1. Overview – The role of firms in wage inequality: Policy lessons from a large-scale cross-country study
Firms’ pay practices play a key role in shaping wages, wage inequality and the gender wage gap, but their contribution has so far not been well reflected in the policy debate. The evidence in this volume shows that around one-third of overall wage inequality can be explained by gaps in pay between firms rather than differences in the level and returns to workers’ skills. Gaps in firm pay, in turn, reflect differences in productivity, but also disparities in wage-setting power. To tackle rising income inequality, worker-centred policies (e.g. education, adult learning) need to be complemented with firm-oriented policies. This involves notably: (1) policies that promote the productivity catch-up of lagging firms, which would not only raise aggregate productivity and wages but also reduce wage inequality; (2) policies that reduce wage gaps at given productivity gaps without limiting efficiency-enhancing reallocation, especially the promotion of worker mobility; and (3) policies that reduce the wage-setting power of firms with dominant positions in local labour markets, which would raise wages and reduce wage inequality without adverse effects on employment and output.1
This chapter provides an overview of the role of firms in wage inequality and discusses the policy implications of the new analysis presented in this volume.
The main findings can be summarised as follows:
On average across the 20 countries covered in this volume, differences in wage-setting practices between firms for similarly-qualified workers account for around one-third of overall wage inequality, both in terms of levels and in term of changes. This suggests that firms have considerable power to set wages independently from their competitors, and that wages are not exclusively determined by skills. The firm where people work matters for their wages.
Firms use their wage-setting power to align wages with performance as reflected in productivity and/or profitability. Low-productivity firms can afford to pay low wages to workers facing barriers to job mobility while high-productivity firms offer higher wages to attract them. On average across the countries covered by the analysis, around one-sixth of productivity gaps between firms are passed on to gaps in firm wage premia.
The transmission of between-firm productivity gaps to firm pay gaps is particularly pronounced when job mobility is low because low-pay firms face a lower risk of seeing their workers move to higher-paying ones. An increase in 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 estimated to lead to 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%.
On average across the countries covered by the analysis, approximately 20% of the workforce are employed in local markets with high employment concentration (based on conventional guidelines used by competition authorities), with the share being even higher for rural and manufacturing workers. The consequent reduction in workers’ job options puts significant downward pressure on wages, especially those of low-qualified workers, thus raising overall wage inequality. However, local labour market concentration has remained broadly flat over the period 2003-17 despite rising sales concentration.
Significant gender gaps persist even among similarly-qualified women and men. This reflects systematic pay differences between the firms for which they work and systematic gender pay gaps within them. On average across the countries currently covered by the analysis, about one-quarter of the wage gap between similarly-qualified women and men reflects the tendency of women to be concentrated in low-wage firms and about three-quarters reflect systematic pay gaps within firms.
These findings imply that public policies that aim to address wage inequality need to complement worker-centred skills policies with policies centred on firms’ wage-setting practices.
The fact that differences in wage-settting practices between firms account for one-third of overall wage inequality and are directly related to differences in productivity suggests that policies that narrow productivity gaps between firms could significantly reduce overall wage inequality. This could be achieved by fostering capabilities in low-performing firms to adopt new technologies, digital business models and high-performance management practices.
Reducing policy-induced barriers to job mobility would narrow wage gaps between firms by reducing the extent to which gaps in productivity are transmitted to gaps in wages. Job mobility could be enhanced by strengthening adult learning and activation policies, reforming labour market regulation, as well as supporting geographical mobility (e.g. via transport and housing policies) and telework.
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 structure of the labour market, including by accounting for the labour market implications of mergers and combating the excessive use of non-compete and non-poaching agreements.
Differences in pay between similarly-qualified women and men can be reduced through policies that narrow differences in opportunities for upward mobility between and within firms, as well as policies promoting equal pay for equal work. Upward mobility could be promoted by family policies that foster an equal distribution of household responsibilities, as well as policies combating gender stereotypes. Equal-pay-for-equal work measures include policies that raise competition, promote pay transparency and raise wage floors where they are currently low.
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.
1.2.1. Framework
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.
1.2.2. Scope
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).
While this volume focuses on the link between public policies and firm wage-setting practices, a large body of work analyses the effect of public policies on returns to skills, skill composition and productivity gaps between firms.
Returns to skills. At a given skill composition of the workforce, within-firm wage inequality reflects the dispersion of returns to skills. For instance, within-firm wage inequality tends to increase when the wage premium associated with a tertiary education degree increases. A large body of work has analysed the structural and policy determinants of returns to skills in the framework of a race between education and technology (Katz and Murphy, 1992[1]; Autor, Goldin and Katz, 2020[2]). The main role of public policies in this framework is to support the supply of skills to meet increasing demand resulting from technological change. Indeed, the evidence suggests that a more abundant supply of skills relative to demand reduces the skills premium and therefore wage inequality (OECD, 2015[3]). However, the supply and demand framework appears to be less relevant at the extremes of the wage distribution. At the bottom of the wage distribution, policies and institutions may be more important than market forces in setting the wages of low-skilled workers, while at the very top superstar effects may be particularly important (Autor, Goldin and Katz, 2020[2]).
Skill composition. An emerging body of evidence analyses the effect of public policies on firms’ skill composition. One strand of work has focused on the increased sorting of workers into firms with similar co-workers which may be linked to domestic outsourcing, including to independent contractors of online platforms (Weil, 2014[4]; Goldschmidt and Schmieder, 2015[5]; OECD, 2021[6]). Firms increasingly resort to specialised firms for the provision of low-skilled labour services, such as cleaning, security and catering. Such worker-to-worker sorting does not have a direct effect on wage inequality, as increased between-firm wage inequality is offset by reduced within-firm wage inequality. But it may weaken lower-qualified workers’ bargaining position and upward mobility, and hence increase the persistence of inequality over the life course. Policies to strengthen collective bargaining and training in firms providing outsourced services could reduce the adverse effects of worker-to-worker sorting. Another strand of work has focused on complementarities between workers’ skills and technologies, which may lead to the sorting of the highest-skilled workers into the highest-paying firms (Card, Heining and Kline, 2013[7]). Such worker-to-firm sorting may enhance efficiency but directly raises wage inequality.
Productivity gaps. Between-firm productivity gaps have tended to widen in several OECD countries (Andrews, Criscuolo and Gal, 2016[8]; OECD, 2015[9]), which has contributed to widening firm-wage gaps (Berlingieri, Blanchenay and Criscuolo, 2017[10]) and rising wage inequality. Public policies can directly influence the extent of between-firm productivity gaps (see Box 1.2 for details) and the extent of pay gaps at a given level of productivity gaps (see Box 1.3 for details).
1.3.1. Firm wage-setting practices play a key role in shaping wage inequality
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.
Note: The height of the bars denotes the level of overall wage inequality in the latest available year (2015-18), with the shaded parts denoting the contributions of firm premia, sorting and within-firm inequality. OECD refers to the average of the 20 countries shown.
1. Figures for the United States are based on Barth et al. (2016[11])” It’s Where You Work: Increases in the Dispersion of Earnings across Establishments and Individuals in the United States”, https://doi.org/10.1086/684045.
1.3.2. Addressing productivity gaps between firms would not only raise growth but also reduce 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).
Note: The figure shows average wage premia and average labour productivity by decile of the productivity distribution. Data are reported as deviations from country-specific means to ensure cross-country comparability. Labour productivity is log output per worker. Wage premia are the estimated firm fixed effects from a regression of log monthly earnings on firm fixed effects and observable worker characteristics. Included countries: Costa Rica, Finland, France, Germany, Hungary, and Portugal.
Firm-centred policies that reduce the productivity gap between lagging and leading firms would not only strengthen aggregate productivity growth, but also contribute to lower wage inequality by reducing pay differences between firms. The COVID-19 crisis has put the importance of these policies into stark relief as firms with digital business models may have pulled away from those with insufficient access to digital technologies and skills. A comprehensive overview of policies aimed at closing gaps in productivity and wages by supporting the digital transformation is provided in OECD (2021[12]). Possible policies include measures to:
Support investment in intangible assets (such as managerial talent, software and R&D) that are complementary to new technologies. Easing financial frictions, accelerating the development of equity markets and providing more generous and targeted support to intangible investment can allow more firms, especially small ones, to increase intangible investment and seize the opportunities offered by the digital transformation (Nicoletti, von Rueden and Andrews, 2020[13]; Bajgar, Criscuolo and Timmis, 2021[14]; Demmou and Franco, 2021[15]). Scaling up public support for innovation, for instance through public procurement, grants, loans and loan guarantees, can disproportionately benefit lagging firms (Berlingieri et al., 2020[16]).
Promote framework market conditions for the digital age. This involves reducing barriers to market entry and post-entry growth, as well as strengthening the enforcement of competition policy to counter widespread declines in business dynamism and increases in market concentration, especially in digital-intensive industries where incentives for digital adoption are key (Nicoletti, von Rueden and Andrews, 2020[13]; Berlingieri et al., 2020[16]). It may also involve levelling the playing field between multinational and domestic firms in terms of tax policies and reducing differences in the scope for tax optimisation across borders (Johansson et al., 2017[17]). Appropriately designed insolvency regimes can facilitate restructuring or the orderly exit of underperforming firms (Adalet McGowan and Andrews, 2018[18]), promoting their catching up or the reallocation of resources from low-performing to high-performing firms (Adalet McGowan and Andrews, 2016[19]).
Improve technology access via digital infrastructure. Digital infrastructure is a necessity for exploiting the opportunities offered by digital technologies and a strong determinant of productivity gains (Gal et al., 2019[20]). However, access to communication networks is still uneven, hampering the take-up of digital technologies and technology diffusion. Fiscal incentives to encourage private investment in underserved areas, direct public investment where private investment is not commercially viable, and ensuring competition in telecommunication markets would improve and widen access to communication networks and support the digital transformation of lagging firms (OECD, 2020[21]).
1.3.3. Promoting job mobility can limit wage inequality even in a context of rising productivity gaps
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.
Note: Based on 10 OECD countries. Countries are classified according to above/below median productivity dispersion and above/below median job-to-job mobility, resulting in the following country groupings: Germany, Hungary, Portugal (high productivity dispersion, low job mobility); Austria, France (high productivity dispersion, high job mobility); Italy, the Netherlands, Norway (low productivity dispersion, low job mobility); Sweden, Finland (low productivity dispersion, high job mobility). The height of each bar denotes average variance of firm wage premia across countries in each group for the last available year.
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.
Job mobility could be enhanced by strengthening adult learning and activation policies, reforming labour market and housing policies, and supporting telework. Enhancing job mobility will become particularly important in the recovery from the COVID-19 crisis, as employment is reallocated from shrinking or unviable businesses to those with better growth prospects.
Strengthening adult learning and taking a more comprehensive approach to activation that goes beyond promoting access to employment would help workers find better jobs in other firms and at the same time reduce productivity gaps between them, yielding double dividends (OECD, 2021[6]). For instance, public employment services in the form of job search assistance, training and career counselling could be made available to workers in jobs that are supported by job retention schemes that were used on a massive scale in most OECD countries during the COVID-19 crisis (OECD, 2020[23]). More generally, public employment services could be made available to all workers who would like to progress in their careers but face significant barriers in moving to better jobs, including people in non-standard forms of work and workers who are currently employed but lack relevant skills or live in lagging regions. This would require additional resources for public employment services and a more active role in advising workers on adult learning opportunities, as well as collecting information on skill requirements of prospective employers.
Limiting regulatory barriers to job mobility in labour and housing markets can foster transitions across firms, occupations and regions. This includes reforming overly restrictive occupational entry regulations (Bambalaite, Nicoletti and von Rueden, 2020[24]); promoting the portability of social benefits and severance pay entitlements (Kettemann, Kramarz and Zweimüller, 2017[25]); limiting non-compete or non-poaching agreements (Krueger and Ashenfelter, 2018[26]; OECD, 2019[27]); and promoting the portability of workers’ ratings across digital platforms (OECD, 2021[12]). Mobility across geographical areas could be fostered by reforms of housing policies, such as the redesigning of land-use and planning policies that raise house price differences across locations, reducing transaction taxes on selling and buying a home, and relaxing overly strict rental regulations (Causa and Pichelmann, 2020[28]). Social policies in the form of cash transfers and in-kind expenditure on housing could also support residential mobility by making housing more affordable for low-income households, especially if such expenditure is designed in such a way that benefits are fully portable across geographical areas.
An expansion of telework could partly compensate for limited geographical mobility. A significant fraction of jobs can potentially be conducted remotely – between one-quarter and one-third of all jobs according to some estimates (Dingel and Neiman, 2020[29]; Boeri, Caiumi and Paccagnella, 2020[30]; OECD, 2020[31]) – potentially raising job opportunities for workers and reducing the costs of moving from one job to another. Telework could be promoted by new regulations on the right to request telework and the conditions under which telework arrangements are implemented (OECD, 2021[6]); the strengthening of digital infrastructure to increase network access and speed for all workers as well as digital adoption by firms; the enhancement of workers’ ICT skills through training; and improvements in employers’ management capabilities through the diffusion of managerial best practices (Nicoletti, von Rueden and Andrews, 2020[13]; OECD, 2020[31]). Notably, the use of teleworking during the pandemic was higher in countries where there was an enforceable right to request teleworking, and highest in countries where this right to access was granted through collective bargaining (OECD, 2021[6]).
1.3.4. The promotion of job mobility needs to be complemented with measures to limit labour market concentration
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%).
Note: Local labour markets are defined as 3-digit industries within TL3 regions, with the Herfindahl-Hirschman index (HHI) being based on new hires. Urban regions are metropolitan TL3 regions (containing a functional urban area of at least 250 000 people) and rural areas are non-metropolitan TL3 regions, where the definition of metropolitan regions follows Fadic et al. (2019[34]). Services include market and non-market services and construction. Primary and utility sectors are excluded. Country coverage: Austria (2016-18), Costa Rica (2015-17), Finland (2015-17), France (2015-17), the Slovak Republic (2017-19) and Spain (2016-18).
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 number of policies could address wage-setting power in specific segments of the labour market, which may not only reduce wage inequality but also raise efficiency by enhancing work incentives.
Labour market policies can counterbalance the downward effects of firms’ wage-setting power on wages. Reducing the costs of job search and mobility for workers would reduce effective labour market concentration at any given level of measured concentration by expanding workers’ outside job options (see Box 1.3). In principle, wage-setting institutions in the form of minimum wages and collectively negotiated wage floors could help to contain the wage-setting power of firms in labour markets with limited job mobility (OECD, 2019[33]). In areas and occupations where wages are well below workers’ productivity, this could even increase 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. Collective bargaining and competition policies need to be articulated in a way that does not prevent certain categories of “false” self-employed workers from collectively bargaining over wages and working conditions, particularly when they are facing situations, in which they have much lower bargaining power than employers. Competition authorities may fruitfully be involved in identifying such situations. In particular, people working for digital platforms may not enjoy full autonomy nor benefit from employees’ rights and protections, and may have only very few job options in their local labour market (e.g. in the food delivery and ride-hailing industries). These workers need to be able to collectively bargain without facing the risk of breaking competition policy rules against collusion (OECD, 2019[27]).
Excessive labour market concentration could be addressed by explicitly integrating labour market power considerations into merger control regimes. The rationale is that if merger control authorities focus exclusively on product market developments, this may not be sufficient to limit employers’ wage-setting power when the definition of the relevant labour market does not perfectly track the definition of the relevant product market. For instance, a competition authority concluding that a merger between two companies does not constitute a threat to competition because they are operating in separate product markets may fail to detect the fact that two companies are hiring in the same local labour market. Increased merger scrutiny from a labour market perspective could be achieved by presuming that an increase in labour market concentration beyond a specific threshold is likely to increase market power, which would trigger more in-depth analyses of the merger on the competitive environment in the relevant labour market (Marinescu and Hovenkamp, 2019[35]; OECD, 2020[36]).
Competition authorities could step up enforcement efforts against anti-competitive agreements in labour markets, including wage fixing, no-poaching agreements and non-compete covenants (OECD, 2019[27]). Such anti-competitive agreements can lead to high effective labour market concentration even if measured concentration is low, since workers effectively have fewer job options when employers in the same local labour market collude. One way for employers to collude is to agree on the wages and non-wage benefits of specific groups of workers, which allows them to restrict their pay. Wage fixing may not always involve an explicit agreement but may be achieved via practices facilitating tacit co-ordination, for instance the exchange of information on wages and non-wage benefits with potential competitors. Another way employers may collude is by agreeing to refrain from poaching each other’s workers. Again, this allows employers to pay lower wages than if they had to match competing employers’ wage offers to retain their workers. A third form of employer collusion is the use of non-compete covenants in employment contracts that prevent employees from working for their employer’s competitors, usually for a limited time or in a specific geographical area. In some cases, such non-compete covenants may be justified from an efficiency perspective to prevent the free-riding of competitors with respect to know-how, training and trade secrets. However, recent evidence suggests that non-compete covenants are often used in contexts where free-riding is unlikely to be an issue, such as for low-qualified and low-wage workers, with such covenants covering almost one-fifth of US workers in 2014 (Lipsitz and Starr, 2021[37]).
1.3.5. Firm pay policies contribute to wage gaps between women and men
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.
Note: Decomposition of gender wage gap between similarly qualified women and men within firms, between firms within sectors and between sectors. The wage gap between similarly qualified women and men is obtained from a regression of log wages on a gender dummy, education dummies (education is not available for Austria and Estonia) and flexible earnings-experience profiles by gender as well as decade-of-birth dummies to control for cohort effects.
Tackling the gender wage gap requires a range of policies to promote the access of women to higher-paying firms and to better jobs in the firms where they work (OECD, 2017[39]).
Family policies. Family policies can contribute to a more equal sharing of household and care responsibilities between men and women and hence enable women to take advantage of opportunities for career progression within their current firms and at other employers. Important family policies include providing more equal parental leave policies for men and women, promoting egalitarian norms in parenting (OECD, 2017[40]); providing universal childcare and out-of-school support; providing universal childcare; and reducing marginal effective tax rates for second earners. While there is strong empirical support for the role of parenthood in the gender wage gap and the need for a more equal sharing of household responsibilities (Kleven et al., 2019[41]), concerns have been raised about the effectiveness of family policies for reducing the gender wage gap in a context where preferences and social norms are deeply anchored in society (Kleven et al., 2020[42]). This suggests that family policies need to be complemented with other policies that can foster more gender-friendly social norms (e.g. school interventions).
Mobility within and between firms. To make good jobs more accessible to women, the use of flexible work arrangements across occupations and firms, including telework and part-time work, should be supported and offered to all workers – not only parents (OECD, 2019[43]). This would reduce the contribution to the gender wage gap of wage differentials related to women’s preference for jobs with flexible working-time arrangements, and the segregation of men and women across firms and jobs with different non-wage characteristics. Voluntary target setting and good management practices that make managers accountable are among the measures that could also help to promote access for women to quality jobs, while at the same time fostering social norms that support gender equality. Voluntary target setting and good management practices that make managers accountable are among the measures that could also help to promote access for women to quality jobs, while at the same time foster social norms that support gender equality. Gender quotas could in principle also help, but need to be used judiciously to avoid the risk that they undermine firm performance, particularly if targets are set too high given the number of suitably-qualified women in the sector/occupation Invalid source specified.. Finely targeted quotas such as those related to company boards seem to hold some promise in this regard. Recent evaluations suggest that although such quotas enhance the representation of women in company boards, they have limited spillover effects on the career progression of other women in those firms (Bertrand et al., 2019[44]; Maida and Weber, 2020[45]).
Equal-pay-for-equal-work measures. These include equal pay legislation, pay transparency rules, and social dialogue and collective bargaining in the workplace. About half of OECD countries have recently put in place pay transparency measures (e.g. Austria, France, Germany, Sweden). A key obstacle to reducing gender wage gaps is that employers and employees are often unaware of them. Pay transparency rules raise awareness of discrimination and make it easier to enforce equal pay legislation. Pay transparency rules come in a variety of forms in OECD countries, and can, for example, provide the right to request information on pay levels by gender within firms, require firms to report information on employment and pay by gender, or incentivise firms to undertake gender pay audits. Recent studies have shown that mandatory reporting requirements can help reduce the gender wage gap within firms (Baker et al., 2019[46]; Bennedsen et al., 2019[47]; Blundell, 2020[48]).
Investing in STEM. While in most countries women outperform men in terms of the level of education – women are more likely to hold a tertiary degree – fewer women than men complete Science, Technology, Engineering and Mathematics (STEM) degrees (Mostafa, 2019[49]). To some extent educational choices may reflect the possibility that teenage boys still perform better in STEM subjects than girls, but gender stereotypes also play an important role. The lower likelihood of women choosing STEM subjects is also likely to contribute to sectoral segregation.
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.
References
[50] Abel, W., S. Tenreyro and G. Thwaites (2018), Monopsony in the UK, https://ssrn.com/abstract=3270944.
[18] Adalet McGowan, M. and D. Andrews (2018), “Design of insolvency regimes across countries”, OECD Economics Department Working Papers, No. 1504, OECD Publishing, Paris, https://dx.doi.org/10.1787/d44dc56f-en.
[19] Adalet McGowan, M. and D. Andrews (2016), “Insolvency Regimes And Productivity Growth: A Framework For Analysis”, OECD Economics Department Working Papers, No. 1309, OECD Publishing, Paris, https://dx.doi.org/10.1787/5jlv2jqhxgq6-en.
[8] Andrews, D., C. Criscuolo and P. Gal (2016), “The Best versus the Rest: The Global Productivity Slowdown, Divergence across Firms and the Role of Public Policy”, OECD Productivity Working Papers, No. 5, OECD Publishing, Paris, https://dx.doi.org/10.1787/63629cc9-en.
[2] Autor, D., C. Goldin and L. Katz (2020), Extending the Race between Education and Technology, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w26705.
[32] Azar, J. et al. (2020), “Concentration in US labor markets: Evidence from online vacancy data”, Labour Economics, Vol. 66, p. 101886, https://doi.org/10.1016/j.labeco.2020.101886.
[14] Bajgar, M., C. Criscuolo and J. Timmis (2021), “Intangibles and industry concentration: Supersize me”, OECD Science, Technology and Industry Working Papers, No. 2021/12, OECD Publishing, Paris, https://dx.doi.org/10.1787/ce813aa5-en.
[46] Baker, M. et al. (2019), Pay Transparency and the Gender Gap, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w25834.
[24] Bambalaite, I., G. Nicoletti and C. von Rueden (2020), “Occupational entry regulations and their effects on productivity in services: Firm-level evidence”, OECD Economics Department Working Papers, No. 1605, OECD Publishing, Paris, https://dx.doi.org/10.1787/c8b88d8b-en.
[11] Barth, E. et al. (2016), “It’s Where You Work: Increases in the Dispersion of Earnings across Establishments and Individuals in the United States”, Journal of Labor Economics, Vol. 34/S2, pp. S67-S97, https://doi.org/10.1086/684045.
[47] Bennedsen, M. et al. (2019), Do Firms Respond to Gender Pay Gap Transparency?, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w25435.
[10] Berlingieri, G., P. Blanchenay and C. Criscuolo (2017), “The great divergence(s)”, OECD Science, Technology and Industry Policy Papers, No. 39, OECD Publishing, Paris, https://dx.doi.org/10.1787/953f3853-en.
[16] Berlingieri, G. et al. (2020), “Laggard firms, technology diffusion and its structural and policy determinants”, OECD Science, Technology and Industry Policy Papers, No. 86, OECD Publishing, Paris, https://dx.doi.org/10.1787/281bd7a9-en.
[44] Bertrand, M. et al. (2019), “Breaking the Glass Ceiling? The Effect of Board Quotas on Female Labour Market Outcomes in Norway”, Review of Economic Studies, Vol. 86/1, pp. 191-239, https://doi.org/10.1093/restud/rdy032.
[48] Blundell, J. (2020), “Wage Responses to Gender Pay Gap Reporting Requirements”, SSRN Electronic Journal, https://doi.org/10.2139/ssrn.3584259.
[30] Boeri, T., A. Caiumi and M. Paccagnella (2020), “Mitigating the work-safety trade-off?”, Covid Economics: Vetted and Real-Time Papers, Vol. 1/2, pp. 60-66, https://cepr.org/sites/default/files/news/CovidEconomics2.pdf.
[7] Card, D., J. Heining and P. Kline (2013), “Workplace Heterogeneity and the Rise of West German Wage Inequality*”, The Quarterly Journal of Economics, Vol. 128/3, pp. 967-1015, https://doi.org/10.1093/qje/qjt006.
[28] Causa, O. and J. Pichelmann (2020), “Should I stay or should I go? Housing and residential mobility across OECD countries”, OECD Economics Department Working Papers, No. 1626, OECD Publishing, Paris, https://dx.doi.org/10.1787/d91329c2-en.
[15] Demmou, L. and G. Franco (2021), “Mind the financing gap: Enhancing the contribution of intangible assets to productivity”, OECD Economics Department Working Papers, No. 1681, OECD Publishing, Paris, https://dx.doi.org/10.1787/7aefd0d9-en.
[29] Dingel, J. and B. Neiman (2020), How Many Jobs Can be Done at Home?, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w26948.
[34] Fadic, M. et al. (2019), “Classifying small (TL3) regions based on metropolitan population, low density and remoteness”, OECD Regional Development Working Papers, No. 2019/06, OECD Publishing, Paris, https://dx.doi.org/10.1787/b902cc00-en.
[20] Gal, P. et al. (2019), “Digitalization and Productivity: In Search of the Holy Grail - Firm-level Empirical Evidence from European Countries”, International Productivity Monitor, Vol. 37, pp. 39-71.
[38] Goldin, C. (2014), “A Grand Gender Convergence: Its Last Chapter”, American Economic Review, Vol. 104/4, pp. 1091-1119, https://doi.org/10.1257/aer.104.4.1091.
[5] Goldschmidt, D. and J. Schmieder (2015), The Rise of Domestic Outsourcing and the Evolution of the German Wage Structure, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w21366.
[22] Hijzen, A., W. Zwysen and M. Lillehagen (2021), “Job mobility, reallocation and wage growth: A tale of two countries”, OECD Social, Employment and Migration Working Papers, No. 254, OECD Publishing, Paris, https://dx.doi.org/10.1787/807becdf-en.
[17] Johansson, Å. et al. (2017), “Tax planning by multinational firms: Firm-level evidence from a cross-country database”, OECD Economics Department Working Papers, No. 1355, OECD Publishing, Paris, https://dx.doi.org/10.1787/9ea89b4d-en.
[1] Katz, L. and K. Murphy (1992), “Changes in Relative Wages, 1963-1987: Supply and Demand Factors”, The Quarterly Journal of Economics, Vol. 107/1, pp. 35-78, https://doi.org/10.2307/2118323.
[25] Kettemann, A., F. Kramarz and J. Zweimüller (2017), Job Mobility and Creative Destruction: Flexicurity in the Land of Schumpeter, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2993376.
[42] Kleven, H. et al. (2020), Do Family Policies Reduce Gender Inequality? Evidence from 60 Years of Policy Experimentation, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w28082.
[41] Kleven, H. et al. (2019), Child Penalties Across Countries: Evidence and Explanations, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w25524.
[26] Krueger, A. and O. Ashenfelter (2018), Theory and Evidence on Employer Collusion in the Franchise Sector, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w24831.
[37] Lipsitz, M. and E. Starr (2021), “Low-Wage Workers and the Enforceability of Noncompete Agreements”, Management Science, https://doi.org/10.1287/mnsc.2020.3918.
[45] Maida, A. and A. Weber (2020), “Female Leadership and Gender Gap within Firms: Evidence from an Italian Board Reform”, ILR Review, https://doi.org/10.1177/0019793920961995.
[35] Marinescu, I. and H. Hovenkamp (2019), “Anticompetitive Mergers in Labor Markets”, Indiana Law Journal, Vol. 94, p. 1031, https://www.repository.law.indiana.edu/ilj/vol94/iss3/5.
[49] Mostafa, T. (2019), “Why don’t more girls choose to pursue a science career?”, PISA in Focus, No. 93, OECD Publishing, Paris, https://dx.doi.org/10.1787/02bd2b68-en.
[13] Nicoletti, G., C. von Rueden and D. Andrews (2020), “Digital technology diffusion: A matter of capabilities, incentives or both?”, European Economic Review, Vol. 128, p. 103513, https://doi.org/10.1016/j.euroecorev.2020.103513.
[6] OECD (2021), OECD Employment Outlook 2021: Navigating the COVID-19 Crisis and Recovery, OECD Publishing, Paris, https://dx.doi.org/10.1787/5a700c4b-en.
[12] OECD (2021), Spurring growth and closing gaps through digitalization in a post-COVID world: Policies to LIFT all boats, OECD, Paris, https://www.oecd.org/global-forum-productivity/events/Spurring-growth-and-closing-gaps.pdf.
[36] OECD (2020), “Competition in Labour Markets”, OECD, Paris, https://www.oecd.org/daf/competition/competition-in-labour-markets-2020.pdf.
[23] OECD (2020), “Job retention schemes during the COVID-19 lockdown and beyond”, OECD Policy Responses to Coronavirus (COVID-19), OECD Publishing, Paris, https://dx.doi.org/10.1787/0853ba1d-en.
[21] OECD (2020), OECD Digital Economy Outlook 2020, OECD Publishing, Paris, https://dx.doi.org/10.1787/bb167041-en.
[31] OECD (2020), “Productivity gains from teleworking in the post COVID-19 era : How can public policies make it happen?”, OECD Policy Responses to Coronavirus (COVID-19), OECD Publishing, Paris, https://doi.org/10.1787/a5d52e99-en.
[33] OECD (2019), Negotiating Our Way Up: Collective Bargaining in a Changing World of Work, OECD Publishing, Paris, https://dx.doi.org/10.1787/1fd2da34-en.
[27] OECD (2019), OECD Employment Outlook 2019: The Future of Work, OECD Publishing, Paris, https://dx.doi.org/10.1787/9ee00155-en.
[43] OECD (2019), Part-time and Partly Equal: Gender and Work in the Netherlands, OECD Publishing, Paris, https://dx.doi.org/10.1787/204235cf-en.
[40] OECD (2017), Dare to Share: Germany’s Experience Promoting Equal Partnership in Families, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264259157-en.
[39] OECD (2017), The Pursuit of Gender Equality: An Uphill Battle, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264281318-en.
[3] OECD (2015), OECD Employment Outlook 2015, OECD Publishing, Paris, https://dx.doi.org/10.1787/empl_outlook-2015-en.
[9] OECD (2015), The Future of Productivity, OECD, Paris, https://www.oecd.org/eco/OECD-2015-The-future-of-productivity-book.pdf.
[4] Weil, D. (2014), The Fissured Workplace: Why Work Became So Bad for So Many and What Can Be Done to Improve It, Harvard University Press.
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).