1. Overview – The role of firms in wage inequality: Policy lessons from a large-scale cross-country study

Many OECD countries have been grappling with low productivity growth and rising income inequality over the past few decades. Meanwhile, gaps in business performance have widened, with a small number of high-performing businesses continuing to achieve high productivity growth while others have been increasingly falling behind. Moreover, high-performing firms are also pulling away in terms of sales and profitability, and industry concentration is growing in many countries. The COVID-19 crisis risks reinforcing these trends, as some unprofitable businesses have been kept afloat and the digitalisation of business models has accelerated. An emerging body of evidence suggests that growing productivity gaps across businesses can at least partly account for low aggregate productivity growth, but evidence about their implications for wage inequality is still limited. While some degree of wage inequality may be desirable to promote incentives for work, skill acquisition and job mobility, excessively high levels can become an obstacle to social cohesion by raising overall income inequality and undermining equality of opportunities.

Until recently, a large part of research into the causes of wage inequality focused on differences in skills between workers in an analytical framework that disregarded differences between firms. In the standard skill demand and supply framework, increases in wage inequality can to a large extent be explained by increases in the demand for skills, which are in turn driven by technological progress, including automation and digitalisation, and globalisation. Labour markets are assumed to be perfectly competitive and wages of high-skilled workers are bid up irrespective of the firm in which they work. Consistent with this framework, policy has mainly focused on ensuring that workers have the skills that are demanded by employers through investments in education and adult learning. However, the standard framework cannot account for a number of empirical facts. First, there is large wage inequality even within narrowly defined skill categories, including between similarly qualified men and women. Second, there are large cross-firm differences in average pay for workers with similar characteristics. Third, workers’ mobility decisions are fairly unresponsive to wages, allowing employers to bid them down, especially in labour markets with a high degree of employer concentration or for groups of workers with few job options, including women.

This volume places the firm at the centre of the analysis into the causes of wage inequality by explicitly taking account of differences in firms’ wage-setting practices. The analytical framework departs from the assumption of perfectly competitive labour markets and typical firms, by explicitly taking labour market frictions and firm heterogeneity into consideration. In this framework, firms benefit from some degree of wage-setting power in the sense that wage differences between them are not immediately neutralised by competition between firms hiring perfectly mobile workers. The implication is that between-firm differences in product market performance and specific features of the labour market, such as employer concentration and differences in mobility between specific groups, including between men and women, can lead to wage differences between workers with similar skills. From a policy perspective, placing firms at the centre of the analysis broadens the scope of policies to address wage inequality, coupling worker-centred policies, such as education and adult learning policies, with firm-based policies, including policies to narrow productivity gaps and limit firms’ wage-setting power.

The work summarised in this volume makes three key contributions. First, it quantifies the contribution of differences in firm wage-setting practices to wage inequality in a cross-country context using a novel set of harmonised linked employer-employee data that contain information on workers and the firms for which they work. Previous research using such data has typically focused on individual countries. A comparison of results based on single-country studies is unreliable as cross-country differences might reflect variation in data treatment (e.g. data sampling procedures and variable definitions) and empirical methodologies rather than genuine variation in institutional settings and structural conditions across countries. This volume harmonises the data treatment as far as possible and uses a unified empirical methodology in order to allow direct comparability of results across countries. Second, the work summarised in this volume documents the role of firm wage-setting practices for wage inequality, including the gender wage gap, and links firm pay policies to structural and public policy factors, including job mobility, product market competition and labour market concentration, by explicitly taking advantage of the cross-country dimension of the data. Third, the volume draws policy conclusions from the empirical evidence, highlighting the need to complement worker-centred policies with firm-centred measures to achieve high growth that is broadly shared with all workers.

The remainder of this chapter is structured as follows. Section 2 presents the conceptual framework underlying the analysis and outlines the scope of the research covered in this volume. Section 3 summarises the main analytical and policy messages and Section 4 concludes by highlighting some open questions and avenues for further policy-relevant research based on linked employer-employee data.

Aggregate wage inequality arises from wage gaps between firms and within them (Figure 1.1). To some extent, wage gaps between firms can be explained by differences in the skill composition of the workforce. For instance, firms employing above-average shares of high-qualified workers generally pay higher wages than the average firm. But wage gaps between firms are also the result of differences in wage-setting practices between them. For instance, higher-productivity firms may offer higher wages than their lower-productivity competitors to attract and retain workers and thus reach their optimal employment levels. Wage gaps within firms largely reflect differences in worker skills, such as education and experience. For instance, lower-qualified workers earn lower wages than their more qualified colleagues. However, even within-firm wage gaps may to some extent be explained by factors unrelated to workers’ skills. For instance, firms may pay women and men with similar education and experience different wages, which may be viewed as a discriminatory firm wage-setting practice. This could be due to differences in women’s bargaining position relative to men, employers’ perceptions of differences in productivity, or employers’ conscious and unconscious biases.

Differences in firm wage-setting practices can only arise in labour markets where firms benefit from some degree of wage-setting power. In a labour market without frictions – where job search, job mobility and hiring are costless – firms have no wage-setting power. A worker with a given set of characteristics (e.g. formal qualifications, experience, motivation, etc.) would immediately move if they were offered a higher wage by a competing firm. In this case, workers’ wages are wholly determined by their specific skill set, with firms bidding up wages until they equal workers’ marginal productivity. Firms with high average productivity employ more workers than their lower-productivity competitors but, since marginal productivity tends to decline with employment and equalise across firms, they do not pay higher wages for workers with a given set of skills. Hence, pay differences in the case of a frictionless labour market entirely reflect differences in skill composition. For instance, one firm may mainly employ high-skilled workers at high wage rates, whereas another one may mainly employ low-skilled workers at low wage rates, because they perform different economic activities or use technologies with different skill requirements.

In a labour market where job search, job mobility and hiring are costly (or workers differ in their preferences regarding the non-wage aspects of jobs), firms can set different wages for workers with similar skills without workers immediately quitting lower-paying jobs. In this case, a positive link between wages and productivity arises at the firm level. On the one hand, high-productivity firms need to raise wages significantly to attract the workers needed to enable the firm to grow. On the other hand, it becomes feasible for low-productivity firms to set wages below those of their higher-productivity competitors since they can nonetheless retain some workers. Consequently, in a labour market with frictions, between-firm differences in productivity are reflected in differences in both wages and employment. The wage response relative to the employment response tends to increase with the degree of labour market frictions. Moreover, in a labour market with frictions, it becomes possible for firms to set differentiated wages for similarly qualified groups of workers within the firm if workers’ job search and mobility costs differ, as may, for instance, be the case for similarly skilled women and men.

Differences in firm wage-setting practices have an immediate impact on overall wage inequality whereas differences in skill composition between firms have no direct impact on overall wage inequality. For instance, at a given composition of skills, it is irrelevant for overall wage inequality whether high-skilled workers cluster in the same firms (which would lead to high between-firm wage inequality and low within-firm wage inequality) or whether they are evenly distributed across firms (which would lead to low between-firm wage inequality and high within-firm inequality). By contrast, differences in firm wage-setting practices directly raise overall wage inequality even between workers with similar levels of skills. Differences in firm pay policies may also lead to differences in skill composition having an indirect impact on overall wage inequality if high-wage workers sort into firms setting high wages. This is more likely to be the case when high-productivity firms use technologies that rely heavily on specific skills.

Given the potentially important, but so far underappreciated, role of firm wage-setting practices in wage inequality for policy makers, this volume examines the implications of complementing the traditional policy focus on skills with a focus on firms. The main measure of wage inequality used in this volume is the dispersion (variance) of wages. Chapter 2 quantifies the contribution of differences in wage-setting practices between firms to wage inequality while Chapter 3 analyses the extent to which they are related to firm productivity. A significant link between firm pay – conditional on workforce composition – and firm-level productivity would suggest that public policies that reduce gaps in productivity between firms could potentially play an important role in addressing wage inequality. Chapter 4 analyses the determinants of firms’ wage-setting power, with a particular focus on labour market concentration and potential policy remedies to it. Chapter 5 analyses the contribution of wage-setting practices within and between firms to the gender wage gap among similarly qualified women and men at different points of the life course.

Distinguishing the effect of firm wage-setting practices from the effects of skill composition empirically requires the use of linked employer-employee data. The linked employer-employee data used in this project are drawn from administrative records designed for tax or social security purposes or, in a few cases, mandatory employer surveys. As a result, these data are very comprehensive, often covering the universe of workers and firms in a country, and of high quality, given the financial implications of reporting errors for tax and social security systems. To overcome confidentiality issues that limit direct data access in many countries, the analysis in this volume is partly based on a “distributed microdata” approach that relies on a network of partners based in participating countries who provide relevant aggregations of individual-level data using a harmonised statistical code. Using a combination of direct access and distributed microdata, the analysis in this volume is based on linked employer-employee data for up to 20 OECD countries (see Annex A). Skill composition is taken into account by controlling for the role of potential experience by education and gender in individual worker wages.

The analysis focuses on the relevance of firm wage-setting practices in wage inequality (including the gender wage gap) by looking at some of their main determinants – namely firms’ productivity, the degree of job mobility and firms’ wage-setting power – which are, in turn, shaped by public policies as well as collective bargaining and social dialogue. The determinants of returns to skills, skill composition and between-firm productivity gaps are outside the scope of this volume but have been analysed extensively in previous work (Box 1.1).

Wage inequality can arise from wage gaps between workers within firms and from gaps in average wages between firms. Between-firm wage inequality, in turn, can be the result of differences in firms’ wage-setting practices or the sorting of workers with different skills into different firms. The contribution of each of these components to overall wage inequality is quantified using statistical decomposition techniques (Chapter 2). In this volume, the contribution of differences in firms’ wage-setting practices is measured as the dispersion of firm wage premia, i.e. the part of average firm wages that is unrelated to the characteristics of the firm’s workforce.2 The contribution of worker sorting is measured as the dispersion of average firm wages that can be attributed to workforce composition, including differences in average workers’ skills across firms. And the contribution of within-firm inequality is measured as the average dispersion of wages within firms, which captures returns to skills and possibly also differences in pay policies between similarly qualified workers within firms (e.g. between women and men).3

The results from this decomposition reveal that between-firm wage inequality represents a sizeable component of overall wage inequality and that this predominantly reflects between-firm differences in pay for workers with similar levels of skills rather than differences in the composition of workers (Figure 1.2). On average across the 18 countries covered by this part of the analysis, between-firm wage inequality accounts for about one-half of overall wage inequality. Firm wage premia dispersion in turn accounts for around two-thirds of between-firm wage inequality. The remaining one-third of between-firm wage inequality is accounted for by differences in workforce composition, i.e. the fact that firms paying higher average wages typically also employ more highly educated and experienced workers.4 Taken together, they suggest that firms have significant wage-setting power, with firm wage setting practices accounting for around one-third of overall wage inequality. Consequently, identifying and quantifying the key determinants of firm pay policies is crucial for the design of public policies to address wage inequality.

Differences in wage-setting practices between firms to an important extent reflect differences in firms’ productivity performance. Descriptive evidence presented in Chapter 3 suggests that gaps in firm productivity are a key determinant of gaps in firm wage premia and that this is higher in countries with higher productivity dispersion (Figure 1.3). More detailed analysis shows that on average across the covered countries, around one-sixth of productivity gaps between firms are passed on to gaps in firm wage premia. In labour markets with frictions that limit job mobility, high-productivity firms offering high wages only attract a limited number of workers from low-productivity ones. In other words, higher productivity is partly reflected in higher wages rather than being reflected exclusively in higher employment, as would be the case in labour markets where workers are perfectly mobile between jobs. Moreover, the evidence shows that there are significant differences across countries in the extent to which productivity differences translate into differences in wage premia, with over one-fifth of productivity gaps passed on in some countries but less than one-tenth in others, pointing to a potentially important explanatory role for country-wide characteristics such as policies and institutions.

The new evidence on the transmission of productivity gaps to gaps in firm wage premia in this volume is particularly relevant in the light of previous research showing that productivity dispersion has tended to rise in many OECD countries (Andrews, Criscuolo and Gal, 2016[8]; OECD, 2015[9]). OECD research by Berlingieri et al. (2017[10])already pointed to a relationship between dispersion in productivity and wages, but could not establish whether this is because higher-productivity firms tend to employ higher-skilled workers or because they pay higher wages to all workers. The new evidence in this volume suggests that productivity gaps and gaps in firm pay policies are directly linked, implying that rising productivity gaps between firms contribute to rising wage inequality.

The strong relationship between firm performance and firm pay has important implications for policies that seek to enhance inclusive growth. Before the COVID-19 crisis, increasing productivity gaps between firms mainly reflected stagnating productivity growth among low-productivity firms rather than exceptionally high productivity growth among high-productivity ones. Hence, business-focused initiatives that help lagging firms catch up with leading firms, or leading firms to expand and create new jobs, would support growth of aggregate productivity and wages. Such initiatives may be particularly important in the wake of the COVID-19 crisis, which may have widened productivity gaps between firms with different access to digital technologies and business models. By directly reducing gaps in firm pay policies between firms, such initiatives would also contribute to lower wage inequality (Box 1.2).

Significant differences in the extent to which productivity gaps translate into differences in wage premia across countries suggest that policies and institutions play an important role in influencing job mobility. The transmission of productivity gaps between firms into wage gaps should in principle be more pronounced in labour markets where frictions reduce the rate of job mobility, as differences in firm pay policies are not immediately competed away by the movement of workers from low-pay to high-pay firms. New analysis presented in Chapter 3 of this volume confirms this conjecture.

High job-to-job mobility – which is mainly voluntary as it excludes layoffs followed by non-employment – dampens the transmission of between-firm productivity gaps to wage gaps (Figure 1.4). As a result, at any given level of productivity dispersion, wage premia dispersion and, hence, overall wage inequality tend to be lower in countries with high levels of job mobility. Moreover, the difference in wage premia dispersion between high-mobility and low-mobility countries tends to be particularly pronounced where productivity dispersion is high. Consequently, raising job mobility can play an important role in reducing wage inequality, especially where productivity dispersion is high (e.g. Germany, Hungary, Portugal). More specifically, the empirical results suggest that raising job mobility from the 20th percentile of countries covered by the analysis (corresponding roughly to Italy) to the 80th percentile (corresponding roughly to Sweden), is associated with a 15% drop in overall wage inequality. To put this reduction in perspective, the median increase in wage inequality across countries over the period 1995-2015 was around 10%. At a given level of job mobility, more centralised collective bargaining (e.g. sector-level bargaining) and higher minimum wages reduce productivity pass-through and wage premia dispersion between firms.

While job mobility is determined by a range of factors, some of which are outside the scope of public policies, these findings nonetheless suggest that policies to promote job mobility (see Box 1.3 for a discussion of such policies) could significantly help in narrowing gaps in firm wage-setting practices, further underlining the importance of job mobility in the recovery from the COVID-19 crisis. By allowing high-productivity firms to expand more easily, such policies would also raise the efficiency of labour allocation and thereby aggregate productivity, employment and wages. However, some barriers to job mobility are likely to remain even after addressing policy distortions. Workers differ in their preferences for jobs in different firms, industries and geographical areas as well as their ability to perform the tasks involved, and firms differ in terms of non-wage working conditions and skill requirements, which creates inherent barriers to job mobility. Hence, mobility-promoting policies should not be seen as a silver bullet but rather as a complement to policies that aim at narrowing productivity gaps between workers and firms (such as skills and innovation policies) and income gaps between workers (such as wage-setting policies or the tax and benefits system).

In principle, wage-setting institutions in the form of minimum wages and collective bargaining could help to contain the wage-setting power of firms in labour markets with limited job mobility, thereby reducing pay differences between them. Indeed, the dispersion of firm wage premia in countries with centralised collective bargaining arrangements is about half that in countries with decentralised ones. Moreover, the difference in wage premia dispersion between high and low-mobility countries is smaller in countries with centralised collective bargaining systems than in countries with decentralised systems. In areas and occupations where wages are well below workers’ productivity, this could even raise employment by raising labour market participation among people who are unwilling to work at current wages. However, there is a risk that wage floors are set at levels in excess of workers’ productivity, which would reduce employment. This risk could be reduced by combining centralised collective bargaining with sufficient scope for further negotiation at the firm level, and focusing minimum wage increases on areas and groups for which initial levels of wages are low. OECD research based on a comparison between Norway and the United States suggests that wage compression between firms does not necessarily reduce the efficiency of labour allocation between firms (Hijzen, Zwysen and Lillehagen, 2021[22]). The key to achieving high productivity through an efficient allocation of labour is to complement wage-setting institutions that constrain the ability of firms to pay different wages for similar workers with measures that promote innovation in low productivity firms and strengthen job mobility.

The fact that firms with different levels of productivity set different wages, or deviate from the average wage in the market, suggests that firms have some degree of wage-setting power. To provide a more direct picture of the degree of wage-setting power by firms, Chapter 4 provides comprehensive new evidence on labour market concentration. At any given level of job mobility, higher labour market concentration reduces workers’ employment options and raises firms’ wage-setting power (Azar et al., 2020[32]). Since workers have few alternative job options in a highly concentrated labour market, firms can set lower wages than in a labour market where many potential employers compete for workers.

Across countries, about 20% of workers are employed in highly-concentrated labour markets (Figure 1.5). High concentration is defined by a level of the Herfindahl-Hirschman Index above 2 500, a common threshold in antitrust analysis corresponding to four firms equally sharing the market (OECD, 2019[33]). The share exposed to high labour market concentration is even higher in manufacturing (around 40%) and in rural areas (around 30%).

The empirical evidence in Chapter 4 supports the view that, for given mobility costs, a high degree of labour market concentration puts downward pressure on wages, with wages being systematically lower in highly-concentrated labour markets even after controlling for other local labour market characteristics (e.g. productivity) and worker characteristics (e.g. skills). A worker in a labour market with high concentration (90th percentile) is estimated to experience a wage penalty of around 6-7% relative to a worker in a market with low concentration (10th percentile). Moreover, both exposure to concentration and its negative wage effects appear to be particularly pronounced for low-qualified workers, thus raising wage inequality.

Labour market concentration has remained broadly flat over the past two decades despite increasing sales concentration in many OECD countries. This reflects the fact that the largest firms in terms of sales are not necessarily those with the largest workforces, especially in digital-intensive sectors where sales can be scaled up without scaling up employment. However, the negative wage effect from labour market concentration has tended to become stronger over time, suggesting that firms are increasingly exercising their wage-setting power. To some extent, this could reflect the weakening of workers’ bargaining position due to the erosion of wage-setting institutions such as minimum wages and collective bargaining in some countries, or increased exposure to domestic and international outsourcing.

The excessive wage-setting power of employers in specific labour market segments and for specific groups of workers could be remedied by rigorously promoting a more competition-friendly labour market structure, such as requiring competition authorities to take account of the labour market implications of mergers, as well as by promoting worker representation in the workplace and collective bargaining (Box 1.4).

A large part of this volume focuses on differences in wage-setting between firms, i.e. differences in average pay between firms for similarly-skilled workers. To the extent that women and men sort into firms with different wage-setting practices, this can also have important implications for the gender wage gap. Additionally, there can also be important differences in pay between similarly-skilled women and men within the same firm. Indeed, recent studies have shown that the bulk of the gender wage gap persists even after controlling for differences in skills (Goldin, 2014[38]). Systematic differences in pay between women and men with similar skills within firms reflect differences in tasks and responsibilities or differences in pay for equal work, which may result, amongst other things, from discrimination by employers or unequal opportunities for career progression more generally.

New evidence in Chapter 5 provides an indication of the role of firm wage-setting practices in the gender wage gap by decomposing the wage gap between similarly-skilled men and women within and between firms (Figure 1.6). About three quarters of the wage gap between similarly skilled women and men reflect pay differences within firms, mainly due to differences in tasks and responsibilities and, to a lesser extent, also differences in pay for work of equal value (e.g. discrimination, bargaining). One quarter of the gender wage gap is accounted for by differences in pay between firms due to higher employment shares of women in low-wage firms. The latter reflects both differences in wage-setting practices between firms within industries and differences in wage-setting practices between industries. The concentration of women in low-wage firms may be the result of discriminatory hiring practices by employers or the preferences of women for firms with flexible working-time arrangements, while their concentration in low-wage industries may in part also reflect the role of past educational choices and gendered socialisation processes earlier in life.

In the majority of countries, the gender wage gap between and within firms increases throughout the working life. This reflects important gender differences in opportunities for career advancement, particularly around the age many women become mothers. Indeed, the bulk of the increase in the gender gap within firms can be traced back to gender differences in the probability of being promoted, which in turn, reflects the fact that workers in part-time jobs are less likely to be promoted and women are more likely to work part-time. Similarly, much of the increase in the gender wage gap between firms is driven by gender differences in the extent and nature of job mobility across firms. Women are not only less likely to move between firms than men, but when they do, this is less likely to be associated with major wage increases. Career breaks around the age of childbirth are associated with significant wage losses and consequently account for an important fraction of the “motherhood penalty”, i.e. the shortfall in wage growth following childbirth.

Tackling the gender wage gap is not straightforward and requires a range of policies (see Box 1.5). To an important extent, the gender wage gap results from differences in gender roles in the household as women continue to take on a larger share of family responsibilities, including during the school closures that were introduced by governments in an effort to stem the spread of COVID-19. This limits the opportunities of women for upward mobility within and between firms, and when coupled with intense work pressures can undermine productivity at work and increase the risk of work-related stress. Family policies that promote a more equal sharing of parental leave between women and men, provide universal childcare and out-of-school support, and reduce marginal effective tax rates for second earners are key to promoting women’s upward mobility. Policies that strengthen competition in product and labour markets, promote pay transparency and raise wage floors where they are currently low also have a role to play. Additional efforts should also be made to encourage women’s participation in Science, Technology, Engineering and Mathematics (STEM) education by addressing gender stereotypes.

This volume provides evidence on the contribution of gaps in firm performance and pay policies to wage inequality in a context where workers are imperfectly mobile and firms have some degree of wage-setting power. In this context, firms have some scope to set wages independently from their competitors and can set different wages for different groups of similarly skilled workers, including women and men.

From an analytical perspective, the main insight is that, on average across the countries covered by the analysis, gaps in wage-setting practices between firms account for around one-third of overall wage inequality and around one-quarter of the gender wage gap. To some extent, gaps in firm wage-setting practices reflect gaps in productivity that are transmitted to wages when workers cannot easily move between firms. But to some extent they also reflect heterogeneity in the wage-setting power of firms operating in labour markets with different competitive environments.

From a policy perspective, the main insight is that firm-centred policies are a key element of a comprehensive strategy to promote broadly-shared economic growth. Narrowing productivity gaps between firms, promoting worker mobility between them and ensuring that pro-competition policies are vigorously enforced not only in product markets but also in labour markets would reduce gaps in pay policies between firms and overall wage inequality, while probably also raising productivity, wages and employment.

The effects of product and labour market policies on productivity, wages and employment are outside the scope of this volume but represent a promising avenue for future research using the linked employer-employee data explored in this volume. Even before the COVID-19 crisis, low productivity growth, stagnating real wages and high levels of inequality in many OECD countries raised questions about declining business dynamism and the ability of labour markets to support worker transitions from struggling firms to high-performing ones. The COVID-19 crisis has put these questions into stark relief, as many governments have provided unprecedented support to existing businesses based on the existing allocation of resources, while many pre-existing structural trends, such as digitalisation and the shift to the green economy, appear to have accelerated.

The relationship between wage inequality, average wages and the extent and efficiency of reallocation will be the focus of the OECD’s next work in this area. The cross-country linked employer-employee data used in this volume would be an ideal tool to analyse the link between worker mobility and reallocation, and by extension aggregate wage and productivity growth. In particular, the data would allow an analysis of the role of policies in influencing the speed and efficiency of reallocation as well as the costs of reallocation for workers and society at large.

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Notes

← 1. This chapter has been written by an OECD team consisting of Chiara Criscuolo, Alexander Hijzen, Michael Koelle and Cyrille Schwellnus with contributions of: Erling Barth (Institute for Social Research Oslo, NORWAY), Antoine Bertheau (University of Copenhagen, DENMARK), Wen-Hao Chen (Statcan, CANADA), Richard Fabling (independent, NEW ZEALAND), Priscilla Fialho (OECD, PORTUGAL), Katarzyna Grabska-Romagosa (Maastricht University, NETHERLANDS), Antton Haramboure (OECD), Ryo Kambayashi (Hitotsubashi University, JAPAN), Valerie Lankester and Catalina Sandoval (Central Bank of Costa Rica, COSTA RICA), Balazs Murakőzy (University of Liverpool, HUNGARY), Andrei Gorshkov and Oskar Nordström Skans (Uppsala University, SWEDEN), Satu Nurmi (Statistics Finland/VATT, FINLAND), Vladimir Peciar (Ministry of Finance, SLOVAK REPUBLIC), Duncan Roth (IAB, GERMANY), Nathalie Scholl (OECD), Richard Upward (University of Nottingham, UNITED KINGDOM) and Wouter Zwysen (ETUI, formerly OECD). Orsetta Causa (OECD, ECO) and Rudy Verlhac (OECD, STI) helped with the access and the analysis of additional data used in the analysis. For details on the data used in this chapter please see the standalone Data Annex and Disclaimer Annex.

← 2. This is obtained by regressing worker wages on a firm fixed effect while controlling for flexible earnings-experience profiles by education and gender.

← 3. A similar decomposition is conducted in Chapter 5 on the role of firms in the gender wage gap.

← 4. Note that these estimates reflect an upper bound on the importance of firm wage premia dispersion for overall wage dispersion because of the role of unobserved differences in worker composition. Controlling for unobserved worker differences reduces the role of wage premia dispersion for overall wage inequality but does not affect the main insight that firms shape wage inequality developments to an important extent (see Chapter 2 for details).

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