment indicators, a
positive association between Equal Opportunities support practices (i.e. collecting
statistics or reviewing procedures) and commitment indicators but only for
traditionally advantaged groups and ethnic minorities. Whilst special recruitment
procedures were negatively associated with commitment indictors for employees
from disadvantaged groups. With this range of findings, it is difficult to conclude
that commitment and Equal Opportunities are positively correlated.
Objective measures were available for too small a sample in WERS 1998.
Introduction
Equal Opportunities and perceived fairness
Forth and Rincon-Aznar (2007) also considered the effect of a range of Equal
Opportunities policies and practices on perceived fairness (which may affect morale
and commitment). Their findings were mixed and some perverse, leading to no
real conclusions about the relationship, whilst Bryson (2000) found no relationship
between a workplace having a formal, written equal opportunities policy and
employees’ perceptions of fair treatment.
These studies seem to lend some support for the hypothesis that Equal
Opportunities in general, and family-friendly practices in particular, improve
business performance. However, the variation in findings for different Equal
Opportunities policies and practices and different performance measures reduces
confidence in this conclusion. Moreover, the methods used identify association and
not causality. It is plausible that Equal Opportunities practices are a consequence
of good business performance rather than vice versa (because good performance
provides the resources to implement Equal Opportunities practices). It is also
possible that other factors result in both Equal Opportunities policies and practices
and better business performance. It is, thus, important to try to address the issue
of causality.
1.2
The aims and scope of the study
The main aim of the study was to try to identify whether Equal Opportunities
policies and practices affect business performance and, specifically, whether such
policies and practices affect productivity or profits.
The study was to:
• map out, conceptually, the relationship between business performance and
Equal Opportunities policies and practices;
• explore how the effects of Equal Opportunities policies and practices on business
performance (namely, on productivity and profits) might be identified, taking
into account, as far as possible, potential reverse causality;
• evaluate the effects of Equal Opportunities policies and practices on business
performance (namely, on productivity and profits).
‘Equal Opportunities practices’ were defined as those activities which were
commonly aimed at improving equality of opportunity, rather than more
general practices which might also have this effect. Examples of the former
included Equal Opportunities monitoring and family-friendly practices.
Introduction
The analysis was to be conducted using the Workplace Employment Relations
Survey 2004 (WERS 2004), the latest in a series of matched employer/employee
datasets. The WERS series (and data linked to these) was the only British dataset
which provided the necessary data on Equal Opportunities policies and practices,
other management practices, productivity and profitability. The latest surveys,
WERS 2004, not only offered the most recent data for investigating the link, but
also a greater range of data than previously.
For the first time, WERS 2004, through the introduction of a financial performance
questionnaire and the linking with the Annual Business Inquiry (ABI), provided
objective (accounts-based) data on labour productivity and profitability. Previous
studies of the business benefits of Equal Opportunities used earlier versions of
WERS which only provided subjective measures of productivity and profitability
(these were the managerial respondent’s assessment of the establishment’s
performance relative to the industry average). A potential problem with the
new objective data was that the number of establishments in the sample with
comparable linked productivity and profits data was relatively small at around 650
(Forth and McNabb, 2007). This could potentially cause problems in identifying
business performance effects.
Moreover, WERS 2004 provided data on a larger range of Equal Opportunities
policies and practices than previously and so offered the opportunity for more
effective measures of Equal Opportunities policies.
The postcode information in WERS 2004 also allowed the linking with local area
characteristics data. This enabled modelling to take into account local labour
market characteristics which could impinge on the relationship between Equal
Opportunities and business benefits, for example, unemployment rates (affecting
labour shortages) and the ethnic composition of the labour force, which is of
relevance to Equal Opportunities with respect to race.
1.3
Key issues
A quantitative investigation of the relationship between Equal Opportunities
policies and practices and productivity and profits is complex.
Department of Trade and Industry (2005) Workplace Employment Relations
Survey: Cross-Section, 2004 [computer file]. 2nd ed. Colchester: The Data
Archive [distributor], April 2007. SN: 5294.
WERS 2004 covers all but the smallest workplaces in Great Britain. It covers
both private and public sectors and almost all areas of industry. The principal
unit of analysis is the establishment or workplace. A workplace is defined
as comprising the activities of a single employer at a single set of premises.
Around 2,300 workplaces took part in the 2004 Cross-section Survey. The
response rate for the Cross-section’s main management interview was
64 per cent.
10
Introduction
A key challenge is identifying causality. Suppose organisations with Equal
Opportunities policies have higher productivity. This may be because:
• Equal Opportunities policies improve productivity (i.e. Equal Opportunities
policies cause higher productivity);
• higher productivity allows organisations to adopt Equal Opportunities policies
(i.e. higher productivity causes the adoption of Equal Opportunities policies);
• other factors which tend to be found where there are Equal Opportunities policies,
improve productivity (i.e. there is no causal link between Equal Opportunities
policies and productivity) (e.g. high commitment management practices, and
not Equal Opportunities practices, may improve productivity and both types of
practice tend to be found in the same organisations).
The analytical techniques should try to throw as much light on causality as
possible. This requires factors which might be associated with the adoption of
Equal Opportunities policies and practices (as well as other factors which affect
productivity) to be identified.
A second difficulty arises from the likelihood that Equal Opportunities policies and
practices are merely part of a package of human resource policies and practices,
elements of which may be substitutes for each other, as well as acting independently
or jointly to affect productivity and profits. This can make it difficult to identify the
effect of Equal Opportunities on business performance (e.g. if Equal Opportunities
and high commitment management practices were always observed together and
never separately) and raises questions about which interactions should, if possible,
be taken into account in the analysis.
The problems of modelling interdependence are exacerbated by measurement
problems: survey data is limited in the extent to which it can capture the nature of
a policy or practice. The quality and effectiveness of each policy and practice will
vary across organisations. For example, it is well known that Equal Opportunities
policies range between merely a statement with no influence on the organisation
(the ‘empty shell’) to those driving a wide range of equality practices. Thus, each
Equal Opportunities policy or practice will differ between organisations and have
varying effects. Whilst these problems can be addressed to some extent, a large
degree of uncertainty remains in designing an appropriate model and which
data to use. These problems are further magnified by the range of other factors
which affect productivity and profits and which, similarly, may interact with Equal
Opportunities policies and practices.
1.4
Limitations of the study
It is worth highlighting a number of limitations of the study at this stage. These
are discussed in more detail within the report.
Introduction
• The study examined Equal Opportunities policies and practices. Practices related
to both formal and informal practices. However, the policies examined were
formal, written policies (whether an establishment had a formal written Equal
Opportunities policy and to which groups this referred). Some establishments
will have similar informal policies. The exclusion of informal policies will reduce
the extent to which effects of the policy can be identified (see Chapter 2).
• The effect on profits and productivity of a selection of Equal Opportunities
policies and practices were analysed. Where policies and practices did not apply
to all equality groups, they related to family-friendly practices or race and so the
study may be seen as exploring gender and race equality policies and practices
to a greater extent than policies and practices specific to other groups (see
Chapter 2).
• The linkages between Equal Opportunities policies and practices and business
performance are complex. Combined with data limitations, this reduced the
likelihood of identifying effects (see Chapters 2 and 3).
• The data on business performance (productivity and profits) was problematic.
Robust performance data, based on accounting information, was available
for only a small subset of the sample. The sample size reduced the likelihood
of identifying performance effects. A subjective measure of performance was
also available (namely, the WERS 2004 management respondent’s subjective
evaluation of productivity and financial performance in the workplace
benchmarked against the industry). However, a subjective assessment of relative
business performance is prone to error, thus reducing the reliability of any
findings. For these reasons, the analysis used all four measures and the findings
were interpreted jointly (see Section 4.3.1).
1.5
The structure of the report
The next chapter focuses on Equal Opportunities policies and practices: what they
are, the variables used in the analysis and what influences their adoption. Chapter
3 discusses how Equal Opportunities policies and practices might affect business
performance and refers to the limited quantitative evidence available. Chapter 4
explains our approach to modelling the impact of Equal Opportunities on business
performance. The results are presented in Chapter 5. Chapter 6 summarises our
findings and presents our conclusions.
11
Equal Opportunities policies and practices
2 Equal Opportunities
policies and practices
2.1
Introduction
There are a wide range of policies and practices which could be seen as promoting
equality of opportunity in employment, not all of which are necessarily directed
at equality (e.g. fairness policies, dignity policies, flexitime). Obviously, not all
are covered in Workplace Employment Relations Survey 2004 (WERS 2004) but,
nevertheless, the potential number of policies and practices which could be
examined is large given the breadth and depth of the WERS 2004 questionnaires.
This chapter explains our choice of variables for analysis and their construction in
the models.
First, we discuss the issues of quality and effectiveness of policies. Section 2.3
describes the types of policies and practices which could be used in the model
and their various merits, and the variables used in the analysis. Finally, Section 2.4
discusses the factors affecting the adoption of Equal Opportunities policies and
practices.
2.2
Equal Opportunities policies, practices and
effectiveness
The starting point for the study was the question whether Equal Opportunities
policies affected business performance. However, the quality of policies varies,
from those which are ineffectual statements to policies which drive (or are
indicative of a drive for) measures to address equality of opportunity. Moreover,
there is evidence of variation in implementation of Equal Opportunities policies
(Sanglin-Grant, 2002; Noon and Hoque, 2004). There is also evidence of a lack
of effectiveness of Equal Opportunities policies (Sanglin-Grant, 2005; Virdee
and Grint, 1994), although in relation to ethnicity, Equal Opportunities policies
may be related to more equal treatment (Noon and Hoque, 2001). It is unclear
whether this lack of effectiveness is a reflection of poor implementation (i.e.
13
14
Equal Opportunities policies and practices
Equal Opportunities policies do not amount to practices that address equality of
opportunity) or genuine policy ineffectiveness (i.e. measures to address equality of
opportunity do not affect business performance).
While the effect of the presence of Equal Opportunities policies is of interest, it is
also important to consider the quality of the policy, otherwise we will incorrectly
estimate the effect of the policy on business performance. This can be done in a
number of ways: Firstly, the content of the policy may be treated as an indicator of
its quality. Secondly, Equal Opportunities practices or actual equality of opportunity
may be treated as proxies for the quality of Equal Opportunities policy (i.e. practices
are assumed to be indicative of the quality of the policy or greater equality is
assumed to be indicative of a higher quality policy). Alternatively, one can drop
these assumptions and simply examine the effect of specific practices or actual
equality of opportunity on business performance.
It was decided that the study should focus on Equal Opportunities policies and on
practices and not actual equality of opportunity. In part, this was because equality
of opportunity could only be measured using rather limited proxies (e.g. change in
the percentage of managers who were female, Fernie and Gray, 2002; employees’
perceptions of how well managers understand the need for work-life balance).
Also, the study’s aim was to reveal the effect of Equal Opportunities policy and
practice on business performance and not to try to disentangle the complexities
of the extent to which diversity outcomes were reflected in profitability and
productivity.
Figure 2.1 Some potential routes to business benefits of Equal
Opportunities policies
e.g. customer
loyalty
e.g.
commitment
Equal
Opportunity
policies
Equal
Opportunity
practices
Business
benefits
Equality of
opportunity
The diagram shows only a few routes. See Chapter 3 for a full discussion of
the linkages between Equal Opportunities and business performance and
Appendix A for a fuller diagrammatic representation.
Equal Opportunities policies and practices
Before moving to the nature of benefits in the following chapter, it should be noted
that, even without effective implementation, Equal Opportunities policies may
yield performance benefits or costs. This may occur, for example, either because
knowledge of the policy affects the behaviour of those outside the organisation
(e.g. customers or shareholders) or because it acts as a signal to employees
and potential employees that they will be treated equally and so change their
behaviour (e.g. leading to an increase in applications for jobs from discriminated
against groups; or, conversely, enhancing behaviours leading to promotion; or
leading to a reduction in applications for jobs from those groups that are not
normally discriminated against if a statement of Equal Opportunities is perceived
as ‘positive’ discrimination) (Figure 2.1).
2.3
Measures of Equal Opportunities policies and
practices
2.3.1
Introduction
There are a large number of Equal Opportunities variables in WERS 2004. The
variables selected were based on management respondents’ assessment of
practice. Two types of choices over the policy and practice measures to be assessed
needed to be made: the type of policies and practices to be included and the way
in which the variable should be constructed.
Our choice was guided by the following criteria:
1 despite the evidence suggesting lack of effectiveness of Equal Opportunities
policies per se, policy should be analysed, because the initial question was
whether Equal Opportunities policies affected business performance;
2 a range of types of practices should be assessed, as costs and benefits will vary
with types of practice;
3 the policies and practices should be limited to those explicitly aimed at Equal
Opportunities and to family-friendly practices;
4 the Department for Work and Pensions‘ (DWP’s) particular interest in race
equality in this study; and
5 the assumed strength or effectiveness of the practice (its ‘quality’).
The first three criteria led us to focus on Equal Opportunities policy, Equal
Opportunities monitoring and reviewing practices, family-friendly practices (leave
and flexible working) and measures directed at disabled access. The fourth criteria
led us to develop measures of Equal Opportunities practices directly concerned
with equality of race. The fifth criteria determined which practices were chosen.
For example, practices designed to counter discrimination on the grounds of
age or sexual orientation were taken to indicate stronger commitment to Equal
Opportunities (higher quality practices) than equivalent practices designed to
counter discrimination on the grounds of gender. Our exact choices within this
range are described below.
15
16
Equal Opportunities policies and practices
2.3.2
Individual and conglomerate variables
The WERS 2004 Equal Opportunities policy and practice variables may be used
individually or used to create conglomerate variables. There are good arguments
for the latter: that, jointly, policies and practices may be better indicators of the
quality or effectiveness of the Equal Opportunities policy or that policies and
practices are complementary and so work jointly (Ross and Schneider, 1992;
Jewson et al., 1995; and Kandola,1998). Equally, some practices may be substitutes
for each other (e.g. the provision of childcare versus childcare vouchers or the
availability of job-sharing versus flexible working) and individual practices do not,
therefore, capture what is being offered. However, operationalising this using
quantitative datasets is problematic. This is because quantitative datasets cannot
include full details of all relevant information required to adequately take into
account complementarity and substitutability. Separately, conglomerate variables
can complicate policy interpretation.
There are numerous ways in which both individual and conglomerate variables
indicating the presence and strength of Equal Opportunities policies and practices
can be constructed using WERS 2004. Previous research into the effectiveness and
business benefits of Equal Opportunities policies does not provide guidance as to
a set of best policy measures and indeed, a variety of measures are likely to be
equally informative. Approaches to constructing composite variables include the
creation of categorical variables based on the number of practices within a given
group. These categorical variables have been either dichotomous, indicating that
any of a number of practices exist or none exist (e.g. Noon and Hoque, 2004),
or multivalue, where the number of practices are further classified to indicate
the strength of policy (e.g. Forth and Rincon-Aznar, 2007). Another approach is
the creation of ‘continuous’ composite variables constructed through summing
the number of practices within a given group or through principal components
analysis (e.g. Nadeem and Metcalf, 2007).
Our approach was in the first instance to consider whether each policy or practice
of interest had substitutes. If it did, then a conglomerate variable was required
and this was created as a dichotomous variable indicating the existence of
any of the relevant practices or none. If it did not, then a simple dichotomous
variable indicating the existence or non-existence of the particular practice was
constructed. Next, a judgment was made on the strength of implementation of
Equal Opportunities policy indicated by these dichotomous variables. For example,
monitoring was considered to indicate greater implementation than no monitoring
but monitoring progression was considered to indicate greater implementation
than general monitoring.
Equal Opportunities policies and practices
2.3.3
Variable choice for the study
The following details the variables used in the study.
Equal Opportunities policies
WERS 2004 has two measures of Equal Opportunities policies: the existence of a
formal written policy on Equal Opportunities or managing diversity and whether
the policy mentions specific groups (and, if so, which of the following: sex/gender,
race, religion or belief, marital status, disability, age, sexual orientation, trade union
membership, other).
Mentioning specific groups has been taken to indicate greater commitment
to equality but we have not encountered any evidence on this. We would
hypothesise, however, that mentioning groups which were not covered by antidiscrimination legislation might indicate greater commitment to equality and
hence, a more effective Equal Opportunities policy. At the time of the WERS 2004
survey, discrimination on the grounds of age and sexual orientation were legal
and so naming these groups in an Equal Opportunities policy may be indicative of
a stronger policy commitment.
Therefore, in the study, three policy variables were examined:
1 Formal written policy on Equal Opportunities.
2 Formal written policy on Equal Opportunities explicitly mentions equality of
treatment or discrimination on the grounds of sex, race, religion or belief,
marital status, disability, age, sexual orientation, trade union membership, or
other type of discrimination.
3 Formal written policy on Equal Opportunities explicitly mentions equality of
treatment or discrimination on the grounds of age or sexual orientation.
Monitoring and reviewing
Monitoring and reviewing are essential aspects of effective policy implementation.
As such they should provide an indicator of policy quality. However, monitoring
practice (and interpretation of its meaning) varies: some organisations merely
collect data, whilst others collect data, analyse it and act on the findings. Therefore,
a major consideration in the selection of monitoring and reviewing variables was
the quality of the practice.
WERS collects information on whether an establishment:
• tries to measure the effects of their Equal Opportunities policy;
• monitors: recruitment and selection; promotions; and, for each type of
monitoring, whether this is done by gender, ethnic background, disability and
age; and
• reviews procedures for indirect discrimination in respect of recruitment and
selection; promotions; pay; and, for each type of reviewing, whether this is
done by gender, ethnic background, disability and age.
17
18
Equal Opportunities policies and practices
We would hypothesise that trying to measure the effects of their Equal
Opportunities policy is a very strong indicator of commitment, and so indicative
of policy effectiveness and quality, as this practice is both difficult and rare
(Table 2.1). We would also assume that reviewing procedures for indirect
discrimination would indicate greater commitment than monitoring (given the
differing quality of monitoring).
What is reviewed may also indicate quality. As with Equal Opportunities policy, we
would expect that monitoring or reviewing factors not covered by legislation (in
this case, age) would indicate greater commitment to equality. Finally, monitoring
recruitment is a more common practice than reviewing pay or promotion and
so reviewing the latter two may indicate greater commitment. Therefore, the
following monitoring and reviewing practices were assessed:
4 Trying to measure effects of Equal Opportunities policies.
5 Monitoring of recruitment or promotions by gender, disability, ethnic
background or age (i.e. any monitoring).
6 Reviewing of recruitment or promotions or relative pay to identify indirect
discrimination by gender, disability, ethnic background or age (i.e. any
reviewing).
7 Monitoring of promotions by gender, disability, ethnic background or age (a
potentially strong monitoring measure).
8 Reviewing of promotions or relative pay to identify indirect discrimination by
gender, disability, ethnic background or age (a potentially strong reviewing
measure).
9 Monitoring of recruitment or promotions by age (a potentially strong monitoring
measure).
10Reviewing of recruitment or promotions or relative pay to identify indirect
discrimination by age (a potentially strong reviewing measure).
In addition, because of the Department’s particular interest in ethnicity in relation
to this study, we also assessed:
11Monitoring of recruitment or promotions by ethnic background (i.e. any
monitoring by ethnicity).
12Reviewing of recruitment or promotions or relative pay to identify indirect
discrimination by ethnic background (i.e. any reviewing by ethnicity).
Disability specific measures
WERS 2004 collects information on whether the establishment has assessed
access for disabled people and, if so, whether assessment had resulted in action
to improve accessibility.
Equal Opportunities policies and practices
These might, at first, appear to be good indicators of the quality of an Equal
Opportunities policy (at least in respect of disability). However, they may be
more an indicator of external stimuli for change (a response to a disabled person
being employed or a disability new to the organisation being presented) or to
physical circumstances (the building is poorly equipped for a given disability).
Thus establishments with disabled-unfriendly premises might score higher than
those with modern, disabled-friendly premises, irrespective of the quality of the
Equal Opportunities policy. Moreover, establishments with relatively good Equal
Opportunities policies may need to make assessments and adjustments less often
as provision may already be good. For these reasons, although these two variables
were included in the initial analyses, they were not included in the more detailed
analyses.
13Formal assessment of workplace accessibility for disabled.
14Formal assessment of workplace accessibility for disabled and adjustments
made.
Family-friendly practices
Family-friendly employment practices may be seen as an indicator of the quality
of Equal Opportunities policies, at least in respect of gender. WERS 2004 collects
information on a range of family-friendly practices, including flexible working
practices and leave related to family responsibilities.
In respect of flexible working practices, employers are asked whether any of
the following ‘family-friendly’ practices are available to employees: working at,
or from, home in normal working hours (termed ‘home working’ below), able
to reduce working hours, able to increase working hours, job sharing, flexitime,
ability to change shift patterns, compressed hours (e.g. a nine-day fortnight,
4½ day week) and night working. We excluded night working and compressed
hours from the analysis because these were not family-friendly, per se. Ability to
change shift pattern was excluded on the grounds that it was only applicable to
some workplaces. Flexitime (which, undoubtedly, can contribute to equality of
opportunity) was excluded because it is instigated for a variety of reasons and so
is a poor indicator of Equal Opportunities commitment.
This left three practices: homeworking, employees able to reduce or increase
working hours and job sharing. To recognise possible substitutability, a composite
dichotomous variable was created taking the value of 1 if any of these practices
were present and 0 otherwise. In addition, homeworking on its own was analysed.
Changed hours and job sharing are both flexible hours arrangements and may be
Flexible working practices can be useful to other groups, particularly some
disabled workers and some older workers. However, the main driver for their
introduction is to support mothers and so their existence is an indicator of
strength of Equal Opportunities with respect to gender rather than towards
other groups.
19
20
Equal Opportunities policies and practices
viewed as close substitutes. Homeworking is less obviously a substitute for these
flexible hours arrangements.
15Any of three flexible working arrangements for some employees (homeworking,
changed hours or job sharing).
16Homeworking during normal hours available to some employees.
In respect of leave related to family responsibilities, WERS 2004 identifies the
extent to which maternity leave is paid; the arrangements for time off for
fathers of new-born children; the arrangements for emergency leave for family
responsibilities; and the arrangements for other time off to look after children.
The types of arrangements identified include whether this is discretionary, paid or
part of annual leave, etc.
To us, allowing time off and the arrangements made did not seem to be a good
discriminator of commitment to the quality of Equal Opportunities policies, with
the exception of when leave was paid. Therefore, the following variables were
analysed:
17Special paid leave for family emergencies.
18Paid leave to look after children (in addition to maternity, paternity and time
off for emergencies).
19Leave arrangements to support working parents beyond the statutory minimum
(i.e. paid leave for emergencies; paid leave for childcare; paid paternity leave;
and maternity leave paid above the statutory minimum).
The last was a dichotomous variable indicating whether any or none of these
practices existed.
The Equal Opportunities policy and practice variables analysed and their incidence
are summarised in Table 2.1. Descriptive statistics on the incidence of policies and
practices by establishment characteristics are given in Table B.1 to Table B.4.
Equal Opportunities policies and practices
Table 2.1
Equal Opportunities policy and practice variables
analysed and their incidence
1
Formal written policy on Equal Opportunities or Managing Diversity, 66 per
cent.
2
Formal written policy on Equal Opportunities explicitly mentions equality of treatment
or discrimination on the grounds of sex, race, religion or belief, marital status, disability,
age, sexual orientation, trade union membership or other type of discrimination, 65 per
cent.
3
Formal written policy on Equal Opportunities explicitly mentions equality of treatment or
discrimination on the grounds of age or sexual orientation, 49 per cent.
4
Tried to measure effects of Equal Opportunities policies, eight per cent.
5
Monitoring of recruitment or promotions by gender, disability, ethnic background or
age, 27 per cent.
6
Reviewing of recruitment or promotions or relative pay to identify indirect discrimination
by gender, disability, ethnic background or age, 22 per cent.
7
Monitoring of promotions by gender, disability, ethnic background or age, nine per
cent.
8
Reviewing of promotions or relative pay to identify indirect discrimination by
gender, disability, ethnic background or age, 13 per cent.
9
Monitoring of recruitment or promotions by age, 19 per cent.
10
Reviewing of recruitment or promotions or relative pay to identify indirect discrimination
by age, 17 per cent.
11
Monitoring of recruitment or promotions by ethnic background, 20 per cent.
12
Reviewing of recruitment or promotions or relative pay to identify indirect
discrimination by ethnic background, 18 per cent.
13
Formal assessment of workplace accessibility for disabled, 47 per cent.
14
Formal assessment of workplace accessibility for disabled and adjustments made,
17 per cent.
15
Flexible working arrangements for some employees (homeworking, changed hours or
job sharing), 74 per cent.
16
Homeworking during normal hours available to some employees, 25 per cent.
17
Special paid leave for family emergencies, 47 per cent.
18
Paid leave to look after children (in addition to maternity, paternity and time off
for emergencies), 23 per cent.
19
Paid leave arrangements to support working parents beyond the statutory minimum (i.e.
paid leave for emergencies; paid leave for childcare; paid paternity leave; and maternity
leave paid above the statutory minimum), 79 per cent.
Percentage gives incidence by establishment. Base: all workplaces; figures are weighted and
based on responses from 2,295 managers. Source: WERS 2004.
Variables in bold are those for which results are given in this report and were subject to analysis
beyond the exploratory analysis.
2.3.4
Selection process
Initially, analysis was conducted on the link between each of the policy and practice
variables listed in Table 2.1 and a range of business performance measures (our
measures of business performance are discussed in Chapter 4). This suggested
21
22
Equal Opportunities policies and practices
that the relationship was complex (given the range of results and the sensitivity
of results to the estimation sample, business performance measure and model
specification) and it was clear that more thorough modelling would be required if
confidence might be placed in the findings. The size of the study did not permit
all selected Equal Opportunities variables to be subject to further analysis and only
seven were selected.
The selection criteria were similar to our initial criteria (Section 2.1): First, we
wished to continue to include the range of types of policies and practices (policy,
monitoring and reviewing, flexible working practices and special leave practices).
Unfortunately, for the reasons given in Section 2.3.3, the measures targeted at
disabled people could not be included in this range. Secondly, we wished to focus
on practices which were hypothesised to indicate stronger commitment to Equal
Opportunities. Thirdly, we wished to include a practice relating to ethnicity, due to
the DWP’s specific interest in this study. Selection was not based on the extent to
which the initial analysis had identified any link with business benefits.
Practices 15 and 19 (flexible working arrangements and paid leave arrangements
to support working parents, respectively) were dropped because of their high
incidence, which made them less suitable for analysis. Our inclusion of policy
variable 1 (the existence of a formal policy on Equal Opportunities), rather than
a stronger policy, despite the high incidence, was due to the initial interest of the
study, namely, whether Equal Opportunities policies led to business benefits.
2.4
Factors affecting the adoption of Equal
Opportunities policies
In analysing the impacts of Equal Opportunities policies on business performance,
rather than the associations between Equal Opportunities policies and business
performance, we need to consider the factors which affect the adoption of Equal
Opportunities policies and practices and whether these may also affect business
performance. Nadeem and Metcalf (unpublished) provide a useful overview of the
application of management theory to understanding the adoption of work-life
policies. The following summarises this, drawing out the implications for Equal
Opportunities more generally.
Institutional theory
Institutional theory ‘suggests that organisations’ environments make social and
cultural demands in addition to technical and economic ones, and that organisations
align with these demands of their environment to improve legitimacy and increase
survival capabilities (Meyer and Rowan, 1977; Powell, 1991)‘ (Nadeem and
Metcalf, unpublished). One possible implication of this is that larger organisations
The high incidence of the policies and practices meant that quality of the
controls was lowered.
Equal Opportunities policies and practices
(which are under greater pressure because of their higher profile) are more likely
to meet social norms (including legislation) and that ‘groups’ (e.g. industries,
sectors, locality, etc.) tend to behave similarly due to within-group pressure. In
respect of Equal Opportunities policies and practices, this would mean that larger
organisations are more likely to adopt them and that adoption will differ by sector
and industry.
Empirical findings are in line with institutional theory, in that size, sector, locality
and managerial awareness of other’s practices have all been found to be associated
with having Equal Opportunities and work-life policies (see, for example, Noon
and Hoque, 2004; Nadeem and Metcalf, 2007; Fernie and Gray, 2002; Wood et
al., 2003; Dex and Smith, 2001; Dex and Smith, 2002).
Resource dependent theory
Resource dependent theory ‘helps identify an organisation’s needed resources,
and suggests that to be effective, managers need to understand the demands
and expectations of the stakeholders that control critical supplies, products and
services to the organisation and must adjust its activities to ensure the continued
support of these stakeholders‘ (Nadeem and Metcalf, unpublished). An implication
is that an organisation’s policies and practices will be tailored to meet the needs
of its larger (or more important) employee groups. This will also be affected
by the power of the group. Thus, the adoption of Equal Opportunities policies
and practices would increase with the relative size of the discriminated groups
(employed or in the labour market) and also with such groups’ power (e.g. their
skill level and seniority). Moreover, suppliers and purchasers should be taken into
account. Thus, those supplying to the public sector or to minority groups, might
be more likely to have Equal Opportunities policies and practices.
In respect of more general Equal Opportunities policies and practices, there is
evidence to suggest that unionisation may be associated with the adoption of
policies (Fernie and Gray, 2002; Noon and Hoque, 2004). However, evidence linking
employee pressure based on measures of the relative size of disadvantaged groups,
has been more mixed: Noon and Hoque (2004) found race equality policies to be
more common in organisations with a relatively large ethnic minority workforce
(although, of course, the direction of causality could go the other way), but no
positive link in respect of other groups. Earlier, Fernie and Gray (2002), in respect
of gender, found limited evidence. Other empirical findings in relation to resource
dependent theory explaining the introduction of work-life policies are mixed (see
Nadeem and Metcalf, 2007).
Finally, family-friendly practices are highly correlated with some hard and soft
Human Resource Management (HRM) policies whereas Equal Opportunities
policies and practices have been shown to be weakly correlated with these (Fernie
and Gray, 2002). The high correlation is problematic for this study, as Dickens
(1998) has identified how many HRM policies may act against gender equality.
23
24
Equal Opportunities policies and practices
Strategic or rational choice theory
Strategic or rational choice theory emphasises how managers’ perceptions,
interpretations and attitudes affect organisational actions. Thus, individual
managers’ views are expected to be important predictors of the adoption of
Equal Opportunities policies and practices. Again, the evidence on an association
between managers’ attitudes and work-life policies is mixed (e.g. Wood et al.,
2003; Dex and Smith, 2001; Dex and Smith, 2002; Wood, 1999). Even if the
evidence was stronger, it does not necessarily point to a causal impact from
managers’ perceptions to the adoption of Equal Opportunities policies. In other
words, it may equally suggest that the adoption of Equal Opportunities policies (or
organisational norms) influences managers’ attitudes, rather than vice versa.
These three theories put forward some of the factors which might lead to the
adoption of Equal Opportunities policies. However, the empirical evidence in
relation to each theory is fairly weak. Moreover, it is clear that reverse causality
could explain some of the correlations found (in particular in relation to managerial
attitudes and the use of high commitment human resource approaches).
The business benefits of Equal Opportunities policies and practices
3 The business benefits of
Equal Opportunities
policies and practices
3.1
Introduction
There are many ways in which Equal Opportunities policies and practices may
affect business performance. For example, they may improve staff commitment
and so reduce turnover and absenteeism and increase output, hence reducing
staff costs and productivity and thus, also improving profits; they may ease
recruitment shortages and hence, cut recruitment costs and improve the quality of
the workforce, hence improving productivity and profits. At the same time, they
may add to administrative and training costs and thus, reduce profits. In order to
model the effect of Equal Opportunities on business performance, one needs to
understand these routes and how they may be affected by the characteristics of
the organisation and its circumstances. In this chapter, potential effects of Equal
Opportunities policies and practices are described, together with the ways in
which these may feed through into business performance.
The scope of the study did not include a review of qualitative research into business
benefits of Equal Opportunities and the mapping does not refer to this literature.
Undoubtedly, some of the benefits owe their identification below to previous
qualitative research. Otherwise their identification, the routes through to business
performance and the consideration of mitigating factors is based on consideration
of first principles of how organisations work and the knowledge of the researchers
developed over many years of research into organisations. However, reference to
quantitative evidence is made where it is available and relevant.
The chapter first considers the potential benefits of equality of opportunity in an
organisation and directly associated costs. The costs of achieving greater equality
(i.e. the implementation costs of Equal Opportunities policies and practices) and
more general costs are discussed in the following section. As well as discussing
25
26
The business benefits of Equal Opportunities policies and practices
Equal Opportunities policies and practices and equality of opportunity, familyfriendly practices are explicitly discussed. This is because these have a wider range
of costs and benefits than most other Equal Opportunities policies and practices.
3.2
Potential business benefits of Equal Opportunities
policies and practices
Successful Equal Opportunities policies (i.e. which increase equality of opportunity
and reduce discrimination) and Equal Opportunities practices may lead to business
benefits through a number of intermediate outcomes:
• improved recruitment;
• improved staff utilisation: matching employees to jobs;
• improved morale and employee commitment;
• greater employee diversity;
• customer approval.
Each of these is discussed below.
Figure 3.1 summarises the potential benefits indicating whether they feed through
to productivity and labour costs or to sales and hence, to profits. For each benefit,
the figure shows whether these may be gained from Equal Opportunities policies
and practices generally or from family-friendly practices in particular.
Equal
Opportunities
policies and
practices
Increased
customer
loyalty
Greater
understanding
of diverse
cultures
The high incidence
of the policies and
practices meant
that quality of the
controls was
lowered
More effective
utilisation of staff
Improved quality of
recruits and easier
recruitment
Lower labour turnover
Lower absenteeism
Greater flexibility
Greater employee effort
Improved teamworking
Product development and
marketing appropriate to
diverse groups
More effective personal
contact with customers/ clients
-
Figure 3.1 Potential business benefits of effective Equal Opportunities policies
Increased
sales
- Lower labour
costs
- Increased sales
- Increased
output/person
The business benefits of Equal Opportunities policies and practices
27
28
The business benefits of Equal Opportunities policies and practices
3.2.1
Improved recruitment
Discrimination in recruitment reduces the pool of workers from which an
organisation draws and means that suitable candidates are rejected (or do not
apply). It is assumed, therefore, that discrimination results in a poorer match
between recruits’ competence and job requirements. This mismatch would grow
with the tightness of the labour market and, in tight labour markets, discrimination
is assumed to result in recruitment difficulties and skill shortages. Moreover, it
is assumed that in a discriminatory labour market, the organisation which does
not discriminate is able to recruit higher quality workers (from those groups
discriminated against).
Lack of discrimination may lead to an increase in the number of applicants and
should lead to a larger pool of candidates who are regarded as suitable. Offering
family-friendly practices and making special provision for minority groups is also
likely to increase the number of applicants from those groups seeking these
benefits. This would be beneficial in a tight labour market, but may incur additional
costs when the labour market is slack (dealing with a larger number of applicants
than is necessary to obtain a suitable recruit). Benefits are also dependent on
the relevant labour pool containing members of the discriminated against group
(i.e. having appropriate skills). If it does, reducing discrimination should result
in improved labour quality. If it does not, improving Equal Opportunities would
have no effect. At the same time, given discrimination in the labour market,
offering equality of opportunity could lower labour costs, through increasing the
employment of groups whose wages were less than the value of their marginal
product (Barrington and Troske, 2001, referring to Becker, 1971).
The recruitment benefit of equality of opportunity is based on two underlying
assumptions: that recruiters are good at recruiting ‘the best for the job’ and that
employee performance is closely aligned to the criteria used for their selection. If
these do not hold (and it is not clear that they do), the quality of recruits may not
be affected by discrimination. Therefore, it is not clear whether the net result of
equality of opportunity policies and practices increasing the number of applicants
would necessarily be of benefit to the organisation.
3.2.2
Enhanced staff utilisation: matching employees and jobs
Lack of discrimination in provision of training and development opportunities and
allocating staff to specific jobs (including promotion) is assumed to result in better
utilisation of staff resources. As with recruitment, this relies on the assumption
of appropriate selection criteria. However, we would expect selection more often
to be effective in identifying appropriate existing staff than for recruitment, as
selectors have much greater knowledge of the existing, rather than the potential,
employees. However, this will vary with the selection process and the extent to
which those familiar with the employee are involved.
The actual benefit to an organisation will depend on the extent to which there is
discretion over work allocation and the extent (and importance) of development
The business benefits of Equal Opportunities policies and practices
and promotion. In organisations where there is little allocation discretion and little
promotion and development, the potential benefits of Equal Opportunities policies
in terms of matching employees and jobs are likely to be less pronounced.
3.2.3
Enhanced staff utilisation: family-friendly working
practices
Some family-friendly flexible working practices, such as flexitime, jobsharing and
part-time working may enhance staff utilisation if they are implemented (by either
staff or managers) with an eye on the workload. Qualitative research shows that
these can introduce an added flexibility to meet varying workloads even where the
practices are designed to assist employees with family responsibilities. However,
many such practices also incur costs (see Section 3.3) and so the net benefit will
depend on the pattern of work and the extent to which implementation actually
addresses work needs.
3.2.4
Morale and employee commitment
Equality of opportunity, Equal Opportunities practices and family-friendly working
practices are purported to improve employee morale and commitment and
therefore, to provide business benefits. Good morale and commitment have been
associated with:
• lower levels of stress and psychosomatic illness and increased psychological
well-being;
• lower staff turnover;
• fewer grievances;
• higher job performance, increased work quality and greater ‘organisational
citizenship’ (extra-role behaviours);
• lower absenteeism.
See Lee et al., 2000; Meyer et al., 2002, Thorsteinson, 2003; Wright and Bonett,
2002; Riketta, 2002; Rhoades and Eisenberger, 2002; Judge et al., 2001.
It seems likely that equality of opportunity would enhance the morale and
commitment of members of those groups which tend to be discriminated against
and family-friendly practices would raise the morale and commitment of those
who can take advantage of the practices. However, the morale effects on those
who tend to benefit from discrimination is less clear and equality of opportunity
could, in fact, have a negative effect. Certainly, in respect of family-friendly
practices, there is some qualitative evidence of resentment from employees who
do not use (or do not need) such practices, either because they believe that the
practices increase their own workload or because they consider them conferring
favourable treatment on others. The impact on the business may therefore depend
on the composition of the workforce, with benefits increasing, the higher is the
percentage of employees who come from discriminated against groups or who
29
30
The business benefits of Equal Opportunities policies and practices
need the family-friendly practices. The net effect in an organisation may be positive
or negative.
The extent of benefit to the organisation due to morale improvements will vary
with the different characteristics of businesses. For example, reductions in staff
turnover will be beneficial if turnover is too high, but may result in costs if it
becomes too low (for example, in organisations where labour demand fluctuates
and voluntary resignations help match to periods of lower demand); the extent
to which job performance may improve will depend on the nature of the job.
Where production costs are low, the benefits may be minimal (Liff and Cameron,
1997: 41).
3.2.5
Greater employee diversity
Equality of opportunity may increase the diversity of the workforce if the labour
market includes groups previously discriminated against. Increased diversity has
been purported to bring three types of benefits: customer approval, better service
to diverse customer groups and greater innovation.
Customer approval is assumed to enhance sales. It is supposed to be derived
through diversity in two ways: Firstly, it is assumed that customers support
equality and disapprove of discrimination and therefore, tend to approve more
of organisations with a diverse workforce (and so are more likely to buy from the
organisation). However, it cannot be assumed that customers support equality
or that support influences custom. Therefore, whether an organisation achieves
this benefit from diversity depends on the composition of its (potential) custom.
Secondly, it is assumed that customers wish to see (or to be served by) a workforce
which includes people like them (i.e. ethnic minorities wish to see ethnic minority
employees, women, female employees, etc.; this tends to be a benefit cited by
retail organisations, amongst others). This benefit can only be derived from visible
staff and applies to visible diversity groups e.g. it is most clear for gender and age,
it will often be clear for some ethnic and religious groups and for some forms
of disability (e.g. wheelchair users are visible as disabled but those with Multiple
Sclerosis may not be visible as disabled). There is little evidence to support the
assumption that customers approve of diversity. Barrington and Troske (2001)
refer to a case reported in Navarro (1988) where a barbeque sauce manufacturer
lost the majority of its largest retailers (who provided up to half its sales revenue)
following a campaign about the founder’s racist statements.
Better understanding of a diverse customer/client base (e.g. understanding
of different cultures, needs and preferences) is assumed to stem from greater
diversity and to enhance sales and service. This may be manifested through
more effective personal contact with customers/clients, product development
appropriate to diverse groups and marketing appropriate to diverse groups (see,
for example, Osborne, 2000). The employment of staff with minority languages
enables employees to communicate with customers in their preferred language.
Whether such benefits are derived depends on the nature of the business and the
composition of customers.
The business benefits of Equal Opportunities policies and practices
Diversity is also purported to increase innovation. Different cultural backgrounds
(which may derive, for example, from ethnicity, religion, nationality, gender,
sexual orientation) produce different experiences, attitudes and approaches. It is
therefore assumed that the range of ideas increases with diversity. This may affect
management and organisation approaches, product development, approaches
to marketing and publicity and approaches to support services and resourcing.
For example, different groups may present different ways of working (e.g.
co-operative, individualistic, combative; for an overview of evidence see Anderson
with Metcalf, 2003).
At the same time, greater employee diversity may have costs in respect of
employee relations. It may reduce effective team working because of differences
in how individuals interact and hostility from prejudiced employees and increase
communication difficulties (Lang, 1986). At worst it may result in harassment,
antagonism and resentment, with consequent management costs, cultural
diversity training costs, costs associated with reductions in morale and, potentially,
legal costs.
Whether diversity, where it results from equality of opportunity, results in net
benefits or costs will vary with the organisation and the context within which it
operates. In a study of the aggregate effects of diversity of business performance
in the US, Barrington and Troske (2001) found that, in aggregate, diversity was
either positively associated with productivity or there was no significant relationship
between diversity and productivity. They concluded that establishments employing
a more diverse workforce are no less productive than establishments that employ
a more homogeneous workforce. However, like the studies of Equal Opportunities
and business performance, this study only examined associations and did not
attempt to address causality.
3.2.6
Shareholder approval
Finally, just as diversity may meet with customer approval, knowledge of the
existence of an Equal Opportunities policy or equality itself may result in share
buyers’ approval. Certainly, Wright, et al. (1995) found that companies recognised
by the U.S. Department of Labor for having an exemplary affirmative action program
experienced an increase in stock price immediately after the announcement, which
may have arisen because of an increase in expected future sales or because of a
publicity effect.
3.3
The costs of implementing Equal Opportunities
policies and practices
The implementation of Equal Opportunities policies and practices entail costs.
As for any policies and practices, Equal Opportunities policies and practices incur
development costs and continuing costs of training and dissemination. In addition,
some practices have other types of costs. Examples are given overleaf for some of
the main aspects of Equal Opportunities policies and practices:
31
32
The business benefits of Equal Opportunities policies and practices
• Fair processes for recruitment, appraisal and promotion: vacancy
advertising costs, time to conduct selection fairly (including appraisees’ time).
• Equal Opportunities monitoring costs: collection of data and its analysis.
• Homeworking: may reduce managers’ control and so increase costs (Riley and
Weaver, 1997, and Baruch, 2000 referred to in Gray, 2002).
• Job-sharing and part-time working: additional costs due to more employees
to do the same amount of work (e.g. training, communication, managing),
hand-over costs (for job-sharing), loss of quality and efficiency due to handover;
at the same time, the organisation may benefit from a wider range of skills and
greater deployment flexibility.
• Family-friendly leave arrangements: cost of paid leave, replacement costs
(including recruitment and training), overtime costs, loss of production (when
no replacement), additional demands on other staff affecting morale and
production, management time (especially for leave at short notice); at the same
time, organisations may benefit from lower turnover amongst those potentially
needing time off and so reduced recruitment and training costs. The effects will
differ depending on the extent to which leave is predictable, whether it is paid
or not and its length.
• Specialist provision: to cater for a diverse workforce, e.g. disability-friendly
washroom facilities.
• Raised awareness of discrimination: Equal Opportunities policies should
raise awareness of discrimination. However, amongst discriminated against
groups and those who care about equality, unless employees are confident that
discrimination is being dealt with, morale may be reduced and grievances and
disputes increased. Thus, costs of Equal Opportunities policies may be higher
unless effectiveness is high.
As with potential benefits, the actual costs of Equal Opportunities policies and
practices will vary with the characteristics of the organisation and its circumstances.
For example, those with pre-existing highly structured human resource policies
and practices will already have the systems for implementation of policies and
practices and their costs will be lower.
Skills needs and production processes will affect the costs of some practices. The
complexity of this can be illustrated in relation to family-friendly leave provision.
Costs will tend to decrease the easier it is to provide coverage (i.e. when job
skills are common or where staffing capacity allows) or where production is more
flexible (i.e. the more able the organisation is to time- (or location-) shift work
or to sub-contract. It may be reasonable to assume that low skilled jobs tend to
be easier to cover or sub-contract and the larger each occupational group, the
easier coverage may be. However, higher skilled jobs may be easier to rearrange
demands. Lean organisations may find it more difficult to cover leave.
The business benefits of Equal Opportunities policies and practices
Costs may also be affected by the extent to which a practice is used. Again,
considering family-friendly leave arrangements, coverage costs would rise with the
number of staff absent. Moreover, the degree of familiarity with the practice will
affect administrative and management costs, including administrative economies
of scale. For some practices, it seems likely that administrative costs would initially
rise, then decline with use (e.g. extensive use of maternity leave may enable
returners to be fitted back in with greater ease). However, very high use is liable
to be more costly.
33
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
4
Identifying the effect
of Equal Opportunities
on business outcomes
using WERS 2004
4.1
The basic identification problem
Given the data available in Workplace Employment Relations Survey 2004 (WERS
2004) it is possible to examine the associations between different indicators
of Equal Opportunities, as discussed in Chapter 2, and business performance
(productivity and profits), although there are a number of measurement issues
that arise. Our objective is not only to consider the links and correlations between
Equal Opportunities and business performance but also to consider the feasibility
of moving further towards establishing the effect of Equal Opportunities on
business performance using WERS 2004.
The difficulty in identifying the causal effect of Equal Opportunities on business
performance, measurement issues aside, arises because of the potentially circular
relationship between Equal Opportunities and business performance. For example,
Equal Opportunities may enhance productivity and productive workplaces may be
more likely to adopt Equal Opportunities. This problem is not unique in policy analysis
and indeed, in any analysis that attempts to establish causal relationships.
Simple regression techniques will only identify the impact effect of Equal
Opportunities on business performance if the presence of Equal Opportunities
policies and practices are independent of business performance given the other
determinants of business performance included in the regression. In other
words, to establish causality, Equal Opportunities policies and practices must be
exogenous to business performance, conditional on the other determinants of
business performance that are taken into account.
35
36
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
If the relationship between Equal Opportunities policies and practices and
business performance is circular, as described above, Equal Opportunities policies
and practices are endogenous rather than exogenous to business performance.
This situation may arise for two reasons: First, productivity may actually cause the
adoption of Equal Opportunities. Second, Equal Opportunities may be correlated
with other factors that influence business performance. The second problem of
other factors that coincide with Equal Opportunities and that affect business
performance may be dealt with by including these factors in the regression model.
However, this strategy can only be successful if it is possible to identify from theory
and measure in the data all the factors that may coincide with Equal Opportunities
and that affect business performance. Separately, the correlation between Equal
Opportunities and other factors that determine business performance needs to
be imperfect so that it is possible to differentiate between the two. In practice it
is usually necessary to adopt other methods than simple regression techniques
to detect causal impacts rather than correlations in the data, the latter of which
can only tell us about the associations between Equal Opportunities and business
performance.
4.2
Identification strategy
Here we outline how we proceed to try and identify the impacts of Equal
Opportunities on business performance using WERS 2004 and handle the issue
of endogeneity (the results are reported in Section 5.2). We start by exploring
the links between Equal Opportunities and business performance using standard
regression analysis. As discussed already, problems that arise in this model are that
we may have omitted from the model some variables which are correlated with
our measure of Equal Opportunities (the ‘treatment’ indicator) and our measure
of business performance (the ‘outcome’ variable) or that Equal Opportunities
policies are genuinely caused by business performance. In either case the estimated
effect of Equal Opportunities on business performance resulting from the simple
regression model will be a biased estimate of the true policy effect.
A standard way forward in this situation is to use ‘instrumental variables’ to help
identify the true policy effect (see e.g. Greene, 1993). Suitable ‘instruments’ need
to be strongly correlated with Equal Opportunities but uncorrelated, or at least
only weakly correlated, with business performance. In other words they need
to be good predictors of whether or not workplaces have Equal Opportunities
policies and practices, but poor predictors of workplace productivity and profits.10
In Section 4.4.2 we identify potential instrumental variables. The way in which
instrumental variables techniques are implemented depends on the nature of
10
Furthermore, suitable instruments need to be based on theory. The fact that
we may find a variable that satisfies certain statistical criteria is not sufficient
in itself.
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
the policy and outcome variables of interest.11 In estimating the effects of Equal
Opportunities on business performance (Chapter 5) we make use of these
instruments in a simultaneous equation system where business performance and
Equal Opportunities are both assumed to be endogenously determined.
In practice instrumental variables analysis is complicated because of the difficulty
in finding suitable instruments. Furthermore, the results are typically very sensitive
to the particular instruments used. Propensity score matching is another technique
used for identifying treatment or policy effects (see e.g. Caliendo and Kopeinig,
2005). The benefit of this approach over instrumental variables techniques is that
we do not need good instruments. However, propensity score matching does not
allow us to control for unobservable determinants of both business performance
and Equal Opportunities. It is generally preferable to standard regression
techniques, particularly when we have rich information on the covariates of the
outcome variable of interest and the policy, as is the case in the current exercise.
One important advantage of propensity score matching is that we are able to
reduce the sample to restrict our attention only to those establishments for which
we have good control establishments, i.e. we are able to compare organisations
that are similar in most respects other than in their adoption of Equal Opportunities
policies and practices. In contrast, in standard regression analysis we rely on the
functional form of the model to compare establishments with Equal Opportunities
to those without. Estimates of the effects of Equal Opportunities on business
performance based on propensity score matching are likely to identify causal
impacts if indeed we have sufficient establishments from which to construct the
control group, if we can balance key covariates of business performance between
those establishments that operate these practices and those that do not and if we
can measure the important covariates of both business performance and Equal
Opportunities.
Finally, we assess the links between Equal Opportunities and business performance
for large establishments (establishments with 50 employees or more). The reason
for this is twofold: First, we find that the incidence of Equal Opportunities is very
much correlated with establishment size, as is business performance. Second,
we might expect the effect of Equal Opportunities to vary by establishment
size, possibly because of differences in implementation. For example, in small
establishments the costs of these practices might be relatively large in comparison
to large establishments where costs are more easily absorbed. Also, in larger
establishments a human resource department will typically be responsible for the
implementation of these practices; unlike in small establishments which may not
have a post designated to human resource issues.
11
In particular, the method of implementation depends on whether these
variables are discrete or continuous.
37
38
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
4.3
Modelling business performance
In this section we discuss how we model business performance in WERS 2004.
In Chapter 5 we augment the models shown here with measures of Equal
Opportunities policies and practices, under different assumptions about the
endogeneity or exogeneity of these policies and practices. Later, these models
also help us select covariates to include in estimating the propensity score.
First, we discuss measures of productivity and profits available in WERS 2004.
Second, we discuss our estimation approach and the adequacy of observable
determinants of business performance for the current purposes.
4.3.1
Measuring business performance in WERS 2004
Measures of business performance in the WERS 2004 Management Questionnaire
include the respondent’s (usually the human resource manager or the owner)
subjective evaluation of productivity and financial performance in the workplace
benchmarked against the industry. Subjective performance is recorded on a
five-point scale (A lot below, Below, Average, Better, A lot better) relative to the
respondent’s perception of the performance of other establishments in their
industry. In reality, few establishments report performance a lot below average,
so we treat replies ‘A lot below’ and ‘Below’ average as similar. Approximately
half of establishments report average, or below average, performance; the other
half report above average performance. In modelling financial performance we
found that models explaining variation in this dichotomous performance indicator
performed better than models explaining variation in the four-category indicator.
There are a number of issues in relation to these performance measures: First,
since performance is measured subjectively, rather than measured on hard facts or
objective data, one might question how well these data measure true performance.
Second, performance is benchmarked against the industry, which is not defined
and which is likely to be interpreted differently by different respondents. Third, it is
not obvious that all respondents will interpret workplace ‘productivity’ or ‘financial
performance’ similarly. Regarding financial performance we are able to separate
out those respondents who interpret financial performance as profits (rather than
turnover, costs, or something else), which reduces the sample of private sector
workplaces by approximately a third.
For workplaces responding to the Financial Performance Questionnaire in WERS
2004 we also have estimates of turnover, labour costs and other costs, making
it possible to derive measures of gross value added and profits. Such data items
can also be obtained for some workplaces by linking their records, via the InterDepartmental Business register, to the Annual Business Inquiry (ABI). These data
are discussed in Forth and McNabb (2007). Here we use their derivations applied
to the April 2007 WERS 2004 release. We also estimate new sample weights as
described in Forth and McNabb (2007). These business performance measures
(which we refer to as objective measures in what follows) are much to be preferred
to the subjective performance measures, were it not for the significantly reduced
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
sample for which these data items are available. We have subjective measures of
productivity for more than 1,500 private sector workplaces in WERS 2004. The
objective measure is available for less than 500 workplaces. All else being equal
this means that we are much less likely to pick up statistically significant effects
with these data.
We evaluate the impacts of Equal Opportunities for workplaces in the private
sector only on the grounds that public sector workplaces are less likely to measure
performance accurately or similarly to workplaces in the traded sector. Table 4.1
illustrates the incidence of the seven different indicators of Equal Opportunities
and practices on which we focus in the samples for which we have subjective
performance data and separately in the sample for which we have objective
measures of performance. We also show the incidence of Equal Opportunities
in large establishments, which we analyse separately as discussed above. Equal
Opportunities are more prevalent in the public sector and in large workplaces,
indeed the presence of a formal written policy on Equal Opportunities or managing
diversity is near universal in public sector and large establishments. The incidence
of Equal Opportunities in the sample of private sector workplaces for which we
have subjective performance data is similar, but not identical, to the incidence of
Equal Opportunities in the sample of private sector workplaces for which we have
objective performance data. Furthermore, the weighting scheme used appears to
have some impact on the results.
39
8
The impacts of Equal Opportunities policies
in the workplace are measured
47
23
Time off for family emergencies is usually
taken as special paid leave
Time of childcare is usually taken as special
or paid parental leave (other than maternity
and paternity leave and emergency leave)
43
75
34
46
20
42
23
14
6
11
62
Percentage of
private sector
workplaces
27
49
39
25
13
21
90
22
38
18
13
6
11
64
26
40
19
15
5
12
69
Percentage of
private sector
workplaces
included in
the financial
performance
sample (prof.
weights)
Notes: Figures are weighted and based on responses from 1,706 managers in private sector workplaces, 906 managers in large (50 employees or more) private
sector workplaces, 589 managers in public sector workplaces and 461 (productivity weights) and 465 (profit weights) managers in private sector workplaces
included in the financial performance sample.
Source: WERS 2004.
25
18
For some employees working time
arrangements include working at or from
home in normal working hours
Family-friendly practices
Recruitment or promotion procedures or
relative pay rates are reviewed to identify
indirect discrimination by ethnic background
25
31
93
Percentage of
public sector
workplaces
Equal Opportunities practices concerning ethnic background
14
66
Promotion procedures or relative pay
rates are reviewed to identify indirect
discrimination by gender, ethnic
background, disability or age
Equal Opportunities practices
The workplace, or the organisation of which
it is a part, has a formal written policy on
equal opportunities or managing diversity
Equal Opportunities policies
Percentage
of all
workplaces
Percentage of
private sector
workplaces
with 50
employees or
more
Percentage of
private sector
workplaces
included in
the financial
performance
sample (prod.
weights)
The incidence of Equal Opportunities policies and practices in UK workplaces
Policy or practice
Table 4.1
40
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
4.3.2
Estimating models of business outcomes in WERS 2004
Factors affecting business outcomes directly and which we can measure using WERS
2004 include workplace characteristics (industry group, region, size of establishment
and/or organisation, culture of ownership, age), employee characteristics (skill
composition of the work force, gender and ethnic and age composition of the
workforce), market characteristics (state of the market, competitiveness of the
industry, trading in the international versus local market), industrial relations and
human resources (trade union representation, participation in control, participation
in returns)12, and job-related factors (training, independence in work, part-time
incidence). In terms of the determinants of business performance in theory, one
of the most obvious determinants of productivity that we cannot capture in WERS
2004 is the ratio of capital to labour. In and of itself there is no specific reason to
expect the capital to labour ratio to be correlated with Equal Opportunities, and
hence this does not pose a problem in the evaluation of the effects on business
performance of these policies and practices.
In practice many of the variables mentioned above, and others, are often included
in models of business performance whether or not they are statistically significant.
We have started our modelling with many of the standard variables, as described
previously, but narrowed these down to those which appear to explain variation
in the outcome variable best.
Note that there are a number of factors that may influence business performance
and that may be regarded as intermediate outcome variables in the current
evaluation exercise, i.e. they are influenced by Equal Opportunities policies and
practices. These are excluded in the outcome models here, so that we do not mask
any potential policy effects. For example, if Equal Opportunities practices affect
business performance exclusively through employee commitment, we will clearly
find no effect of Equal Opportunities if we include employee commitment in the
business performance model. At the same time, it is important that we include the
determinants of these intermediate outcomes in the business performance model,
so that, once we get to the evaluation stage in the next section, the estimated
Equal Opportunities effect does not pick up the effect of these intermediate
outcome variables on business performance, other than where these occur
through Equal Opportunities. Based on the discussion in Chapters 2 and 3, key
intermediate outcomes include the gender and ethnic minority composition of the
establishment’s workforce and employee commitment, and in the profits model
one might also reasonably argue that productivity is an intermediate outcome.
We exclude these factors from our models of business performance, but include
12
The ‘participation in control’ variable is a composite variable constructed
using factor analysis of three variables measuring the extent of briefing
between managers and employees, joint consultative committees, and
quality circles. The ‘participation in returns’ variable is a composite variable
constructed using factor analysis of three variables measuring the extent of
performance-related pay, profit-related pay and employee share schemes.
41
42
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
exogenous determinants of these factors such as the gender or ethnic minority
composition of industry employment, the ethnic minority composition of the
local population, industrial relations and Human Resource Management (HRM)
factors.13
Table 4.2 reports our models of business performance. We show models of
productivity and profits measured by the subjective (first two columns) and objective
(last two columns) data respectively. Subjective performance is modelled as a probit.
Objective performance is modelled as a linear regression of logged performance.
All models capture the influences of industrial relations and HRM factors (e.g. union
presence is always negatively correlated with business performance, regardless of
how this is measured), influences on employee characteristics (e.g. the share of
industry employment from an ethnic minority background appears to have a large
and significant negative effect on the subjective productivity performance indicator,
which probably reflects the sorting of disadvantaged groups in the labour market
into low paying sectors), market conditions and competitiveness (e.g. a declining
or turbulent market typically has an adverse effect on business performance), skills
and basic establishment characteristics (e.g. large establishments tend to perform
better than equivalent smaller establishments, although large organisations seem
to have lower productivity than equivalent smaller organisations), although the
way in which these are represented varies across models and was determined by
statistical significance.
The models are reasonably specified. Interestingly, we are better able to explain
variation in the objective measures of business performance than in the subjective
measures of business performance. This is not entirely due to differences in outcome
measures, but is also explained by differences in the sample of workplaces. Thus,
we are better able to explain variation in the subjective measures of performance
on the sample for which we have objective data than on the larger sample for
which we have subjective measures of performance.
13
The gender and ethnic minority composition of industry employment is
derived from the Labour Force Survey (LFS) and linked to WERS 2004 via the
Standard Industrial Classification. The ethnic minority composition of the
local population is derived from the Census and is linked to the WERS 2004
via postcodes.
-.053
.006
Share of industry employment
from ethnic minority
background
Share of industry employment
that is female
Share of TTWA population
from ethnic minority
background
Influences on employee characteristics
(.016)
(.013)
(.169)
.050
-.053
.004
-.026
.249
.041
Independence in work
(.281)
.045
Culture of head office: other
non-UK
.042
Participation in control
(.051)
-.042
Coeff.
.319
.077
Participation in returns
(.251)
p-value
(.150)
(.326)
(.088)
(.035)
(.120)
(.311)
(.361)
(.578)
p-value
Subjective indicator of
above average financial
performance (profits)
Culture of head office: USA
-.065
Coeff.
Union presence
Industrial Relations and HRM
Independent variables
Subjective indicator
of above average
productivity performance
Models of business performance
Dependent variable
Table 4.2
-.003
.247
.259
.088
-.106
Coeff.
(.087)
(.002)
(.021)
(.023)
(.022)
p-value
Log gross value added per
employee
-.004
.173
.173
-.031
.074
-.066
Coeff.
Continued
(.011)
(.005)
(.036)
(.077)
(.007)
(.052)
p-value
Log profits per employee
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
43
Continued
Coeff.
-.073
-.122
State of the market: mature
State of the market: declining
or turbulent
(.071)
-.094
.002
-.002
(.233)
(.049)
(.496)
Coeff.
Share of employees age 1621
(.003)
-.098
-.134
-.049
p-value
(.070)
(.381)
(.042)
p-value
Log gross value added per
employee
-.001
.004
(.075)
(.028)
(.210)
(.009)
(.129)
Coeff.
Subjective indicator of
above average financial
performance (profits)
Share of employees in routine
unskilled occupations
Share of employees in
managerial/professional
occupations
Skills
Trading in the international
market
.122
.149
Extent to which demand
depends on quality: high
State of the market: mature,
declining or turbulent
.091
Extent to which demand
depends on quality: medium
p-value
Subjective indicator
of above average
productivity performance
Market conditions and competitiveness
Independent variables
Dependent variable
Table 4.2
.002
-.089
Coeff.
Continued
(.050)
(.022)
p-value
Log profits per employee
44
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
Continued
1,402
Sample (unweighted)
-.223
853
0.081
(.073)
(.027)
(.137)
(.081)
(.458)
p-value
-.051
-.252
Coeff.
461
0.377
(.337)
(.000)
p-value
Log gross value added per
employee
-.049
-.050
Coeff.
465
0.378
(.190)
(.237)
p-value
Log profits per employee
Notes: Estimation takes into account survey weights; subjective (objective) performance modelled as a probit (linear regression); probit coefficients shown
as marginal effects; independent variables include major Standard Industrial Classification indicators and a constant term; participation in returns variable
constructed from factor analysis of indicators of performance-related pay, profit-related pay, employee share schemes; participation in control variable
constructed from factor analysis of indicators of briefing between managers and workers, joint consultative committees, and quality circles; independence in
work variable constructed from factor analysis of indicators of the extent of variety in work, discretion in work, control over pace of work, and design of work;
sample includes private sector trading establishments; sample for subjective financial performance includes only those establishments who regard financial
performance as profits.
Source: WERS 2004.
0.084
R-squared (pseudo for probit
models)
Young establishment
Share of employees working
part-time
-.121
Organisation size: 100
employees or more
.166
.095
.053
Establishment size: 50
employees or more
(.032)
-.228
Coeff.
Ownership: predominantly
foreign
(.282)
p-value
Subjective indicator of
above average financial
performance (profits)
-.083
Coeff.
Subjective indicator
of above average
productivity performance
Ownership: partly foreign
Establishment characteristics
Independent variables
Dependent variable
Table 4.2
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
45
46
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
4.4
Modelling treatment selection
Here we discuss the empirical determinants of Equal Opportunities policies and
practices or ‘treatment selection’, where the particular Equal Opportunities policy
or practice is the ‘treatment’ and ‘selection’ refers to whether or not workplaces
operate such policies and practices. The purpose of this is to assess which factors
appear to be important covariates of both business performance outcomes and
Equal Opportunities policies and practices. This provides us with guidance as to
which variables are important to include in modelling the propensity score. We
also assess which factors appear to explain the presence of Equal Opportunities
policies and practices, but which do not help explain business performance in
and of themselves. These variables are used as instrumental variables when we
assume in the evaluation exercise in Chapter 5 that Equal Opportunities policies
and practices are endogenously determined.
4.4.1
Models of Equal Opportunities
We model the workplace presence of each of seven measures of Equal Opportunities
policies and practices using a probit model. In Table 4.3 we report these models
estimated on the sample of private sector workplaces for which we have subjective
performance measures of productivity. We list the variables included in estimation
in terms of whether (A in Table 4.3) or not (B and C in Table 4.3) they determine
subjective productivity performance, i.e. whether or not they are included in the
model in the first column of Table 4.2. The factors that are not included in the
model of subjective productivity performance, but that are included in the models
of treatment selection here in Table 4.3, are statistically independent of subjective
productivity performance.
Many of the variables that influence subjective productivity performance appear
also to determine the probability of having in place different Equal Opportunities
policies and practices. Industrial relations and HRM factors are significant covariates,
much as we might expect given the discussion in Chapters 2 and 3. The share of
ethnic minority employees and female employees in the industry have a statistically
significant effect on the presence of review procedures and home working, but not
on other indicators of Equal Opportunities. Market conditions and competitiveness
factors are in many instances statistically significant covariates. The skill composition
of establishments’ workforce determines the incidence of home working. Both the
size of the establishment and the size of the organisation appear to be important
explanatory factors of the incidence of several Equal Opportunities policies and
practices here. In comparison to similar but small organisations, large organisations
are more likely to have a formal written Equal Opportunities policy and are more
likely to adopt review procedures to identify discrimination in general and to
identify discrimination in relation to ethnic background. Larger organisations
appear to be less likely to facilitate home working than smaller organisations, but
larger establishments appear to be more likely to facilitate home working than
smaller establishments.
.146
.151
-.013
Participation in returns
Participation in control
Independence in work
.008
-.001
Share of ethnic minority
employees in the industry
Share of female employees in
the industry
Influences on employee
characteristics
.068
Coeff.
Union presence
Industrial Relations and Human
Resource Management
A. Determinants of
subjective productivity
performance
Independent variables
(.677)
(.768)
(.657)
(.002)
(.001)
(.305)
pvalue
Formal
written policy
.000
.013
.021
.027
.027
-.019
Coeff.
(.898)
(.062)
(.030)
(.100)
(.110)
(.366)
pvalue
Review
procedures
-.000
.002
.004
.021
-.010
.042
Coeff.
(.458)
(.540)
(.451)
(.006)
(.234)
(.002)
pvalue
Equal
Opportunities
impact
measurement
Models of Equal Opportunities selection
Dependent variable
(Equal Opportunities
treatment indicator)
Table 4.3
.001
.001
.019
.034
-.017
.020
Coeff.
(.184)
(.887)
(.191)
(.051)
(.369)
(.440)
pvalue
Review
procedures
concerning
ethnic
background
-.005
.033
.066
.049
.054
-.011
Coeff.
(.003)
(.018)
(.001)
(.069)
(.045)
(.777)
pvalue
Home
working
.001
.013
.085
.049
.082
-.008
Coeff.
(.724)
(.511)
(.002)
(.198)
(.031)
(.887)
pvalue
Special
paid leave
for family
emergencies
(.412)
(.368)
(.025)
(.116)
(.278)
(.976)
pvalue
Continued
.001
.012
.044
.041
.027
-.001
Coeff.
Additional
paid leave for
childcare
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
47
Continued
-.059
.014
-.052
-.148
Extent to which demand
depends on quality: high
State of the market: mature
State of the market: declining
or turbulent
Trading in the international
market
.001
.003
Share of employees in
managerial/professional
occupations
Share of employees age
16-21
Skills
-.103
Coeff.
(.074)
(.690)
(.070)
(.361)
(.813)
(.325)
(.095)
pvalue
Formal
written policy
Extent to which demand
depends on quality: medium
Market conditions and
competitiveness
Independent variables
Dependent variable
(Equal Opportunities
treatment indicator)
Table 4.3
-.000
-.000
.013
.051
.048
-.004
-.002
Coeff.
(.328)
(.470)
(.628)
(.041)
(.094)
(.850)
(.914)
pvalue
Review
procedures
-.000
.000
-.021
.009
-.011
.010
-.008
Coeff.
(.584)
(.686)
(.037)
(.396)
(.368)
(.331)
(.465)
pvalue
Equal
Opportunities
impact
measurement
-.001
.000
-.014
-.006
.031
.007
.015
Coeff.
(.218)
(.737)
(.635)
(.796)
(.289)
(.782)
(.561)
pvalue
Review
procedures
concerning
ethnic
background
-.003
.003
.031
-.095
-.108
-.065
-.015
Coeff.
(.039)
(.000)
(.537)
(.007)
(.002)
(.073)
(.699)
pvalue
Home
working
-.002
-.001
.007
.073
.036
-.127
-.131
Coeff.
(.147)
(.530)
(.921)
(.173)
(.513)
(.017)
(.016)
pvalue
Special
paid leave
for family
emergencies
(.150)
(.354)
(.236)
(.342)
(.146)
(.265)
(.865)
pvalue
Continued
-.001
-.001
.068
-.034
.059
-.043
.007
Coeff.
Additional
paid leave for
childcare
48
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
Continued
.380
Organisation size: 100
employees or more
.254
-.130
-.148
Culture of head office: USA
Culture of head office: other
non-UK
Young establishment
B. Additional determinants
of objective productivity
performance or profits
.097
Coeff.
(.025)
(.332)
(.138)
(.000)
(.104)
pvalue
Formal
written policy
Establishment size: 50
employees or more
Establishment characteristics
Independent variables
Dependent variable
(Equal Opportunities
treatment indicator)
Table 4.3
-.011
-.061
.079
.076
.012
Coeff.
(.687)
(.000)
(.130)
(.001)
(.582)
pvalue
Review
procedures
.012
-.024
.125
.010
.006
Coeff.
(.449)
(.047)
(.001)
(.407)
(.612)
pvalue
Equal
Opportunities
impact
measurement
.091
-.058
.040
.072
.025
Coeff.
(.045)
(.005)
(.415)
(.005)
(.331)
pvalue
Review
procedures
concerning
ethnic
background
.025
-.021
.054
-.151
.270
Coeff.
(.628)
(.721)
(.478)
(.000)
(.000)
pvalue
Home
working
-.004
.086
.070
.038
-.037
Coeff.
(.955)
(.395)
(.485)
(.481)
(.452)
pvalue
Special
paid leave
for family
emergencies
(.812)
(.000)
(.199)
(.178)
(.599)
pvalue
Continued
-.010
-.141
.111
.052
.018
Coeff.
Additional
paid leave for
childcare
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
49
Continued
(.001)
(.000)
(.588)
(.391)
(.911)
pvalue
1,516
.184
.107
-.010
.001
-.000
Coeff.
Review
procedures
(.007)
(.360)
(.918)
(.023)
pvalue
1,516
.228
.031
.009
-.000
.001
Coeff.
EO impact
measurement
(.000)
(.220)
(.125)
(.070)
pvalue
1,516
.223
.125
.025
.004
.002
Coeff.
Review
procedures
concerning
ethnic
background
(.394)
(.024)
(.018)
(.558)
pvalue
1,516
.278
.031
-.071
.008
-.001
Coeff.
Home
working
(.372)
(.338)
(.503)
(.791)
pvalue
1,516
.094
.045
.044
-.003
.001
Coeff.
Special
paid leave
for family
emergencies
(.449)
(.125)
(.539)
(.765)
pvalue
1,516
.100
.026
.049
.002
-.001
Coeff.
Additional
paid leave for
childcare
Notes: Estimation takes into account survey weights; probit coefficients shown as marginal effects; independent variables include major Standard Industrial
Classification indicators and a constant term; participation in returns variable constructed from factor analysis of indicators of performance-related pay,
profit-related pay, employee share schemes; participation in control variable constructed from factor analysis of indicators of briefing between managers and
workers, joint consultative committees, and quality circles; independence in work variable constructed from factor analysis of indicators of the extent of variety
in work, discretion in work, control over pace of work, and design of work; sample includes private sector trading establishments.
Source: WERS 2004.
1,471
.175
Human resource manager/
owner qualified in personnel
management
(.011)
.358
.118
Human resource manager/
owner is female
(.122)
Sample (unweighted)
.010
Share of employees with a
disability
(.895)
pvalue
Pseudo R-squared
-.000
Coeff.
Formal
written policy
Share of TTWA population from
ethnic minority background
C. Independent of
productivity performance
Independent variables
Dependent variable
(Equal Opportunities
treatment indicator)
Table 4.3
50
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
4.4.2
Instrumental variables
Next we look at the variables included in modelling treatment selection that are
unrelated to subjective productivity performance (B and C in Table 4.3). To the
extent that this set of variables explains the presence of Equal Opportunities policies
and practices we can use them as instrumental variables to aid identification of
causal impacts, assuming that the correlation with Equal Opportunities and their
independence of business outcomes is justified on theoretical grounds.
Both the gender and occupational training of the human resource manager are
important determinants of whether or not establishments have formal written
policies on Equal Opportunities. The latter is also an important determinant
of review procedures concerning Equal Opportunities and other general Equal
Opportunities practices. The culture of the head office is also an important
determinant of the presence of Equal Opportunities policies and practices. These
policies are more likely to be adopted in workplaces where the culture of the
head office is US-influenced; and less likely to be adopted in workplaces where
the culture of the head office is non-UK and non-US. The share of employees
with a disability is an important covariate of home working, as is the gender of
the human resource manager or establishment owner, although the sign of the
latter effect is perhaps surprising if we consider that home working is a familyfriendly policy that promotes equality on the basis of gender. The share of the
population in the local Travel-to-Work Area from an ethnic minority background
is an important determinant of the workplace incidence of measuring the effects
of Equal Opportunities policies and the incidence of review procedures to identify
indirect discrimination on the basis of ethnic background.
None of these variables influence subjective productivity performance in the
model illustrated in Table 4.2. Thus, for most of our treatment indicators we have
several potential instrumental variables.14 We note that in terms of the variables
discussed here, the incidence of family-friendly practices measured by special paid
leave for family emergencies or additional paid leave for childcare, is least well
explained. In particular, we do not have many strong covariates of these treatment
indicators that are independent of business performance. In other words, we do
not have strong instrumental variables for these two treatment indicators, limiting
our ability to identify the causal impacts of these policies.
14
We repeat this modelling exercise to identify potential instrumental variables
for each Equal Opportunities indicator separately for the different measures
of business performance.
51
52
Identifying the effect of Equal Opportunities on business outcomes
using WERS 2004
4.5
Summary
To summarise, identifying the causal impact of Equal Opportunities policies and
practices on business performance is complicated by the possibility that high
performance workplaces may be more likely to adopt these policies and practices.
To deal with this potential endogeneity problem we use instrumental variables and
propensity score methods to assess the impacts of Equal Opportunities policies
and practices on business performance.
In the first instance we need to model business performance. WERS 2004 offers
both subjective and objective measures of workplace productivity and financial
performance. The subjective measures are prone to a number of measurement
problems. The objective measures are only available for a small sample of
workplaces. Each of these business performance indicators can be reasonably
explained by the additional information available in WERS 2004. However, there
remains significant unexplained variation in workplace performance, which we
cannot account for with the information available.
The adoption of Equal Opportunities policies and practices depends on many of
the same factors that determine business performance. We are able to construct
instrumental variables for several indicators of Equal Opportunities. We do not
have good instrumental variables for all family-friendly policies, which makes it
more difficult to identify the causal impacts of these on business performance.
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
5
Estimates of the
relationship between
Equal Opportunities and
business outcomes using
WERS 2004
5.1
Sample correlations between Equal Opportunities
and business performance
Before discussing the results of our econometric analysis of the relationship between
Equal Opportunities and business outcomes and the extent to which these are
likely to identify causal impacts, it is instructive to look at the simple correlations in
the data between Equal Opportunities and business performance. Table 5.1 shows
the mean differences in business performance between establishments with and
without Equal Opportunities policies/practices. These are cross-tabulations of the
data and should not be interpreted as the effects of Equal Opportunities policies
and practices on business performance: correlation, not causation, is reported. Our
estimates of the impact of Equal Opportunities policies and practices on business
performance are reported in a separate section (Section 5.2 and Tables 5.2-5.8).
In Table 5.1 a positive (negative) number implies that establishments with a
particular Equal Opportunities policy or practice are more (less) likely to have higher
productivity or profits than establishments without such a policy. We show these
cross-tabulations for the three different samples included in our analysis: private
sector workplaces, private sector workplaces with 50 employees or more and
private sector workplaces included in the Financial Performance Questionnaire. In
the latter, business performance is measured by the objective data on productivity
and profits per employee.
53
54
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Interestingly, the differences in business performance by treatment status are
large in the subjective data in comparison to the objective data, although these
data are not directly comparable as they have completely different scales/metrics.
Also, the correlation of differences in profits with differences in productivity across
treatment status is positive in the objective data, i.e. if, on average, workplaces
with a particular Equal Opportunities practice are more (less) productive, they are
also more (less) profitable. The correlation of differences in profits with differences
in productivity varies across treatment status in the subjective performance data.
These factors point to the limitations of using measures of perceptions of business
performance when modelling the relationship between Equal Opportunities and
productivity and profits.
Now consider in turn the four sets of Equal Opportunities policies and practices
that we analyse: formal policies; monitoring and reviewing practices; practices
concerning ethnic background; and family-friendly practices. Looking at
Equal Opportunities policies, workplaces with formal written policies on Equal
Opportunities or managing diversity are significantly less likely to report above
average productivity. For those workplaces with formal policies, the percentage
reporting above average productivity is 11.2 percentage points less than for those
workplaces without formal written policies. For the sake of comparison between
productivity and profit effects, Table 5.1 also shows the difference in the proportion
of workplaces reporting above average productivity for the sample of firms that
interpret financial performance as profits. The tendency for workplaces with
formal written policies on Equal Opportunities to report relatively poor productivity
performance, as measured by the subjective indicator, is at least as strong in
this sample. This negative association between Equal Opportunities policies and
productivity performance is not always apparent for larger workplaces and does
not appear amongst private sector workplaces in the Financial Performance
Questionnaire where productivity is measured objectively. In all the samples in
Table 5.1, workplaces with formal written policies on Equal Opportunities are
likely to be more profitable than workplaces without, although the difference is
never statistically significant.
-.007
-.039
The impacts of Equal
Opportunities policies in the
workplace are measured
-.112**
Promotion procedures or relative
pay rates are reviewed to
identify indirect discrimination
by gender, ethnic background,
disability or age
Equal Opportunities practices
The workplace, or the
organisation of which it is
a part, has a formal written
policy on equal opportunities or
managing diversity
Equal Opportunities policies
(all)
.015
-.092
-.138**
(including
in profit
sample)
Difference in
proportion reporting
above average
productivity
.066
.058
.054
Difference in
proportion
reporting
above average
profits
Private sector workplaces
.014
-.028
-.023
(all)
-.029
.009
.026
(including
in profit
sample)
Difference in
proportion reporting
above average
productivity
Private sector workplaces
included in the financial
performance sample
.120*
.104
.121
-.08
.03
.07
Continued
-.06
.01
.04
Difference in
proportion
Difference
reporting
in log gross
Difference in
above average value added
log profits
profits
per employee per employee
Private sector workplaces with
50 employees or more
Difference in business performance between establishments with and without Equal Opportunities
policies/practices
Policy or practice
Table 5.1
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
55
Continued
-.090*
Time off for childcare is usually
taken as special or paid parental
leave (other than maternity and
paternity leave and emergency
leave)
-.034
.107**
.097
-.045
.059
.043
.005
.134*
Difference in
proportion
reporting
above average
profits
-.010
-.086*
-.038
.040
(all)
-.041
-.078
-.073
.056
(including
in profit
sample)
Difference in
proportion reporting
above average
productivity
Private sector workplaces
included in the financial
performance sample
.095
.009
-.017
.109*
.07
.06
.08
-.00
.09
.05
.10
-.02
Difference in
proportion
Difference
reporting
in log gross
Difference in
above average value added
log profits
profits
per employee per employee
Private sector workplaces with
50 employees or more
Notes: *** indicates statistically significant at the one per cent level; ** indicates statistically significant at the five per cent level; * indicates statistically
significant at the ten per cent level; point estimates and standard errors take into account survey weights; estimated productivity differentials in the ‘including
in profit sample’ are shown for direct comparison to estimated profit differentials (this sample is filtered on the variable KERFIS=1).
Source: WERS 2004.
.062
.100**
.013
(all)
(including
in profit
sample)
Difference in
proportion reporting
above average
productivity
Private sector workplaces
Time off for family emergencies
is usually taken as special paid
leave
For some employees working
time arrangements include
working at, or from, home in
normal working hours
Family-friendly practices
Recruitment or promotion
procedures or relative pay
rates are reviewed to identify
indirect discrimination by ethnic
background
Equal Opportunities
practices concerning ethnic
background
Policy or practice
Table 5.1
56
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
The correlations in the data between our two measures of Equal Opportunities
monitoring and reviewing practices and business performance are also wideranging. On both treatment indicators it appears that Equal Opportunities
monitoring and reviewing practices are associated with relatively poor productivity
performance in the full sample of private sector workplaces. For large workplaces
and for workplaces included in the profit sample, this is only the case for review
procedures to identify indirect discrimination. For large workplaces in the profit
sample and for workplaces in the financial performance sample this is only the case
for our other indicator of Equal Opportunities monitoring and reviewing practices.
None of these differences in productivity outcomes are significant. It also appears
that workplaces with Equal opportunities monitoring and reviewing practices, as
measured here, are more likely to report above-average profits. Amongst larger
workplaces this difference in performance is statistically significant.
Workplaces with review procedures concerning ethnic background are more
likely to report above average profits. Amongst workplaces with such procedures,
the percentage reporting above-average productivity is 13.4 percentage points
higher than amongst workplaces where there are no such procedures. Amongst
large workplaces the difference is 10.9 percentage points. These differences are
statistically significant, but do not appear in the financial performance sample
where profits are measured from the objective data.
Amongst private sector workplaces with family-friendly practices such as home
working and special paid leave for family emergencies, both profits and productivity
are higher than in private sector workplaces without these practices. This is
regardless of whether performance is measured on the subjective or objective
data. Amongst large workplaces this relationship is reversed. Workplaces where
time off for childcare is usually taken as special paid or parental paid leave are
more likely to report average or below average productivity than workplaces
without these practices, but this relationship does not appear when productivity
is measured by gross value added. Workplaces with these family-friendly leave
practices are more likely to report above-average profits.
The picture of the relationship between Equal Opportunities policies and practices
and business performance that emerges from these cross-tabulations of the data
is very mixed. At one level this might be expected given the range of practices
we consider, as discussed in Chapter 2. However, the mixed picture also arises
because of differences across samples and business performance measures, if
anything, suggestive of a complex relationship between Equal Opportunities and
business performance.
57
58
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
5.2
Estimates of the effects of Equal Opportunities on
business performance
The tables in the following sections of this chapter provide estimates of the effects
on workplace performance of having in place Equal Opportunities policies and
practices. Here we provide a brief explanation of the layout of these. Further
details of the individual statistical models are provided in Appendix C.
Each table (Tables 5.2-5.8) gives estimates for one particular measure of Equal
Opportunities policy or practice (treatment indicator). The text accompanying
the tables (in Sections 5.2.1-5.2.4) gives our interpretation of these results and is
divided into four sections, reflecting the four different sets of Equal Opportunities
measures. The upper (lower) half of each table gives estimates of the effect of
Equal Opportunities on business productivity (profits). For each business outcome
(productivity or profits) each table shows three sets of results, distinguished by
outcome measure and sample. The first of these is the subjective indicator of
business performance derived from the Workplace Employment Relations Survey
(WERS 2004) Management Questionnaire, equal to one if business performance
is reported to be above average and zero otherwise, and the second of these is
the natural logarithm of gross value added per employee or profits per employee
derived from the WERS 2004 Financial Performance Questionnaire linked to the
Annual Respondents Database. The last set of results refers to the subjective
performance indicator, where the sample is restricted to workplaces with 50
employees or more.
All results represent estimates of the average treatment effect on the treated (ATT),
i.e. the average effect of having in place a particular Equal Opportunities policy
or practice amongst those who have these in place, under different identifying
assumptions, i.e. different assumptions about the nature of endogeneity and
the way this is dealt with. In the case of the subjective performance outcome
measure, the ATT measures the percentage point difference in the probability of
reporting above-average performance associated with having in place a particular
Equal Opportunities policy or practice. In the case of the objective performance
outcome measure the ATT measures the per cent difference in outcomes (gross
value added or profits per head) associated with having in place a particular Equal
Opportunities policy or practice. We report in brackets the probability that the ATT
is zero based on the standard error and central estimate of the ATT.
5.2.1
Workplace performance and Equal Opportunities policies
Table 5.2 reports estimates of the workplace performance effects of having
a written policy on Equal Opportunities or managing diversity. The simple
probit model of subjective productivity performance that assumes treatment is
exogenously determined is suggestive of a negative and statistically significant
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
relationship between Equal Opportunities policies and workplace productivity [.141 (.016)].15 This echoes the findings in the raw data illustrated in Table 5.1. The
ATT based on the propensity score estimates show a similar picture [-.131 (.001); .093 (.001)], but there are two reasons in particular why we would be reluctant to
interpret these propensity score estimates (and equally the simple probit/exogenous
treatment estimate) as evidence of a causal impact from Equal Opportunities
policies to productivity. First, because a large proportion of establishments have
written policies on Equal Opportunities, there are relatively few establishments
against which to benchmark the treated. The few workplaces without policies
are repeatedly used to compare against the broad range of workplaces that have
written Equal Opportunities policies. Second, although the mean propensity score
is similar between the matched sample of the treated (establishments with formal
written policies) and the non-treated (establishments without formal written
policies), other important covariates are not balanced between the two groups.
Most importantly, establishment size remains significantly different between the
treated and non-treated in the matched sample. Indeed, once we focus on large
establishments only, the propensity score estimates no longer suggest a clear
negative correlation between productivity and Equal Opportunities policies [.055
(.159); -.053 (.083)]. These issues suggest that both the propensity score estimates
and the estimates derived under the assumption that the policy is exogenous, are
biased estimates of the true impact of Equal Opportunities policies on business
performance. In particular, once we allow for the possibility that Equal Opportunities
policies are endogenously determined, there does not appear to be any statistically
significant impact of Equal Opportunities policies on workplace productivity, as
measured by the subjective performance indicator [-.040 (.775)].16 Looking at gross
value added per employee, there is similarly no discernable statistically significant
impact of Equal Opportunities policies on productivity, much as suggested by the
comparison of means in the raw data. In conclusion, the analysis discussed so
far does not point to any impact of having a formal written Equal Opportunities
policy on workplace productivity.
Turning to the lower half of Table 5.2, the simple probit model of subjective
financial performance, assuming treatment is exogenously determined, shows
no statistically significant relationship between Equal Opportunities policies and
financial performance [-.017 (.809)]. The estimated ATT based on propensity
score matching is suggestive of a positive and significant impact of Equal
Opportunities on financial performance [.092 (.037); .098 (.004)]. As before, we
15
16
We report the [estimated effect (p-value)] to facilitate cross reference to the
tables of results.
Although the correlation of unobservables in the endogenous treatment
model does not appear to be statistically different from zero judging by
the reported Wald test [-.104 (.726)], this is not a particularly strong test of
exogeneity. Given the problems discussed in relation to the other estimates,
the endogenous treatment model provides the more prudent estimate of
the impact of Equal Opportunities policy on business performance.
59
60
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
have reservations about interpreting these effects as causal due to the availability
of relatively few workplaces that do not have Equal Opportunities policies and
due to the imbalance of important covariates in the matched sample. However,
a statistically significant effect remains in the propensity score based estimates
once we focus on large establishments only [.166 (.001); .140 (.000)]. But, we
note the deterioration in the overall quality of the matched sample as given by the
widening of the difference in the mean propensity score between the treated and
non-treated. Indeed, there are few large establishments that do not have formal
written Equal Opportunities policies. Furthermore, it is questionable whether we
are able to control adequately for significant determinants of business outcomes
for large establishments, i.e. much of the variation in the performance of large
firms remains unexplained. Using instrumental variables to help identify causal
impacts, the ‘endogenous treatment’ model shows a positive effect of Equal
Opportunities policies on the subjective measure of profits [.139 (.233)], but this
effect is not statistically significant at conventional levels and is not supported by
the endogenous treatment model estimated on the objective profits data [-.064
(.247)]. In conclusion, the analysis here does not support either a positive or a
negative effect of Equal Opportunities policies on business’ profits.
To summarise, some of the statistical models estimated here are suggestive of
statistically significant relationships between subjective business performance
and Equal Opportunities policies. However, without further evidence, given the
statistical issues in identifying causal impacts discussed here and taking into
account the range of evidence in Table 5.2, it is unlikely that these relationships
in the data reflect the causal impacts of policy. Finally, as discussed in Chapter 2,
we note that the indicator of Equal Opportunities used here is relatively weak,
i.e. it does not necessarily reflect the presence of Equal Opportunities practices.
This is yet a reason for being wary of interpreting sometimes large and statistically
significant differences in business performance in Table 5.2 as the results of Equal
Opportunities policies.
(.541)
(.930)
.002
(.374)
-.064
Endogenous treatment
.019
(.693)
-.016
(.001)
-.093
Exogenous treatment
Propensity score estimates
Linear regression
Log gross value added per employee
(.001)
(.775)
-.040
Endogenous treatment
-.131
(.016)
-.141
Exogenous treatment
Propensity score estimates
Probit
Estimated effect (pvalue)
K
NN
K
NN
Match
method
.497
.367
Nontreated
.701
.767
Nontreated
.704
.769
Treated
Matched sample
Mean propensity score of
306
306
1051
1051
Match
sample
.173
-.104
Continued
(.390)
(.726)
Correlation of
unobservables
(Chisq probability
that zero)
Estimated workplace performance effects of having a formal written policy on Equal Opportunities
or managing diversity
Subjective indicator of above average
productivity
Table 5.2
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
61
Continued
(.037)
(.004)
.098
(.233)
.139
Endogenous treatment
.092
(.809)
-.017
(.083)
-.053
Exogenous treatment
Propensity score estimates
Probit
Subjective indicator of above average
financial performance
(.159)
(.019)
-.143
(small workplaces)
.055
(.293)
-.117
Estimated effect (pvalue)
Exogenous treatment
Propensity score estimates
Probit
Subjective indicator of above average
productivity – workplaces with 50
employees or more
Table 5.2
K
NN
K
NN
Match
method
.350
.753
Nontreated
.736
.910
Nontreated
.741
.913
Treated
Matched sample
Mean propensity score of
636
636
560
559
Match
sample
-.368
Continued
(.186)
Correlation of
unobservables
(Chisq probability
that zero)
62
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Continued
(.001)
(.000)
.140
(.778)
-.021
(small workplaces)
.166
(.672)
.060
(.812)
Exogenous treatment
Propensity score estimates
Probit
Subjective indicator of above average
financial performance – workplaces with
50 employees or more
(.087)
.004
(.247)
-.064
Endogenous treatment
.047
(.506)
-.017
Estimated effect (pvalue)
Exogenous treatment
Propensity score estimates
Linear regression
Log profits per employee
Table 5.2
K
NN
K
NN
Match
method
.603
.535
Nontreated
.901
.700
Nontreated
.909
.704
Treated
Matched sample
Mean propensity score of
288
288
304
304
Match
sample
.267
(.281)
Correlation of
unobservables
(Chisq probability
that zero)
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
63
64
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
5.2.2
Workplace performance and Equal Opportunities
monitoring and reviewing practices
Table 5.3 reports estimates of the workplace performance effects of reviewing
promotion procedures or relative pay rates to identify indirect discrimination.
Table 5.4 reports estimates of the workplace performance effects associated with
measuring the impacts of Equal Opportunities policies in the workplace. Both are
intended to be indicators of Equal Opportunities policy and practice in general.
Looking first at the results in Table 5.3 regarding subjective measures of business
performance, the different models in which treatment is assumed exogenous show
no statistically significant relationship between Equal Opportunities monitoring
and reviewing practices and business performance. In the instrumental variables
analysis (endogenous treatment) of review procedures the estimated ATT for
productivity is positive and statistically significant [.026 (.033)]. In this model
the correlation of unobservable determinants of both treatment and outcomes
is negative and, although not significant at conventional levels, probably needs
to be accounted for [-.599 (.159)]. In other words it casts more doubt on the
model in which treatment is assumed exogenous. This positive relationship
between productivity and review procedures to identify indirect discrimination is
not supported by the analysis of the gross value added data, where if anything,
the relationship between performance and Equal Opportunities appears negative
[-.085 (.444)], although we note the very small sample available for analysis.
Before considering the results for large workplaces we note that in Table 5.4,
measuring Equal Opportunities monitoring and reviewing practices by whether
or not workplaces evaluate the impacts of their Equal Opportunities policies,
we consistently find no evidence of a statistically significant relationship or
effect of Equal Opportunities monitoring and reviewing practices on business
performance.
Some estimates of the ATT for large firms based on propensity score matching
in Tables 5.3 and 5.4 are suggestive of a positive and significant effect of Equal
Opportunities monitoring and reviewing practices on business performance.
However, we are cautious in interpreting this evidence as conclusive given the
small sample on which the analysis is based and the difficulty, given the data
available, in controlling adequately for the determinants of business performance
in large establishments.
To summarise, the evidence in the data for either a large or widespread impact,
positive or negative, of Equal Opportunities monitoring and reviewing practices on
business productivity or profits is not strong. To the extent there are any positive
effects the data suggest these are more likely to arise in larger establishments.
(.182)
(.194)
-.071
(.444)
(.094)
-.140
-.085
Endogenous treatment
Propensity score estimates
-.115
(.649)
.027
Exogenous treatment
Linear regression
Log gross value added per employee
(.538)
(.033)
(.845)
.051
.026
Endogenous treatment
Propensity score estimates
-.013
Exogenous treatment
Probit
Estimated effect (pvalue)
K
NN
K
NN
Match
method
.080
.097
Nontreated
.314
.194
Nontreated
.319
.194
Treated
Matched sample
Mean propensity score of
69
69
303
302
Match
sample
-.087
-.599
Continued
(.673)
(.159)
Correlation of
unobservables
(Chisq
probability that
zero)
Estimated workplace performance effects of reviewing promotion procedures or relative pay rates
to identify indirect discrimination
Subjective indicator of above average
productivity
Table 5.3
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
65
Continued
(.309)
(.827)
.018
(.193)
(.836)
.094
.015
Endogenous treatment
Propensity score estimates
-.020
(.141)
Exogenous treatment
Probit
Subjective indicator of above average
financial performance
(.128)
.088
(.827)
(.931)
.134
-.017
(small workplaces)
Propensity score estimates
.006
Estimated effect (pvalue)
Exogenous treatment
Probit
Subjective indicator of above average
productivity – workplaces with 50
employees or more
Table 5.3
K
NN
K
NN
Match
method
.076
.174
Nontreated
.212
.345
Nontreated
.212
.347
Treated
Matched sample
Mean propensity score of
154
154
224
224
Match
sample
-.446
Continued
(.193)
Correlation of
unobservables
(Chisq
probability that
zero)
66
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Continued
(.012)
(.015)
.148
(.686)
(.257)
.233
-.047
(small workplaces)
Propensity score estimates
.098
(.369)
Exogenous treatment
Probit
Subjective indicator of above average
financial performance – workplaces with
50 employees or more
(.214)
.025
(.640)
(.190)
.059
-.061
Endogenous treatment
Propensity score estimates
-.084
Estimated effect (pvalue)
Exogenous treatment
Linear regression
Log profits per employee
Table 5.3
K
NN
K
NN
Match
method
.142
.075
Nontreated
.335
.435
Nontreated
.337
.444
Treated
Matched sample
Mean propensity score of
113
112
75
75
Match
sample
-.100
(.796)
Correlation of
unobservables
(Chisq
probability that
zero)
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
67
Propensity score estimates
(.843)
(.662)
.078
(.766)
-.036
-.069
Endogenous treatment
(.789)
(.899)
.009
.023
(.864)
(.771)
-.002
.018
(.490)
-.051
Exogenous treatment
Linear regression
Log gross value added per employee
Propensity score estimates
Endogenous treatment
Exogenous treatment
Probit
Estimated effect (pvalue)
K
NN
K
NN
Match
method
.059
.052
Nontreated
.118
.141
Nontreated
.120
.141
Treated
Matched sample
Mean propensity score of
46
46
197
197
Match
sample
.282
.011
Continued
(.560)
(.976)
Correlation of
unobservables
(Chisq
probability that
zero)
Estimated workplace performance effects of measuring the impacts of Equal Opportunities policies
in the workplace
Subjective indicator of above average
productivity
Table 5.4
68
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Continued
(.764)
(.429)
.076
(.988)
(.578)
.039
-.001
Endogenous treatment
Propensity score estimates
.062
(.218)
Exogenous treatment
Probit
Subjective indicator of above average
financial performance
(.024)
.087
(.507)
(.839)
.178
-.060
(small workplaces)
Propensity score estimates
-.020
Estimated effect (pvalue)
Exogenous treatment
Probit
Subjective indicator of above average
productivity – workplaces with 50
employees or more
Table 5.4
K
NN
K
NN
Match
method
.036
.120
Nontreated
.104
.196
Nontreated
.104
.197
Treated
Matched sample
Mean propensity score of
98
98
147
147
Match
sample
.151
Continued
(.977)
Correlation of
unobservables
(Chisq
probability that
zero)
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
69
Continued
(.361)
(.037)
.138
(.715)
(.299)
.105
.052
(small workplaces)
Propensity score estimates
.097
(.583)
.077
Exogenous treatment
Probit
Subjective indicator of above average
financial performance – workplaces with
50 employees or more
(.649)
.067
(.899)
-.020
Endogenous treatment
Propensity score estimates
(.507)
.045
Estimated effect (pvalue)
Exogenous treatment
Linear regression
Log profits per employee
Table 5.4
K
NN
K
NN
Match
method
.107
.047
Nontreated
.251
.090
Nontreated
.253
.091
Treated
Matched sample
Mean propensity score of
77
77
47
47
Match
sample
.280
(.181)
Correlation of
unobservables
(Chisq
probability that
zero)
70
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
5.2.3
Workplace performance and Equal Opportunities practices
concerning ethnic background
Table 5.5 reports our findings regarding the effects on workplace performance of
reviewing recruitment or promotion procedures, or relative pay rates, to identify
indirect discrimination on the grounds of ethnic background. Estimates of the ATT
are generally positive, but statistically no different from zero, with the exception
of the ATT estimated from the objective performance data using linear regression
methods, where estimates of the ATT are negative, again not statistically significant.
The regularity in the sign of the estimated ATT and the estimates derived from the
propensity score models both point to the possibility that there is a positive effect
of these practices on business performance. The propensity score estimates are in
some instances nearly significant at the ten per cent level [.130 (.119); .122 (.110)]
and in others (in the objective profits data [.121 (.046); .081 (.053)] and kernel
matching estimates for large establishments [.159 (.002); .168 (.003)]) statistically
significant at conventional levels (although, judging by the poor quality of the
match indicated by the difference between the mean propensity score of the nontreated (.347) and the treated (.362) in the matched sample, the propensity score
estimates on the objective profits data are questionable). Taken together, there is
little evidence in the data to suggest either a strong or widespread effect of Equal
Opportunities practices concerning ethnic background on business performance.
At the same time, it is difficult on the basis of these results to rule out entirely
the potential existence of some positive impact from these practices on business
performance in large establishments.
71
Propensity score estimates
(.123)
(.600)
.043
(.348)
.160
-.110
Endogenous treatment
(.935)
(.245)
.064
-.007
(.119)
(.444)
.018
.130
(.558)
.037
Exogenous treatment
Linear regression
Log gross value added per employee
Propensity score estimates
Endogenous treatment
Exogenous treatment
Probit
Estimated effect (pvalue)
K
NN
K
NN
Match
method
.112
.116
Nontreated
.328
.236
Nontreated
.329
.236
Treated
Matched sample
Mean propensity score of
80
80
344
344
Match
sample
.297
-.288
Continued
(.101)
(.492)
Correlation of
unobservables
(Chisq
probability that
zero)
Estimated workplace performance effects of reviewing recruitment or promotion procedures or
relative pay rates to identify indirect discrimination on the grounds of ethnic background
Subjective indicator of above average
productivity
Table 5.5
72
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Continued
(.240)
(.110)
.122
(.742)
(.210)
.164
.006
Endogenous treatment
Propensity score estimates
.115
(.002)
Exogenous treatment
Probit
Subjective indicator of above average
financial performance
(.112)
.043
(.629)
(.479)
.097
.035
(small workplaces)
Propensity score estimates
.046
Estimated effect (pvalue)
Exogenous treatment
Probit
Subjective indicator of above average
productivity – workplaces with 50
employees or more
Table 5.5
K
NN
K
NN
Match
method
.079
.209
Nontreated
.187
.362
Nontreated
.188
.363
Treated
Matched sample
Mean propensity score of
169
168
249
249
Match
sample
-.032
Continued
(.955)
Correlation of
unobservables
(Chisq
probability that
zero)
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
73
Continued
(.137)
(.003)
.168
(.312)
(.127)
.140
.113
(small workplaces)
Propensity score estimates
.121
(.314)
Exogenous treatment
Probit
Subjective indicator of above average
financial performance – workplaces with
50 employees or more
(.705)
.081
(.314)
(.705)
.121
-.098
Endogenous treatment
Propensity score estimates
.026
Estimated effect (pvalue)
Exogenous treatment
Linear regression
Log profits per employee
Table 5.5
K
NN
K
NN
Match
method
.174
.112
Nontreated
.322
.347
Nontreated
.324
.362
Treated
Matched sample
Mean propensity score of
128
128
83
83
Match
sample
.307
(.082)
Correlation of
unobservables
(Chisq
probability that
zero)
74
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
5.2.4
Workplace performance and family-friendly practices
Tables 5.6-5.8 show our estimates of the workplace performance effects of three
different indicators of family-friendly practices: working time arrangements include
working from home in normal working hours; time off for family emergencies is
usually taken as special paid leave; time off for childcare is usually taken as special
or parental paid leave.
In Table 5.6, where the treatment indicates the presence of working time
arrangements that include working from home in normal working hours, the sign
of the estimated ATT on productivity is consistently positive in the subjective and
objective performance models, similar to the findings in the raw data illustrated in
Table 5.1. The ATT effect estimated using propensity score methods is significantly
different from zero in some cases. When we break the sample into small and large
establishments, we find some evidence of a statistically significant negative impact
on productivity of working from home in larger establishments. In contrast, the
effect of facilitating these family-friendly practices appears to be largely unrelated
to business profits, although there is some evidence of a positive effect on profits
in large establishments.
75
Propensity score estimates
(.076)
(.220)
.065
(.640)
.159
.027
Endogenous treatment
(.383)
(.080)
.075
.047
(.546)
(.809)
.011
.032
(.594)
.030
Exogenous treatment
Linear regression
Log gross value added per employee
Propensity score estimates
Endogenous treatment
Exogenous treatment
Probit
Estimated effect (pvalue)
K
NN
K
NN
Match
method
.143
.166
Nontreated
.330
.456
Nontreated
.335
.458
Treated
Matched sample
Mean propensity score of
158
158
489
489
Match
sample
.037
-.023
Continued
(.729)
(.955)
Correlation of
unobservables
(Chisq
probability that
zero)
Estimated workplace performance effects of working time arrangements that include working
from home in normal working hours
Subjective indicator of above average
productivity
Table 5.6
76
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Continued
(.950)
(.665)
-.023
(.917)
(.521)
.005
-.006
Endogenous treatment
Propensity score estimates
.045
(.118)
Exogenous treatment
Probit
Subjective indicator of above average
financial performance
(.082)
-.071
(.415)
(.151)
-.100
.053
(small workplaces)
Propensity score estimates
-.093
Estimated effect (pvalue)
Exogenous treatment
Probit
Subjective indicator of above average
productivity – workplaces with 50
employees or more
Table 5.6
K
NN
K
NN
Match
method
.191
.287
Nontreated
.411
.535
Nontreated
.414
.540
Treated
Matched sample
Mean propensity score of
294
294
346
346
Match
sample
.113
Continued
(.801)
Correlation of
unobservables
(Chisq
probability that
zero)
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
77
Continued
(.061)
(.188)
.069
(.511)
(.997)
.161
.052
(small workplaces)
Propensity score estimates
.000
(.638)
Exogenous treatment
Probit
Subjective indicator of above average
financial performance – workplaces with
50 employees or more
(.126)
.014
(.428)
(.503)
.071
.075
Endogenous treatment
Propensity score estimates
.037
Estimated effect (pvalue)
Exogenous treatment
Linear regression
Log profits per employee
Table 5.6
K
NN
K
NN
Match
method
.284
.122
Nontreated
.523
.472
Nontreated
.526
.478
Treated
Matched sample
Mean propensity score of
182
182
162
162
Match
sample
-.186
(.480)
Correlation of
unobservables
(Chisq
probability that
zero)
78
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
In Table 5.7 we report estimates of the effect of arrangements where time off for
family emergencies is usually taken as special paid leave. Looking at the effects of
these practices on subjective productivity performance they appear positive and in
some cases statistically significant. The estimated ATT is positive in the probit model
where treatment is assumed exogenous and close to being significant at the 10
per cent level [.074 (.110)]. Once we allow for endogeneity of the treatment, the
ATT rises substantially and becomes very significant statistically [.254 (.000)]. This
result needs to be interpreted with caution given the lack of instrumental variables
for this particular treatment indicator, as discussed in Section 4.4. However, the
need to take into account endogeneity is illustrated by the estimated correlation
of unobservable determinants of productivity and these practices [-.986 (.059)].
The propensity score estimates are also positive and in the case of kernel matching
statistically significant at the five per cent level [.075 (.023)]. However, this positive
relationship between family-friendly practices and workplace productivity is not
supported by the models estimated on the objective data. Given the results
reported for large establishments, any significant productivity effects are more
likely to be observed in smaller establishments. There does not appear to be any
particularly strong relationship between arrangements where time off for family
emergencies is usually taken as special paid leave and business profits, although
the propensity score estimates of the effect on profits per employee [.054 (.081);
.042 (.296)] may be suggestive of a positive link.
79
Propensity score estimates
(.762)
(.411)
.033
(.747)
-.021
-.027
Endogenous treatment
(.987)
(.023)
.075
-.001
(.398)
(.000)
.254
.038
(.110)
.074
Exogenous treatment
Linear regression
Log gross value added per employee
Propensity score estimates
Endogenous treatment
Exogenous treatment
Probit
Estimated effect (pvalue)
K
NN
K
NN
Match
method
.296
.374
Nontreated
.507
.494
Nontreated
.509
.494
Treated
Matched sample
Mean propensity score of
200
200
684
684
Match
sample
.097
-.986
Continued
(.650)
(.059)
Correlation of
unobservables
(Chisq
probability that
zero)
Estimated workplace performance effects of arrangements where time off for family emergencies
is usually taken as special paid leave
Subjective indicator of above average
productivity
Table 5.7
80
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Continued
(.420)
(.470)
.031
(.221)
(.614)
.049
.146
Endogenous treatment
Propensity score estimates
.029
(.843)
Exogenous treatment
Probit
Subjective indicator of above average
financial performance
(.497)
.042
(.072)
(.199)
-.008
.092
(small workplaces)
Propensity score estimates
-.075
Estimated effect (pvalue)
Exogenous treatment
Probit
Subjective indicator of above average
productivity – workplaces with 50
employees or more
Table 5.7
K
NN
K
NN
Match
method
.367
.432
Nontreated
.471
.500
Nontreated
.472
.501
Treated
Matched sample
Mean propensity score of
381
381
395
395
Match
sample
-.530
Continued
(.385)
Correlation of
unobservables
(Chisq
probability that
zero)
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
81
Continued
(.304)
(.638)
.026
(.529)
(.376)
.075
.040
(small workplaces)
Propensity score estimates
-.066
(.296)
Exogenous treatment
Probit
Subjective indicator of above average
financial performance – workplaces with
50 employees or more
(.081)
.042
(.980)
(.703)
.054
-.002
Endogenous treatment
Propensity score estimates
-.014
Estimated effect (pvalue)
Exogenous treatment
Linear regression
Log profits per employee
Table 5.7
K
NN
K
NN
Match
method
.371
.282
Nontreated
.474
.579
Nontreated
.476
.583
Treated
Matched sample
Mean propensity score of
222
222
203
203
Match
sample
-.029
(.922)
Correlation of
unobservables
(Chisq
probability that
zero)
82
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
In Table 5.8 we illustrate the effect on workplace performance of arrangements
where time off for childcare is usually taken as special paid or paid parental leave,
other than maternity and paternity leave and time off for emergencies. The simple
probit model of subjective productivity performance that assumes treatment is
exogenously determined gives a negative and statistically significant estimate of the
ATT. Estimates of the ATT based on the propensity score model are also negative,
but are not significant at conventional levels. The negative effect in the ‘exogenous
treatment’ model is not found in the ‘endogenous treatment’ model [.046 (.558)],
nor is it found in the models estimated on the objective data, suggesting we
should not rush to conclude that these practices reduce workplace productivity.
To the extent that there is a negative effect of these practices on workplace
productivity, the results for large and small establishments suggest this arises in
small establishments. The estimated ATT on profits is insignificantly different from
zero, except when profits are measured by the subjective performance indicator
and treatment is assumed endogenous [.055 (.000)], and in large establishments
[.194 (.034); .106 (.056)]. We note that lack of good instrumental variables for
this treatment indicator, as discussed in Section 4.4, suggests that the results from
the ‘endogenous treatment’ model should be interpreted with caution.
83
Propensity score estimates
(.429)
(.111)
.089
(.844)
.102
-.022
Endogenous treatment
(.171)
(.171)
-.064
.054
(.164)
(.558)
.046
-.096
(.022)
-.127
Exogenous treatment
Linear regression
Log gross value added per employee
Propensity score estimates
Endogenous treatment
Exogenous treatment
Probit
Estimated effect (pvalue)
K
NN
K
NN
Match
method
.163
.175
Nontreated
.371
.270
Nontreated
.373
.270
Treated
Matched sample
Mean propensity score of
Estimated workplace performance effects of arrangements where time off
for childcare is usually taken as special or parental paid leave
Subjective indicator of above average
productivity
Table 5.8
118
118
366
366
Match
sample
.185
-.559
Continued
(.480)
(.547)
Correlation of
unobservables
(Chisq
probability that
zero)
84
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Continued
(.715)
(.883)
.009
(.000)
(.824)
-.032
.055
Endogenous treatment
Propensity score estimates
-.016
(.123)
Exogenous treatment
Probit
Subjective indicator of above average
financial performance
(.570)
.076
(.025)
(.621)
.037
-.142
(small workplaces)
Propensity score estimates
-.030
Estimated effect (pvalue)
Exogenous treatment
Probit
Subjective indicator of above average
productivity – workplaces with 50
employees or more
Table 5.8
K
NN
K
NN
Match
method
.142
.256
Nontreated
.257
.323
Nontreated
.258
.324
Treated
Matched sample
Mean propensity score of
197
197
236
235
Match
sample
-.853
Continued
(.429)
Correlation of
unobservables
(Chisq
probability that
zero)
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
85
Continued
(.034)
(.056)
.106
(.792)
(.837)
.194
-.022
(small workplaces)
Propensity score estimates
.017
(.227)
.061
Exogenous treatment
Probit
Subjective indicator of above average
financial performance – workplaces with
50 employees or more
(.939)
.004
(.350)
-.092
Endogenous treatment
Propensity score estimates
(.227)
.036
Estimated effect (pvalue)
Exogenous treatment
Linear regression
Log profits per employee
Table 5.8
K
NN
K
NN
Match
method
.229
.156
Nontreated
.352
.579
Nontreated
.354
.583
Treated
Matched sample
Mean propensity score of
133
133
122
122
Match
sample
.482
(.173)
Correlation of
unobservables
(Chisq
probability that
zero)
86
Estimates of the relationship between Equal Opportunities and business
outcomes using WERS 2004
Summary and conclusions
6 Summary and conclusions
6.1
Introduction
This study has tried to address the relationship between Equal Opportunities
policies and practices and business benefits in all its complexity. It has described
the processes by which Equal Opportunities policies and practices might affect
business performance. It has analysed the extent to which a range of Equal
Opportunities policies and practices affect profits and profitability for employers
in aggregate and for certain subsets (by size and sector). This chapter highlights
the main findings of the study, draws out implications for policy and identifies
areas for further research.
6.2
Linkages between Equal Opportunities policies and
practices and business performance
The relationship between Equal Opportunities policies and practices and business
performance is complex. The complexity mainly arises from the range of routes
by which an Equal Opportunities policy or practice in an organisation might affect
business performance. Routes may be direct or indirect, affecting one or more sets
of intermediate outcomes en route. Moreover, Equal Opportunities policies and
practices incur costs, as well as benefits.
Complexity in identifying the business performance effects of Equal Opportunities
policies and practices also results from differences in the extent to which they are
implemented and to which they are effective for equality. Nominally similar policies
or practices in two different organisations may, in reality, differ extensively. At the
extreme, there are ‘empty-shell’ policies, where an Equal Opportunities policy is
merely a statement. Therefore, even nominally similar policies and practices will
have differing effects on business performance.
Business performance effects depend not only on the Equal Opportunities policies
and practices but also on other factors affecting the establishment. Net benefits to
an organisation may be positive or negative, depending on the Equal Opportunities
practice, the organisation’s characteristics and its circumstances. There is no reason
87
88
Summary and conclusions
to assume that different types of Equal Opportunities policies and practices have
the same effects on business performance. Nor is there reason to assume that
the same type of Equal Opportunities policy or practice has the same effect in
different business and organisational contexts.
6.3
Limitations of the evaluation of the impacts of
Equal Opportunities policies and practices on
business performance using WERS 2004
The study was able to examine the performance effects of Equal Opportunities
policies and practices in considerable depth but the study also has significant
limitations and it is important to bear these in mind. These stemmed primarily
from data limitations, in respect of variables and sample sizes, exacerbated by the
pattern of implementation of policies and practices.
The data collected through the Workplace Employment Relations Survey 2004
(WERS 2004) includes rich information on Equal Opportunities policies and
practices and provides a useful tool for assessing the relationship between Equal
Opportunities and business performance but there are a number of issues that
make it difficult to draw robust conclusions about these linkages.
Robust performance measures (i.e. productivity and profit measures based on
accounts data) are only available for a small subset of the WERS 2004 sample.
This reduced the likelihood of identifying performance effects. For the full sample,
subjective measures of performance (namely, the WERS 2004 management
respondent’s subjective evaluation of productivity and financial performance in
the workplace benchmarked against the industry) were used. However, these
subjective assessments are prone to measurement error, thus reducing the reliability
of the findings.
Whilst the study examined the effect of a range of Equal Opportunities policies and
practices, this was still limited. In respect of Equal Opportunities policies, using WERS
2004 only formal, written policies can be assessed. The exclusion of informal (or
unwritten) Equal Opportunities policies is likely to lead to an underestimate of the
magnitude of the effect of Equal Opportunities policies on business performance.
In respect of Equal Opportunities practices, budget as well as data constraints
meant that whilst a number of generic policies and practices were explored, there
was some concentration on gender and race equality practices.
Sample sizes in WERS 2004 are relatively small, reducing the likelihood of identifying
performance effects. This problem was accentuated by the need to look at subsamples of the data, due to measurement issues and the correlation of policy
with other factors affecting business outcomes. For example, Equal Opportunities
policies and practices are highly coincident with workplace size and other factors
that are correlated with business performance such that subset analysis is to be
preferred.
Summary and conclusions
The complexity of the linkages between Equal Opportunities policies and practices
and business performance (differences in implementation and the range of routes
by which performance effects might occur) increases the need for detailed high
quality data. WERS 2004 provides some of the most extensive data for our
purposes, but, as a survey covering a wide range of issues, it could not capture
all the data useful to this evaluation. Moreover, as a cross-sectional dataset, our
ability to control for unobserved differences between establishments was reduced.
Both of these issues reduce the likelihood of identifying the performance effects
of policy accurately.
6.4
Evidence of the effects of Equal Opportunities
policies and practices on business performance
using WERS 2004
It is difficult to argue that the business benefits of Equal Opportunities policies and
practices are large and widespread amongst the establishments which implement
these. However, we cannot rule out that certain Equal Opportunities practices
may be associated with enhanced workplace productivity.
• There are some statistically significant relationships between subjective business
performance and Equal Opportunities policies, but these are unlikely to reflect
the causal impacts of policy.
• The evidence in the data for either a large or widespread impact, positive or
negative, of Equal Opportunities monitoring and reviewing practices on
business productivity or profits is not strong.
• To the extent there are any positive effects on business productivity or profits
of Equal Opportunities monitoring and reviewing practices, these are more
likely to arise in larger establishments.
• There is some, but limited, evidence to suggest there are positive effects of
some family-friendly practices on business productivity and profits. To the
extent there are positive productivity (profit) effects these are more likely to arise
in smaller (larger) establishments.
• The evidence does not support the notion that Equal Opportunities policies
and practices place disproportionate burdens on business. In other words,
Equal Opportunities policies and practices do not appear to cost the private
sector profits.
• There is no evidence that Equal Opportunities policies and practices result in
a net cost (or benefit) to employers in aggregate (i.e. on average). However, it
is likely that some employers will derive net benefits from implementing Equal
Opportunities policies and practices and others will see a net cost.
89
90
Summary and conclusions
6.5
Policy implications
Equality of opportunity in the labour market may bring economic and social
benefits. Notably, it can increase the supply of labour and improve the efficiency
with which human resources are used, reducing labour costs and raising aggregate
income. It may also help to reduce social inequalities. Individuals, society at large,
and individual businesses may all share in these benefits. At the same time, the
evidence presented in this report, suggests that, on average, individual employers
do not necessarily gain (nor lose) from implementing policies and practices to
promote equality of opportunity. The implication is that there is likely to be a
difference between the private and public costs and benefits of Equal Opportunities
policies and practices. Addressing this market failure might lead to an increase
in economic and social well-being. Two standard measures to address market
failure could be useful: regulation and changing the net costs to employers, either
through subsidies or penalties.
6.5.1
Regulation
Currently, regulation requires employers not to discriminate in employment with
respect to six equality groups (by gender, race and ethnicity, faith and belief,
disability, sexual orientation and age below the age of 65). In addition, there are
statutory requirements in respect of family-friendly working practices and leave
(e.g. maternity and paternity leave) and the requirement to make reasonable
adjustments in respect of disabled employees. Regulatory requirements are greater
for the public sector, with public sector employers required to promote equality (in
respect of certain equality groups) and to publish a Race Equality Scheme. Some
parts of the public sector have further equality reporting requirements. Equality
could be enhanced through expanding the range of Equal Opportunities policies
and practices required. This could include, for example, requiring employers to
monitor and review policies and practices by equality group, requiring equality
audits and requiring publication of monitoring data. Extending rights to flexible
working and time off would be a second approach, as would requiring Equal
Opportunities training. Other approaches would be to strengthen the antidiscrimination legislation, for example, to allow group actions.
6.5.2
Changing the net costs: subsidies and penalties
The second approach is to bring the private and public costs and benefits of
Equal Opportunities policies and practices closer together. This could be done
either through subsidising employers for implementing policies and practices or
raising the cost of non-implementation. The latter could be done through contract
compliance, i.e. requiring Government (or public sector) sub-contractors to have
certain Equal Opportunities policies and practices. Both approaches are already
used in the public sector. For example, there has been a long-standing policy
of subsidy of maternity leave payments, whilst some public sector organisations
require evidence (or statements) of equality of opportunity. Subsidies or penalties
could be tied to specific or general policies and practices.
Summary and conclusions
Subsidy would encounter the problem of deadweight, i.e. subsidies would go
to employers who would have implemented policies and practices without the
subsidy, as well as to those who would have not. This could be reduced by directing
subsidies towards those employers for whom the Equal Opportunities policies and
practices would have a net cost (and away from those where there would be a
net benefit). The evidence from this study provides weak support for targeting
subsidies at smaller establishments for implementing monitoring and reviewing
practices and some family-friendly practices.
The contract compliance approach may be useful but has the obvious limitation
that it would only apply to sub-contractors and suppliers to the public sector.
6.6
Further research
An overriding concern in conducting this study has been the complexity of the
linkages between Equal Opportunities policies and practices and business outcomes.
Although not strictly essential to the derivation of business benefits, there is the
expectation that policies and practices affect equality. However, this assumption
has not yet been proven. We identified a large number of routes by which
Equal Opportunities policies and practices might affect profits and productivity.
However, which of these routes are important is not known. Moreover, the likely
range of linkages, combined with data limitations, will have reduced the potential
for detecting effects. These difficulties suggest two important areas for further
research:
First, research into the impact of Equal Opportunities policies and practices on
equality in the workplace would be useful: whether policies and practices appeared
to make a difference and, if so, which and to whom.
Secondly, further evidence on the extent and nature of business benefits would
be useful and could be gained through examining intermediate effects of Equal
Opportunities policies and practices. Because intermediate outcomes are (by
definition) closer in the causal chain to the policies and practices, effects, if any,
are more likely to be identified. Given the potential routes hypothesised and data
availability, investigating the effect on morale, in particular, would be useful.
Both aspects would be useful for policy: the first helping to identify where
Government emphasis for employer action would be most useful and the second
increasing the knowledge of business benefits developed in this study.
91
Appendices – The possible routes to business benefits of Equal Opportunities
policies and practices
Appendix A
The possible routes to
business benefits of Equal
Opportunities policies and
practices
93
Part-time,
jobshare, etc
Flexible working
practices including
Family-friendly
practices
Human
Resources
Management
approach
Labour skills
Absence
staff turnover
industrial relations
Labour market
composition and
tightness
Production quality
Production efficiency
Employee diversity
Commitment/morale
Equality of Opportunity/
Equal Opportunities practices
Unionisation
Capital
Establishment age
Labour costs
Product
Size
Industry
Financial
performance
productivity
94
Appendices – The possible routes to business benefits of Equal Opportunities
policies and practices
Appendices – Descriptive statistics on Equal Opportunities policies and practices
Appendix B
Descriptive statistics on Equal
Opportunities policies and
practices
95
81
90
95
95
96
25-49 employees
50-99 employees
100-199 employees
200-499 employees
500 or more
employees
82
Part of a larger
organization
39
81
93
94
Less than 100
100 to less than 1,000
1,000 to less than
10,000
10,000 or more
Size of organization
37
Stand-alone workplace
Organization status
63
10-24 employees
66
(1)
85
84
66
30
70
28
93
89
88
82
65
53
56
(2)
Policy
75
75
58
24
62
23
89
83
79
69
56
48
49
(3)
18
10
12
3
11
3
36
24
19
13
12
8
8
(4)
39
36
36
17
33
16
66
54
49
35
34
25
27
(5)
38
28
31
11
27
11
56
51
43
31
28
20
22
(6)
19
13
10
4
12
4
32
23
19
14
12
8
9
(7)
26
19
19
6
18
6
40
33
27
20
16
11
13
(8)
27
23
27
14
23
13
44
33
30
24
22
18
19
(9)
31
19
23
9
21
9
35
30
30
24
20
16
17
(10)
Equal Opportunities monitoring practices
37
32
26
7
27
7
63
50
44
32
25
19
20
(11)
33
25
26
8
23
8
51
43
36
26
24
16
18
(12)
Ethnicity
practices
64
56
50
35
54
33
72
62
65
64
56
42
47
(13)
24
22
22
9
21
8
56
40
34
35
24
16
17
(14)
Disability
practices
90
82
79
62
80
61
98
95
89
90
80
73
74
(15)
18
22
26
29
22
30
65
41
40
37
28
21
25
(16)
60
56
45
38
51
39
70
56
55
59
49
46
47
(17)
88
88
81
71
84
69
94
87
81
90
79
77
79
(19)
Continued
32
34
18
15
26
15
41
31
38
33
27
21
23
(18)
Family-friendly working
practices
Presence of Equal Opportunities policies and/or practices (percentage of workplaces), by workplace
characteristics
Workplace size
All workplaces
Table B.1
96
Appendices – Descriptive statistics on Equal Opportunities policies and practices
93
Public
96
54
61
49
61
94
67
100
96
85
77
Electricity, gas and
water
Construction
Wholesale and retail
Hotels and restaurants
Transport and
communication
Financial services
Other business services
Public administration
Education
Health
Other community
services
73
75
82
87
55
84
54
38
49
49
96
27
86
51
(2)
65
71
71
81
45
75
44
32
44
38
93
22
80
44
(3)
13
18
9
35
7
14
12
3
3
8
24
2
24
6
(4)
41
46
49
67
17
38
33
21
18
23
70
15
60
22
(5)
40
37
37
56
17
38
16
12
13
20
62
9
47
18
(6)
16
20
18
38
6
18
5
7
4
2
19
4
28
6
(7)
24
25
19
40
11
24
6
10
9
7
33
5
31
11
(8)
27
33
28
42
10
29
21
18
14
20
47
12
40
16
(9)
33
28
26
40
10
32
11
11
12
19
50
4
34
14
(10)
Equal Opportunities monitoring practices
Base: All workplaces; figures are weighted and based on responses from 2,295 managers.
39
Manufacturing
Industry
62
Private
(1)
Policy
Continued
Sector of ownership
Table B.1
35
38
45
67
14
36
26
6
10
14
68
5
57
14
(11)
34
34
35
56
12
36
12
5
10
14
60
7
46
14
(12)
Ethnicity
practices
61
66
77
88
55
48
27
36
39
24
70
28
75
42
(13)
24
30
47
48
15
12
12
10
11
11
42
5
42
13
(14)
Disability
practices
81
89
90
93
79
92
79
76
67
50
98
49
89
71
(15)
31
34
37
44
42
24
20
7
10
27
69
28
34
23
(16)
64
53
71
56
49
75
58
15
39
45
64
38
75
42
(17)
32
27
51
33
19
49
18
10
16
28
38
14
43
20
(18)
86
80
98
96
84
93
90
56
79
68
100
65
98
76
(19)
Family-friendly working
practices
Appendices – Descriptive statistics on Equal Opportunities policies and practices
97
73
Mostly women (over
half) at workplace
66
74
26%-74%
75% or more
83
10% or more
73
5% or more
70
25% or more
58
25% or more
49
58
58
52
57
53
72
48
65
57
42
63
56
(2)
42
51
54
44
54
46
66
41
58
51
33
56
49
(3)
7
5
3
9
10
7
16
5
10
9
5
10
8
(4)
28
19
17
30
34
25
33
23
33
26
20
32
27
(5)
18
18
14
22
36
19
30
18
29
20
14
27
22
(6)
9
8
3
11
11
8
16
6
13
9
4
12
9
(7)
10
12
8
14
24
12
20
10
18
13
8
17
13
(8)
19
16
14
20
24
18
23
17
24
19
15
23
19
(9)
14
13
11
17
24
15
23
14
24
15
11
22
17
(10)
Equal Opportunities monitoring practices
Base: All workplaces; figures are weighted and based on responses from 2,295 managers.
68
None
Employees aged 50
or over
62
None
Employees aged 16
to 21
64
None
Disabled employees
59
None
Ethnic minority
employees
56
25% or less
Female employees
66
(1)
Policy
21
13
9
23
29
17
29
15
28
19
11
26
20
(11)
15
13
10
19
34
15
28
14
25
17
10
23
18
(12)
Ethnicity
practices
44
44
42
47
61
44
46
44
58
47
31
55
47
(13)
17
15
13
18
27
14
19
13
23
17
8
22
17
(14)
Disability
practices
70
80
77
72
82
71
87
67
83
80
52
84
74
(15)
23
20
8
30
40
22
25
22
17
33
22
22
25
(16)
47
40
32
53
46
46
48
44
48
50
39
47
47
(17)
26
14
18
24
31
21
27
20
27
24
15
26
23
(18)
78
73
73
81
81
78
79
77
81
82
71
80
79
(19)
Family-friendly working
practices
Presence of Equal Opportunities policies and/or practices (percentage of workplaces), by workforce
compositions
All workplaces
Table B.2
98
Appendices – Descriptive statistics on Equal Opportunities policies and practices
64
69
Average for industry
Below average
62
71
82
Better than average for
industry
Average for industry
Below average
A lot better than average
for industry
62
66
Better than average for
industry
Managerial assessment
of workplace labour
productivity
75
A lot better than average
for industry
66
(1)
66
62
52
48
61
54
57
62
56
(2)
Policy
59
54
45
41
54
47
49
53
49
(3)
6
10
7
8
9
8
7
10
8
(4)
24
28
27
27
24
26
26
34
27
(5)
17
22
23
18
19
20
22
23
22
(6)
5
11
8
5
8
8
9
10
9
(7)
12
15
14
13
11
12
14
17
13
(8)
20
20
19
21
20
18
19
25
19
(9)
10
18
17
16
13
16
16
19
17
(10)
Equal Opportunities monitoring practices
16
20
21
19
17
20
19
25
20
(11)
12
19
19
14
13
17
18
18
18
(12)
Ethnicity
practices
54
46
45
52
40
46
43
62
47
(13)
19
13
18
21
9
15
19
20
17
(14)
Disability
practices
81
71
73
82
69
71
77
81
74
(15)
13
22
25
39
25
25
24
26
25
(16)
38
47
49
47
32
50
46
49
47
(17)
84
82
79
80
74
81
81
79
79
(19)
Continued
29
26
20
18
14
26
21
24
23
(18)
Family-friendly working
practices
Presence of Equal Opportunities policies and/or practices (percentage of workplaces), by workplace
performance outcome
Managerial assessment
of workplace financial
performance
All workplaces
Table B.3
Appendices – Descriptive statistics on Equal Opportunities policies and practices
99
64
76
66
Better than average for
industry
Average for industry
Below average
65
63
54
54
(2)
Policy
44
55
47
46
(3)
7
9
8
6
(4)
27
28
28
22
(5)
8
26
22
18
(6)
2
9
10
6
(7)
2
19
13
11
(8)
21
21
19
17
(9)
7
19
17
15
(10)
Equal Opportunities monitoring practices
Base: All workplaces; figures are weighted and based on responses from 2,295 managers.
64
A lot better than average
for industry
(1)
Continued
Managerial assessment
of workplace product/
service quality
Table B.3
27
23
20
16
(11)
8
19
18
15
(12)
Ethnicity
practices
36
53
44
46
(13)
16
23
12
20
(14)
Disability
practices
69
74
71
77
(15)
12
23
24
26
(16)
45
53
45
47
(17)
26
21
21
27
(18)
67
79
79
81
(19)
Family-friendly working
practices
100
Appendices – Descriptive statistics on Equal Opportunities policies and practices
72
Above average for
industry
62
70
70
Agree
Neither agree nor
disagree
Disagree
52
59
54
60
64
57
56
(2)
42
54
46
53
57
52
49
(3)
5
9
8
8
11
10
8
(4)
23
32
26
26
31
30
27
(5)
19
20
23
18
26
25
22
(6)
6
10
11
6
13
13
9
(7)
14
13
15
9
17
15
13
(8)
18
21
20
18
23
20
19
(9)
14
15
19
13
21
20
17
(10)
Equal Opportunities monitoring practices
Base: All workplaces; figures are weighted and based on responses from 2,295 managers.
74
Strongly agree
Employees fully
committed
to values of
organization
(managers’
assessment)
70
Not above average
66
(1)
Policy
19
23
19
20
24
23
20
(11)
14
17
19
16
22
21
18
(12)
Ethnicity
practices
39
44
46
53
46
46
47
(13)
15
16
14
24
17
17
17
(14)
Disability
practices
71
77
70
81
74
81
74
(15)
13
21
24
34
23
23
25
(16)
33
45
47
49
53
43
47
(17)
20
18
23
25
27
22
23
(18)
69
78
79
82
83
77
79
(19)
Family-friendly working
practices
Presence of equal opportunities policies and/or practices (percentage of workplaces), by workplace
intermediate outcome
Ranking of
absenteeism by
industry
All workplaces
Table B.4
Appendices – Descriptive statistics on Equal Opportunities policies and practices
101
Appendices – Notes to Tables 5.2-5.8
Appendix C
Notes to Tables 5.2-5.8
For the full sample results, i.e. all private sector workplaces for which we have
non-missing values of a particular outcome and treatment measure, we show
the average treatment effect on the treated (ATT) estimated from three types
of model distinguished by the identification assumptions assumed and the way
in which we control for observables. In the first type of model we augment a
model of business performance with the relevant treatment indicator. The basic
outcome models used in this exercise (excluding treatment indicators), for both
subjective and objective profits and productivity, are discussed in Section 4.3 and
reported in Table 4.2. In these models treatment is assumed to be exogenous,
given the other determinants of business performance included as controls. In the
tables here these results are labelled ‘exogenous treatment’. In the second type of
model treatment is assumed to be endogenously determined and these results are
labelled ‘endogenous treatment’. These results are obtained by estimating jointly
the determinants of business performance and the probability of having a particular
Equal Opportunities policy or practice in place. In other words, we estimate jointly
one of the outcome models in Table 4.2, augmented with the relevant treatment
indicator, and one of the selection models in Table 4.3, estimated on the sample in
question and including the determinants of the particular performance indicator
(except industry dummies) and the additional determinants of treatment selection
that do not appear to influence outcomes as discussed above. We also report
the estimated correlation between the error terms in these two equations, i.e.
the correlation of unobservable influences on both business performance and
treatment selection and the estimated probability that given the model specified,
this correlation is no different from zero. A zero correlation between unobservable
influences on business outcomes and treatment selection may suggest that the
Equal Opportunities policy or treatment is exogenous to the particular business
performance measure, although the power of this test as a test of exogeneity is
not very strong.
Finally we report estimates of the ATT from comparison of outcomes between
a matched sample of workplaces that operate a particular Equal Opportunities
103
104
Appendices – Notes to Tables 5.2-5.8
policy or practice and comparable workplaces that do not operate such policies or
practices. Matching is conducted on estimates of the propensity score, and these
are derived as the predicted values of treatment selection. The propensity score
model is estimated separately for the sample in question (for example, the sample
of private sector firms who interpret financial performance as profits or the sample
of firms for which we have objective measures of productivity per employee),
which varies by outcome measure and whether or not we restrict our attention to
large workplaces only. We include as determinants of the propensity score all the
determinants of business performance included in the models in Table 4.2.
We report propensity score estimates of the ATT using two different matching
techniques, to get an idea of the sensitivity of our results, as indicated in the column
denoted ’Match method’: single nearest neighbour matching with replacement
(NN) and kernel matching (K). The kernel matching uses the Epanechnikov kernel.
Both the nearest neighbour and kernel matching are implemented using the
‘psmatch2’ commands available for STATA (Leuven and Sianesi, 2003). The size
of the matched sample available for the ATT estimates derived using propensity
score matching refers only to the treated and should not be directly compared
to the sample size available for estimating the ’exogenous treatment’ models
(reported in Table 4.2). It is also reduced (but this is a smaller influence) by the
imposition of common support. The average propensity score of the matched
sample (treated and non-treated) are reported for the models using single nearest
neighbour matching, and give an indication of the accuracy of the match. For
comparison, and indicating the importance of controlling for observable covariates
of outcomes and selection, we also show the propensity score of unmatched nonparticipants.
The standard errors underlying the reported p-values of the ATT estimates
take into account the sampling structure of Workplace Employment Relations
Survey 2004 (WERS 2004). However, they do not take into account the stratification
of the sample, which means that the p-values are relatively conservative. Note
that the standard errors of the ATT estimate derived using propensity score
matching are approximate and do not take into account that the propensity score
is estimated. One common method of adjusting for this is to bootstrap estimates
of the standard errors, but it is questionable whether this is valid (Abadie and
Imbens, 2006).
For the sample of large (50 employees or more) workplaces we report only estimates
of the ATT from the ’exogenous treatment’ model and the results obtained using
propensity score matching. In the ’exogenous treatment’ model we allow the
treatment indicator to vary across establishment size and we report the resulting
estimates of the ATT for large as well as small workplaces. To implement the
equivalent ’endogenous treatment’ model we would need three equations, further
complicating the analysis, and we avoid this. An alternative is to restrict the sample
for the exogenous and endogenous treatment models to large establishments
only. However, this does not yield an adequate model of outcomes. The propensity
score matching results are derived from the sample of large workplaces only, and
we note that the difficulty in establishing the determinants of performance in
large workplaces raises concern about the adequacy of the matching.
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