Re-evaluating the Returns to Labour in Microenterprises: A Statistical Replication and Critical Review of de Mel et al. (2019)

Kayongo, Patrick Sunday Article — Published Version Re-evaluating the Returns to Labour in Microenterprises: A Statistical Replication and Critical Review of de Mel et al. (2019) The Indian Journal of Labour Economics Provided in Cooperation with: Springer Nature Suggested Citation: Kayongo, Patrick Sunday (2025) : Re-evaluating the Returns to Labour in Microenterprises: A Statistical Replication and Critical Review of de Mel et al. (2019), The Indian Journal of Labour Economics, ISSN 0019-5308, Springer India, New Delhi, Vol. 68, Iss. 3, pp. 1113-1132, https://doi.org/10.1007/s41027-025-00583-z This Version is available at: https://hdl.handle.net/10419/330914 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Vol.:(0123456789) The Indian Journal of Labour Economics (2025) 68:1113–1132 https://doi.org/10.1007/s41027-025-00583-z ISLE RESEARCH NOTE Re‑evaluating theReturns toLabour inMicroenterprises: AStatistical Replication andCritical Review ofde Mel etal. (2019) PatrickSundayKayongo1 Received: 26 February 2024 / Accepted: 14 August 2025 / Published online: 8 October 2025 © The Author(s) 2025 Abstract This paper replicates de Mel etal. (Am Econ J Appl Econ 11(1):202–235, 2019), a field experiment in Sri Lanka evaluating the effects of wage subsidies on microenterprise employment. While the original study found no lasting impact on profits or firm scale—interpreting this as evidence of diminishing labour returns—this replication confirms the empirical patterns but challenges that conclusion. It argues that short-lived gains likely reflect deeper structural and behavioural constraints, such as limited managerial capacity, informal labour dynamics, and institutional uncertainty. Beyond verification, the paper extends the original heterogeneity analysis, revealing that firms with pre-existing employees were significantly more responsive to the subsidy, while solo firms were not—shifting the focus from sectoral effects to baseline employment structure. This refinement offers new insights for targeting wage subsidies. The replication also raises ethical concerns about temporary hiring, which may erode worker morale and firm stability. By reinterpreting null results as symptoms of policy design gaps rather than firm-level inefficiency, the study underscores the need for bundled, ecosystem-level support. It draws concrete lessons for India’s microenterprise schemes, arguing that wage subsidies alone are insufficient for durable transformation. Replication, in this light, becomes a tool for theory building and policy diagnosis—not just empirical scrutiny. Keywords Replication· Marginal returns to labour· Microenterprises· Wage subsidies· Sri Lanka· India JEL Classification C93· J22· J38· L26· J38· O15· O17 * Patrick Sunday Kayongo [email protected]; kay[email protected] 1 Chair ofPublic Finance, Faculty ofBusiness andEconomics, University ofDuisburg-Essen, Essen, Germany 1114 The Indian Journal of Labour Economics (2025) 68:1113–1132 ISLE 1 Introduction Microenterprises are often regarded as engines of economic growth, particularly in developing economies where they dominate the informal sector and provide livelihoods for millions (Muske & Woods 2016). However, their capacity to scale—especially through hiring additional labour—remains a subject of ongoing debate in both economic theory and policy. A central question in this literature is whether hiring an additional worker yields positive and sustained returns in microenterprise settings, or whether such firms operate under conditions of rapid diminishing marginal returns to labour (de Mel etal. 2019). Neoclassical models typically predict that microenterprises are optimally small, exhibiting steep declines in marginal productivity when labour inputs increase beyond a minimal scale (Lucas 1978). This theory has guided much of the skepticism around subsidised employment interventions targeted at small firms. However, recent empirical research has challenged this assumption, arguing that under certain conditions—such as improved information flows, reduced frictions, or supportive institutional contexts—additional labour may lead to meaningful and sustained productivity gains (Bryan etal. 2014; Beaman etal. 2014; Hardy & McCasland, 2023). These competing perspectives reveal an unresolved theoretical and empirical tension regarding the nature of labour constraints in microenterprises. Replication studies have emerged as a vital tool in navigating this tension. As emphasised by Clemens (2017) and McKenzie (2012), replications play a critical role not only in verifying empirical results but also in challenging their theoretical interpretation and policy relevance. Particularly in development economics—where context sensitivity and measurement limitations are common—replication enhances the credibility and external validity of research findings. As Duflo et al. (2007) argue, the capacity to reproduce results using transparent and standardised methods is foundational to building cumulative knowledge in experimental economics. To contribute to this debate, De Mel et al. (2019) conducted a landmark field experiment in Sri Lanka, in which wage subsidies were offered to a randomised group of male-owned microenterprises. The aim was to test whether temporary reductions in hiring costs would induce firms to expand employment—and, crucially, whether these effects would persist beyond the subsidy period. The study found that while treated firms hired more workers and were more likely to survive during the intervention, there were no lasting improvements in employment, profits, or business scale after the subsidies ended. These findings appeared to reinforce the canonical view that microenterprises are not labour constrained in the long run. In this paper, I undertake a statistical replication of de Mel etal. (2019) using their publicly available replication package. My primary objective is to verify the reproducibility of the study’s findings using updated analytical tools. However, I go beyond mere duplication. I critically engage with the design, context, and interpretation of the experiment, addressing broader methodological and theoretical concerns raised in the literature on microenterprise development. My replication confirms the main empirical results of the original study, with only minor numerical differences. Yet, I argue that the interpretation of these 1115 The Indian Journal of Labour Economics (2025) 68:1113–1132 ISLE findings requires more nuance. In particular, I highlight short-term employment gains as potentially meaningful in contexts where labour market scarring and firm informality are prevalent. I also discuss the limits of randomised interventions in capturing complex constraints facing microenterprises, such as behavioural inertia, thelack of managerial capital, and institutional uncertainty. This paper is guided by the following hypothesis: Temporary wage subsidies can induce short-term employment and survival gains in microenterprises, but the absence of long-term profitability improvements may be attributable to deeper structural and behavioral constraints— not necessarily to diminishing marginal returns alone. The rest of the paper is organised as follows: Section 2 details the replication strategy and empirical results. Section 3 offers a critical assessment of the original experiment’s methodology and theoretical framing. Section4 discusses policy implications, particularly in the context of Indian and Global South microenterprise policy. Section5 concludes with recommendations for future research and experimental design. 2 Replication andResults 2.1 Replication Strategy Given the ongoing debate around labour constraints in microenterprises, I replicate the experimental analysis of de Mel etal. (2019) using the original replication package they publicly provided.1 The dataset and Stata.do files include all variables and code used in the published paper, which enables a step-by-step verification of their estimation procedures.2 The experiment was conducted in Sri Lanka in 2009 and involved 1533 maleowned microenterprises. A randomised subset of these firms received a wage subsidy intended to offset the cost of hiring a worker for up to 8months. The primary outcome variables included firm survival, employment, profits, and capital stock. Data were collected over 12 survey rounds, with the first two rounds serving as baseline. I begin by inspecting and re-running the original code to reproduce the results exactly as they appeared in the published paper.3 After confirming consistency, I re-estimate the key specifications using Stata 18, ensuring compatibility with current statistical packages and applying clustering and multiple hypothesis corrections 1 The authors of de Mel etal. (2019) provide a publicly accessible replication package for whoever is interested in replicating the study at: https:// www. openi cpsr. org/ openi cpsr/ proje ct/ 113732/ versi on/ V1/ view. 2 For a detailed step by step description of the study’s estimation procedures, see Section II of the research paper: https:// doi. org/ 10. 1257/ app. 20170 497; pp. 208–215. 3 For complete and more comprehensive results, see Section IV of the original research paper: https:// doi. org/ 10. 1257/ app. 20170 497; pp. 216–227. 1116 The Indian Journal of Labour Economics (2025) 68:1113–1132 ISLE where relevant. The regression models follow the original study’s event-time framework, estimating treatment effects over distinct periods: pre-treatment, during-treatment, and post-treatment years 1 through 4. The baseline estimation model is specified as: where Y is the outcome for firm i in period t = 3, …, 12. Treat is a dummy variable indicating whether the firm received the wage subsidy treatment. Pre denotes the pretreatment period, specifically post-baseline round 3. During refers to survey rounds 4 and 5, when the wage subsidy was in effect. Year1, Year2, and Year3 to 4 correspond to survey rounds conducted approximately 1year, 2years, and 3–4years post-intervention, respectively. 1(t = s) represents a set of survey round time dummies, while X includes controls for the randomisation strata and for the baseline variables used in the randomisation process. The error term, ε < sub > i,t < /sub > , is clustered at the firm level. Coefficients β₂ through β₅ are the main parameters of interest, capturing the trajectory of treatment effects over time. To account for multiple hypothesis testing across periods, the equality β₂ = β₃ = β₄ = β₅ is tested, as well as the joint null hypothesis β₂ = β₃ = β₄ = β₅ = 0, to assess the stability of treatment effects. Finally, β₁ serves as a placebo test, as it corresponds to the pre-treatment period. As in the original study, I test the joint significance of treatment coefficients (β₂ throughβ₅), and assess stability over time. I also interpret β1 as a placebo check, since it captures any spurious treatment effects before intervention. The output tables presented in Sects.2.2 through 2.4 are drawn directly from the Stata output. Where necessary, I have reformatted these for clarity. 2.2 Firm Survival andEmployment Effects The replication confirms that wage subsidies increased firm survival and employment during the intervention period, but these effects weakened over time. Treated firms were more likely to remain operational up to 1-year post-treatment, but the advantage dissipated by years 3–4. Employment effects peaked during the subsidy phase, with modest spillovers into year one before fading thereafter (Table1). 2.2.1 Employment Effects The number of paid workers increased significantly during the subsidy period. Firms were more likely to hire at least one paid worker during rounds 4–5, when the subsidy was in effect. However, these employment gains were not sustained Yi,t=𝛼+𝛽 1 Treat i ×Pr e t +𝛽2Treati×Duringt+∑12 s=4𝛿s1(t=s)+𝜃�Xi+𝜀i, t +𝛽3Treati×Year1t +𝛽4Treati×Year2t +𝛽 5Treati × Year 3 to 4 t 1117 The Indian Journal of Labour Economics (2025) 68:1113–1132 ISLE Table 1 Reproduced treatment effects on firm survival Self-employed1 and 2 refer to self-employed–assuming that firms which close and are never observed again have stayed closed; and self-employed, assuming that all attritors are closed, respectively Source: Author’s computations based on de Mel etal. (2019)’s replication package Parameter Panel A: Self-employed in survey round Panel B: Selfemployed 1 Panel C: Self-employed 2 Panel D: Survival as per Firm Death Paper Panel E: Employed at all Pre-treatment − 0.006 − 0.006 − 0.008 0.012 − 0.007 (0.023) (0.023) (0.023) (0.023) (0.023) During-treatment − 0.009 − 0.010 − 0.012 − 0.006 − 0.006 (0.018) (0.018) (0.018) (0.021) (0.013) Post-treatment_ year1 0.058*** 0.056*** 0.055** 0.066** 0.034** (0.021) (0.021) (0.022) (0.026) (0.015) Post-treatment _year2 0.082*** 0.075*** 0.064** 0.079** 0.003 (0.025) (0.026) (0.028) (0.032) (0.019) Post-treatment _year3 0.054** 0.054* 0.055* 0.074** 0.013 (0.027) (0.029) (0.030) (0.034) (0.021) Sample size 5055 5092 5185 5057 5185 P-value 1 0.001 0.003 0.009 0.004 0.022 P-value 2 0.002 0.006 0.018 0.010 0.046 Control mean Pre 0.927 0.927 0.927 0.920 0.927 Control mean during 0.958 0.958 0.958 0.939 0.971 Control mean Year 1 0.885 0.885 0.875 0.839 0.927 Control mean Year 2 0.850 0.847 0.825 0.773 0.933 Control mean Year 3 0.831 0.815 0.788 0.729 0.906 Standard errors in parentheses = *p < 0.10 **p < 0.05 ***p < 0.01” 1118 The Indian Journal of Labour Economics (2025) 68:1113–1132 ISLE beyond the first post-treatment year. Table 2 reports the treatment effects on employment outcomes, including both the number of paid workers (Panel A) and the probability of hiring any paid worker (Panel B). As in the original study, these effects peak during the subsidy period and fade thereafter. These results align closely with those of de Mel etal. (2019), validating their core finding that short-run employment gains are not accompanied by long-run shifts in firm size or structure. This dynamic is further illustrated in Fig.1, which plots the average number of paid workers over time for treated and control firms. A sharp divergence is visible during the subsidy period (Rounds 4–5), followed by convergence in later rounds, visually reinforcing the short-lived nature of the treatment effect. 2.3 Profitability andReturns toLabour I replicate the profit impact models using both unconditional and conditional profit measures. The original study reports that the subsidy had no significant effect on profits during or after the intervention, despite the temporary increase in employment. My estimates corroborate this result. I also estimate the return to hiring an additional worker by regressing profits on the number of paid workers, controlling for time effects and firm-level covariates. Without firm fixed effects, the marginal return to an extra worker appears statistically significant, with treated firms earning approximately 6214 LKR more per week. However, when fixed effects are included, this falls to around 4902 LKR, below the subsidy value (4000 LKR), implying limited cost-effectiveness (Table3). However, as pointed out by de Mel etal. (2019), this estimate is not free from unobserved firm characteristics for example firm-level own productivity, which may jointly influence profits. For this reason, time-invariant firm behaviour is controlled by adding firm-level fixed effects to Eq.(2). This reduces the marginal labour returns to 4902.61 LKR (14% weekly profit increment) (Table4). 2.4 Capital Stock andConfounding Effects Finally, I replicate the capital stock regressions to verify whether capital-labour interactions confound the observed treatment effects. Like the original study, I find no statistically significant change in capital accumulation attributable to the wage subsidy. This supports the conclusion that the observed employment effects are not mechanically driven by concurrent increases in firm capital (Table5). 2.4.1 Summary ofReplication Results Overall, the replication exercise confirms the robustness of the original study’s empirical findings. The short-term gains in employment and survival are real but temporary. There are no sustained improvements in profitability, and marginal returns to labour are modest at best. The interpretation of these results—and whether they imply inherent 1119 The Indian Journal of Labour Economics (2025) 68:1113–1132 ISLE inefficiency in subsidising microenterprise labour—will be discussed critically in the next section. 2.5 Comparative Summary withde Mel etal. (2019) To synthesise the replication results presented in Sects.2.2 through 2.4, Table6 provides a side-by-side comparison of key estimates from the original study and this replication. The Table summarises treatment effects across employment, survival, profitability, and returns to labour. The replication aligns closely with the original findings in both direction and statistical significance. Minor differences in effect size are observed—likely due to rounding, updated statistical software, or treatment of missing values—but none alter the substantive interpretation. Notably, the replication reaffirms the temporary nature of employment gains and the absence of long-term improvements in profitability or capital accumulation. It also Table 2 Reproduced treatment effects on firm employment Source:Author’s computations based on de Mel etal. (2019)’s replication package Parameter Panel A Number of paid workers Panel B Any paid worker Pre-treatment − 0.073 − 0.012 (0.081) (0.035) During-treatment 0.194** 0.138*** (0.075) (0.035) Post-treatment_year1 0.126 0.111*** (0.077) (0.034) Post-treatment _year2 0.051 0.028 (0.079) (0.035) Post-treatment _year3 − 0.024 − 0.005 (0.083) (0.032) Base paid workers 0.000 0.000 (.) (.) Base any paid 0.251*** (0.087) Sample size 4879 4879 P-value 1 0.057 0.000 P-value 2 0.038 0.000 Control mean Pre 0.48 0.25 Control mean during 0.48 0.27 Control mean Year 1 0.45 0.24 Control mean Year 2 0.50 0.28 Control mean Year 3 0.60 0.29 Standard errors in parentheses = ”*p < 0.10 **p < 0.05 ***p < 0.01” 1120 The Indian Journal of Labour Economics (2025) 68:1113–1132 ISLE reproduces the marginal labour return estimates with remarkable precision. This consistency strengthens the credibility of the original study and confirms the replicability of its empirical claims. 2.6 Subgroup Heterogeneity inEmployment Effects de Mel etal. (2019) explored heterogeneity in the wage subsidy’s effects by interacting treatment status with various baseline characteristics, including firm age, prior hiring history, management practices, capital stock, household wealth, and sector (Table 7). While their findings suggested that firms with better baseline business practices and those in manufacturing were somewhat more likely to hire, most subgroup differences were statistically insignificant, and treatment effects dissipated over time across all categories. This replication extends and partially refines that analysis by examining heterogeneity in employment responses along two key dimensions: firm sector (manufacturing vs. non-manufacturing) and initial firm size, defined by whether the firm had any paid employees at baseline. These criteria align closely with those used in the original study, though our approach simplifies the analysis by focusing on binary subgroup splits and estimates the average treatment effect on the probability of hiring any paid worker over the panel. The results, presented in Table7, reaffirm the original study’s key findings while offering new precision: Fig. 1 Graph of employment trends over time, treatment vs. control. Source: Author’s computations based on de Mel etal. (2019)’s replication package 1127 The Indian Journal of Labour Economics (2025) 68:1113–1132 ISLE continue beyond the subsidy period can foster job insecurity and reduce worker morale. Economic theory and empirical evidence suggest that perceived employment instability may lead workers to underinvest in firm-specific human capital and disengage from tasks that deliver long-run productivity gains (Becker 1962; Kahn 2007). These behaviours reflect rational responses to insecure employment environments and are further corroborated by findings in labour economics that link job insecurity to declines in worker effort, organisational commitment, and productivity (Greenhalgh & Rosenblatt 1984; Böckerman etal. 2012). While the original study does not specify whether workers were informed about the temporary nature of their employment, ethical standards for field experiments—such as those outlined by the American Economic Association (AEA, 2019)—suggest that full disclosure should have been provided. If this was indeed the case, the absence of sustained profit gains could partially reflect anticipatory reductions in worker engagement stemming from an awareness of their short job tenure. These potential behavioural responses highlight the importance of incorporating ethical design principles and managing worker expectations in experimental labour market interventions. 4 Policy Implications andRelevance toIndia The findings of this replication study—while rooted in Sri Lanka’s policy context—hold significant implications for India, where micro, small, and medium enterprises (MSMEs) constitute over 90% of all businesses and contribute approximately 30% to GDP and 45% to exports (Ministry of MSME, 2023). As in Sri Lanka, India’s microenterprises operate under substantial constraints: limited access to formal credit, low managerial capacity, and informal labour markets (Maheshkar & Soni 2022). These characteristics complicate the evaluation of employment-based interventions such as wage subsidies or hiring incentives. 4.1 Implications forIndian MSME Policy The Indian government has deployed a range of employment-linked schemes to encourage microenterprise growth (Directorate General of Employment, 2025), including: • Prime Minister’s Employment Generation Program (PMEGP): Offers financial support to new and existing microenterprises to create employment opportunities. • MUDRA scheme: Provides microloans to non-corporate, non-farm small businesses, many of whom use the funds for hiring informal labour. • Aatmanirbhar Bharat Rozgar Yojana (ABRY): Offers EPF subsidy support to incentivise formal hiring in MSMEs post-COVID. 1128 The Indian Journal of Labour Economics (2025) 68:1113–1132 ISLE These schemes share a common logic with the intervention studied by de Mel etal. (2019): the idea that reducing labour costs will induce small firms to hire more workers and, ideally, grow. However, as my replication confirms, such interventions tend to produce short-term gains in employment and firm survival, without corresponding long-term improvements in profitability or firm scale. This finding should not be interpreted, as de Mel etal. suggest, as confirmation that microenterprises are not labour constrained. Instead, it may reflect the structural and behavioural limitations of firms that prevent them from productively absorbing labour, especially once subsidies end. Indian empirical studies point in this direction. For instance, Banerjee and Duflo (2011) show that many Indian microenterprises underinvest in both labour and capital due to informational asymmetries, credit constraints, and low entrepreneurial capacity—rather than because of rapidly diminishing returns. Similarly, Patwardhan and Tasciotti (2022) find that wage subsidy schemes under the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) had short-lived effects on rural labour allocation, with little evidence of lasting enterprise creation. In a closely related domain, Field etal. (2013) showed that business training and peer mentoring among female entrepreneurs in urban India can substantially improve business outcomes—while access to credit alone has little effect. These findings suggest that wage subsidies or financial support schemes are more likely to succeed when complemented with managerial or organisational support that enables firms to productively deploy resources over time. My replication thus reinforces a critical insight for Indian MSME policy: labour subsidies, when implemented in isolation, may temporarily alleviate hiring frictions but are unlikely to yield structural transformation. The observed short-term gains in employment and firm survival are not trivial—but without complementary support in areas like managerial training, access to working capital, and formalisation incentives, such gains tend to dissipate. This calls for a policy shift away from standalone hiring incentives toward bundled, context-aware interventions tailored to the persistent constraints faced by India’s microenterprises. In a landscape where public programmes like PMEGP, MUDRA, and ABRY continue to prioritise employment generation, my findings underscore the need for more rigorous evaluation frameworks—ones that assess not only immediate job creation but also the conditions required for durable enterprise growth. 4.2 Beyond Subsidies: Towards Integrated andContext‑Sensitive Interventions The evidence from my replication suggests that temporary wage support alone is insufficient to produce lasting improvements in firm profitability or scale—especially in environments marked by informality, low managerial capacity, and weak demand linkages. These insights echo a growing body of work in India that questions the standalone efficacy of credit and employment subsidies for microenterprise development. Programmes such as PMEGP and MUDRA have achieved substantial outreach but have shown mixed results in terms of enterprise sustainability and job creation. In response, policy discussions have increasingly focused on integrated support models—those that combine access to finance with capacity-building, market access 1129 The Indian Journal of Labour Economics (2025) 68:1113–1132 ISLE facilitation, and digital onboarding. Recent assessments by the World Bank (2018) indicate that addressing India’s MSME financing gap is necessary but not sufficient. Without complementary interventions—such as support for digital adoption (Parameswaran & Kadam 2025), workforce skilling, and supply chain integration—most microenterprises remain stuck in low-productivity equilibria (World Bank, 2018). Incorporating behavioural insights into programme design is equally critical. Research by Karlan etal. (2019) has shown that small firm owners often underinvest not because of poor returns, but due to misperceptions about risk, time inconsistency, or limited cognitive bandwidth. These frictions are not addressed by wage subsidies alone. In such cases, peer mentoring, planning tools, or light-touch managerial training—as tested by Field etal. (2013) in India—can significantly improve firm outcomes, particularly among women and informal entrepreneurs. This shift in understanding has also shaped gender-focused MSME policy. The IFC (2019) finds that finance-only programs have limited impact for women-led businesses unless accompanied by non-financial services such as business development support, digital access, and training in bookkeeping and compliance. India’s digital infrastructure offers promising avenues for scaling such integrated approaches. Platforms like the Udyam portal and GSTN provide an emerging data backbone for tracking enterprise performance over time (Alonso etal. 2023). These tools could enable a move toward adaptive policy designs, where support evolves based on observed firm behaviour, rather than fixed eligibility rules. Ultimately, the findings from this replication suggest that the problem is not merely one of firm size or capital access, but of policy fragmentation. A wage subsidy may enable a firm to hire one additional worker. But unless that firm is connected to formal markets, equipped with basic managerial skills, and supported by complementary interventions, the productivity gains will remain transitory. The unit of intervention, therefore, must shift—from the firm in isolation to the broader ecosystem in which that firm operates. 5 Conclusion This paper has conducted a rigorous statistical replication of de Mel etal. (2019), validating their key empirical finding: temporary wage subsidies for microenterprises in Sri Lanka produced short-term gains in employment and firm survival, but these effects did not persist after the subsidy ended. The replication reproduced treatment effects across all major outcomes—employment, profits, capital stock, and marginal returns to labour—with remarkable precision, confirming the empirical robustness of the original study. However, this replication goes beyond technical verification. First, it revisits and expands the heterogeneity analysis initially conducted by de Mel et al. (2019), sharpening its interpretive value. While the original paper found suggestive but statistically weak evidence that manufacturing firms and those with better baseline business practices were more likely to hire, this replication finds that firms with paid employees at baseline were significantly more responsive to the wage subsidy, whereas solo firms showed no such effect. This nuance—absent 1130 The Indian Journal of Labour Economics (2025) 68:1113–1132 ISLE from the original emphasis—suggests that baseline employment structure, rather than sector per se, may be a stronger predictor of subsidy responsiveness. This insight not only affirms but also extends the original heterogeneity findings, making a novel contribution to the literature and offering practical guidance for better targeting of wage subsidy programmes. Second, the replication challenges the original study’s conclusion that the null long-run results confirm the neoclassical model of diminishing marginal returns to labour. Instead, it argues that such transience may be symptomatic of deeper structural and behavioural constraints—including limited managerial capacity, informality, low trust in long-term contracts, and policy discontinuity. In fragile or post-conflict economies, even temporary hiring gains can have non-trivial welfare benefits, such as smoothing income, preserving firm survival, or reducing labour market scarring. Finally, by situating these findings within the context of India’s MSME support programs (e.g., PMEGP, MUDRA, and ABRY), the paper demonstrates how replication can serve as a diagnostic tool for policy refinement, not merely an academic exercise in verification. While India shares Sri Lanka’s emphasis on employment-based support, the replication underscores that without complementary investments in firm capabilities and institutional scaffolding, such programmes are unlikely to produce sustainable enterprise transformation. In sum, this study affirms the empirical validity of de Mel etal. (2019) while recasting its interpretation through a richer theoretical and policy lens. The contributions of this replication lie not only in what it confirms, but also in what it reframes. It advocates for an expanded view of replication—one that includes critical reinterpretation, nuanced subgroup analysis, and policy contextualisation—as an essential pillar of cumulative knowledge in development economics. Future research should prioritise bundled interventions that combine wage subsidies with managerial training, access to finance, or technology support to test whether sustained productivity gains can be achieved. Experimental designs should also explore longer-duration subsidies, as well as graduated phase-out mechanisms, to assess whether a more gradual withdrawal enhances retention effects. Additionally, mixed-methods approaches—combining RCTs with qualitative tools—may uncover mechanisms that are obscured in purely quantitative analyses, such as worker morale, managerial intentions, or informal labour dynamics. Finally, replication efforts should become a more routine component of empirical economics, especially in contexts where policy decisions hinge on findings from a single study. Funding Open Access funding enabled and organized by Projekt DEAL. Data availability The original data that support the findings of this study are openly available at the named data sources, while the replication data and code are available on request from the author. Declarations Conflict of interest The author reports no potential conflict of interest. 1131 The Indian Journal of Labour Economics (2025) 68:1113–1132 ISLE Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 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