Do High Performance Work Practices Exacerbate or Mitigate the …/file/F... · 2017. 2. 7. · WISERD Cardiff University 46 Park Place Cardiff CF10 3BB Email: [email protected]

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Do High Performance Work Practices Exacerbate or Mitigate the Gender Pay Gap?

Rhys Davies*, Robert McNabb** and Keith Whitfield**

WISERD, Cardiff University

**Cardiff Business School, Cardiff University

Address for Correspondence:

Rhys Davies Wales Institute of Social and Economic Research, Data and Methods (WISERD) WISERD Cardiff University 46 Park Place Cardiff CF10 3BB Email: [email protected] Tel: +44 (0)29 208 70328

Word Count: 4728 words

mailto:[email protected]

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Do High Performance Work Practices Exacerbate or Mitigate the Gender Pay Gap?

Abstract

The impact of the introduction of performance-oriented work practices on the gender pay gap has been the subject of considerable conjecture, but of little empirical investigation. Using the 2004 Workplace Employment Relations Survey (WERS2004), this study suggests that such practices exacerbate the gender pay gap. Organisations therefore need to be more careful in reconciling their performance and equality strategies, as suggested in Dickens (1998). The study also finds that the gender pay gap is lower, and in places reversed, in male-dominated jobs in low performance workplaces.

Key Words: Gender, Wage Differentials, Organisational Performance

JEL: J31, J71 L23, M5

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1. Introduction

It is well documented that the way work is organised has been subject to considerable change during the past quarter-century (Guest, 1987, 1989; Appelbaum and Batt, 1994; Whitfield and Poole, 1997; Boxall and Macky, 2009). These new forms of work organisation have attracted a variety of labels, including ‘high performance work systems’, ‘high commitment organisations’ and ‘flexible specialisation’, reflecting the diverse range of work systems and human resource practices that are involved. The rationale for the introduction of these changes typically arises from the need to attain/maintain competitive advantage in the face of changing product markets and the emergence of markets in which commercial success depends upon product quality and/or innovation rather than low cost mass production. To this end, firms have introduced policies aimed at promoting quality, flexibility and commitment (Guest, 1987, 1989).

As the adoption of these new human resource and workplace practices has increased, so too has the literature documenting the nature of the policies used and their impact on organisational performance (Gittleman, Horrigan and Joyce, 1998; Huselid, 1995; Inchniowski, Kochan, Olsen and Strauss, 1996; McNabb and Whitfield, 1998, 1997; Black and Lynch, 2001; Bartel, 2004)). More recently, a number of studies have examined the impact these innovative work practices have had upon employees such as on earnings1 (Capelli and Neuwark, 2001; Black, Lynch and Kriveyova, 2004, Forth and Millward, 2004, Osterman, 200, 2006; McNabb and Whitfield, 2007), well-being (Wood and de Menezes, 2011) and commitment (Sengupta, Whitfield and McNabb, 2007; Brown, Hardy, McNabb and Taylor, 2011).

Attention has also been paid to the way the introduction of new work practices affects the extent of wage inequality within establishments (Cappelli, 1996; Lindbeck and Snower, 2000; and Osterman, 2006), though very little attention has been paid to the way these work systems have affected the relative position of men and women in the workplace. Notable exceptions are Gupta and Eriksson, (2006), Drolet, (2002), Garcia et al, (2002) and Lausten (2001) - though none of these are for the UK. Moreover, they have generally limited coverage of different types of work practice. Despite a (typically implicit) assumption or belief that high performance work practices promote gender equality, Dickens (1998) has argued that there are reasons why the introduction of the human resource practices associated with them might exacerbate gender equality rather than the reverse, particularly in Britain. The aim of the present study is to consider how the relative position of women within workplaces, in terms of pay levels, is affected by the nature of the work systems employers adopt. In Section 2, the context to the study is presented. In Section 3, the data to be used (including details of the workplace practices included) and the empirical methodology are described. The results of the empirical analysis are reported in Section 4 followed by concluding comments in Section 5.

2. High Performance Work Systems, Segregation and the Gender Pay Gap

High Performance Work Systems and Earnings Organisations that have sought to use innovative work practices as the basis for improved organisational performance have introduced a variety of human resource management practices. The core elements, however, focus on those practices that seek to improve employee participation through the delegation of responsibilities to individuals and teams, and those that focus on work enrichment (Wood and de Menezes, 2011). Innovations such as quality circles, 1 See Handel and Levine (2004) for a survey of studies looking at the impact on earnings.

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briefing groups, total quality management and team-working have been associated with major changes in the way work is organised (Appelbaum and Batt, 1994). These work practices involve employees taking more responsibility for key parts of the production process and being responsive to market pressures. They have therefore also been associated with more flexible workplace systems and job design that also involve flexibility and multi-tasking. These work systems also entail an increase in the demand for a more skilled workforce, including so-called soft skills such as team-working and problem-solving. Since such work practices involve enhanced skill-acquisition and some degree of gain-sharing, employees should exhibit wage premiums over both employees in those establishments that do not introduce such practices, as well as relative to those employees within the same workplace to whom they are not extended (Lindbeck and Snower, 2000). In so far as high performance work practices vary between rather than within workplaces, one would expect greater wage equality within establishments, but greater inequality between them - though, as Handel and Levine (2004) argue, the actual impact of new work systems will be complex.

The impact of high performance work practices on earnings has been considered in a number of studies, though they present a mixed bag of results with few consistent threads running through them. Amongst the studies reporting positive results (at least for some work practices) are Cappelli (1996), Applebaum et al (2000) Batt (2001), Capelli and Newark (2001), Hunter and Lafkas (2003) and Osterman (2006). In contrast, Osterman (2000), Black et al (2004) and Handel and Gittleman (2004) do not find that the introduction of new work practices result in higher average earnings amongst employees in a workplace. Findings that the introduction of these work practices actually result in lower average earnings have been reported by Bauer and Bender (2001), who also suggest that new work practices are skilled-biased and, as a result, increase wage inequality both between and within establishments, something also found by Caroli and van Reenen (2001) and Black et al (2004). Osterman (2006), in contrast, finds the wage inequality falls following the introduction of new work practices.

A number of studies have attempted to determine whether bundles of work practices produce positive effects by considering a range of interactions (see, inter alia, Black et al, 2004; McNabb and Whitfield, 2007; and Osterman, 2006). These suggest that bundles can be important in increasing earnings, though again the picture is complex and the nature of the relationships varies across studies.

That it is very difficult to draw firm conclusions about the impact of high performance work systems on employee earnings is, perhaps, not unexpected. Studies differ in terms of the data used (nationally representative samples, and industry- and establishment-specific studies), in their coverage and measurement of work practices, in the groups of workers compared, and in the methodology adopted. If nothing else, they highlight the complexity of the inter-relationships that may exist between different types of work systems and organisational and employee outcomes. One suggestion is that greater employee empowerment and involvement in decision-making has been found to be successful only in those organisations where they are associated with compatible gain-sharing mechanisms, such as performance-related-pay, and profit sharing and share-ownership schemes (McNabb and Whitfield, 1998), and practices to promote motivation, commitment and loyalty.

High Performance Work Systems and the Gender Pay Gap The question as to whether high performance work systems have an effect on the relative pay of women has been most directly addressed by Dickens (1998). She challenges the notion that innovative performance-oriented HRM work practices will foster equal opportunities and argues that such practices will have systematically different consequences for men and women

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reflecting, for the most part, the gendered nature of the model itself. In part this reflects, she suggests, the way these work practices have been introduced in workplaces in Britain involving, what Storey (1994) has called, a ‘hard’ version of the model with a focus on the most cost-effective use of labour as a resource. In contrast, much of the literature concentrates on a ‘soft’ version which is more about employee empowerment and involvement. However, Dickens argues that, even here, there is little evidence to suggest that the introduction of new practices increases gender equality, and possibly even the reverse.

Dickens considers a number of ways in which the high performance model is gendered in such a way to increase the gender pay gap. Gender stereotyping is especially significant in the reality of policies aimed at encouraging employee involvement and commitment. Whilst the focus of the high involvement model is on the relationship between greater employee responsibility, empowerment and commitment, the reality is that women encounter an implicit assumption by managers that they have lower organisational commitment than men. This arises because of the way commitment is typically measured as being defined in terms of being seen at work, of 24-hour availability and total dedication as the expected standard. The demands of domestic and caring work conflict with the expectation of ‘presentism’ with the result that there is an assumption of lower commitment.

Similarly, whilst the literature has highlighted functional flexibility and job design involving multi-tasking, practices which Dickens considers have the potential to improve the relative position of women at the workplace by reducing gender-based job segregation, the reality is that new work practices have worked to strengthen gender segregation. In part, this reflects the core-periphery division that exists in many workplaces and that new work systems are predominantly introduced for male-dominated core jobs. In contrast, employee flexibility in periphery jobs, which are mainly filled by women, involves numerical flexibility enabling organisations the freedom to vary labour input in an unconstrained way through the use of part-time or temporary employment.

In the key areas of selection, appraisal, and pay, Dickens also points to the way gender stereotyping affects the criteria upon which employees are appointed and their performance appraised. That seemingly objective criteria and assessment are often gender-biased and based on male attributes and behaviour results in the contribution of women being under-valued, undermining their commitment and motivation and their ability to benefit from such things as performance-related-pay systems introduced to promote the very outcomes they undermine. Indeed, Dickens notes several studies which have found that gender-based job segregation is such that women are often in jobs in which the potential to benefit from these performance-based pay systems is, in fact, limited or that there is gender-bias in performance assessment, both of which increase gender pay inequality.

The argument that high performance work systems do not promote the interests of all workers and may actually exacerbate the gender pay gap has, however, been subject to very limited empirical scrutiny. Drolet (2002) considered the impact on workplace attributes, including a number of work system variables, on the gender pay gap in Canada. Using a standard decomposition technique, Drolet finds that differences in workplace characteristics contribute significantly more to the gender pay gap than do differences in the personal characteristics of employees. The latter is found to explain less than twenty percent of the observed gender wage gap compared with over forty percent explained by differences in workplace attributes. In addition, Drolet finds that the introduction of self-directed work groups and performance-related-pay increase gender inequality at the workplace, though their impact is modest. Both the

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presence of self-directed work groups and performance-related-pay increase the gender wage gap by just over two percent each.

A more extensive range or work practices is considered in a study of how new work practices affect the gender pay gap in Denmark by Gupta and Eriksson (2006). Six groups of variables are included in the analysis - self-managed teams, job rotation, quality circles, total quality management, benchmarking, and project organisation. The analysis indicates that women are more likely to be employed in workplaces that have adopted one or more of these new work practices but that, on average, wages are actually lower for women in these establishments relative to those in workplaces where new work systems have not been introduced. Indeed, there is a significant gender divide in the way such work systems are correlated with earnings: on average, they increase male earnings but have a negative impact on female wages, especially amongst hourly paid workers. In terms of the gender pay gap within establishments, wage inequality therefore increases as establishments introduce high involvement work systems with the notable exception of establishments which employ job rotation and total quality management schemes, which tend to lower the gender pay gap. The authors also consider the role of performance-related pay schemes, which are associated with higher workplace earnings, but also with greater gender wage inequality.

Two studies which do not directly look at the role of performance-oriented work practices on the gender pay gap but whose analysis includes some such practices are Garcia, Hernandez and Lopez (2002) and Villar and Castano (2008). The former examine the impact of a number of job characteristics on the gender pay gap in Spain, capturing the level of autonomy in setting working-pace, the extent of directive and supervisory power over other employees, the ability to control the work-pace of others and the ability to make decisions regarding other workers. Overall, there are significant gender-based differences in nearly all aspects of the level of autonomy, responsibility, and in the degree of control over other employees. Again, however, these are found to only have a small impact on the actual gender pay gap, amounting to around two percent, as in the Drolet study.

Villar and Castano (2008) also consider the impact of job characteristics on the gender pay gap in Spain, though they include a more extensive range of attributes than Garcia et al. Specifically, they look at working conditions, knowledge and aptitudes, effort and responsibility. While there are differences between men and women in terms of the characteristics of the jobs and in the wage premia associated with them, the job attributes considered in this study have very little impact on the wages of women at the workplace.

Segregation and the Gender Pay Gap As noted earlier, a potential barrier that could affect the way work practices impact upon the pay of women relative to that of men is the prevalence of job segregation. Previous research on the relative importance of different types of segregation and their contribution to the gender pay differential is available for a range of other countries though the findings do not provide a consistent picture of the main sources of gender pay differences. In an influential study, Groshen (1991) indicated that much of the observed gender wage gap in the US could be attributed to segregation by occupation, establishment and job-cell (i.e. within jobs within establishments), with occupational segregation the main source. However, Groshen’s study has limited industrial and regional coverage and the data contain only a small number of control variables. In contrast, Carrington and Troske (1998), using more detailed information on workers, firms and segregation for the US manufacturing industry, found that both men and women earn less when they work in plants that are predominantly staffed by women. Similarly, Reilly and Wirjanto (1999), using matched establishment-employee data for the Maritime Provinces of Canada,

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estimated that the proportion of females in the establishment accounts for over one-quarter of the gender wage gap.

Other studies that have also found important workplace effects include de la Rica (2003) and Drolet (2002), both of which use matched employee-employer data sets. De la Rica, using data for Spain, found that firm segregation accounts for one-fifth of the gender pay gap, occupational segregation within firms for a further one-third and stratification into different professional categories within firms and occupations a further one-third. She also found that the returns to skills were lower for women.

Drolet’s analysis focused on whether differences in the types of workplaces in which men and women work are important. She found that workplace characteristics are more significant compared with the characteristics of employees in determining male-female earnings differences in Canada. Her results indicate that part-time employment at the establishment is especially important. This variable, she suggests, may be acting as a proxy for the gender composition of the workplace (not directly measured) or for unmeasured differences in worker skills. Drolet also reports that a significant part of the gender pay gap cannot be explained by differences in either workplace or personal characteristics.

Bayard et al (2003) replicated Groshen’s analysis, but using matched employer-employee data for the US that are more representative in terms of occupational, industrial and regional coverage. They report important workplace effects, with segregation within jobs within establishments the main contributory factor, a result also found for Britain (Forth, McNabb and Whitfield, 2005). However, they also found that about half the observed wage gap arises because women are treated differently in the labour market, and that men and women within the same organisations and working in the same narrowly-defined jobs are paid different wages.

Finally, a comparative study for Britain and Canada shows that workplace-specific effects can account for a significant part of the gender pay gap suggesting that women are more likely to be employed in low-paying establishments (Drloet and Mumford, 2011).

3. Data and Methodology

Data In order to explore the relationship between the adoption of high performance work systems and the gender pay gap in Britain, data from the 2004 Workplace and Employee Relations Survey (WERS2004) are analysed. This survey provides nationally representative data on the state of workplace relations and employment practices in Britain. The survey population is all British workplaces with at least five employees, except for those in agriculture, hunting and forestry, fishing, mining and quarrying, private households with employed persons, and extra-territorial organizations. In addition to detailed workplace information, up to 25 employees from each workplace were asked to complete an employee questionnaire.

The dependent variable in the analysis is the gross hourly earnings of full-time employees. It is calculated by dividing the mid-point of the weekly earnings band in which respondents placed themselves by the number of hours they stated they worked in a typical week. There is clearly some imprecision in this as actual earnings will be distributed throughout the range of each earnings band. There are also assumptions made as to the mid-point of the two end bands. The sample was restricted to full-time employees because of the recognition that the gender pay gap for part-time employees is determined by different factors from full-time employees, and that the low number of part-time male employees makes analysis very unreliable.

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The high performance work practices are based on those developed by Wood and de Menezes (2008). We thus identify six key areas: work enrichment; flexible work practices; skill acquisition; motivation; family-friendly policies (not part of the Wood and de Menezes framework); and total quality management. Each area is made up of a number of work practices as shown below.

• Work enrichment: task variety or variety in work undertaken; timing control or control over the pace at which someone works; method control or discretion over how they do their work.

• Flexible work practices: Teamwork involving formally designated teams; functional flexibility involving being trained to carry out jobs other than their own; quality circles or problem-solving groups; suggestion schemes; team briefing involving a formal system of briefing to workers other than managers and supervisors.

• Skill acquisition: The existence of a standard induction programme; the provision of off-the-job training on improving communication and/or team-work; provision of information by management on the financial position of the establishment, internal investment or staffing plans; and the existence of an appraisal scheme for non-managerial employees.

• Motivation: The use of formal surveys of employees’ views or opinions; the use of motivation as a selection criteria; preference given to internal candidates in filling vacancies; the existence at the establishment of a policy of guaranteed job security; that managers and non-managers have the same level of benefits in terms of pension provision, private health insurance, four weeks or more paid annual leave, and sick pay in excess of the statutory requirement; the use of variable pay systems such as profit related pay and performance related pay.

• Family-friendly policies: The ability of employees to work at home, job share or have flexi-time; for females employees can have maternity leave at full pay; for employees to be entitled to term-time working, nursery, subsidised childcare, financial help with the care of elders or leave for adult caring.

• Total quality management: The monitoring of work quality via the use of individual employees, keeping records on faults and complaints and the undertaking of customer surveys; the keeping of records to check the quality of the establishment’s product or service; and training in quality control procedures.

Using these work practices to define high performance work systems, establishments are then classified as those that have adopted them and those that have not. Clearly, this is problematic since adoption is not either/or and establishments will vary in terms of the intensity or level to which they have introduced the practices. In addition, it is likely that establishments will also differ in the way they have combined different practices.

Given the number of practices considered here, a pragmatic approach is employed in which low, intermediate and high levels of adoption are considered. An establishment is defined as having an intermediate level of adoption if it uses at least one of the practices listed in a particular area, but not all. For the high adoption level, an establishment must have introduced all of the practices in an area. An overall measure is calculated by assigning the values of 0, 1 and 2 to low, intermediate and high adoption in each area respectively and defining overall-low as a score of 0 to 5, overall-intermediate as 6 to 7, and overall-high as 8 to 12. These overall ranges have been chosen to give a relatively even distribution across the three groups. The resultant distributions are summarised in Table One.

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---PLACE TABLE ONE ABOUT HERE--- The key explanatory variables are four measures of segregation, a vector of variables

relating to the background characteristics of the respondents, variables capturing the nature of the workplace in which they work, plus variables relating to the occupational group and industry in which they are located. A full list of the variables used is given in Appendix One

The segregation variables measure the extent of segregation by workplace, occupation and job-cell. The first is taken from the employee questionnaire and is based on whether the type of work that the respondent personally does is done mainly by men, equally by men and women or mainly by women. The second is also based on the employee questionnaire and is based on the percentage of women in the same Standard Occupational Classification Sub-Major Group as the respondent. The third is taken from the management questionnaire and is based on the percentage of males at the workplace.

The distribution of full-time employees between different segregation categories is shown in Table Two. It indicates that jobs in which work is only or mainly done by men are more likely to be found in low than high performance workplaces. For the overall measure the difference is 44.3% versus 31.6%. The reverse applies for those only or mainly done by women, the equivalent difference being 16.3% versus 19.6%. Occupational segregation is more prevalent in low than high performance workplaces with lower proportions of workers working in occupations that are dominated by workers of their own gender. For the overall measure the difference is 34.8% as against 27.3%. The same applies to workplace segregation, where there is a much lower prevalence of high performance workplaces where the workforce is dominated by men. For the overall measure the proportion for low performance workplaces is 47.3 % and for high performance workplaces it is 27.4%.

---PLACE TABLE TWO ABOUT HERE---

Method The empirical analysis involves a number of distinct steps. In the first, the gender pay gap is estimated using standard earnings equations. The WERS data being used is a very rich source of information not just on the personal characteristics of employees but also on the attributes of the establishments in which they work. One particular issue that is especially relevant in the present context is the role played by job segregation in determining the gender pay gap. As noted earlier, a key issue identified by Dickens is that women may not benefit from high performance work practices because these are not extended to the types of jobs women often have access to.

The present study builds upon the current segregation literature by examining how segregation interacts with work practices in determining the relative pay levels of men and women within the workplace. In order to identify both the structure of the gender wage gap and the role of workplace characteristics as a source of this gap, pooled and separate wage equations for men and women are estimated as follows:

ijk kijkn nijnh hijhijij ZXSw εβα +Φ+Θ++= ∑∑∑ln (1) where wij is the hourly wage of person i in the j-th establishment, Shij are the four measures of segregation, namely, the percentage of females employed in the person’s occupation across all establishments, the percentage of females in the person’s industrial group, the percentage of females employed in the establishment, and the extent to which the job undertaken by the person

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within the establishment (the job-cell) is carried out by men or women or both. ijX is a set of personal attributes and Zj is a set of establishment characteristics (including regional location). Clearly, both the gender composition of the workplace and the measure of whether jobs within an establishment are carried out mainly by women are themselves workplace attributes. However, we have grouped them with the other segregation variables to maintain consistency with previous segregation studies. Because of the hierarchical nature of the data used in the analysis, the error term can be written as, jijij θϕε += where ijϕ represents that part of the error term that varies independently across individuals both within and between establishments and jθ measures that part that varies across establishments but which is constant for workers within establishments. This assumes that employees have some unobservables that are common to those of co-workers within an establishment and others that vary randomly across all workers. This error structure describes a random effects model and the efficient estimator is therefore feasible generalised least squares. Using the estimated coefficients from equation (1), a standard decomposition technique is used to breakdown the average gender pay gap into that part which arises because of differences in employee and workplace attributes and that part which arises because these attributes are treated differently in the labour market for women compared with men (Oaxaca and Ransom, 1994).In particular, the decomposition uses the wage structure obtained from a pooled equation across the whole sample to approximate what the wage structure would be in the absence of discrimination. This enables differences in the wages paid to comparable men and women working in the same types of establishment to be divided into the extent to which there is an advantage favouring male employees compared with a second component that captures the relative disadvantage faced by female employees. Of course, differences in attributes may themselves reflect feedback effects of discrimination. The use of this decomposition approach is not seen therefore as a way of ‘explaining’ the gender pay gap but rather as an accounting procedure that enables the gender pay gap to be broken down into different sources.

4. Results The basic gender pay gaps for each of the different types of workplace are shown in Table Two. Overall, the gender pay gap between full-time male and female employees in private sector establishments in the sample analysed is 17.6%. Average earnings are substantially higher in those workplaces that have introduced high performance work practices compared with those that have not, with the exception of those establishments that have introduced all flexible work practices relative to those that have adopted some or none of these. This finding applies equally to men and women.

---PLACE TABLE THREE ABOUT HERE---

Perhaps what is most striking about the table, however, is that the gender pay gap is substantially higher in those establishments that adopt high performance work systems. This is especially so in workplaces where two or more total quality management practices are in place, where the gender pay gap is 23.8%. It is also high where skill acquisition and flexible work practices are prevalent, where the gap is 21.6% and 21.0% in those workplaces with two or more

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of the practices present. Using the overall measure of a high performance work system, the difference in the gender pay gap in those workplaces classed as high performance is 20.0%, as against 14.8% in those classed as low performance. These findings lend support to Dickens’ argument that such practices exacerbate the gender pay gap.

Examining the gender pay gap across different segregation categories, summarised in Table Four indicates that women tend to do least badly, on average, in jobs that are dominated by men and, in fact, do better than men in male-dominated jobs in low and intermediate performance workplaces. In particular, women in male-dominated jobs in workplaces with low levels of such practices in place (as measured using our overall measure) earn 12.2% more than males in the same jobs and workplaces. This is particularly marked in workplaces where there are no work enrichment practices, where the female advantage is 17.7%. The gender pay gap tends to be higher where there is an equal number of men and women in the job-cell, rather than an imbalance in either direction.

---PLACE TABLE FOUR ABOUT HERE---

Women also earn more than men in low performance workplaces where they dominate the occupation concerned (defined as having more than 75% female in the same Standard Occupational Group Sub-Major Group), though this varies substantially between the individual practice types, being highly positive for those with no work enrichment practices and no flexible work practices, but negative or small for the rest. In terms of workplace segregation, there is very little pattern to the results.

In order to consider why the introduction of high performance work systems operates against females employees, we turn to the decomposition analysis in which the basic gender pay gap is broken down into its component parts. The key results are summarised in Table Five. In the first part of the table, and as a precursor to the decomposition results, a pooled equation is estimated which includes just a variable measuring the effect of gender on earnings, in other words, the gender pay gap. This is shown as Model 1 in the table estimated for the Overall measure of workplace characteristics. Models 2 through 5 show what happens when other sets of variables are included in the pooled equation. So, when a set of personal characteristics are included the gender wage gap falls, in the case of the High incidence of adoption from 24.04% to 15%.

---PLACE TABLE FIVE ABOUT HERE---

A number of points are clearly evident from the analysis. First, the gender pay gap that exists in all types of workplaces is, in part, a reflection of differences in employee and workplace characteristics. For example, in the overall analysis, the gender wage gap for high performance workplaces falls from 24.0% to 7.2% when this is corrected for all the various attributes being considered. The fall is less for low performance workplaces, from 17.2% to 9.1%.

Second, gender segregation would appear to be the key correlate associated with the gender pay gap. The gender coefficient falls by between 34.3% and 46.4% with the inclusion of the segregation variables, significantly more than is the case for employee personal characteristics and workplace attributes.

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Third, as indicated in the decomposition results shown at the bottom of Table Five, the main factor that contributes to the gender pay gap in all establishments is that men and women have different attributes rather than in the way the wage premiums/penalties associated with them. In those workplaces defined as operating high performance work systems over eighty percent of the gender pay gap reflects differences in a range of characteristics, ten percent is associated with the unequal treatment of women relative to men and about eight percent to male advantage. The impact of differences in attributes is least in thiose establishments where the adoption of high performance practices is limited.

As noted earlier, caution should, however, be used in labelling this part of the wage gap as ‘explained’. Indeed, the fourth main finding of the decomposition analysis (shown in detail in Table 6) is that the two most important contributors to the gender pay gap overall are job segregation within establishments and sex segregation between workplaces, which are themselves unexplained. Moreover, the impact of gender segregation of pay across the different types of establishment is complex. For example, job segregation within workplaces contributes to lower relative wages for women across all establishments, though it is more important in explaining lower women’s pay in establishments that have not adopted high performance work practices. In contrast, limited access to workplaces that have adopted these practices contributes relatively more to the gender pay gap in these establishments as compared to other establishments. It is also worth highlighting the fact that female disadvantage is generally less in relative terms for women employed in jobs predominantly undertaken by women. In other words, those women working in jobs from which women are generally excluded face the greatest earnings penalty. It is therefore only in low performance workplaces that there is any earnings advantage for women working in male-dominated jobs. Elsewhere, the reverse strongly applies. It is also the case that women are, in general, employed in occupations that are lower paid and that this penalty is especially large in establishments that have adopted high performance practices. This is offset, in part, by the fact that there is a higher relative wage premium for women in better paying occupations.

---PLACE TABLE SIX ABOUT HERE---

A consistent feature of the results is that differences in educational qualifications between men and women have a significant impact on the gender pay gap, and this is especially so in those workplaces that have introduced high participation work systems. The relative returns to education are, however, generally higher for women.

As one might expect, the impact of age on earnings is less for women than for men, especially in those establishments that have not adopted high performance work practices. Not unrelatedly, being married and having child-care responsibilities both result in lower relative earnings, especially in workplaces adopting high performance work practices. Similarly, differences are found in the way the length of job tenure impacts upon earnings. In particular, women’s commitment to an employer, as measured by years of service, is treated less favourably than is the case for comparable male employees, especially in workplaces using high performance work practices. Disability and ethnicity are not found to contribute to the gender earnings gap to any significant degree. Neither do we find that occupational and industrial segregation play a role in the relationship between the adoption of performance-related work practices and the gender pay gap. Union membership improves women’s relative pay, on average.

Finally, the measures included to capture differences in workplace characteristics are found to contribute to the gender pay gap, but that there is no real pattern to the estimated

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correlations. Perhaps the one exception here is that greater competition in the product market is found to increase the gender pay gap in those establishments that have not introduced innovative work practices.

5. Conclusions

The impact of the holistic introduction of a range performance-oriented work practices (generically labelled high performance work practices) has been the subject of intense debate. Of particular conjecture has been the impact of such practices on the gender pay gap. In a persuasive systematic review of the evidence, Dickens suggested that the human resource management components of such innovations were unlikely to reduce the magnitude of the gender pay gap and may even increase it even further. The aim of this study was to test whether this was the case.

Taking a slightly broader definition of the work practices than Dickens, based on the work of Wood and Menezes, this study found strong evidence in support of the suggestion of a positive relationship between the presence of a high performance work system and the gender pay gap. There is also evidence that job segregation is a key component of this difference, and that women are less well rewarded for job tenure than men.

These results have major implications for management practice and suggest that there is a need for those organisations introducing performance-oriented work practices to carefully consider their gender impacts. There is also a case that public policy intervention, such as compulsory pay audits, should be introduced in both the public and private sectors in order to bring these issues to the fore.

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Table One: Distribution of Establishments by High Performance Practice Score

HPW Practice Measures

Full Time Employee

% Female Employees

Enrichment Low 10.3 32.6

Intermediate 44.8 37.9

High 44.9 41.3

Flexible Work Low 7.4 35.3


High 7.8 41.4

Skill Acquisition Low 10.9 26.4


High 22.4 43.2

Motivation Low 29.3 35.5


High 7.5 45.5

Family Low 12.9 34.4


High 17.1 43.4

Quality Low 5.3 48.2


High 17.9 34.6

Overall Low 26.3 33.7


High 29.9 44.0

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Table Two: High Performance Workplaces and Segregation

Full Time Employees

Job Cell Segregation Occupational Segregation (% of Women in Group)

Workplace Segregation (% of Males at Workplace)

Only & Mainly by Men Only & Mainly by Women 0-25% 25-50% 50-75% 75-100% 0-25% 25-50% 50-75% 75-100% Enrichment

Low Performance 43.40% 15.1 33.4% 31.8% 31.4% 3.5% 4.7% 22.5% 26.5% 44.3% Intermediate Performance 39.6 17.2 26.4% 30.1% 35.2% 8.3% 11.0% 23.7% 23.6% 40.6% High Performance 35.9 20 21.6% 31.7% 36.8% 9.9% 10.2% 31.5% 24.4% 31.9% Total 38.4 18.3 25.0% 31.0% 35.5% 8.5% 10.0% 27.1% 24.3% 37.1%

Flexible Work Low Performance 41.7 17.4 23.0% 29.8% 38.2% 9.0% 6.7% 24.6% 20.5% 46.8% Intermediate Performance 36.7 18.7 23.7% 31.1% 36.2% 9.0% 10.2% 29.0% 24.6% 34.9% High Performance 35.4 17 25.4% 32.6% 38.3% 3.7% 9.7% 35.1% 14.4% 38.5% Total 37 18.5 23.8% 31.1% 36.5% 8.6% 9.9% 29.1% 23.5% 36.1%

Skill Acquisition Low Performance 53.1 11.7 32.1% 30.8% 31.8% 5.3% 6.5% 15.8% 20.6% 52.7% Intermediate Performance 37.9 18.7 24.9% 30.9% 35.6% 8.6% 14.3% 28.1% 23.4% 31.6% High Performance 33.1 19.9 22.0% 31.5% 36.6% 9.9% 15.9% 36.8% 20.7% 24.8% Total 38.5 18.2 25.1% 31.0% 35.4% 8.6% 13.8% 28.7% 22.5% 32.4%

Motivation Low Performance 42.8 18.3 28.6% 31.4% 29.4% 10.6% 15.7% 21.5% 23.1% 35.2% Intermediate Performance 37.7 18 24.3% 30.4% 37.2% 8.2% 13.0% 31.0% 21.2% 32.9% High Performance 26.4 19.7 16.6% 34.4% 46.0% 3.1% 10.7% 45.0% 29.8% 14.0% Total 38.4 18.3 25.0% 31.0% 35.5% 8.5% 13.7% 29.1% 22.4% 32.2%

Family Low Performance 45.7 16.6 31.3% 32.0% 31.1% 5.7% 10.8% 14.6% 19.3% 51.1% Intermediate Performance 37.9 18.5 24.0% 31.7% 34.8% 9.5% 10.0% 26.6% 26.1% 36.2% High Performance 29.6 20.3 19.6% 29.4% 44.1% 6.9% 9.8% 43.6% 22.7% 23.6% Total 37.6 18.5 24.2% 31.3% 35.9% 8.6% 10.1% 28.0% 24.6% 36.0%

Quality Low Performance 25.9 24.5 15.0% 29.9% 40.4% 14.7% 15.9% 34.4% 23.4% 21.9% Intermediate Performance 38.1 18.4 24.3% 30.5% 36.5% 8.6% 10.2% 28.9% 22.3% 37.2% High Performance 42.9 16 30.3% 33.3% 30.1% 6.3% 7.5% 17.7% 32.3% 40.9% Total 38.2 18.3 24.9% 31.0% 35.6% 8.5% 10.0% 27.2% 24.1% 37.0%

Overall Low Performance 44.3 16.3 27.6% 31.1% 32.9% 8.5% 9.4% 18.9% 22.8% 47.3% Intermediate Performance 35.8 19.2 23.1% 31.2% 36.7% 9.0% 9.7% 27.9% 26.9% 34.2% High Performance 31.6 19.6 20.8% 31.2% 39.6% 8.3% 10.8% 40.2% 21.1% 27.4% Total 36.9 18.6 23.6% 31.2% 36.6% 8.7% 9.9% 29.2% 24.1% 35.6%

16

Table Three: Earnings Descriptives

Hourly Earnings of Full Time Employees High Performance Work

Practice HPWS Group Male Female Total %Diff

Work Enrichment Low 9.65 8.02 9.12 -16.9% Intermediate 10.09 8.38 9.44 -16.9% High 11.76 9.47 10.81 -19.5% All 10.76 8.87 10.02 -17.60%

Flexible Work Practices Low 10.68 8.96 10.07 -16.1% Intermediate 11.04 9.16 10.29 -17.0% High 10.41 8.22 9.51 -21.0% All 10.96 9.07 10.21 -17.3%

Skill Acquisition Low 9.36 8.03 9.01 -14.2% Intermediate 10.65 8.76 9.91 -17.7% High 11.97 9.38 10.86 -21.6% All 10.76 8.86 10.02 -17.6%

Motivation Low 9.54 8.26 9.08 -13.4% Intermediate 11.14 8.96 10.28 -19.6% High 12.75 10.11 11.55 -20.8% All 10.76 8.87 10.03 -17.5%

Family-Friendly Low 9.06 7.48 8.52 -17.5% Intermediate 10.86 8.82 10.05 -18.8% High 12.38 10.00 11.35 -19.2% All 10.85 8.89 10.08 -18.1%

Quality Low 10.04 8.14 9.13 -19.0% Intermediate 10.82 9.09 10.14 -16.0% High 10.69 8.14 9.81 -23.8% All 10.76 8.88 10.03 -17.5%

Overall Low 9.71 8.27 9.22 -14.8% Intermediate 11.30 9.15 10.42 -19.1% High 11.90 9.52 10.85 -20.0% All 11.01 9.07 10.24 -17.6%

17

Table Four: Segregation and the Gender Pay Gap

Full Time Employees

Job Cell Segregation

Occupational Segregation (% of Women in same SOC sub-major Group as

employees) Workplace Segregation (% of Males at Workplace) Overall Differential

Mainly by

Men Equally by Men

& Women Mainly by Women 0-25% 25-50% 50-75% 75-100% 0-25% 25-50% 50-75% 75-100%

Enrichment

Low Performance 17.7% -20.0% -8.4% -15.3% -27.2% -14.2% 16.3% 8.8% -21.2% -21.2% -4.7% -16.9%

Intermediate Performance 2.3% -14.6% -15.0% -8.3% -9.5% -18.0% -3.3% -15.0% -12.4% -16.8% -10.8% -16.9%

High Performance -4.4% -21.6% -15.1% -2.7% -13.5% -19.5% -14.0% -15.9% -18.6% -18.8% -15.2% -19.5% Flexible Work

Low Performance 6.5% -23.7% -15.7% -34.6% -7.0% -15.9% 19.2% -25.7% -24.8% -12.0% -3.3% -16.1%


High Performance -13.4% -16.3% -2.8% -27.3% -0.6% -19.8% 1.4% 2.0% -15.3% -22.4% -14.8% -21.0% Skill Acquisition

Low Performance -4.1% -14.5% -13.9% -5.1% -18.3% -15.2% -5.7% -8.3% -10.8% -13.8% -12.3% -14.2%


High Performance -7.7% -19.1% -7.7% -12.9% -9.5% -20.9% -18.5% -9.4% -15.7% -19.6% -12.9% -21.6% Motivation

Low Performance 11.9% -16.4% -16.6% -10.7% -15.6% -14.0% -5.0% -15.5% -14.7% -21.0% -8.1% -13.4%

Intermediate Performance -3.2% -18.5% -15.4% -12.4% -13.0% -19.3% -0.131* -14.5% -17.2% -17.9% -14.8% -19.6%

High Performance -4.2% -22.3% -2.9% 5.3% -12.1% -16.7% Missing -5.3% -17.3% -21.4% -3.2% -20.8% Family

Low Performance 7.4% -23.3% -1.2% -25.6% -21.5% -10.2% -7.7% -15.8% -25.7% -14.1% -15.6% -17.5%

Intermediate Performance 0.3% -17.9% -17.2% -9.5% -13.6% -19.7% -7.1% -14.9% -15.0% -19.8% -11.5% -18.8% High Performance -3.3% -18.4% -7.8% -5.5% -10.5% -17.2% -11.5% -10.3% -18.2% -15.0% -15.8% -19.2%

Quality

Low Performance 8.0% -12.9% -27.2% 14.0% -23.6% -16.9% 2.6% -19.0% -8.9% -6.1% -27.6% -19.0%


High Performance -11.3% -21.0% -21.9% -17.4% -22.4% -19.7% -3.7% -17.0% -11.5% -25.0% -13.9% -23.8%

Overall

Low Performance 12.2% -19.3% -5.7% -9.6% -11.3% -17.5% 3.2% -12.0% -16.5% -16.2% -10.6% -14.8%


High Performance -7.1% -18.4% -12.0% -11.5% -8.8% -18.3% -13.0% -10.6% -16.8% -18.2% -14.2% -20.0%

18

Table Five: Model Summary

Full Time Employees Overall Gender Co-efficients Low Intermediate High Model 1- Gender Only -0.1720 -0.2201 -0.2404 Model 2- Gender & Personal Characteristics -0.1473 -0.1508 -0.1500 Model 3- Gender, &Workplace Characteristics -0.1538 -0.1823 -0.1846 Model 4- Gender &Segregation -0.1130 -0.1269 -0.1287 Model 5- Gender, Personal, Workplace & Segregation -0.0907 -0.0757 -0.0724

% of Reduction in Gender Differential Model 1- Gender Only

Model 2- Gender & Personal Characteristics 14.4% 31.5% 37.6% Model 3- Gender & Workplace Characteristics 10.6% 17.2% 23.2% Model 4- Gender & Segregation 34.3% 42.3% 46.4% Model 5- Gender, Personal, Workplace & Segregation 47.3% 65.6% 69.9%

Decomposition Model 3- Gender, Personal & Workplace Characteristics Xbarm*(bm-bt) - Male Advantage 20.1% 17.6% 15.1% Xbarf*(bt-bf) - Female Disadvantage 37.1% 25.3% 19.3% bt*(xbarm-xbarf)- Attributes 42.8% 57.0% 65.6% Wage Gap (Log Points) 0.1713 0.2188 0.2394 Model 5- Gender, Personal, Workplace & Segregation Male Advantage 9.8% 7.9% 7.7% Female Disadvantage 17.5% 11.1% 10.1% Attributes 72.7% 80.9% 82.2% Wage Gap (Log Points) 0.1727 0.2182 0.2394

19

Table Six: Overall Decomposition Analysis

Low Intermediate High

Variables Male

Advantage Female

Disadvantage Attributes Wage Gap

Male Advantage

Female Disadvantage Attributes

Wage Gap

Male Advantage

Female Disadvantage Attributes

Wage Gap

Age 0.0163 0.0251 0.0095 0.0508 0.0059 -0.0022 0.0114 0.0152 -0.0036 0.0145 0.0084 0.0193

Marital Status 0.0082 -0.006 0.0058 0.008 0.0429 0.0366 0.0056 0.085 0.0034 -0.002 0.0042 0.0056

Disability -0.0036 -0.0065 -0.0001 -0.0102 0.0006 0.0012 0.0001 0.0018 -0.0003 -0.0008 -0.0011 -0.0023

Educ. Qualification -0.0054 -0.0101 0.0019 -0.0136 -0.0311 -0.0495 0.0363 -0.0443 -0.0261 -0.0093 0.0472 0.0118

Ethnicity 0.0012 -0.0019 -0.0006 -0.0013 -0.0009 0.0003 0.0002 -0.0003 -0.0045 -0.008 0.0033 -0.0092

Dependent 0.0031 0.0094 -0.0004 0.0121 0.002 0.0165 0.0036 0.022 0.0129 0.0206 0.0051 0.0385

Job Segregation 0.013 -0.1578 0.0506 -0.0942 0.0199 0.0006 0.0303 0.0508 0.0176 -0.0111 0.0168 0.0233 Occupation (% female) 0.0017 -0.0014 0.0311 0.0314 0.0011 -0.0444 0.0347 -0.0086 0.0046 -0.0734 0.0485 -0.0202 % females at Workplace -0.0019 0.0048 0.0162 0.019 0.0132 0.014 0.0275 0.0546 0.026 0.0208 0.0351 0.0819

Tenure -0.0153 -0.0282 0.0093 -0.0343 0.0186 0.0286 0.0075 0.0547 0.0419 0.0387 0.0095 0.0902

Union Membership -0.0007 -0.0002 0.0003 -0.0007 -0.0091 -0.0117 -0.0038 -0.0247 -0.0124 -0.0129 0.0009 -0.0245

Industry (% female) -0.0138 -0.064 0.0056 -0.0722 0.0073 0.01 -0.0069 0.0104 -0.0075 -0.0117 0.0107 -0.0084

Region 0.0063 -0.0051 -0.0105 -0.0094 -0.003 0.0064 -0.0049 -0.0014 -0.0153 -0.0003 -0.0109 -0.0265

Workplace Size 0.0518 0.0419 -0.0079 0.0857 -0.0702 -0.016 0.0091 -0.077 0.1074 0.0692 0.0025 0.179 No. of Establishments 0.0052 0.002 0.006 0.0132 0.0153 0.0269 0.0033 0.0456 -0.0091 0.0083 0.0111 0.0102

Ownership 0.0018 0.0189 0.007 0.0278 0 0.008 0.017 0.0251 0.0024 0.0022 0.0006 0.0052

When Established 0.008 0.022 0.0016 0.0316 -0.0268 -0.0258 0.0044 -0.0482 -0.0134 -0.0061 0.0034 -0.0161

Attitudes to 0.0009 0.001 0.0004 0.0023 0.0087 0.0133 0.0012 0.0231 0.0103 0.0069 0.0017 0.0188

Constant -0.0598 0.1865 0 0.1267 0.0228 0.0116 0 0.0344 -0.1158 -0.0214 0 -0.1372

Total 0.0169 0.0302 0.1257 0.1727 0.0173 0.0243 0.1766 0.2182 0.0185 0.0242 0.1968 0.2394

20

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