Labour Rights Status of Construction Workers: Evidence from Raipur City

¹Ravi Kushwah, ²Archana Sethi

^1-2SoS in Economics, Pt. Ravishankar Shukla University, Raipur, Chhattisgarh, India.

ravikushwah@prsu.ac.in, archanasethi96@gmail.com

*Corresponding Author: archanasethi96@gmail.com 

 Abstract

Construction workers are recognised as one of the most vulnerable groups in the informal sector and have received considerable attention in the labour literature. This study adds to the existing body of work by developing a multidimensional Labour Rights Index (LRI). Using a labour rights framework, a composite index is constructed to assess the working conditions of 100 construction workers in Raipur City. The index draws on 18 indicators grouped into four domains: Wage and Income Security (WSI), Social Security and Welfare (SSI), Safety and Working Conditions (SAI), and Rights and Voice (RVI). Data were analysed using descriptive statistics, demographic comparisons, correlation matrices, and statistical tests (t-tests, ANOVA). The results portray a picture of moderate overall labour rights achievement, but with notably poor outcomes in welfare and grievance-related dimensions. Whilst caste and migration status show some association with lower rights scores, substantial deficits appear across all worker groups, indicating systemic enforcement failures that affect workers broadly, with social marginalisation due to caste and migration compounding baseline vulnerabilities. The study highlights critical gaps in policy implementation, particularly around safety standards, social security enrolment, and grievance redressal mechanisms.

Keywords: Labour Rights Index, Informal Workers, Construction Labour, Social Security, Occupational Safety.

1.   Introduction

Labour precarity within India’s informal economy constitutes a structural and persistent challenge, particularly in labour-intensive sectors. The construction sector mainly depends on migrant, casual, and unregulated workers. Economic shocks, especially the 2008 crisis and COVID-19, made construction workers more insecure. These conditions point towards the fundamental instability of labour governance mechanisms. The BOCW Act givesprotection on paper, but due to poor implementation and monitoring, construction workers remain marginalized.

Like the lack of transparency after the Global Financial Crisis, labour rights violations in the informal sector show weak accountability and poor monitoring. Conventional labour statistics – largely depend on employer reporting, which remains inadequate in capturing their live realities. This highlights the need for worker-centred, multidimensional frameworks, similar to ESG indicators, used to improve corporate accountability.

Human development and capability approaches see deprivation as multi-dimensional, not just about income. Construction workers face many problems, such as low wage security, limited access to welfare, unsafe conditions, and a lack of proper grievance systems. Although the Indian labour literature is vast and covers these deficits, it remains limited by the absence of a composite, empirically grounded LRI that captures wage security, welfare access, workplace safety, and workers ‘voice.

This study addresses this gap by developing a composite Labour Rights Index (LRI) with 4 components and 18 indicators: Wage and Income Security (WSI), Social Security and Welfare (SSI), Safety and Working Conditions (SAI), and Rights and Voice (RVI). The index is based on the ILO’s decent work framework. This study uses primary data from construction workers in Raipur and examines labour rights across different groups.

2. Review of Literature

The construction sector employs a substantial size of informal workers in the Indian economy. Informal economy in India is characterised by the absence of written contracts, irregular wages, limited job security, and a lack of social protection. According to Chen (2012), the informal economy is marked by unstable employment conditions and weak regulatory oversight. This contributes to the precarity and human rights violations workers face. Construction workers are highly vulnerable because their work is temporary and often subcontracted.

Many studies show that wage insecurity is a major problem for construction workers. Srivastava (2011) found that migrant workers often face delayed payments, low wages, and long working hours. Workers depend on contractors and middlemen, which reduces their bargaining power and increases wage exploitation.

Wage insecurity is a major problem for construction workers. Anand and Thampi note that income instability and wage inequality are common, especially among casual and migrant workers.

Another key issue in the literature is access to social security and welfare schemes. The Government of India introduced the BOCW Act to provide welfare benefits like health insurance, pensions, and accident compensation to construction workers. However, studies show that these provisions are not fully implemented. Dutta and Mishra (2019) argue that paperwork issues, lack of documents, and low awareness prevent workers from registering for welfare benefits.

Safety and health are major concerns in construction. Workers often do risky tasks like working at heights, using heavy machines, and working in unsafe conditions. The ILO (2018) identifies construction as one of the most accident-prone industries in the world. Research finds that workers often lack safety gear, clean facilities, and basic medical help.

Research shows that informal workers often have no proper representation or grievance systems. According to Bhowmik (2010), informal workers are not part of unions, so they cannot negotiate better wages and conditions. As a result, many labour rights violations go unreported and unresolved.

Scholars now understand that labour rights and wellbeing are not just one-dimensional. The ILO’s Decent Work Agenda highlights the need to combine job security, social protection, safety, and worker voice. However, most studies in India look at these aspects separately, not together.

Therefore, this study fills this gap by developing an LRI to assess workers’ conditions in Raipur. It combines wages, welfare, safety, and worker voice to evaluate labour rights.

Objectives

·     To construct a Labour Rights Index (LRI) based on four dimensions: wage security, social security, safety, and workers’ voice.

·     To analyse the interrelationship between different dimensions of labour rights (WSI, SSI, SAI, RVI).

·     To examine differences in labour rights outcomes across demographic groups such as gender, caste, education, and migration status.

·     To identify the key determinants of labour rights outcomes among construction workers.

3. Hypothesis Development

Labour rights are multidimensional, including wages, welfare access, safety, and worker voice. The ILO framework highlights that these factors work together to affect workers’ lives. Studies show that construction workers often face irregular wages, poor access to welfare, unsafe conditions, and weak complaint systems, leading to ongoing vulnerability. Labour rights outcomes depend on connected factors and worker characteristics like education, caste, gender, and migration. A composite index can help measure their overall effect.

Accordingly, this study formulates testable hypotheses to examine

H1: There is a significant correlation among the dimensions of labour rights (WSI, SSI, SAI, RVI).

H2: There are significant differences in Labour Rights Index (LRI) across socio-demographic groups (gender, caste, education, migration status).

H3: Socio-economic and demographic factors have a significant effect on the Labour Rights Index (LRI).

H4: The domain indices (WSI, SSI, SAI, RVI) significantly contribute to the Labour Rights Index (LRI).

3. Data and Methodology

3.1 Sample Selection

This study examines labour rights conditions of construction workers in Raipur City, India. Data were collected using a structured questionnaire from 100 workers at different construction sites during 2025–26. Workers were selected using purposive sampling to ensure diversity in age, caste/community, gender, education and migration status. The sample represents a realistic cross-section of unskilled and semi-skilled construction workers typically engaged in urban construction activities.

Data were screened for completeness and consistency. All 100 observations were retained for analysis. Labour-rights indicators were coded in binary format (Yes = 1, No = 0) to enable the construction of multidimensional indices following standard practice in welfare and rights-based measurement. All statistical analyses were conducted using Stata 16 and EViews 12, ensuring robust estimation and diagnostics.

3.2 Variable Description and Domain Structure

The questionnaire captured 18 labour-rights indicators, grouped into four conceptual domains grounded in the ILO Decent Work framework (ILO, 2019) and multidimensional welfare theory (Anand & Sen, 1997; Alkire & Foster, 2011). These domains reflect the recurring deficits documented in India’s informal construction sector.

3.2.1 Wage & Income Security (WSI)

·     Minimum wage compliance

·     Timely wage payment

·     Mode of wage payment

·     Overtime payment

·     Weekly rest day

3.2.2 Social Security & Welfare (SSI)

·     Work documentation

·     BOCW registration

·     Access to welfare schemes

·     Employer support for injuries

·     Awareness of legal/welfare entitlements

3.2.3 Safety & Working Conditions (SAI)

·     Drinking water

·     Sanitation facilities

·     Personal protective equipment (PPE)

·     Medical assistance during accidents

·     Harassment-free environment

3.2.4 Rights & Voice Index (RVI)

·     Ability to report harassment

·     Representation/collective voice

·     Grievance awareness

All indicators were coded as:

Demographic variables included:

·     Age group, gender, education, caste/community, marital status, migration status, religion

These variables allow examination of demographic disparities in labour-rights outcomes.

Table 1. Variables and Their Description

3.3 Construction of Domain Indices

Consistent with composite-index methodologies in welfare research (UNDP, 2020), domain scores were computed as the average of their respective indicators:

where , , , .

3.4 Composite Labour Rights Index (LRI)

The composite LRI was constructed as the unweighted arithmetic mean of the four domain indices:

The LRI ranges from 0 (no rights) to 1 (full rights). This formulation ensures transparency, interpretability and comparability across workers.

3.5 Econometric Modelling Framework

To assess determinants of labour-rights outcomes and examine demographic disparities, an econometric model was estimated using LRI as the dependent variable:

Where:

·                  = worker’s age category

·                  = male/female

·                  = education level

·                  = caste/community category

·                  = migrant vs local worker

·                  = marital status

This model evaluates whether rights deficits cluster among specific demographic groups or are systemic across the workforce.

4. Results and Discussion

Table 2 showcases the summary statistics, which reflect on the nature of the variables used in the study. It is observed that the mean value of SAI (Safety and Working conditions index is 0.488 (SD = 0.186) while WSI (wage and income security) records the highest mean of 0.617 (SD=0.131).

The composite LRI stands at 0.497 (SD=0.123), which indicates that, on average, construction workers in the sample realise roughly half of the labour-rights measures/ services/ facilities as evident by the indicators.

The domain – level dispersions show SSI and RVI display greater disparity with SD 0.221 and 0.196 respectively, highlighting unequal access to welfare entitlements and unaddressed grievances.

Table 2. Summary statistics

Source(s): Created by authors

the mean value of the constructed LRI is 0.497 accounting partial rights realisation and existence of precarious working conditions among study groups in India (Srivastava, 2012; Bhowmik, 2010). While wage-related indicators (WSI) tend to be relatively better enforced—likely because wages are the most visible and regularly monitored aspect—critical gaps remain in safety, welfare access, and worker voice.

Pearson’s correlation matrix between the domain indices and LRI is reported in Table 3. The strongest bivariate association is found between SAI and LRI (r = 0.772), followed by RVI–LRI (r = 0.682) and SSI–LRI (r = 0.672). WSI is positively correlated with LRI (r ≈ 0.486) but the magnitude is smaller compared with safety and voice dimensions. All pairwise correlations remain under conventional multicollinearity thresholds (no value > 0.80), and the VIF diagnostics confirm that predictor collinearity is not problematic (VIFs < 3). These diagnostics support the suitability of multivariate regression analysis.

Table 3. Correlation metrics

Source(s): Created by authors

Group-wise comparisons (Tables 4–6) help explain differences in inequality. Table 4 shows the mean LRI by gender. Male workers have a mean LRI of 0.4942, while female workers have 0.10076. A two-sample t-test gives a value of t = −0.3449 with p = 0.7341. This shows that there is no statistically significant difference between male and female workers in the sample. However, the descriptive results suggest that some gender-related issues may still exist. For example, female workers may face more problems related to sanitation and workplace safety. These differences may not appear clearly in the overall index because the sample size is small.

Table 4. LRI by Gender

Source(s): Created by authors

Table 5 Caste-wise comparisons indicate variation in labour rights outcomes across groups. Workers belonging to OBC (mean = 0.5134) and ST (mean = 0.5300) categories exhibit relatively higher LRI scores compared to SC (0.4621) and General category workers (0.4028), suggesting uneven distribution of labour rights across social groups.

Table 5. LRI by Caste

Table 6 shows that higher education is associated with higher LRI, as workers with secondary or higher education perform better in documentation, welfare registration, and grievance awareness.

Table 6. LRI by Education

Source(s): Created by authors

The multivariate analysis (Table 7) examines the determinants of the composite LRI. The preferred OLS specification regresses LRI on the four domain indices (WSI, SSI, SAI, and RVI) along with demographic controls (AGE_num, gender_dummy, edu_num, migrant_dummy, married_dummy, and caste/religion dummies). Table 7 displays coefficient estimates, robust standard errors, t-statistics and p-values.

Table 7. Regression results — Determinants of LRI

Note(s): Robust standard errors (HC3) reported. VIF diagnostics indicate no serious multicollinearity.

The regression analysis points to three clear findings. SAI and RVI are the most consistent factors affecting LRI, with strong and significant effects. These effects are significant and meaningful. Second, education also matters. Workers with higher education have better outcomes, as they are more aware of their rights and can claim them. Being a migrant or from a disadvantaged caste is associated with lower scores, though the impact varies with different controls. Finally, gender does not have a significant independent effect after controlling for other factors, consistent with earlier t-test findings.

VIF results show no multicollinearity problem, as all values are within acceptable limits. SAI and RVI have the biggest impact, meaning safety and worker voice are most important. This contrasts with a wages-first narrative: although wage security (WSI) matters, it is insufficient on its own to secure comprehensive rights realisation. In other words, ensuring punctual pay does not automatically translate into safer work sites or effective grievance channels.

These findings resonate with the broader literature on multi-dimensional vulnerability (Anand and Sen, 1997) which argues that well-being is shaped by the interplay of multiple deprivations – safety risks, gaps in social security schemes and lack of voice? Rather than by any single factor in isolation. Thus, policy solutions need to be broad and include an array of interventions in matters related to wage disputes, social security and redressal mechanisms, etc.

We further test alternative model specifications by estimating domain-specific regressions in which each domain index is regressed on core demographics (results available in the supplemental tables). These domain-level tests indicate that education and registration status (BOCW linkage) consistently predict higher SSI and RVI outcomes, while migrants are predominantly disadvantaged in SAI and SSI measures. This heterogeneity underscores the need for targeted policy measures (for example, mobile welfare-registration drives for migrant clusters and mandatory PPE provisioning at the supervisor/contractor level).

Table 8 summarises domain contributions and hypothesis outcomes. The SAI and RVI domains provide the largest marginal contributions to LRI, followed by SSI and then WSI. The pattern supports the hypothesis that voice and safety are critical mediators of labour-rights realisation.

Table 8. Domain Contribution Summary

Source(s): Created by authors

Overall, the results suggest clear actions. Safety measures like PPE, water, sanitation, and medical support should come first. They affect the LRI more than wage measures alone. Better complaint and representation systems can also improve workers’ rights. Third, increasing awareness and BOCW registration will improve the impact of safety and grievance measures, as they are linked to higher LRI. Finally, one policy is not enough. A combined approach—safety, welfare registration, worker voice, and training—is needed. Migrant and lower-caste workers are more vulnerable and need special support.

5. Conclusion, Implications, Limitations and Future Research

This study used a LRI based on data from 100 construction workers in Raipur. The index uses four domains: WSI, SSI, SAI, and RVI. The results show a moderate level of labour rights (mean LRI = 0.497), meaning workers get only about half of the basic rights. WSI performs better (mean = 0.617), while SAI (0.488) and especially RVI (0.340) are weaker. The results show that SAI (r = 0.772) and RVI (r = 0.682) have the strongest correlation with LRI, making them key factors. Gender differences are not significant (p = 0.734), but educated workers, especially graduates, have better outcomes. Regression results show that all domains affect LRI, with SSI (0.2215) and RVI (0.1962) having stronger effects, and education also having a positive impact (p < 0.05). The findings suggest that labour rights are complex and unequal, and wages alone cannot solve the problem. Government efforts should prioritize safety, access to welfare, and proper complaint systems.

Policy implications. The results suggest that policymakers should focus on (i) improving on-site safety, such as PPE, first aid, and safety checks. (ii) rapidly increasing BOCW registration and making documentation easier (iii) ensuring workers have a voice through easy complaint and representation systems. There should be focused efforts for migrants and marginalized groups through camps, awareness, and quick grievance services.

Limitations. The study has some limitations. First, the sample size is small (N = 100). This limits the strength of the results. It also reduces how widely the findings can be applied. Therefore, the results should be seen as exploratory and specific to Raipur. Second, the study uses self-reported yes/no data. This may lead to reporting bias. Third, the study is cross-sectional. It cannot establish cause and effect. Panel data or experimental methods would provide better evidence of causal relationships.

Future Research. Future research should: (a) Use larger samples from different cities to make the LRI more widely applicable. (b) Apply longitudinal methods to study the impact of safety and registration on LRI over time. and (c) Add variables such as contract type, contractor compliance, and union presence to better explain supply-side factors.

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