metadata: authors: 0: author: Hollweg,Claire Honore
count: Vietnam
docna: 0: docna: Firm Compliance and Public Disclosure in Vietnam
docty: Policy Research Working Paper
abstracts: cdata!: Global consumers, international brands,
            and governments in producing and outsourcing countries aim
            to improve working conditions in global value chains, but
            uncertainty exists about what is the best approach. This
            research uses firm-level data from the International Labour
            Organization–International Finance Corporation Better Work
            Vietnam program to assess the relationship between
            transparency on working conditions and firm compliance in
            the apparel sector in Vietnam between 2010 and 2018. It
            exploits a change in the policies of Better Work Vietnam
            when, in 2015, the program announced the launch of a new
            public disclosure program that would see factories'
            names made publicly available along with their compliance
            (or lack thereof) with certain "critical issues."
            The paper first examines which firm characteristics
            correlate with reductions in noncompliance rates over time,
            and then examines the impact of the public disclosure policy
            on compliance rates and firm dropout using different
            empirical techniques. It finds that while continued
            participation in the Better Work Vietnam program has the
            strongest effect on changes in firm compliance with labor
            standards over time, public disclosure is also associated
            with increased compliance, with stronger effects in some
            compliance points, including occupational health and safety,
            work time, and child labor. There is some evidence of
            increased dropout, but no evidence of firms only making
            progress on the critical issues is found. The research
            findings suggest that public disclosure within global value
            chains matters for firm behavior.
geo_reg_key: 517198,517191
repnme: repnme: Firm Compliance and Public Disclosure in Vietnam
display_title: Firm Compliance and Public
            Disclosure in Vietnam
listing_relative_url: /research/2019/09/31436584/firm-compliance-public-disclosure-vietnam
publishtoextweb_dt: 2019-09-26T00:00:00Z
no_of_pages: 41
author_keys: 0: author_key: 1183206
model_extractions: Policy Research Working Paper 9026 Firm Compliance and Public Disclosure in Vietnam _Claire H. Hollweg_ Macroeconomics, Trade and Investment Global Practice September 2019
Policy Research Working Paper 9026

# **Abstract**

Global consumers, international brands, and governments in producing and outsourcing countries aim to improve working conditions in global value chains, but uncertainty exists about what is the best approach. This research uses firm-level data from the International Labour Organization–International Finance Corporation Better Work Vietnam program to assess the relationship between transparency on working conditions and firm compliance in the apparel sector in Vietnam between 2010 and 2018. It exploits a change in the policies of Better Work Vietnam when, in 2015, the program announced the launch of a new public disclosure program that would see factories’ names made publicly available along with their compliance (or lack thereof) with certain “critical issues.” The paper first examines which firm characteristics correlate with reductions in noncompliance rates over time, and then examines the impact of the public disclosure policy on compliance rates and firm dropout using different empirical techniques. It finds that while continued participation in the Better Work Vietnam program has the strongest effect on changes in firm compliance with labor standards over time, public disclosure is also associated with increased compliance, with stronger effects in some compliance points, including occupational health and safety, work time, and child labor. There is some evidence of increased dropout, but no evidence of firms only making progress on the critical issues is found. The research findings suggest that public disclosure within global value chains matters for firm behavior.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The author may be contacted at chollweg@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Firm Compliance and Public Disclosure in Vietnam

Claire H. Hollweg<sup>1</sup>

## **JEL classification:** J8, D22, F16

**Keywords:** Labor standards, Global value chains, Compliance, Public disclosure

1 Claire H. Hollweg is a Senior Economist in the East Asia and Pacific Region, Macroeconomics, Trade & Investment Global Practice, World Bank. This paper is a joint product of the Trade & Regional Integration Unit, Macroeconomics, Trade & Investment Global Practice, World Bank and the International Labour Organization. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The author may be contacted at chollweg@worldbank.org. The author thanks Daria Taglioni, Mary Hallward‐Driemeier, Jeffrey Eisenbraun, Arianna Rossi, and two anonymous peer reviewers for valuable comments, and Martin Kanz for excellent research assistance. The study has been made possible through a grant from the World Bank’s Jobs Umbrella Trust Fund, which is supported by the Department for International Development/UK AID, and the Governments of Norway, Germany, Austria, the Austrian Development Agency, and the Swedish International Development Cooperation Agency, as well as data access and collaboration with the International Labour Organization.
# Introduction

Understanding mechanisms to improve working conditions in GVCs is a policy priority for governments in both producing and outsourcing countries, both from a social and economic point of view. Working conditions often fall short of international standards in producing countries. At the same time, a growing number of studies show that better working conditions are positively associated with improvements in profits, productivity, and firm survival (World Bank 2015).

Labor and social standards for firms in GVCs have been introduced in countries to address poor working conditions, but their effectiveness is not fully evident. Moreover, there is limited availability of firm‐level evidence about factors that facilitate increased compliance with labor and social standards. This paper helps fill this gap by strengthening the micro‐level analysis of firms' compliance with labor standards in Vietnam’s apparel sector through one possible policy measure: transparency. The findings support evidence‐based policy making.

This research leverages factory‐level data from the ILO‐IFC Better Work Vietnam program to assess the relationship between transparency of working conditions and firm compliance with labor standards in Vietnam. It exploits a change in the policies of Better Work Vietnam when, in 2015, the launch of a new Public Disclosure Programme was announced that will make factories’ names publicly available along with their compliance (or lack thereof) with certain “critical issues”. These critical issues include compliance clusters around discrimination, child labor, minimum wage payments, and various aspects of safety and health in the workplace. The primary objective of the Public Disclosure Programme is to accelerate the pace of improvements across the industry, thus raising worker well‐being and the industry’s reputation for ethical standards (Better Work Vietnam 2015).

We test whether changes in the transparency mechanism through public disclosure in GVCs changes firms’ adoption of better practices regarding working conditions. Specifically, the key question around compliance with labor standards in Vietnam that the paper addresses is:

- _Is there evidence that transparency through the Public Disclosure Programme accelerates adoption of compliance requirements? Does this vary by firm characteristics or compliance cluster?_ We test whether firms’ compliance with labor standards increases after the announcement and/or launch of the Public Disclosure Programme. We then test whether these results vary by firm characteristic or compliance cluster.

The effect of firm participation in monitoring and training programs on compliance has been more widely studied, in particular ILO‐IFC Better Factories or Better Work programs, focused largely on Cambodia. We also test whether overall results of the impact of program participation on compliance holds for Vietnam. This helps us to identify the effect of the disclosure policy specifically, rather than program participation generally. In doing so, we address three additional questions:

- _Are there certain characteristics of firms that do not meet compliance requirements?_ We test if firms of different size or age are less likely to comply with certain types of compliance clusters (including child labor, contracts, discrimination, forced labor, freedom of association, occupational health and safety, and work time).

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- _Are there certain characteristics of firms that adopt compliance requirements?_ We test if certain types of firms are more likely to change compliance behavior within certain types of compliance clusters (including child labor, contracts, discrimination, forced labor, freedom of association, occupational health and safety, and work time).

- _In what compliance clusters are firms more likely to adopt compliance requirements during Better Work Vietnam participation?_ We test whether firms are more likely to adopt compliance requirements in certain compliance clusters, and whether this varies by firm characteristics.

Finally, to understand additional impacts of the Public Disclosure Programme on firm behavior, we also look at two additional questions, namely:

- _Does transparency shift factory efforts to alternative areas of compliance?_ One concern with selecting critical issues to report on is whether firms would only make progress to the critical issues at the expense of other issues. We test whether, after the announcement of the Public Disclosure Programme, firms were less likely to make progress towards compliance in areas outside the 26 critical issues.

- _Does transparency lead some firms to drop out of the program? If so, which ones?_ We test whether firm dropout of the Better Work Vietnam program is greater after the announcement of the Public Disclosure Programme, and whether this varies by firm characteristics.

The Public Disclosure Programme publishes factories’ names along with their compliance (or lack thereof) with certain “critical issues” on a publicly‐available transparency portal.<sup>2</sup> The transparency portal makes key findings from Better Work assessments public, revealing which factories have been found ‘non‐ compliant’ on the critical issues such as occupational safety and health, child labor, forced labor, discrimination, worker compensation, contracts and freedom of association.

A factory’s compliance findings remain on the transparency portal until a new Better Work assessment report is published, at which point the site is updated to reflect just the most recent data. The transparency portal is updated continuously and includes information on factory name, factory type, country, assessment date, cycle number and the number of publicly reported issues found not to comply with international labor standards or national law. The findings are published in English.

The 26 critical issues of the Better Work Vietnam’s Public Disclosure Programme were approved and announced to all factories in August 2015. The program went into implementation in June 2016, and in April 2017 the first compliance reports within the 26 critical issues were made publicly available when the transparency portal went live.

In our analysis, however, we use the full set of data collected in the Compliance Synthesis Report during unannounced visits where monitoring teams of usually two people carry out an assessment of working conditions in participating factories. This data set is available from 2010 through mid‐2018 and includes information on all compliance points, including the 26 critical issues. Data from the Compliance Synthesis Report are subsequently merged with Better Work Vietnam’s Registration Document, which contains

> 2 The transparency portal is available at <u>https://portal.betterwork.org/transparency.</u>

3
additional information on firm characteristics including firm size, firm age, and information on buyer relationships.

Although earlier studies analyze similar research questions to those posed in this paper, this paper contributes to the literature in a few notable ways. It is most closely related to Ang et al. (2012) and Robertson (2017), who explored the role of transparency on firm compliance of labor standards in Cambodia. First, we provide additional evidence of this relationship for Vietnam, where earlier findings for Cambodia were inconclusive. Second, participation in ILO‐IFC Better Work in Cambodia is mandatory for exporting firms, while in Vietnam participation is voluntary. This allows us to explore how public disclosure impacts compliance in a country where participation is voluntary. Third, we consider additional impacts such as whether transparency leads to shifts in areas of improvement or firm drop out.

In the first part of the analysis, we examine which firm characteristics correlate with noncompliance outcomes as well as changes in noncompliance outcomes over time. To do so, we estimate cross‐sectional fixed‐effects regressions, controlling for other observable characteristics of the firm. The dependent variable is the noncompliance outcome of a firm for different compliance points.

In the second part of the analysis, we examine the impact of the public disclosure policy on compliance rates using heterogenous effects regressions. It is important to note that no firm in the sample was entirely unaffected by the policy, so we do not have a control group that would allow for causal identification. Instead, this approach compares compliance rates for firms before and after the policy announcement, to study how effective disclosure is conditional on firm characteristics.

We find that while continued participation in the Better Work Vietnam program has the strongest effect on changes in firm compliance with labor standards over time, public disclosure is also associated with increased compliance. Public disclosure appears to have a stronger impact on particular compliance points including occupational health and safety, work time, and child labor. No evidence of firms only making progress on the critical issues is found. Policy implications suggest that public disclosure, at least within global value chains, matters for firm behavior.

# Related literature

Firm‐level evidence of factors that impact working conditions within global value chains is limited in developing countries. However, several strands of literature look at the relationship between working conditions and trends in global markets, firm performance, monitoring and training programs, and transparency.

Changing conditions in the global apparel market may be one factor that affects the ability or desire for firms to improve working conditions. For example, Rawanpura et al. (2011) describe how the financial crisis, where falling demand increased competitive pressure on exporters, may have made it more difficult for Sri Lankan garment producers to improve working conditions. On the other hand, Beresford (2009) finds that working conditions did not fall in response to an increasingly competitive environment in Cambodia when the MultiFibre Agreement ended at the end of 2004, which effectively increased the number of suppliers that competed directly with each other.

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A growing number of studies have taken various approaches to try to identify the relationship between firm performance and working conditions. These studies show that profits, productivity, and firm survival are positively associated with improvements in working conditions and increased compliance with labor standards (World Bank Group, 2015). A discrete‐time survival analysis model of 595 Cambodian garment factories by Jetha and Linsen (2015) found that increased compliance with social protection standards was associated with reduced odds of factory closure. A survey of management and laborers in the Lao PDR garment sector found that failure to increase worker well‐being led to dissatisfaction, higher labor turnover, lower productivity, and impaired firms’ opportunities to strengthen participation in garment GVCs (World Bank, 2012). Brown et al. (2016) demonstrate that garment factories with higher compliance with international labor standards have higher labor productivity and higher profitability. Oka (2012) examines the link between labor standards and supplier competitiveness. The study finds that better labor standard compliance increases suppliers’ likelihood of retaining buyers that are reputation‐conscious, though it does not drive buyers’ sourcing decisions. Other criteria such as price, quality, and delivery time matter more.

Firm participation in monitoring and training programs, in particular ILO‐IFC Better Factories or Better Work programs, has been more widely studied. These programs combine monitoring, remediation and training for participating factories. For example, Better Factories Cambodia was shown to be successful at improving compliance with national law and international standards since its implementation in 2001 (Robertson 2017). Other studies have shown a positive relationship between program participation and working conditions in Cambodia (Adler and Woolcock 2010, Beresford 2009, Berik and van der Meulen Rodgers 2010, Miller et al. 2009, Oka 2010a, Oka 2010b, and Polaski 2006). Shea et al. (2010) and Brown et al. (2016) find that the improvements in working conditions and factory compliance come through engagements with multiple stakeholders as part of the program in Cambodia. Bair (2017) show similar results for Nicaragua. This stand of literature relates most closely to the three additional research questions of this paper.

Two papers examine transparency through public disclosure and compliance in Cambodia, which relate most closely to the primary research question of this paper. First, using firm‐level data from Cambodia, Ang et al. (2012) find that the end of public disclosure in 2006 adversely affected compliance. The authors also use linear probability modeling to test if compliance in different compliance categories is correlated with a binary indicator during the period of public disclosure. The authors also test for differences in compliance performance of firms that sell to reputationally sensitive buyers. Their results suggest that the threat of public disclosure of noncompliance induces compliance, even in factories lacking reputation sensitive buyers. In the post‐public disclosure period, all groups of factories maintained a significant record of compliance, but the propensity for improvement fell.

Second, Robertson (2017) exploit a policy reversal in Cambodia when in 2014 Better Factories Cambodia announced the return to public disclosure to study changes in compliance trends before and after the policy change. The paper evaluates the change in compliance in Cambodian garment factories using different empirical approaches: estimating endogenous trend breaks in compliance, probit regressions, and survival analysis. Overall, the results found in Robertson (2017) are inconclusive. Compliance was generally falling prior to the change. Controlling for year effects in probit regressions, the author finds 5
that, in general, compliance after the policy change is higher than it may have been otherwise. The results show trend breaks for two categories of compliance – emergency and minimum wages – which changed from a negative trend to a positive trend close to the policy announcement. Other categories of compliance, such as use of safety guards or barriers, showed consistent downward trends that did not seem to change around the time of the policy change. Controlling for variables that may also affect the factory’s compliance decision with Probit regressions, such as number of factory visits, shows no relationship pre‐ and post‐disclosure period with compliance. Only when year effects are controlled for does the compliance in the disclosure period show it is higher than it would otherwise be. Survival analysis, which looks at whether the change to public disclosure changed the propensity to become compliance, instead shows that becoming noncompliant is more likely during the public disclosure period.

Although earlier studies analyze similar research questions to those posed in this paper, this paper contributes to the literature in a few notable ways as noted above. First, we provide additional evidence of the impact of transparency on firm compliance from Vietnam, where earlier findings were inconclusive for Cambodia. Second, earlier research on transparency in Cambodia was undertaken in a country where program participation for exporting firms is mandatory. We instead explore if public disclosure of compliance data might lead to more compliance in a country where participation in Better Work is voluntary for exporting firms. In addition, there is a “Low Compliance” factory list in Cambodia while in other countries, including Vietnam, there is not. The effects of a public disclosure program could be very different when participation is voluntary where, for example, firms can drop out of the program. Third, we consider additional impacts such as whether transparency leads to shifts in areas of improvement or firm drop out.

# Public disclosure in Vietnam

Better Work Vietnam was created in 2009 as a partnership between the UN’s International Labour Organization (ILO) and the International Finance Corporation (IFC), a member of the World Bank Group. The program engages with workers, employers, and governments to improve working conditions and boost competitiveness of the garment industry. As of 2018, Better Work Vietnam was working with 524 factories across 59 brands and retailors accounting for 733,000 jobs. The program has conducted over a thousand assessments and advisory visits to help factories identify and improve their working conditions and labor standards. Better Work Vietnam also works with national stakeholders in the Government, Trade Union and Employer’s Organization to build their capacity to support compliance and improvement in the industry and develop practical, evidence‐based policies for more effective labor market governance.

In late 2014, Better Work Vietnam started working towards a new policy of public disclosure of the names of firms that failed to meet compliance requirements in select issues deemed critical for working conditions. Consultations first took place with select stakeholders to introduce the concept of the portal in early 2015. Several rounds of consultations took place through a Better Work Vietnam Project Advisory Committee, which included the Ministry of Labour, Invalids and Social Affairs (MOLISA), Vietnam General Confederation of Labour (VGCL) and Vietnam Chamber of Commerce and Industry (VCCI), to finalize the list of critical issues to be reported on. These consultations continued through 2015.

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Factory consultations also took place in 2015 through several Better Work factory focus groups in Hanoi and Ho Chi Minh City. Enterprise advisors also communicated the initiative during their advisory visits with factories, and gathered feedback. However, the 26 issues to be reported on had not yet been decided.

In August of 2015, the portal and the 26 issues to be reported on were approved by the Better Work Vietnam Project Advisory Committee. Notification letters were sent out to all factories, which was part of a broader communications package that also included factsheets and FAQs.

Between late‐2015 and early‐2016 industry seminars were held with Better Work Vietnam member factories in Hanoi and Ho Chi Minh City to further prepare factories for the launch of public reporting. Factories were also frequently reminded by enterprise advisors that public disclosure was coming. As such, it is possible that factories may have started changing their behavior prior to the program implementation. Dialogue of the new policy was also held with buyers. Better Work Global led the buyer consultation process, and Better Work Vietnam reinforced the messages through their regular buyer dialogues, including buyer forums and quarterly calls.

The program went into implementation in June 2016, when factory assessments would start monitoring the 26 critical issues. However, in July 2017 the first compliance reports within the 26 critical issues were made publicly available when the transparency portal was launched. When launched, the portal included non‐compliance results on the 26 issues for all factories that had at least a Cycle 2 assessment as of June 2016 or later. There have been no changes to public reporting questions since June 2016, and the list is continuously updated on the portal as newer assessments are completed for each factory.

Given the timeline of the roll‐out of the Public Disclosure Programme in Vietnam, we treat August 2015 as the date of Vietnam Public Disclosure Programme announcement, and July 2017 as the date of Public Disclosure Programme implementation. Each factory has at most 3 compliance reports since announcement.<sup>3</sup> Factories’ names along with their compliance (or lack thereof) with certain “critical issues” are publicly‐ available on the transparency portal.<sup>4</sup> A factory’s compliance findings remains on the transparency portal until a new Better Work assessment report is published, at which point the site is updated to reflect just the most recent data. The transparency portal is updated continuously and includes information on factory name, factory type, country, assessment date, cycle number and the number of publicly reported issues found not to comply with international labor standards or national law. The findings are published in English. Advance searches can be made by factory name, assessment date, compliance cluster, and critical issue.

# Methodology

Our hypothesis is that the Vietnam Public Disclosure Program will influence firm compliance, as long as the benefits of improving compliance (retaining buyers or increasing firm performance) outweigh the

> 3 After the announcement in 2015, 106 firms have had one assessment, 217 have had two assessments, and 35 firms have had three assessments in our data set.

> 4 The transparency portal is available at <u>https://portal.betterwork.org/transparency.</u>

7
costs (changing compliance behavior). As discussed in Ang et al. (2012), the benefits, and thus the impact of the program, could also to depend on the reputation sensitivity of the buyer. That is, more reputationally sensitive buyers would be more likely to stop buying for non‐compliant firms. In addition, the cost of changing compliance behavior would vary by compliance question. There is therefore no reason to expect that public disclosure will induce compliance equally cross all questions. We test this hypothesis using descriptive as well as empirical analysis, differentiating by compliance cluster to allow for heterogeneity in the results.

# Graphical analysis

We start the analysis by presenting a graphical overview of trends in the average noncompliance rate of firms that participate in Better Work Vietnam between 2010 and 2018. These include trends in average compliance by year, as well as average compliance by evaluation cycle (duration of participation in the program). We explore these trends across (i) all compliance questions, (ii) compliance questions mapped to broader compliance clusters of child labor, compensation, contracts, discrimination, forced labor, freedom of association, occupational health and safety, and work time, and (iii) compliance questions that fall within the 26 critical issues of public disclosure versus all other non‐disclosure compliance questions.

We use the graphical analysis as a first indication of evidence that the introduction of public disclosure impacted firm compliance, by looking for trend breaks around the time of Vietnam Public Disclosure Program announcement and implementation.<sup>5</sup> However, changes in trends over time could be because firms are changing their behavior in response to the policy change, or because worse / better firms are entering / exiting the Better Work Program, given that participation in the Program is voluntary. As such, a more robust analysis is needed exploiting the firm‐level data to distinguish between trends across firms over time and changes within firms. In addition, the graphical analysis helps inform the empirical strategy. For example, the empirical literature suggests that noncompliance falls with program participation. Controlling for valuation cycle in the empirical strategy would then be important, to separately identify the impact of public disclosure from the impact of program participation on firm compliance.

# Empirical analysis

To start the analysis of the impact of the Public Disclosure Programme on firm compliance, we first examine which firm characteristics correlate with noncompliance rates as well as within‐firm changes of noncompliance rates over time. To do so, we will estimate regressions of the form: or where Noncompliance�,�� is the noncompliance rate (equal to 0 if compliance or 1 if noncompliant) of firm i for compliance question s in compliance cluster c during cycle t, α is a constant, x� is an observable

> 5 Ideally, one would test formally for trend breaks.

8
characteristic of firm i (such as firm size, firm age, number of reputation‐sensitive buyers, etc.), τ are year fixed effects, ω are firm fixed effects, and ε� is a stochastic error term.

We estimate the regression equations for all compliance questions as the outcome variable of interest. We then estimate the regression equations for only compliance questions that fall within each of the eight compliance clusters as the outcome variable of interest. Both equations are estimated using OLS fixed effects.

Thus, in these specifications, the coefficient estimates β� measure which firm characteristics n are associated with noncompliance, overall and with a specific compliance cluster. Equation (1) tests which firm characteristics correlate with noncompliance rates, and Equation (2) tests which firm characteristics correlate with within‐firm changes in noncompliance rates over time by additionally controlling for firm fixed‐effects.

Thus, this part of the analysis allows us to answer the questions:

- _Are there certain characteristics of firms that do not meet compliance requirements (equation 1)?_

- _Are there certain characteristics of firms that adopt compliance requirements over time (equation 2, full sample)?_

- _In what compliance clusters are firms more likely to adopt compliance requirements during Better Work Vietnam participation (equation 2, by compliance cluster)?_

As a first step to explore the key question of this analysis, we then amend equations (2) to be: where POST is a dummy variable equal to 1 if the assessment took place after the public disclosure announcement in August 2015, CYCLE is the number of the cycle assessment (or the length of firm participation), and BASE controls for the firm’s compliance at its initial assessment. Firm‐level characteristics include firm size and firm age.

We control for the cycle assessment to differentiate between the effect of public disclosure per se and the advisory services that factories receive as part of Better Work. The graphical analysis (below) as well as the literature suggests that the advisory services Better Work offers are effective, whereby firms improve compliance over time. Moreover, the intensity of the advisory services for the “at risk” factories may be higher. By controlling for CYCLE, we are better able to identify the effect of public disclosure on firm compliance.

We again estimate the regression equation for all compliance questions as the outcome variable of interest, and then estimate the regression equations for only compliance questions that fall within each of the eight compliance clusters as the outcome variable of interest.

Thus, in equation (3), the coefficient estimate δ measures the change in the non‐compliance rate from before to after policy announcement.

9
We also estimate the regressions for disclosure questions only, to identify whether progress towards compliance of disclosure questions is happening at a faster rate than progress towards compliance of all questions, which would suggest factories are shifting their efforts to ‘teach for the test’.

This part of the analysis allows us to answer the question:

- _Is there evidence that transparency through the Public Disclosure Programme accelerates adoption of compliance requirements? Does this vary by compliance cluster?_

- _Does transparency shift factory efforts to alternative areas of compliance?_

Exploiting the policy change in the disclosure program is therefore the primary identification of the empirical work. Intuitively, this approach compares compliance rates for firms before and after the policy announcement. It shows how effective disclosure is conditional on firm characteristics.

Ideally, we would compare this change against a control group using a difference‐in‐difference specification that would allow for causal identification. However, it is important to note that no firm in the sample was entirely unaffected by the policy.

For robustness we use an additional specification to also examine the impact of the public disclosure policy on firm compliance. We assume that firms with reputation‐sensitive international buyers are more likely to be affected by the public disclosure program, and test whether firms with more reputation‐ sensitive internal buyers increased compliance more post‐program announcement.

Specifically, we will estimate heterogenous effects equations of the form: � � Noncompliance�,�,� �ω�τ�γ���TREAT� ∗POST���∑��� β�x� �γCYCLE�,� �ρBASE�,� �ε�� (4) where Noncompliance�,�,�� is the noncompliance rate (equal to 0 if compliance or 1 if noncompliant) of firm _i_ for compliance question s in compliance cluster c during cycle t, ω are firm fixed effects, τ are time fixed effects, TREAT� is a treatment indicator equal to one for firms affected by the public disclosure policy (e.g. firms with reputation‐sensitive international buyers), POST� is an indicator equal to one for all observations after the program announcement, BASE�,� controls for the firm’s compliance at its initial assessment, x� is an observable characteristic of firm i, and ε�� is a stochastic error term. Firm‐level characteristics include firm size, firm age and baseline non‐compliance.

Thus, in equation (4), the coefficient estimate γ measures the change in the non‐compliance rate from before to after policy announcement conditional on firm characteristics.

We again first estimate this regression using each firm’s overall compliance rate (or compliance with the public disclosure questions) as the outcome of interest. We then estimate the regression using compliance rates for each of the eight compliance clusters as the outcomes of interest. This will enable us to test whether certain types of firms accelerate adoption of compliance requirements, and whether transparency through the Public Disclosure Programme accelerates adoption in some compliance clusters more than others.

10
As in equation (3), we control for the evaluation cycle, that is, how long a firm has already participated in the program to ensure that the results are not biased by more entry of new firms into the program in certain years. This is important, because in years where more new firms join the program this could worsen average compliance rates for reasons unrelated to the program. Firm‐level characteristics include firm size, firm age, and baseline non‐compliance. Firm size, firm age, baseline non‐compliance, and length of participation in program are all measured as a dummy variable equal to 1 if the firm is above the median value of these variables. This is to be able to also control for firm‐level fixed effects.

Thus, this part of the analysis allows us to answer the question:

- _Is there evidence that transparency through the Public Disclosure Programme accelerates adoption of compliance requirements? Does this vary by firm characteristic or compliance cluster?_

Our analysis uses question‐level observations as the dependent variable (equal to 0 if compliance or 1 if noncompliance). However, the right‐hand side variables are at the firm‐level. As robustness, we use the firm‐level noncompliance rate as the dependent variable (over). As a second robustness, we use a Probit estimation instead of OLS. The overall results in terms of sign and statistical significance hold for both robustness checks and are available from the author upon request.

Finally, we explore whether transparency is associated with greater dropout following the announcement of the Public Disclosure Programme. To do so, we will estimate regressions of the form: where Lastyear�,� is a dummy variable equal to one if it is the last year t that firm i participated in ILO‐ IFC Better Work Vietnam, which identifies whether public disclosure is associated with increased dropout. Endrate is the noncompliance rate of the firm in the last year it participated in ILO‐IFC Better Work Vietnam, which identifies whether poor‐performing firms are more likely to drop out.

Thus, this part of the analysis allows us to answer the question:

#  _Does transparency lead some firms to drop out of the program? If so, which ones?_

One limitation with the empirical methodology is that we are not able to fully control for endogeneity. As discussed, prior to public disclosure, firms were advised of the policy change, and low‐compliance factories also received notice that they are low‐compliance. We find below that firms’ baseline non‐ compliance has a positive correlation with non‐compliance over program participation. That is, firms that have lower compliance when they enter the Better Work Vietnam program are more likely to have lower compliance throughout their participation in the program. Endogeneity would then be an issue if low‐ compliance factories are more at risk of public disclosure. There are other limitations that we acknowledge with the data. The fact that Better Work Vietnam is voluntary raises selection issues that we acknowledge. Though we cannot fully control for these, we do use within‐firm estimation and also test for dropout.

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# Data and descriptive statistics

## Data

This paper uses data primarily from Better Work Vietnam’s Compliance Synthesis Report. The compliance data are collected during unannounced visits where monitoring teams of usually two people carry out an assessment of working conditions in participating factories. In Vietnam, the monitoring instrument contains several hundred questions designed to evaluate working conditions relative to national law and international standards. For each question, Better Work Vietnam then decides whether the factory is or is not compliant. Like other studies, this paper relies on Better Work Vietnam’s assessment of compliance and does not re‐evaluate their compliance decision (see, for example, Robertson 2017).

An initial compliance assessment is undertaken when a firm first joins Better Work Vietnam. As part of membership in the program, Better Work Vietnam supports the factory through advisory services during the cycle and monitors firm compliance in the cycle. Factory visits and assessments are subsequently undertaken once a year for every year (or cycle) the firm is in the Better Work Vietnam program. The data set thus contains compliance data of a firm over time. The number of assessments per firm varies, depending on when the firm jointed (or exited) the Better Work Vietnam’s program. Table 1 shows the factory counts by the maximum number of compliance assessments. A total of 1,508 factory assessments are available for 461 firms.

The data are available starting in 2010 through 2018. The number of factories for which compliance data is available for each year is given in Table 2 (including both new and revisited factories). Data for 2018 run only through June, which explains why the number of factories is smaller in 2018 than other years. Table 3 presents the factory count by evaluation cycle and shows that there are both firms entering and exiting the sample each year.

**Table 1: Number of factory assessments per factory**

|**Number of factory assessments**|**Number of firms**|
|---|---|
|1|124|
|2|84|
|3|76|
|4|63|
|5|29|
|6|28|
|7|33|
|8|24|

Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

**Table 2: Number of assessed factories per year**

|**Year**|**Number of firms**|
|---|---|
|2010|65|
|2011|116|
|2012|136|
|2013|139|
|2014|177|
|2015|219|
|2016|253|
|2017|286|

12
|2018|106|
|---|---|

Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

**Table 3: Factory count by evaluation cycle (number of visits)**

|**Year**|**1**|**2**|**3**|**4**|**5**|**6**|**7**|**8**|
|---|---|---|---|---|---|---|---|---|
|2010|64|1|||||||
|2011|64|52|||||||
|2012|45|50|41||||||
|2013|19|42|48|30|||||
|2014|71|17|30|42|17||||
|2015|75|45|20|25|38|16|||
|2016|41|75|32|24|30|37|14||
|2017|62|37|68|24|24|22|39|10|
|2018|17|17|12|30|3|9|4|14|

Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

Questions are grouped into compliance points, and sub‐grouped into clusters. The eight clusters are: child labor, discrimination, forced labor, freedom of association and collective bargaining, compensation, contracts and human resources, occupational health and safety, and working time. There are 39 compliance points across the eight clusters. Table A.1 lists the different compliance points under each of the eight clusters.

Moreover, not all questions in the Compliance Synthesis Report are compliance questions. For example, the Compliance Synthesis Report collections information on the number of staff employed by the factory. The data set on firm compliance was restricted to just questions that directly imply compliance. These non‐compliance questions were either saved as part of the firm characteristics when appropriate, or dropped. Table A.2 lists the variable names and their definitions available on the Compliance Synthesis Report.

The eight compliance clusters have not changed over time, however the compliance questions asked in the Compliance Synthesis Report have changed. Though changes to the monitoring instrument are needed to accommodate learning and shifting emphasis of working conditions, this creates difficulties in tracking compliance to individual questions over time. Moreover, question codes were also changed, and more frequently than the individual questions (that is, the same questions would be coded differently over time). To maximize comparability of compliance over time, careful attention was given to identifying and using only compliance questions that were available over the entire sample period. The individual compliance questions from each Compliance Synthesis Report were matched manually. The resulting data set contains 161 individual compliance questions that appear consistently throughout the sample period.<sup>6</sup> Better Work Vietnam identified 26 “critical issues” for which public disclosure would be assessed, listed in Table A.3. The analysis of whether transparency through public disclosure accelerates adoption of compliance requirements focuses on these critical issues. However, not all 26 critical issues have

> 6 Dropping questions that enter or leave the sample introduces potential bias, depending on why questions were added or removed. In some cases, multiple questions were replaced with a single question and vice‐versa. As an extension, the average across component questions could be used to measure compliance, following Robertson (2017).

13
questions that are included in the full sample period. Moreover, given the large number of questions, the assessment does not consider compliance question‐by‐question. Rather, it focuses on in what clusters / compliance points are firms more likely to adopt compliance requirements, overall and within the 26 critical issues. Table 4 gives the number of compliance questions per cluster, the number of questions that appear consistently throughout the sample period, and the number of public disclosure questions. It shows that the compliance questions are a minority of the total questions in the sample.

**Table 4: Number of compliance questions per cluster**

|**Compliance cluster**|**Total questions**|**Public disclosure**<br>**questions**|**Questions asked**<br>**consistently**|
|---|---|---|---|
|Child Labor|7|2|6|
|Compensation|40|4|24|
|Contracts and Human Resources|31|2|15|
|Discrimination|56|3|35|
|Forced Labor|18|4|9|
|Freedom of Association and Collective Bargaining|33|5|18|
|Occupational Safety and Health|83|7|43|
|Working Time|26|0|11|

Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

Data from the Compliance Synthesis Report are then merged with firm‐level information collected from Better Work Vietnam’s Registration Document. These data are used as control variables in the assessment, including firm size, firm age, and information on buyer relationships. Table A.4 lists the variables names and their definitions available in the Registration Document.<sup>7</sup>

# Descriptive statistics

Table 5 shows the mean compliance across all questions and factories without controlling for any other potentially relevant variables. The mean compliance in Table 5 is therefore the simple arithmetic average of the 0/1 compliance variable taken over all questions, all factories and all years. Since 0 indicates compliance (and 1 non‐compliance), higher numbers in Table 5 indicate lower average compliance. Overall, firms are found to be non‐compliant in about 9 percent of all compliance questions in the Compliance Synthesis Report.

**Table 5: Finding of non‐compliance**

|**Finding**|**Frequency**|**Percent**|
|---|---|---|
|No evidence of non‐compliance found|219,154|91.01|
|Evidence of non‐compliance found|21,650|8.99|

Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

Table 6 shows the average non‐compliance rates over time for all compliance questions, as well as for compliance questions that are related and non‐related to public disclosure (“critical issue groups”). It also presents the number of firms that are available in the sample for each year. Overall, compliance tends to be lower for disclosure questions than non‐disclosure questions, across the sample years. On average, 7 We also explored the possibility of merging additional firm‐level data from Better Work Vietnam’s Impact Assessment Survey. The firm identifier needed to merge the data sets is currently not available, though we are exploring the possibility of accessing the appropriate identifier.

14
firms comply with 91 percent of compliance questions, 92 percent of nondisclosure questions, but 88 percent of disclosure questions.

**Table 6: Number of firms and mean compliance rates over time**

|**Year**|**Firms**|**All**|**Disclosure**|**Non‐disclosure**|
|---|---|---|---|---|
|2010|65|0.888|0.876|0.890|
|2011|116|0.911|0.902|0.913|
|2012|136|0.908|0.902|0.909|
|2013|139|0.917|0.895|0.921|
|2014|177|0.901|0.843|0.911|
|2015|219|0.887|0.834|0.895|
|2016|253|0.911|0.871|0.918|
|2017|286|0.922|0.881|0.929|
|2018|106|0.942|0.876|0.947|
|All years|457|0.910|0.875|0.916|

Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

Table 7 explores the non‐compliance rate before and after program announcement, for all compliance questions, all compliance questions that are related to public disclosure, and all compliance questions within each compliance cluster. For now, we limit the analysis of the public disclosure program to focus on the date of program announcement.<sup>8</sup> The non‐compliance rate for all questions and non‐disclosure questions are different: 10% versus 13% before the program announcement, and 8% and 12% after the program announcement.

It is also clear that compliance is much higher in some compliance clusters than others. For example, nearly all firms comply with discrimination and forced labor, with non‐compliance rates in these clusters of less than 1%. On the other hand, non‐compliance within occupational health and safety is near 20%. For working time and contracts and human resources, firms show noncompliance with about 13% of compliance questions within these clusters.

Table 7 also calculates differences in the mean noncompliance rate before and after program announcement, without controlling for any other potentially relevant variables. We find a positive result for all questions, that is, noncompliance has fallen, as well as most compliance clusters. Exceptions are child labor, discrimination and forced labor. In addition, we see initial evidence of a reduction in noncompliance before and after program announcement within compliance questions that relate to public disclosure.<sup>9</sup>

> 8 Testing for changes in compliance around the launch of the public disclosure portal is left for follow‐up work, given that only one year of data is currently available post‐portal launch.

> 9 Alternatively, we could regress the non‐compliance outcome of each compliance question for all firms and all years on a dummy variable equal to one if the compliance visit was post‐program announcement.

15
**Table 7: Summary statistics of non‐compliance rate**

||**Before pr**|**ogram announ**<br>|**cement**<br>|||**After pro**|**gram announce**<br>|**ment**<br>|||**Change**|
|---|---|---|---|---|---|---|---|---|---|---|---|
||**mean**|**median**|**sd**|**min**|**max**|**mean**|**median**|**sd**|**min**|**max**|**mean**|
|All questions|0.098|0.087|0.061|0|0.379|0.079|0.068|0.054|0|0.360|‐0.019|
|Disclosure|0.132|0.136|0.085|0|0.455|0.118|0.091|0.088|0|0.455|‐0.014|
|Child labor|0.076|0|0.167|0|0.667|0.038|0|0.125|0|0.667|‐0.038|
|Compensation|0.099|0.083|0.099|0|0.667|0.078|0.042|0.091|0|0.583|‐0.021|
|Contracts and human resources|0.136|0.133|0.133|0|0.667|0.132|0.133|0.116|0|0.667|‐0.004|
|Discrimination|0.003|0|0.010|0|0.086|0.003|0|0.014|0|0.229|0|
|Forced labor|0.001|0|0.009|0|0.111|0.000|0|0.004|0|0.111|‐0.001|
|Freedom of association|0.070|0|0.068|0|0.333|0.034|0|0.050|0|0.556|‐0.036|
|Occupational safety and health|0.190|0.163|0.116|0|0.558|0.150|0.140|0.104|0|0.581|‐0.04|
|Working time|0.135|0.091|0.122|0|0.727|0.134|0.091|0.115|0|0.545|‐0.001|

Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

16
Table 8 looks at attrition of firms in the sample. It shows both the number of firms that dropped out that year, as well as the mean non‐compliance rate of those firms that dropped out. It also shows the total number of firms, and the dropout rate. It is interesting to note that in 2015, the year of disclosure program announcement, there was a high incidence of poorly performing firms dropping out. The higher number reported for 2017 results from data only being available for half of 2018.

**Table 8: Summary statistics of firm attrition**

|**Year**|**Number of firms**|**Number of firms dropping out**|**Dropout rate**|**Mean noncompliance rate**|
|---|---|---|---|---|
|2010|65|4|0.062|0.162|
|2011|116|11|0.095|0.094|
|2012|136|15|0.110|0.102|
|2013|139|19|0.137|0.110|
|2014|177|29|0.164|0.144|
|2015|219|25|0.114|0.179|
|2016|253|31|0.123|0.132|
|2017|286|211|0.738|0.084|

Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

Note: Attrition is defined as dropping out of the ILO‐IFC Better Work Program.

Table 9 provides the summary statistics of the other firm characteristics available in the data set. The average age of firms that participate in the Better Work Vietnam program is about 13 years, though with substantial variation across firms, ranging from only 1 year to more than 50 years in operation. There is also substantial variation across firm size. The largest firm in the sample had more than 15,000 employees, compared to the average of about 1,300 employees.

**Table 9: Summary statistics of firm characteristics**

||**N**|**mean**|**p50**|**sd**|**min**|**max**|
|---|---|---|---|---|---|---|
|Firm age|454|12.7|12|8.0|1|52|
|Total employees|458|1314.7|819|1574.1|50|15057|
|Noncompliance rate at baseline|458|0.125|0.112|0.064|0.012|0.379|

Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

# Results

## Graphical analysis

Figure 1 and Figure 2 present a graphical overview of trends in the average noncompliance rate of firms that participate in Better Work Vietnam between 2010 and 2018. Figure 1 shows trends in average compliance by year, and Figure 2 shows average compliance by valuation cycle (duration of participation in the program). Each graph presents trends for all compliance questions, as well as compliance questions mapped to broader compliance clusters of child labor, compensation, contracts, discrimination, forced labor, freedom of association, occupational health and safety, and work time.

The top left panel of Figure 1 presents some evidence that non‐compliance rates are falling soon after the announcement of Better Work Vietnam Public Disclosure Programme. However, this follows increasing trends in non‐compliance a few years prior to the program. These trends may or may not be the direct 17
results of the disclosure policy. For example, other factors could be driving these trends in the data, such as the entry or exit of less‐compliant firms into the program before or after the policy announcement.

Trends over time in average non‐compliance rates in compensation, contracts, occupational health and safety, work time, and to a lesser extent freedom of association mimic the overall trends – increasing a few years prior to the program, and decreasing in the years after the program announcement. On the other hand, non‐compliance with child labor began to decline prior to program announcement, while non‐ compliance with forced labor shows no clear trend patterns. These results suggest it will be important to differential the empirical results of the Public Disclosure Programme by compliance cluster, given the differences in trends around announcement.

As identified in earlier literature, compliance also tends to improve with program participation. We check this with the Vietnam data, and find similar results. Figure 2 shows that participation in the program appears to be correlated with compliance overall, where noncompliance goes down linearly with participation. Therefore, it will be important to control for duration of program participation for the empirical analysis. Work time, occupational health and safety, freedom of association, and contracts all exhibit steady and declining non‐compliance alongside program participation. Non‐compliance within the compliance clusters of child labor and forced labor appear to drop off relatively quickly after a firm joins the program, within a few cycles. Non‐compliance with the compliance cluster of discrimination shows less clear trends.

18
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exception of forced labor. It is interesting to note that the magnitudes of the coefficient is larger for the disclosure questions, meaning that baseline noncompliance and length of program participation have a stronger negative correlation with compliance.

_Second, we test whether there are systematic trends in the characteristics of firms that adopt compliance requirements._ Table 11 presents the regression results of equation (2), which now controls for firm fixed‐ effects. As such, the results can be interpreted as the change in compliance within firms over time. There is a negative and significant correlation of firm size with non‐compliance for child labor and compensation, meaning that larger firms are more likely to become compliant in these compliance clusters over time. However, there is no relationship overall or with disclosure questions.

There is no significant correlation between firm age and change in compliance within firms, with the exception of the compensation compliance cluster: larger firms are more likely to increase their non‐ compliance over time.

There is a significant and positive correlation between baseline non‐compliance and within‐firm change in compliance over time. That is, firms that were less compliant when they entered the program were less likely to increase their non‐compliance. This holds for all questions as well as disclosure questions only, in addition to the compliance clusters of compensation, contracts, freedom of association, occupational safety and health, and work time. Length of participation in the program continues to have a negative correlation with changes in non‐compliance within‐firm.

_Third, we test in what compliance clusters firms are more likely to adopt compliance requirements during Better Work Vietnam participation._ Table 7 (above) shows that the largest changes in non‐compliance were observed in occupational health and safety, child labor, and freedom of association, followed by compensation.

_Fourth, we test whether transparency through the Public Disclosure Programme accelerates adoption of compliance requirement, and whether this varies by compliance cluster._ Tables 12 and 13 amend the specifications of Tables 10 and 11 by including the dummy variable of whether the Compliance Synthesis Report was undertaken after the announcement of the Public Disclosure Programme, which estimates equation (3). The key result is there the coefficient estimate of the dummy variable POST. A statistically significant and negative coefficient estimate in Table 10 indicates lower non‐compliance _across_ firms after the announcement of the Public Disclosure Program, controlling for other firm characteristics. A statistically significant and negative coefficient estimate in Table 11, which also includes firm‐fixed effects, indicates lower non‐compliance _within_ firms after the announcement of the Public Disclosure Program.

As above, the results are presented for all questions, for only public disclosure questions, and for all questions in each of the compliance clusters. The same firm‐level characteristics are maintained as controls. Tables A.6 and A.7 in the appendix instead present the results of the regression of the change in the firm’s non‐compliance between the first and last evaluation cycle.

Table 12 shows a negative and statistically significant correlation between non‐compliance and public disclosure when the sample includes all compliance questions. The estimated effect is a 3.7 percent lower average non‐compliance rate in the period after the announcement of the Public Disclosure Program.

22
Table 13 shows a stronger within‐firm effect for changes in non‐compliance after the announcement of the Public Disclosure Program; the estimated effect is a 4.5 percent lower average non‐compliance rate within a firm. As such, the results suggest that the Public Disclosure Program is correlated with higher firm compliance.

The coefficient estimate of POST shows a stronger negative correlation with non‐compliance in the compliance clusters of freedom of association, occupational health and safety, contracts, work time, and child labor. As such, freedom of association, occupational health and safety, contracts work time, and child labor show the largest fall in non‐compliance associated with the Public Disclosure Program. There is no correlation found in the compliance cluster of forced labor.

23
**Table 10: Determinants of non‐compliance, between firm**

||**All**<br>**categories**|**Disclosure**<br>**categories only**|**Child**<br>**labor**|**Compensation**|**Contracts**|**Discrimination**|**Forced**<br>**Labor**|**Freedom of**<br>**association**|**Occupational safety**<br>**and health**|**Work**<br>**time**|
|---|---|---|---|---|---|---|---|---|---|---|
|Firm size|‐0.015***|‐0.012***|‐0.040***|‐0.029***|‐0.027***|‐0.001**|0.000|‐0.009***|‐0.016***|‐0.023***|
||(0.001)|(0.004)|(0.005)|(0.003)|(0.005)|(0.001)|(0.000)|(0.003)|(0.003)|(0.006)|
|Firm age|‐0.000|‐0.001|‐0.013**|0.002|‐0.001|‐0.001*|‐0.000|0.002|0.003|‐0.011**|
||(0.001)|(0.004)|(0.005)|(0.003)|(0.005)|(0.000)|(0.000)|(0.003)|(0.003)|(0.005)|
|Baseline|0.078***|0.080***|0.144***|0.125***|0.122***|0.004***|‐0.000*|0.036***|0.115***|0.104***|
|noncompliance|(0.002)|(0.007)|(0.013)|(0.007)|(0.009)|(0.001)|(0.000)|(0.006)|(0.006)|(0.011)|
|Length of|‐0.035***|‐0.042***|‐0.031***|‐0.035***|‐0.067***|‐0.000|0.000|‐0.025***|‐0.061***|‐0.051***|
|participation|(0.001)|(0.004)|(0.005)|(0.003)|(0.005)|(0.000)|(0.000)|(0.003)|(0.003)|(0.006)|
|Constant|0.119***|0.129***|0.132***|0.095***|0.110***|0.008***|0.003|0.164***|0.221***|0.160***|
||(0.003)|(0.009)|(0.017)|(0.008)|(0.011)|(0.002)|(0.002)|(0.011)|(0.008)|(0.014)|
|Year FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Firm FE|No|No|No|No|No|No|No|No|No|No|
|Observations|240,805|32,934|8,937|35,928|22,455|52,332|13,473|26,946|64,269|16,465|
|R‐squared|0.016|0.017|0.063|0.035|0.038|0.002|0.002|0.024|0.021|0.023|

Note: Non‐compliance=1. Firm size, firm age, baseline non‐compliance, and length of participation in program are all identified as a dummy variable equal to 1 if the firm is above the median. Standard errors in parentheses. * = 10% significance, ** = 5% significance, *** = 1% significance. Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

24
**Table 11: Determinants of non‐compliance, within‐firm**

||**All**<br>**categories**|**Disclosure**<br>**categories only**|**Child**<br>**labor**|**Compensation**|**Contracts**|**Discrimination**|**Forced**<br>**Labor**|**Freedom of**<br>**association**|**Occupational safety**<br>**and health**|**Work**<br>**time**|
|---|---|---|---|---|---|---|---|---|---|---|
|Firm size|‐0.027|‐0.051|‐0.484***|‐0.153*|0.010|0.001**|0.001|‐0.020|‐0.064|0.051|
||(0.031)|(0.082)|(0.163)|(0.080)|(0.104)|(0.000)|(0.001)|(0.065)|(0.067)|(0.116)|
|Firm age|‐0.038|0.085|0.049|0.139*|0.010|0.001**|0.001|0.035|0.030|0.051|
||(0.030)|(0.082)|(0.162)|(0.080)|(0.104)|(0.000)|(0.001)|(0.065)|(0.067)|(0.116)|
|Baseline|0.076**|0.182**|‐0.049|0.256***|0.309***|0.001|0.001|0.123*|0.160**|0.235**|
|noncompliance|(0.030)|(0.083)|(0.162)|(0.080)|(0.105)|(0.001)|(0.001)|(0.065)|(0.067)|(0.117)|
|Length of|‐0.014***|‐0.014**|‐0.010|‐0.006|‐0.037***|0.001|0.000|‐0.014***|‐0.029***|‐0.008|
|participation|(0.002)|(0.007)|(0.009)|(0.005)|(0.008)|(0.001)|(0.001)|(0.005)|(0.005)|(0.010)|
|Constant|0.233***|0.174**|0.600***|0.193**|0.124|0.003|0.000|0.140**|0.357***|0.134|
||(0.034)|(0.075)|(0.225)|(0.077)|(0.090)|(0.002)|(0.000)|(0.056)|(0.074)|(0.089)|
|Year FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Firm FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Observations|240,805|32,934|8,937|35,928|22,455|52,332|13,473|26,946|64,269|16,465|
|R‐squared|0.029|0.041|0.218|0.073|0.081|0.027|0.028|0.047|0.055|0.069|

Note: Non‐compliance=1. Firm size, firm age, baseline non‐compliance, and length of participation in program are all identified as a dummy variable equal to 1 if the firm is above the median. Standard errors in parentheses. * = 10% significance, ** = 5% significance, *** = 1% significance. Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

25
**Table 12: Effect of disclosure by firm characteristic, between firm**

||**All categories**|**Disclosure**<br>**categories only**|**Child labor**|**Contracts**|**Discrimination**|**Forced**<br>**Labor**|**Freedom of**<br>**association**|**Occupational safety**<br>**and health**|**Work time**|
|---|---|---|---|---|---|---|---|---|---|
|POST|‐0.037***|‐0.031|‐0.064***|0.150***|‐0.005**|‐0.004|‐0.143***|‐0.070***|0.003|
||(0.005)|(0.024)|(0.021)|(0.013)|(0.002)|(0.003)|(0.013)|(0.009)|(0.016)|
|Firm size|‐0.014***|‐0.009|‐0.049***|‐0.030***|‐0.001**|0.000|‐0.009***|‐0.016***|‐0.024***|
||(0.001)|(0.006)|(0.006)|(0.005)|(0.001)|(0.000)|(0.003)|(0.003)|(0.005)|
|Firm age|0.002|0.005|‐0.012**|‐0.002|‐0.001*|0.000|0.003|0.008***|‐0.009*|
||(0.001)|(0.006)|(0.006)|(0.005)|(0.000)|(0.000)|(0.003)|(0.003)|(0.005)|
|Baseline|0.050***|0.028***|0.077***|0.081***|0.002***|0.000|0.025***|0.083***|0.056***|
|noncompliance|(0.001)|(0.006)|(0.006)|(0.005)|(0.001)|(0.000)|(0.003)|(0.003)|(0.005)|
|Length of|‐0.043***|‐0.033***|‐0.044***|‐0.087***|0.000|0.000|‐0.028***|‐0.064***|‐0.057***|
|participation|(0.002)|(0.006)|(0.006)|(0.006)|(0.001)|(0.000)|(0.003)|(0.003)|(0.006)|
|Year FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Firm FE|No|No|No|No|No|No|No|No|No|
|Observations|209150|3004|7465|20671|48001|12016|24032|77959|17504|
|R‐squared|0.015|0.031|0.058|0.05|0.001|0.002|0.029|0.025|0.023|

Note: Non‐compliance=1. Firm size, firm age, baseline non‐compliance, and length of participation in program are all identified as a dummy variable equal to 1 if the firm is above the median. Standard errors in parentheses. * = 10% significance, ** = 5% significance, *** = 1% significance. Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

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**Table 13: Effect of disclosure by firm characteristic, within firm**

||**All categories**|**Disclosure**<br>**categories only**|**Child labor**|**Contracts**|**Discrimination**|**Forced**<br>**Labor**|**Freedom of**<br>**association**|**Occupational safety**<br>**and health**|**Work time**|
|---|---|---|---|---|---|---|---|---|---|
|POST|‐0.046***|‐0.060**|‐0.094***|0.106***|‐0.006**|‐0.003|‐0.141***|‐0.105***|‐0.081***|
||(0.005)|(0.026)|(0.024)|(0.017)|(0.002)|(0.002)|(0.014)|(0.011)|(0.022)|
|Firm size|0.052*|‐0.473*|0.047|0.035|‐0.009|0.003|‐0.034|0.027|‐0.016|
||(0.028)|(0.272)|(0.036)|(0.102)|(0.016)|(0.002)|(0.089)|(0.059)|(0.127)|
|Firm age|0.009|0.027|0.060*|‐0.068|‐0.017|0.000|‐0.04|0.05|‐0.016|
||(0.028)|(0.272)|(0.035)|(0.102)|(0.015)|(0.000)|(0.089)|(0.059)|(0.127)|
|Baseline|0.046|0.033|‐0.060*|0.003|‐0.014|0.000|0.04|0.043|0.107|
|noncompliance|(0.028)|(0.273)|(0.035)|(0.102)|(0.015)|(0.000)|(0.089)|(0.059)|(0.127)|
|Length of|‐0.018***|‐0.016*|‐0.013|‐0.044***|0.001|0.000|‐0.017***|‐0.028***|‐0.012|
|participation|(0.003)|(0.008)|(0.010)|(0.009)|(0.001)|(0.001)|(0.006)|(0.005)|(0.009)|
|Year FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Firm FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Observations|209150|3004|7465|20671|48001|12016|24032|77959|17504|
|R‐squared|0.029|0.245|0.256|0.096|0.024|0.035|0.053|0.056|0.071|

Note: Non‐compliance=1. Firm size, firm age, baseline non‐compliance, and length of participation in program are all identified as a dummy variable equal to 1 if the firm is above the median. Standard errors in parentheses. * = 10% significance, ** = 5% significance, *** = 1% significance. Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

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We continue to explore whether transparency through the Public Disclosure Program accelerates firm compliance, and whether this varies by firm characteristic, using an alternative specification. Table 14 presents the regression results of equation (4). The results show how effective disclosure is conditional on different firm characteristics, by interacting the variable POST with each of the firm characteristics.

The results in column (5) show that the disclosure program continues to have a negative relationship with non‐compliance, where the coefficient estimate of POST is significant and negative. We find that this negative relationship between non‐compliance and the public disclosure program is stronger for larger firms, given by the significant and negative interaction of POST with firm size. The negative relationship is also stronger for firms that had a higher non‐compliance rate during their first evaluation. We find no evidence that firm age interacts with the impact of public disclosure on firm compliance. The interaction between the length of participation in ILO‐IFC Better Work Vietnam and the non‐disclosure period is instead positive, suggesting that firms that participating longer in the program in the non‐disclosure period are slower to improve compliance, conditional on other firm characteristics.

**Table 14: Effect of disclosure by firm characteristic, heterogenous effects**

||(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
|POST|0.011**<br>(0.005)|0.019***<br>(0.005)|‐0.023***<br>(0.005)|0.014***<br>(0.004)|‐0.009*<br>(0.005)|
|Firm size * POST|0.001||||‐0.006**|
||(0.003)||||(0.003)|
|Firm age * POST||0.002|||‐0.004|
|||(0.003)|||(0.003)|
|Length of participation * POST|||0.041***||0.025***|
||||(0.003)||(0.003)|
|Baseline noncompliance * POST||||‐0.017***<br>(0.003)|‐0.015***<br>(0.003)|
|Firm size|‐0.017***||||‐0.010***|
||(0.002)||||(0.002)|
|Firm age||0.007***|||0.004*|
|||(0.002)|||(0.002)|
|Length of participation|||‐0.118***<br>(0.005)||‐0.054***<br>(0.002)|
|Baseline noncompliance||||0.057***|0.056***|
|||||(0.002)|(0.002)|
|Test: x * POST + x + POST=0|0.91|32.12|327.33|139.68||
||0.34|0.00|0.00|0.00||
|Year FE|Yes|Yes|Yes|Yes|Yes|
|Evaluation cycle FE|Yes|Yes|Yes|Yes|Yes|
|Observations|209150|209150|209150|209150|209150|
|R‐squared|0.011|0.011|0.011|0.017|0.016|

Note: Non‐compliance=1. Standard errors in parentheses. * = 10% significance, ** = 5% significance, *** = 1% significance.

Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

_Fifth, does transparency shift factory efforts to alternative areas of compliance?_ One concern is whether the Public Disclosure Program incentivizing firms to shift efforts towards the disclosure questions at the expensive of other compliance areas. We test this by estimating equation (3) for the disclosure questions only, presented in Tables 12 and 13. The results do not show evidence that firms are improving more on the disclosure questions than the non‐disclosure questions in the post‐disclosure period. In Table 12 (between firm), the estimated coefficient of POST is nearly identical for disclosure questions and all questions (though not statistically significant in the latter). In Table 13 (within firm), there is some 28
evidence that disclosure categories react slightly more than the other categories, but the difference is not significant and small in magnitude. This supports the descriptive statistics that similarly do not show greater improvements in the disclosure categories than overall (either before/after program announcement or when looking at changes between first/last evaluation cycle, in Table 7 and Table A.5, respectively). In fact, the raw means suggest that there is less improvement for the disclosure questions than the other questions.

_Sixth, we explore whether transparency leads some firms to drop out of the program._ Table 15 tests for factors correlated with firm attrition, including firm size, firm age, baseline non‐compliance, the non‐ compliance rate of the last compliance assessment, as well as the Public Disclosure Program. There is some evidence that firms are more likely to drop out of ILO‐IFC Better Work Vietnam after the announcement of the Public Disclosure Program than before. There is a positive and statistically significant correlation between the variable POST and firm attrition, though the coefficient is relatively small in magnitude. This holds when also controlling for firm size, firm age, and baseline non‐compliance.

Non‐compliance rates are also a strong overall predictor of dropping out of the program; we find evidence that firms with higher non‐compliance rates in their last compliance cycle are more likely to drop out of ILO‐IFC Better Work Vietnam. This suggests that the average trends in non‐compliance rates over time may be influenced by firms dropping out of the program. Larger firms are also less likely to drop out, suggesting that they have more to gain from successfully participating in the program. Current evidence therefore shows previous compliance performance remains the strongest predictor of whether a firm drops out of the programme, but public disclosure seems to add to that effect.

**Table 15: Determinants of attrition**

||(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
|Non‐compliance rate in t‐1|1.610***||1.527***||1.505***|
||(0.133)||(0.146)||(0.138)|
|POST||0.290***||0.289***|0.287***|
|||(0.023)||(0.023)|(0.022)|
|Firm size|||‐0.079***|‐0.142***|‐0.086***|
||||(0.024)|(0.022)|(0.022)|
|Firm age|||‐0.046**|‐0.03|‐0.017|
||||(0.022)|(0.022)|(0.021)|
|Baseline noncompliance|||‐0.023|0.060***|‐0.027|
||||(0.024)|(0.022)|(0.022)|
|Test: x * POST + x + POST=0|0.91|32.12|327.33|139.68||
||0.34|0.00|0.00|0.00||
|Year FE|No|No|No|No|No|
|Observations|1386|1386|1386|1386|1386|
|R‐squared|0.099|0.111|0.109|0.147|0.217|

Note: Firm drops out=1. Standard errors in parentheses. * = 10% significance, ** = 5% significance, *** = 1% significance.

Source: Author’s calculations using data from ILO‐IFC Better Work Vietnam.

# Conclusions

This research leveraged factory‐level data on compliance from the ILO‐IFC Better Work Vietnam program to assess the relationship between transparency on working conditions and firm compliance of labor standards in Vietnam. It exploited a change in the policies of Better Work Vietnam when, in 2015, the 29
program announced the launch of a new public disclosure program that will make factories’ names publicly available along with their compliance (or lack thereof) with certain “critical issues”.

We first examined which firm characteristics correlate with noncompliance outcomes as well as reductions in noncompliance outcomes over time using cross‐sectional fixed‐effects regressions. We then examined the impact of the public disclosure policy on compliance rates using heterogenous effects regressions. We also tested whether the public disclosure policy had an impact on firm drop‐out.

It found that while continued participation in the Better Work Vietnam program has the strongest effect on changes in firm compliance with labor standards over time, public disclosure is also associated with increased compliance. Public disclosure appears to have a stronger impact on particular compliance points including occupational health and safety, work time, and child labor, where we found a stronger correlation between compliance and the public disclosure period in these compliance clusters. No evidence of firms only making progress on the critical issues is found. Policy implications suggest that public disclosure, at least within global value chains, matters for firm behavior.

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