About the authors

Guillaume Delautre (Msc in Economics) joined the ILO in 2015 under the France-ILO agreement on research and in relation with the Future of work initiative. His research mostly deals with global supply chains, manufacturing and corporate social responsibilities. He previously worked from 2006 to 2015 for the French ministries of labour and social affairs as an economist and regularly represented his country in different intergovernmental and multilateral forums (EU, OECD, ILO and G20).

Bruno Dante Abriata (MSc in Economics) is a consultant to the ILO since 2016, engaging in research projects in the fields of CSR and business environment, and since 2019 he is also working as supply chain economist at a major energy firm. He specializes in economic analysis and econometrics applied to cost intelligence, business development and public policy. Previously, he worked as Director-General of Budget at the Argentinian Ministry of Defense and as economic analyst in other state dependencies.

Abstract

Relying on the data provided by an ESG rating agency, this paper aims at bringing more understanding on the diversity of firms’ behaviours in terms of labour related CSR and filling a gap on the potential role of labour market institutions, including workers’ collective rights, to contribute to an effective CSR policy. Focusing on four different dimensions of labour CSR (freedom of association, non-discrimination, health & safety and the social monitoring of the supply chain), we assess the influence of a series of economic and institutional characteristics on the level of commitment taken by companies and on the decoupling between firms’ commitment and concrete implementation.

In line with the proponents of the complementarity thesis of CSR, our empirical analysis provides evidence that the existence of strong labour institutions is positively associated with more commitments taken by companies despite sizeable variations according to the issues analysed and the institutions concerned. However, the analysis of decoupling provides a somewhat more nuanced perspective.

Introduction

In the last decades, civil society has increased it pressures on enterprises in order for them to take better account of their social and environmental impacts. Concerning labour issues, the internationalization of companies and the expansion of global production networks in countries with weak regulating capacities have brought out governance deficits and consequently generated demands for better governance (Gereffi and Mayer 2006). Many initiatives have blossomed from governments, enterprises, trade unions and non-governmental organizations (NGOs) in order to address these deficits. For example, the use of private governance mechanisms such as social audits and codes of conducts which first appeared in labour intensive sectors such as garment, sportswear and electronics has since expanded in other sectors. At the same time, multinational enterprises have been urged to be more transparent and to communicate on their own operations, those of their suppliers and their compliance with international labour standards. New voluntary standards, such as the UN Global Compact or the Global Reporting Initiative, have emerged to help and encourage companies in their corporate social responsibility (CSR) activities and reporting (Vigneau et al 2014). More recently, public authorities have also taken legislative initiatives which go further the pure promotion of CSR practices by requiring the largest enterprises to publicly disclose information on specific aspects of their operations, such as the UK Modern Slavery Act or the EU directive 2014/95/EU on non-financial reporting (Phillips et al, 2018), and even to undertake human rights due diligence, such as the “Duty of Care” Act adopted in France in 2017 (Moreau 2017). Recent research shows that mandatory disclosure initiatives may have a positive impact on business responsibility by reducing the variation in CSR activities among firms (Jackson et al 2019).

Relying on the data provided by the ESG rating agency VigeoEiris[1], which covers more than 3,000 of the most capitalized companies listed on the stock market worldwide, we aim at bringing more understanding on the diversity of firms’ behaviours in terms of labour related CSR. Drawing on institutional analysis, we would like to pay special attention to the role of national labour institutions and rights in shaping companies’ CSR policies and their implementation. There is a lack of research on the potential role of trade unions in CSR and their potential contribution to an effective CSR policy (Harvey et al 2017). In this context, this paper addresses the issue of CSR determinants but also questions to what conditions CSR commitments are turned into concrete measures. Thus, it provides empirical complements to two bodies of academic literature: the comparative literature on the institutional embeddedness of CSR practices and the literature on organizational decoupling.

We provide empirical findings for four different dimensions of labour CSR: three of them are related to internal employees (freedom of association, non-discrimination and health & safety) and the last one is related to external workers (the social monitoring of the supply chain). For each of these dimensions, we run two sets of regressions. The first one aims at measuring the influence of a series of economic and institutional characteristics on the level of commitment taken by these companies. The second one aims at assessing the effects of the same characteristics on the gap between two indexes measuring firms’ commitment and their concrete implementation. We also provide some metrics quantifying the occurrence and the intensity of decoupling.

The article starts with a brief presentation of the conceptual framework in which we make a critical review on how the issues of the determinants of CSR and decoupling have been considered by management studies and institutional approaches in the last decades. Next, we introduce our methodology, the sources and the variables used. In the following section, we present and discuss the results, separately for the two sub-questions. In line with the proponents of the complementarity thesis of CSR, our empirical analysis provides evidence that the existence of strong labour institutions is positively associated with more commitments taken by companies despite sizeable variations according to the issues analysed and the institutions concerned. However, the analysis of decoupling provides a somewhat more nuanced perspective. We conclude this article by discussing the main findings and by proposing avenues for further research.

[1]  ESG stands for Environmental, Social and Governance

Conceptual Framework

The institutional determinants of CSR

The present article builds on the insights of two distinct bodies of literature. The first one seeks to identify the determinants of corporate social responsibility and has already led to intense debate among scholars in the last decades. In response to a general scepticism for this type of practices in the context of primacy of the shareholder value paradigm, oldest research tended to focus on the economic value of CSR through an empirical analysis of internal and economic determinants (Margolis and Walsh, 2003). In this literature, company related factors such as size, profitability and other signs of external visibility are often seen as positively correlated with CSR disclosure. This disclosure can also depend on the nature of the industry and on the level of stakeholders' interest or public and media pressure (Fifka, 2013, Ali et al 2017, Lucchini and Moisello 2017). However, the large number of research which tried to identify a relationship, positive or negative, between corporate social performance (CSP)[1] and corporate financial performance (CFP) of the firms led so far to very mixed results (Orlitzky et al, 2003, Margolis et al 2009, Allouche and Laroche, 2005)[2].

More recently, our knowledge on CSR has been also challenged by a complementary thesis drawing on institutional analysis (Granovetter 1985). Several research works have pointed the diversity in CSR behaviour according to firms’ country of origin (Gond et al 2011, Ioannou and Serafeim 2012, Kang and Moon 2012). For the proponents of institutional analysis, firms’ practices must be analysed with regard to their institutional ecosystems and resituated in a social space between purely voluntary practices and socially binding responsibilities (Brammer et al, 2012). In this perspective, these efforts cannot be solely analysed through the lens of firm-specific characteristics but also with regard to structural and political factors at the national and international levels (Campbell, 2007, Aguilera et al, 2007, and Gjolberg, 2009)[3]. Of course, state regulation and its enforcement through well designed institutions, for example in the case of working conditions, a sufficiently funded labour inspectorate, is in many cases a precondition for business responsibility. Nevertheless, many enterprises take also public commitments which go beyond the requirements provided by the Law in their country of origin and in their countries of operation.

Theoretically, a broad set of institutional elements should be taken into account when analysing the diversity of CSR policies. Yet, in this paper, we would like to pay a special attention to labour rights, and more particularly to the institutional elements which ensure workers to have a collective voice. The potential role of trade unions in CSR has been little explored in the scholarly discussion until now (Harvey et al 2017). This question should however be considered in the context of the discussion on the relationship between CSR and social regulation in general which has led to contradictory interpretations. On one side, unions and corporatist arrangements, as well as other protective institutions, can be seen as empowering elements for employees and can thus help to promote higher labour standards. These elements provide resources for pressuring the management to adopt for example higher standards of Health & Safety, ensure a diversity in human resource and promote women in the workplace but also incentivize its subsidiaries and suppliers to act in the same way. An illustration is provided by the last generation of International Framework Agreements signed by MNEs and global union federations. There is a clear tendency for this type of agreement to go beyond issues related to internal employees only such as the social monitoring of the supply chain (Hadwiger, 2015, Bourguignon and Mias, 2018) as well as the environmental impact of the company (ILO, 2018). More broadly, it is fair to consider that social dialogue and tripartism are factors of consensus-building in societies helping to consider broader social and environmental concerns beyond profit maximisation (Campbell, 2007 and Gjolberg, 2009)[4].

However, on the other hand, several scholars have also argued in favour of a substitution thesis (as opposed to the mirror or complementarity thesis presented above) which presents the expansion of CSR as the consequence of insufficiently regulated environments or economic liberalization (Jackson and Apostolakou, 2010, Kinderman, 2012). According to Matten and Moon (2008), more liberal or deregulated economies might be in fact more characterized with “explicit” forms of CSR by companies. In these countries, these explicit forms of CSR would have aimed at substituting relatively weaker institutions and protections for the workers and their jobs. In contrast, in more regulated economies, the social responsibilities of companies are clearly more strongly defined by law and collective bargaining and the level of protection of workers is higher. This would lead to more “implicit” forms of CSR.

Empirical findings have provided support for both thesis but most recent research has tended nevertheless to bring a more nuanced perspective. For Kinderman and Lutter (2018), economic liberalization had indeed a strong effect on the expansion of CSR among OECD countries in the early years. Yet, now that these practices have achieved substantial acceptance into the society, economic liberalization is no longer driving them. To the contrary, their expansion now seems to be more related to stronger economic regulation. Other findings also show that the mirror and the substitution thesis can be both supported but not for the same dimensions of CSR (Barkemeyer et al 2019). In addition, the development of global production networks has largely complexified the situation for multinational companies and brand leaders as they are getting exposed to a more diversified set of stakeholders in their country of origin and abroad (in their countries of operation or purchase) while facing substantial differences in terms of regulation and compliance mechanisms from public authorities. The geographical diversification of firms is a key factor explaining the diversity in corporate social performance (Brammer et al 2006). It has also been showed in the case of European multinational companies that CSR can work both as a complement of institutionalized stakeholder power in their country of origin and as a substitute for its absence in their countries of operation (Jackson and Rathert 2017).

The possibility of decoupling in CSR

The second body of research seeks to understand the discrepancies between companies’ public commitments through for example private regulation mechanisms, such as audits and codes of conducts, and the little achievement of these mechanisms (Pope and Wæraas 2016; Kuruvilla et al. 2019; Bartley and Egels-Zandén 2016). The concept of decoupling, initially coined to analyse the gap between policy and practice in organizations (Meyer and Rowan, 1977), has been applied in the last decade by different authors in order to analyse specifically the limits of CSR policies. In their influential article, Bromley and Powell (2012) proposed the differentiation of two forms of decoupling: policy-practice and means-ends decoupling. The first can be characterized by a symbolic or a ceremonial adoption of a policy which is poorly implemented, monitored and evaluated. It corresponds to the most commonly analysed form of decoupling in management literature. In this case, potentially conflicting policies can be adopted in response to external pressures without causing any disruption in companies’ operations. The second type of decoupling represents a context in which policies lead to concrete measures and organizational consequences but their effectiveness and outcomes remain low. Means-ends decoupling gives insights into how institutional forces generate heterogeneity within and between organizations and therefore belie the myth of “causality, control, and coherence that organizations are structured around” (Bromley and Powell 2012). In the case of labour issues, an illustration of this type of decoupling is provided by the rather limited impacts of private compliance initiatives taken by many lead brands concerning labour rights enforcement and working conditions in suppliers’ workplace (Barrientos and Smith 2002, Anner 2007). Most recent research points out in particular the lack of alignment between social responsibility practices and sourcing practices as a reason for this limited impact (Amengual and Distelhorst 2019). It seems also that symbolic adoption is not a sufficient explanation for these poor outcomes. Field opacity stemming from multiplicity in practices and difficulties in measuring the behaviours of actors and in defining causal relationships is a key factor explaining this decoupling (Kuruvilla et al 2019).

Empirical literature on decoupling in CSR placed a particular attention to measuring the impacts of public and private instruments which aim at rationalizing and standardizing CSR practices such as the United Nations Global Compact (UNGC) and the Global Reporting Initiatives (GRI). This literature leads until now to relatively mixed results but tends to show that the degree of decoupling is a function of the requirements of each initiative. For example, Berliner and Prakash (2015), who analysed a sample of 3,000 US public listed companies, showed that due to UNGC’s voluntary nature and its lack of stringent monitoring mechanisms, adherents do not tend to adopt costly steps to comply with program obligations. Instead, these companies rather adopt symbolic, low-cost steps to convey the impression of obligation fulfilment. In a similar sense, through an in-depth case study of a US multinational corporation, Vigneau et al. (2015) found that GRI is having a significant impact on practices, influencing both reporting and management efforts. However, the outcome of this is an overemphasis on CSR representation over CSR performance, which is leading to unintended consequences on management practices. Firms maintain their legitimacy by documenting CSR activities and translating them into a report, rather than by assessing and improving them. On the other hand, based on a sample of 1000 companies in 24 countries, Graafland and Smith (2019) found that application of GRI standards lead to better implementation and that even CSR reporting of low quality contributes to CSR implementation and therefore indirectly to CSR impact. For them, policy-practice decoupling is negatively related to the quality of CSR policy and means-ends decoupling decreases with the quality of the implementation programs. They argue that even if the chance of means-ends decoupling increase when a company applies CSR programs of low quality, having a low-quality program is still better than having no programme.

In the case of environmental issues, the role of institutions and more specifically those related to public mobilization has been highlighted in the literature. Marquis et al (2016) showed that most environmentally damaging enterprises, especially those in countries where they are more exposed to scrutiny (presence of NGOs, collective voice) and global norms, are less likely to engage in selective disclosure (e.g. the publication of positive information while withholding negative information). On a more general case, Lim and Tsutsui (2012) also demonstrated that both national and international-level factors can combine in the global expansion of CSR. In particular, global institutional pressure through non-governmental linkages encourages CSR adoption, but leads to different outcomes according to the level of development: in developed countries, these commitments remain relatively “ceremonial” while they are more substantive in developing economies.

For methodological matters (detailed in the next section), our analysis of decoupling is limited to the first type, between policies and practices. However, our research brings novelty to the current literature on different points. First, it provides a specific focus to the labour-related dimension of CSR. Empirical research on CSR has been criticized for relying often on aggregate proxies that do not distinguish between the different dimensions of CSR. Yet, there are few reasons to believe that these dimensions are correlated (Rowley and Berman 2000). Furthermore, when looking at institutional determinants of CSR policies in specific dimensions, it seems also that environment has received much more attention from scholars than labour. To our knowledge, very few research has tried to analyse the factors influencing decoupling between policies and practices on a systematic base in the domain of labour-related CSR. Second, our research makes a distinction between two types of stakeholders: internal employees and the workers involved in the supply chain. Prior empirical research has until now given little space to the analysis of the different stakeholders in CSR policies (Orlitzky et al 2017). Mitchell et al (1997) introduced the concept of stakeholder salience which measures the “degree to which managers give priority to competing stakeholder claims”. Following Jackson and Rathert (2017), we consider this salience to draw from the institutions that shape the power and legitimacy of different stakeholders. Third, our research provides new insights based on a very diversified panel of enterprises. Our sample covers more than 3,126 of the most capitalized companies listed on the stock market from various developed and developing economies in the world while usually empirical research, especially when it concerns decoupling, is based on more homogeneous set of (developed) economies.

[1]  Actually, the notion of corporate social performance remains particularly ambiguous (Rowley and Berman 2000).

[2]  Young and Makhija (2014) aimed at reconciling the institutional and the profit led approaches of CSR. These authors managed to demonstrate that variations in firms’ visibility and vulnerability can moderate the needs for societal goodwill driven by institutions, including labour regulatory institutions.

[3]  Young and Makhija (2014) aimed at reconciling the institutional and the profit led approaches of CSR. These authors managed to demonstrate that variations in firms’ visibility and vulnerability can moderate the needs for societal goodwill driven by institutions, including labour regulatory institutions.

[4]  The same could also be expected from strong employers’ associations which can help in disseminating good practices and guidelines among their members (Gjolberg 2009).

Research design and methodology

Data

Drawing on these two sets of literature, we would like to assess the role of a series of firms characteristics and labour institutions on firms’ commitments and on decoupling. For this, we rely on the data provided by the ESG rating agency VigeoEiris, which covers more than 3,000 of the most capitalized companies listed on the stock market worldwide. VigeoEiris provides scores to investors and ‎assets managers on six macro-domains (Human rights, Human resources, Business Behavior, Corporate Governance, Environment and Community Involvement) subdivided in 38 subdimension[1]. For each subdimension[2], it provides three kinds of sub-scores, established on a scale from 0 to 100: 1) the level of commitments (known as “leadership” in VigeoEiris methodology), measuring their visibility, exhaustiveness and degree of ownership by the company[3]; 2) the level of implementation of these commitments, measuring their means, coverage and scope; and 3) the results measured through indicators, stakeholders’ feedback and company responsiveness to public controversies.

For methodological matters, our analysis relies on the two first scores only, those related to the level of commitments and to the level of implementation. Consequently, our analysis of decoupling will be limited to the discrepancy between policies and practices only. The decision to let aside the scores related to results is motivated by the type of information used to compute these indicators. VigeoEiris relies widely on public information regarding controversies faced by companies. Yet, it is fair to consider that all the companies are not competing on the same ground in this regard as the capacity to document this type of information relies primarily on the capacity of external and internal stakeholders, including workers representatives, to exercise freedom of association or on the capacity of media to relay this kind of information and investigate independently. These human rights and liberties are unfortunately not insured and guaranteed everywhere in the world. While we could consider the means-end decoupling to be comparable on a relatively homogeneous sample of enterprises in terms of origin or countries of operation, the diversity of our sample prompts us though to restrain our analysis to policy-measures decoupling only. To the contrary, we assume the policy-means decoupling to be more comparable, especially due to the harmonizing and incentivizing effects of CSR initiatives such the Global Reporting Initiative or the Global Compact on CSR disclosure.

Out of the list of 38 CSR subdimensions, we retain four of them, all related to labour. Three of them are targeted to internal stakeholders: “Respect for Freedom of Association and the Right to Collective Bargaining” (to which we will refer as “Freedom of Association” or FOA for the rest of the paper), “Non-Discrimination” (ND), and “Improvement of Health & Safety” (“Health & Safety” or HS). As for the remaining one, “Integration of Social Factors in the Supply Chain” (“Social Factors in the Supply Chain”, or SSC), is targeted at external stakeholders. We also use data from Factset 2015 which allows us to complete the dataset with indicators on firms’ characteristics, such as revenues, employment etc.

In line with the discussion in the previous section, we propose to complete the database with information related to labour institutions in the country of origin of the company. The first information is provided by the labour rights indicator computed by Kucera and Sari (2019), made available recently as a time series for the period 2000 to 2015 and measuring trade union rights at the country level. The strength of this indicator ("Labour Rights"in the remaining of the article) is that it takes into consideration at the same time the violation in law (i.e. the degree of conformity of the national legislation with the rights to freedom of association and collective bargaining as defined by the ILO) and the violations in practice (i.e. the number and the severity of the acts committed in violation to these rights)[4]. Such an indicator allows thus to point out the situations of clear and widespread problems of compliance even in cases where the legal protection is theoretically high.

In addition, we supplement this indicator by two indicators made available by the Centre for Business Research (CBR) at the University of Cambridge in a dataset measuring the level of protection provided by law to workers in 117 countries from the 1970s to 2013 (Adams et al 2017). Contrary to the first indicator, these two indicators are thus only measuring the theoretical (de jure) protection of workers. From the 40 variables available in this dataset, we retain the information related to 1) employee representation, and more particularly to codetermination such as the right for workers to nominate board-level directors and the obligation regarding information and consultation of workers[5] (“Codetermination”, from now on), and 2) to employment protection legislation[6] (EPL).

By taking into account codetermination, we recognize that in many countries the role of workers’ representatives is also to provide employees with a voice in corporates strategic issues, including those related to business responsibility (Campbell, 2007). Following Harvey et al (2017), trade unions, especially through their involvement in strategic places such as corporate boards, can be considered as “well placed to monitor and respond to activities that contradict agreements reached through deliberative process, but also to challenge activities (…) that have not featured for discussion during this process but which are socially irresponsible”. The link between employment protection and CSR might seem more indirect than with indicators related to collective voice such as labour rights and codetermination. However, it can be considered as a good proxy indicator reflecting the general context of regulation (or deregulation) of national labour markets (Kinderman and Lutter 2018). Besides, previous empirical research allowed identifying potential associations between these dimensions and CSR. For example, Bartosch and Jackson (2016) showed that institutional indicators such as participation to boards, work council rights, employment protection (but also union density and coverage of collective bargaining) were positively associated with CSR for companies originating from OECD countries, especially in the field of human rights and to a lesser extent diversity. Employment protection and work council rights are also negatively associated with the average level of corporate social irresponsibility[7]. Moreover, Scholz and Vitols (2019) showed that the degree of codetermination among German companies is positively associated with substantive policies in the environmental dimensions of CSR, such as the adoption of targets for reducing pollution.

Certain modifications are applied to the data in order to implement our empirical strategy. They involve synthetizing, transforming, constructing and imputing, and were applied on variables describing labour institutions and certain firm characteristics[8] Two modifications are applied on Labour Rights. First, we impute the values missing on years immediately before or after a non-missing value by replicating it. For instance, the indicator only presents values for years 2000, 2005, 2009, 2012, 2015 and 2016, so that we fill the gaps in 1999, 2001, 2004, 2006, 2008, 2010, 2011, 2013 and 2014 by replicating the values in the respective available adjacent years. Although it might seem a questionable approach, to our view, the gains (duplication of sample size) clearly outweighs the costs (assuming changes in labour rights from one year to the next are negligible). As for the second modification, it consists of a linear transformation in order to ease interpretation. As the original score ranges between 0 (no violations, best score) and 10 (maximum violations, worst possible score), we turn into a score that increases as situation improves (violations decrease) and rescale it so that the bounds are between 0 and 1. Let Labour Rightsorig be the original score, and then we transform it into Labour Rights = 1 – (Labour Rightsorig/10).

Our dataset consists of a panel of 3,126 firms along 31 years (1986-2016). This number of firms is determined by the possibility of identifying each firm simultaneously in the VigeoEiris and the Factset datasets. As for the time span, it is determined by the oldest and newest observations available among Factset (going from 1986 to 2015) and VigeoEiris (2003 to 2016) data, resulting in a panel ranging across 31 years. Table 5 (in appendix B) shows the main descriptive statistics, and there it can be observed that the panel is strongly unbalanced[9]. In the VigeoEiris data, for instance, each firm presents on average less than four non-missing values along 14 years, partly because, for most firms, observations are (presumably) reported every two years. Factset data presents some major unbalances as well, due to missing observations for domestic assets as they were greater than total sales and assets, respectively, or also negative, so that they were eliminated. Data from the CBR Labour Regulation Index are almost fully complete since they correspond to the country level and are available for every year between 1970 and 2013.

Empirical strategy

In order to identify the potential determinants of CSR, a set of regressions is run for each leadership indices of the four main dimensions (FOA, HS, ND, SSC) on firm characteristics and labour market institutions. Since the variables describing the latter are correlated, we do not present results of regressions containing all of them together but only those where each of them is included without the other two. Finally, in order to mitigate omitted country-level variables bias that might distort these labour institutions coefficients, we control for lagged (5 years) GDP per capita at country level.

To analyse the decoupling between leadership and implementation, two approaches are employed. First, we quantify decoupling by studying its density, both in terms of observation headcount and of its “intensity” (by how much leadership stands above implementation in each observation). Second, we compute headcount ratios setting different threshold values for the indicators, above which decoupling is considered to happen. In order to study the relations between labour institutions, firms’ characteristics and decoupling, we regress decoupling indicators on a set of relevant firm features and labour institution indicators. Again, this analysis is carried out for the four dimensions, focusing on regressions where the dependent variable is the decoupling measured in terms of intensity, which of course works on the assumption that leadership and implementation scores are strictly comparable. Again, we present one specification for each labour institution variable in order to avoid collinearity problems.

To check for robustness in our decoupling models, we employ several procedures. We first compare the results across regressions that only differ in the labour indicators. Then, we run again these models but restricting the sample to only those observations where leadership is above 30[10] points in order to avoid spuriously low levels of decoupling, that is, those caused by substantially low levels of commitment rather than by ceremonial behaviour. We rerun our regressions using a different type of decoupling indicator, one which ignores intensity and only looks whether the threshold is crossed, missing variation in decoupling intensity but relaxing the assumption about strict 1-to-1 comparability across leadership and implementation indicators.

Finally, to interpret our results, we integrate those on the determinants of leadership in CSR with those on decoupling. We will look whether behaviours across CSR dimensions differ, and if the relation with possible determinants (particularly labour institutions) changes signs from leadership and decoupling. The interpretation of differences can shed light on the understanding of incentives to foster CSR leadership and to accompany it with implementation, as well as of varying incentives to do so across dimensions.

Estimations

We use fractional regression models to study how labour institutions and firm characteristics relate to CSR leadership and decoupling. The reason is that our dependent variables in both sets of regressions are not continuous but limited between 0 and 100. Papke and Wooldridge point out that, in such cases, linear regression models can lead to prediction out of the bounds, so that we make use fractional Probit regressions as descripted below, using the Stata®[11] command fracglm [12].

Equation 1 is the specification for the model that explains the possible determinants of leadership in CSR. LCSRi,t is the leadership indicator of each CSR dimension (FOA, ND, HS and SSC) for firm i at time t. The expectation of LCSRi,t conditional on our set of regressors X and their respective coefficients β is equal to the standard normal cumulative density function Φ valued at the expression in brackets, where the first summation contains the k1 continuous variables Xh that could potentially have a non-linear statistical association with LCSR (internationalization, size, equity growth and GDP per capita) and the second one comprehends the other k2 regressors (age, Labour Rights, EPL, Codetermination, sector, year).

Equation 1: CSR Leadership as a function of labour institutions and firm characteristics

E L C S R i , t X i , t β = Φ ∑ h = 1 k 1 β h X h i , t + β s q , h X h , i , t 2 + ∑ j = k 1 + 1 k 1 + k 2 β j X j , i , t

Regarding the quantification of decoupling, as we mentioned before, two approaches are applied. The first one measures the intensity of decoupling as the difference in scores of leadership over implementation (ICSR), as shown in Equation 2. This approach has the advantage of capturing all possible differences, which allows more variation and richer regression results. However, it relies on the assumption that both leadership and implementation indicators are directly comparable.

Equation 2: Individual decoupling intensity

I D I N i , t = L C S R i , t - I C S R i , t

The aggregate decoupling indicators (ADIN) are shown in equations 3 and 4. We compute them using only the last observation available (that is to say, at period t=L) for those firms present in the database in the last available years in order to avoid the distortion caused by the unbalanced panel and the inconvenience of mixing data from distant points in time, so we arbitrarily decide to look only at the last three years. We divide the index over the sum of leadership scores in order to express it as a ratio of commitments (Equation 3) but, since the maximum theoretical value it can take is 1, it can also be expressed in absolute terms as a plain percentage, in which case the denominator would be the number of firms observed in the last three years, N (Equation 4).

Equation 3: Aggregate decoupling intensity, relative to leadership

A D I N = ∑ i I D I N i , t = L ∑ i L C S R i , t = L

Equation 4: Aggregate decoupling intensity, absolute

A D I N = ∑ i I D I N i , t = L N t = L

The other quantification of decoupling provided is the headcount ratio, which we call “Decoupling Headcount Ratio” (DHRγ). It is computed for each relevant dimension and can be expressed mathematically as shown in Equation 5. Parameter γ is the threshold of decoupling intensity above which the firm is considered to incur into decoupling, and z is a binary indicator equal to 1 if the last available observation of IDIN for each firm considered surpasses the threshold γ.

Equation 5: Decoupling headcount ratio

D H R γ = ∑ i z i , γ N t = L ;   z i , γ 1   i f   I D I N i , t = L > γ   0   i f   I D I N i , t = L ≤ γ

Finally, we present the regression models to study the possible determinants of decoupling. Equation 7 shows the regression model to study the relation between decoupling intensity and our variables of interest. The structure is analogue to that of Equation 1, except for the fact that, since in some cases implementation is greater than leadership and, hence, IDIN gets values below 0, we must also transform the dependent variable by subtracting the sample minimum (see Equation 6), obtaining IDINi,t*. Finally, this implies that interpretation will require dividing these coefficients by the standard deviation of this transformed variable in order to be interpreted.

Equation 6: Transformed dependent variable

I D I N i , t * = I D I N i , t - m i n ⁡ I D I N i , t

Equation 7: Decoupling intensity as a function of labour institutions and firm characteristics

E I D I N i , t * X i , t β = Φ ∑ h = 1 k 1 β h X h i , t + β s q , h X h , i , t 2 + ∑ j = k 1 + 1 k 1 + k 2 β j X j , i , t

In order for to avoid an error from the econometric software, we apply one final transformation to the variables and reverse it in the output. Since the command we use for fractional regressions only accepts values between 0 and 1 for the dependent variable, leadership and decoupling variables will be divided by their maximum values (of the variables expressed as standard deviations) before entering the regression, and the resulting coefficients multiplied by these maximums. As a result, the coefficients will be interpreted in terms of standard deviations of our CSR indicators.

As mentioned before, robustness checks include Probit specifications. As shown in Equation 8, the only difference with respect to the original specification is the dependent variable. Instead of decoupling intensity score, we make of use of the previously presented z binary indicator for firms with intensity indicator above 30.

Equation 8: Probit specification for robustness check

E z i , t , γ X i , t β = Φ ∑ h = 1 k 1 β h X h i , t + β s q , h X h , i , t 2 + ∑ j = k 1 + 1 k 1 + k 2 β j X j , i , t

[1]  For a detailed presentation of VigeoEiris data, please refer to Delautre (2017). As a matter of example, the subdimension of freedom of association seeks to measure the extent to which the firm ensures that employees have the right to unionize and promote collective bargaining internally, for example through awareness-raising campaigns or providing infrastructure and time for employee participation.

[2]  The computation of the scores has several stages and has an important impact in our empirical approach. The first one is the “activation” of dimensions in each sector according to their relevance in terms of nature, exposure and corporate risk. Then, the data is obtained by surveying firms that answer standardized forms containing binary response questions. Hence, this process affects our empirical strategies in two ways: first, by reducing sample size because the dimensions that are not activated for a certain firm represent a missing value, and second, leading us to consider the CSR indicators as fractional variables as they are the result of averaging across ratios with possible values between 0 and 100.

[3]  The visibility criteria measures the degree of disclosure the company wants to give to a certain CSR issue. It ranges from no disclosure at all to a strongly mediatized public commitment. The exhaustiveness criteria will vary depending on coverage of all duties related to a given issue. In the case of non-discrimination for example, it will vary according to the number of discrimination factors specified (ethnicity, religion, etc.). Lastly, the ownership criterion depends on the internal support granted to the commitment inside the enterprise. Following the methodology, a score of 0/100 for commitment in a particular dimension simply means that the company has not disclosed any public commitment (in a CSR report for example), or taken part in any initiative at the sectoral or global levels regarding this specific dimension.

[4]  This index is based on the coding of violations in textual sources from the ILO supervisory system, national legislations and other related reports.

[5]  From the CBR dataset, we retain two variables which are converted into a single synthetic indicator (Codetermination) through simple averaging which measures de jure workers’ participation rights in the firm: Variables 30 (Codetermination: board membership) and 31 (Codetermination and information/consultation of workers).

[6]  Following Adams et al (2019), we measure employment protection through a composite indicator averaging multiple variables (EPL, see Appendix A). However, contrary to these authors who integrate the two variables on codetermination in the measure of employment protection, we chose to exclude them from the indicator in order to single out the specific effect of codetermination on CSR.

[7]  Bartosch and Jackson’s index of corporate social responsibility is based on information on controversies brought forward in the public realm by media or NGO reports.

[8]  Regarding economic characteristics, we construct two indicators. The degree of internationalization of the firm’s assets, Internationalization, is computed as 1-((Domestic Assets)⁄(Total Assets)). It is therefore an indicator which measures the firms’ presence abroad. As for equity growth, g, it is computed as a growth rate, Growth=log(〖Equity〗_t )-log(〖Equity〗_(t-1) ). Finally, we must also mention that we include a control for country GDP per capita.

[9]  Table 6 in Appendix C also provides information on the disaggregation of data by sector.@

[10]  We choose this threshold because 30 points is the score where performance switches from the poorest qualification (“Weak”) to immediately better one (“Limited”) in VigeoEiris methodology.

[11]  StataCorp (2011).

[12]  It is important to make a clarification regarding the use of this command. As it requires that the values of the dependent variable belong to the [0;1] segment, we divide it by 100. Finally, it must be noticed that fractional regression is not suitable for individual fixed effects due to the “incidental parameter problem” (Neyman & Scott, 1948) so we limit ourselves to present pooled data models.

Results

Determinants of CSR leadership

Table 1 presents the results on the determinants of CSR leadership for each of the subdimensions. On the three dimensions related to internal stakeholders, freedom of association, non-discrimination and Health & Safety, results are relatively identical regarding the influence of firms’ characteristics, such as age, internationalization, size and growth with some limited variations in terms of magnitude. It seems that bigger, older1 and more internationalized companies tend to disclose higher levels of commitment which is relatively consistent with previous empirical findings. Nevertheless, it could also be interpreted as a consequence of the greater ability and resources these companies have to report on their policies. The impacts of internationalization and size however decreases as these variables grow, as shown by the negative signs of the coefficients of the squared indicators[2]. The subdimensions also show similar patterns of negative evolution with regards to the growth of firms’ equities: the faster a firm grows, the less it commits on internal dimensions of CSR. It could possibly indicate that managers in those companies tend to neglect these issues and maybe postpone them until the firm becomes more mature and exposed.

Results in terms of industries are also relatively close as Mining and Utilities are always among the industries with the highest effects, and this is also the case for Manufacturing in two of them (Freedom of association and Health & Safety). Finally, the Health industry seems to place also great emphasis on committing on non-discrimination issue[3]. The reasons for this higher level of commitment might vary substantially from one industry to another and we can only make hypothesis on the factors driving this higher interest for CSR. For example, the Mining industry has been the target of many campaigns by NGOs in the last decades for the harsh working conditions in the lowest tier of its value chain. In the sector of Utilities, many companies are former public companies and have public authorities for major clients. Then, they might be more in demand of social reporting and responsibility. Finally, the rate of unionization is traditionally higher in the manufacturing industry.

Labour rights are positively associated with all the internal dimensions of CSR with some sizeable variations in terms of magnitude. This relation is unsurprisingly strong with the subdimension of Freedom of Association, less important for Health & Safety and relatively weak in the case of Non-Discrimination. The effects of other labour indicators are relatively close, as higher protection levels for workers tend to be positively associated with the internal dimensions of CSR, especially for Freedom of Association and Health & Safety. Capacity of workers to take part to companies’ decision or to be consulted and informed is also associated with positive outcomes in these two dimensions. However, the relatively weak (in case of labour rights) or absent (in the case of codetermination) effects of collective workers’ rights in the case of disclosure on Non-Discrimination could indicate that, for this specific dimension, other factors (for example cultural or historical ones) could be overriding. Finally, the level of GDP per capita has a divergent effect on CSR commitments: it is negative with Freedom of Association, positive with Non-Discrimination and non-significant with Health & Safety.

Regarding the only labour dimension which is related to external stakeholders, Social Factors in the Supply Chain, the results emulate those of the regressions on internal dimensions for age, size, internationalization (to a lesser extent) and growth rate, showing that, in terms of commitment, it does not make a difference to firms whether CSR is targeted on their own employees or to the workers in their sphere of influence. More mature firms tend to commit more also in this dimension. Concerning sectorial influences, Retail and Hotels & Restaurants appear as key committers with regards to the social dimension of the supply chain. The Retail sector gathers at the same time wholesale and specialized distributions, such as for example clothing and apparel retailers. Several leading brands in this area have been particularly scrutinized by social and labour activities and became the object of regular public campaigns because of the poor working conditions in their supply chains in recent years. The industry of Hotels and Restaurants also features an interesting pattern as it is at the same time one of the most committing sectors in the domain of Social Factors in the Supply Chain and one the least committing in terms of Freedom Association for internal employees.

Finally, companies which originate from countries with stronger collective labour rights (and to a lesser extent with more protected employees) tend to commit more also in the supply chain dimension. One possible driver for this might be the existence of a transnational solidarity from workers in the country of origin where labour rights are better guaranteed towards their counterparts based in countries with often less protective institutions. The positive, albeit weak, impacts of codetermination legislations might also show that workers’ participation in management board could be a resource for more workers’ pressure on firms’ decisions in this domain.

Table 1 Determinants of leadership

Decoupling assessment

Several indicators have been computed to describe the occurrence of decoupling among the firms in the sample. The first three columns of Table 2 are the decoupling headcount ratios indicators presented in Equation 5, whereas the last two present the aggregate decoupling intensity indicators detailed in Equation 3. Policy-means decoupling appears to be a relatively widespread phenomenon. As shown in Table 2, almost 58% have a difference of at least 30 points between leadership and implementation scores in at least one dimension and 40% of them decouples in two or more dimensions. Non-Discrimination is clearly the subdimension that decouples the more in terms of headcount rates: almost 30% of firms have a leadership score 30 points or more above that of implementation. On the contrary, Health & Safety is the dimension where more firms avoid having commitments not being coupled with actions.

Yet, assessing the intensity of decoupling depends on the indicator used. In absolute terms (percentile points on a 100% basis), there are no big differences among dimensions since in all cases decoupling lies between 4.2 and 7.1 percentile points. However, when we look at relative scores (in relation to leadership), there are signs that decoupling is clearly more intense for freedom of association, as it reaches almost three times the score of Health & Safety. Results indicate that, for some reason, firms might as well put more effort in turning commitment into action in Health & Safety rather than in other dimensions.

Table 2 Decoupling indicators, last observation by firm from 2014 to 2016

Determinants of decoupling

Regarding the determinants of decoupling, the results of the four main regressions are presented in Table 3, whereas robustness checks can be found in Appendix D. As explained earlier, the robustness checks correspond to regressions applied to smaller samples (firms with a substantial level of leadership, above 30/100) and Probit regression (see Section 3.2). When considering both main regressions and robustness checks, results appear somewhat divergent between Freedom of Association, the two other internal dimensions of CSR and Social Factors in the Supply Chains.

In the case of FOA, our results on the influence of LMIs on decoupling are inconclusive due to lack of robustness. The outcomes are indeed contradictory across specifications: while in Table 3 (columns 1 to 3) the coefficients are significant at 1% and positive, restricting the sample for the fractional regression to those observations with leadership above 30 (Table 7) delivers a negative and significant coefficient for Labour Rights while the coefficients on codetermination and employment become non-significant. One possible explanation could be the existence of spuriously low levels of decoupling. In fact, around half of the sample has leadership scores in this subdimension below 30 points. Therefore, due to the way the decoupling indicator is elaborated, those firms have automatically low decoupling values as well. In other words, there is “no room” for decoupling, or no commitments to be implemented. In turn, leadership in FOA is strongly and positively correlated with labour rights and other labour indicators. Then, having half of the sample with low decoupling and low Labour Rights values might determine that the overall coefficient is positive, even if within the group with greater levels of leadership the relation is negative. If this were the case, then the results of Table 7 should be taken for valid and we would have evidence to conclude that stronger Labour Rights (but also employment protection) reduce decoupling in Freedom of Association.

Table 3 Determinants of decoupling (Fractional Regression on full sample)

Regarding Non-Discrimination and Health & Safety, the analysis of the impacts of labour rights on decoupling shows relatively similar and robust results across specifications. Labour rights seem to have a negative association with decoupling for both subdimensions, meaning that stronger de jure and de facto protection of workers’ rights leads to greater implementation of policies by companies in these domains (Table 3, column 6 and 9). For example, an increase of one standard deviation in the Labour Rights indicator is associated with reductions in decoupling of between 0.15 and 0.22 standard deviations in Non-Discrimination of between 0.17 and 0.56 standard deviations in Health & Safety. For other LMI indicators, results diverge: they are non-significant in the case of ND (reinforcing our earlier observation that corporate policies in this domain might be more prominently motivated by other institutional elements) and they are negative and significant in the case of Health & Safety, meaning that having more protected employees with a voice in corporate decisions might have an impact in this dimension.

Regarding the Social Factors in the Supply Chain, evidence is only partially conclusive. While the main regression does not show any significant coefficients, both the fractional regression on the restricted sample and the Probit bring negative and significant association between Labour Rights and decoupling, as well as for other labour institutions indicators (SeeTable 3, 7 and 8, columns 10 to 12). This could be interpreted as if the effects of stronger labour rights and protection on decoupling are visible only for the more committing firms.

Regarding firms’ characteristics, the results on FOA are mostly inconclusive due to lack of robustness across specifications, with the notable exception of internationalization. An increase of one standard deviation in internationalization rises decoupling by around 0.385 standard deviations, pointing that more internationalized firms tend to commit more without implementing (Table 3, columns 1 to 3), even if the negative and significant coefficient of the squared term indicates that this effect fades away as internationalization grows.

Health & Safety and Non-Discrimination share relatively similar patterns of evolution with regards to firms’ characteristics. For both, we find robust evidence of being negatively associated with firm size. For example, we observe that for every additional 100.000 employees decoupling decreases, respectively, by around 0.11 standard deviations for Non-Discrimination[4] and 0.037 standard deviations for Health & Safety[5] (and that these effects are non-linear, slowly weakening as firm size increases). In the case of SSC, evidence remains inconclusive. When we restrict the sample above 30 points of leadership (Table 7, columns 10 to 12), the apparent effect of age and GDP per capita that we observe in Table 3 vanishes, and in the case of firm size, its coefficient stays significant but switches signs.

There are clear differences across subdimensions when it comes to sectorial effects on decoupling. Firms in two particular industries, Manufacturing and Mining, appear to be strong committers yet weak implementers in three dimensions at the same time (FOA, ND and SSC). The case of Hotels and Restaurants is also interesting as it seems to be a sector where high levels of commitments in the domain of SSC are not always accompanied by implementation measures. The Construction and the Real Estate sectors also show high effects in at least two subdimensions (respectively Freedom of Association and Non-Discrimination, and Health & Safety and Non-discrimination). Finally, it is worth mentioning the specific case of Utilities in the three internal subdimensions, where high effects on commitment are not paired by high effect on decoupling.

It must be noted that we have obtained only partial evidence on the determinants of decoupling. Although the regressions' output indicates consistent and logical relations between labour rights and decoupling in two CSR dimensions (ND and HS), and between all LMIs and HS, other results are not robust to changes in the LMI indicator included in the specification or to changes in estimator. Then, the latter should not at all be considered as conclusive evidence and the authors suggest further research on these relationships.

[1]  For example, an additional year of age increases FOA commitments by 0.0141 to 0.151 standard deviations.

[2]  If the effects of internationalization and size are fading, they never reverse as this would only happen in impossible or implausible values of the explained variables (above 4 standard deviations).

[3]  It is not clearly seen in the table because we chose to present sectors with up to the third highest and lowest significant coefficients, but health and manufacturing have very similar scores in the three specifications, disputing the last place in the “podium” of sector effects.

[4]  Regarding ND, we also find other interesting results in our regressions, but do not rely on them as they do not fully meet our robustness criteria. Older and more internationalized firms seem to decouple less than their younger and/or local counterparts. These results are in line with the coefficients on size and our results on CSR determinants (positive effect of age and internationalization on commitment), in the sense that more mature (large, old and international) firms tend to commit and implement more. However, the lack of robustness (signs do not change but coefficients become non-significant) to changes in estimators LMI indicators casts doubt about the validity of these results.

[5]  As the non-significance of the coefficient in column 8 casts doubts about robustness of our results, we proceed to check further. The results on the subsample above 30 points of leadership in columns 7 to 9 of Table 7 show that the effect ranges between 0.07 and 0.1 standard deviations and is significant in all three models. Moreover, the Probit specification in Table shows that, for the full sample, that same increase in size decreases the probability of decoupling by 7.15% to 9.79%.

Conclusion

This article aimed at furthering the reflexion on the economic and institutional determinants of CSR and on the decoupling between corporates’ commitments in this regard and their concrete implementation. In this purpose, this article paid a special attention to the role of labour institutions, especially collective labour rights which have remained only little explored in the scholarly discussion until now. The dataset provided by VigeoEiris allowed us to cover a diversified panel of (highly capitalized) enterprises originating from both developed and emerging economies and distinguish between different dimensions related to labour in firms’ policies. In the continuation of the literature on stakeholders’ salience (Mitchell et al 1997, Jackson and Rathert 2017), our research thus provided insights on the way labour institutions in the country of origin can influence the prioritisation between different dimensions of CSR.

In the last years, academic discussion on the relationship between CSR and social regulation has structured around two contradictory interpretations: the complementarity thesis which considers strong social regulation as a condition for more CSR and the substitution thesis which sees the expansion of CSR as a consequence of economic liberalization and deregulation. Our empirical analysis provides evidence supporting the first thesis as the existence of strong labour institutions seems to significantly influence all the four dimensions of labour CSR analysed in this article (Freedom of Association, Non-Discrimination, Health & Safety and the Social Factors in the Supply Chain).

Clearly, institutions matter in this regard even if there are sizeable variations in terms of magnitude according to the dimensions analysed and the institutions concerned. The relation between the quality of collective labour rights (measured by a composite indicator considering at the same time de jure and de facto violations of labour rights) is unsurprisingly strong with Freedom of Association, positive for Health & Safety and SSC, yet relatively weak in the case of Non-Discrimination. The effects of other LMI indicators (measured by de jure indicators) are relatively close, as higher protection levels for workers tend to be positively associated with all the dimensions of CSR. Likewise, the capacity of workers to take part to companies’ decisions or to be consulted and informed is also associated with positive outcomes in all the dimensions except Non-Discrimination. The relatively weak (in case of labour rights) or absent (in the case of codetermination) effects of collective workers’ rights in the case of disclosure on non-discrimination could indicate that for this specific dimension other factors (for example cultural or historical factors) could be overriding. In addition, the fact that companies which originate from countries with stronger collective labour rights tend to commit more also in the supply chain dimension could be possibly interpreted as a sign of a transnational solidarity from workers in the country of origin where labour rights are better guaranteed towards their counterparts based in countries with often less protective institutions.

Regarding the economic determinants of CSR, our results are relatively in line with previous empirical findings. Globally, it seems that bigger, older and more internationalized companies tend to disclose higher levels of commitments in all the labour-related dimensions of CSR. Our research also helped to identify differences between industries in terms of priorities: everything else being equal, companies operating in sectors such as Mining, Utilities and Manufacturing tend to stand out regarding the internal dimensions while those in the sectors of Utilities (again), Retail and Hotels & Restaurants generally feature higher commitments with regards to the social monitoring of the supply chains.

Nevertheless, the analysis of the institutional determinants of decoupling between commitments and implementation provide a somewhat more nuanced perspective. Some authors have considered that the presence of trade unions and their involvement in corporate governance could be a lever to make firms’ commitments more effective (Harvey et al 2017). Our empirical findings seem to partially support this assumption in the subdimensions of Non-Discrimination and Health & Safety where an improvement in labour rights is significantly associated with a reduction of decoupling. Higher employment protection and improvement in rights of codetermination and/or information and consultation also seem to have a positive influence on Health & Safety (but not for Non-Discrimination for which non-significant results are observed). In the case of the concrete implementation of commitments concerning Freedom of Association, our results on the influence of labour rights as well as other institutional indicators on decoupling are inconclusive due to lack of robustness. As well, regarding the Social Factors in the Supply Chain, evidence is only partially conclusive as the effects of stronger labour rights and protection on decoupling are visible for the more committing firms solely.

Concerning economic determinants, empirical analysis does not feature very clear-cut results except for company size. This variable seems to be negatively related to decoupling in the dimensions of Health & Safety and Non-Discrimination. Nonetheless, we manage to identify clear differences across dimensions when it comes to sectorial effects on decoupling. For example, two industries, Manufacturing and Mining, appear to be at the same time strong committers and weak implementers in several subdimensions at the same time while Utilities show high level of commitments in all the dimensions targeted at internal employees without any showing any signs of decoupling significantly more than the rest.

Finally, we should point out some of the shortcomings of our current work. The first one draws from the lack of information on the companies’ involvement in other countries either through their foreign subsidiaries or through their supply chains. Various research in recent years have pointed out the role of local institutions and local stakeholders, including trade unions, on the CSR policies undertaken by multinational companies (Jackson and Rathert 2017) and their concrete impacts in terms of working conditions and access to rights for the workers in their global supply chains (Toffel et al 2015, Amengual and Chirot 2016, Dupper et al 2016, Bartley and Egels-Zanden 2016). We recognize that identifying the respective roles of institutions and stakeholders in the country of origin and in the countries of operation represents a major issue for further research. Second, our research has been limited to the analysis of the discrepancies between policies and practices. By definition, the data used in this paper rely on the public information voluntarily disclosed by private companies. In consequence, it favours a relatively explicit conception of CSR. The difficulty in measuring CSR behaviour has long been recognized in the literature (Brammer et al, 2012), not only because of the many ambiguities on what business responsibility should entail or not, but also because of the field opacity which often prevents to identify the concrete impacts of these initiatives (Kuruvilla et al 2019). In sum, we acknowledge that the analysis of causal relationships between commitments, implementation and results of labour related CSR policies needs further investigation.

Appendix A

Table 4 Variables related to employment protection (top) and codetermination (bottom)

Source: Adams et al (2016)

Appendix B

Table 5 Descriptive statistics

Appendix C

Table 6 Number of firms by sector – Aggregated classification

Appendix D

Table 7 Determinants of decoupling (robustness check, LCSR>30)

Table 8 Determinants of decoupling (robustness check, Probit)

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Acknowledgements

The authors would like to thank the two internal peer reviewers for their helpful and constructive comments that greatly contributed to improving this working paper. The authors remain of course responsible for all errors contained in the text.

This research benefited from the financial support of the French government as part of the cooperation agreement between the French government and the ILO.