Abstract

The introduction of the Goods and Services Tax (GST) on 1 July 2017 marked one of the most far-reaching indirect tax reforms in India’s post-independence economic history. Although GST has strengthened revenue mobilisation and expanded the taxpayer base, its implications for rural and informal enterprises remain unevenly understood. This paper develops the GST-Induced Formalisation and Equity (GIFE) framework to examine whether GST has produced inclusive formalisation or induced a capability–compliance mismatch for rural micro and small enterprises. Using an observed dataset of 120 enterprises from milk, silk, and granite-linked clusters in Kanakapura, Karnataka, the paper analyses employment change, compliance burdens, liquidity stress, and forced formalisation pressures. The findings show a statistically significant decline in average employment after GST across the full sample and within each sector. Working-capital blockage emerges as the most cluster-sensitive channel of distress, while compliance-cost strain and forced formalisation pressure remain high across all sectors. A supplementary structural model, treated only as an illustrative rather than field-estimated layer, further supports the proposition that GST institutional pressure affects socio-economic outcomes directly and indirectly through compliance burden. The paper contributes to debates on tax reform, informality, and inclusive transition by showing that formalisation under GST may be institutionally deepening while remaining socially uneven.

Keywords: Gst, Informal Sector, Formalisation, Rural Livelihoods, Social Equity, Compliance Burden, Kanakapura, India

1. Introduction

The Goods and Services Tax (GST) was introduced in India to replace a fragmented system of central and state levies with a unified destination-based tax architecture. From a public finance perspective, GST was expected to simplify taxation, reduce cascading effects, improve inter-state market efficiency, and deepen compliance through digitised reporting and invoice-based verification. Official data indicate that gross GST collections reached ₹22.08 lakh crore in FY 2024–25 and that active registrations expanded from 66.5 lakh in 2017 to about 1.51 crore in 2025, reinforcing the dominant policy narrative that GST has strengthened compliance and accelerated formalisation (Ministry of Finance, 2025).

However, macro-fiscal success does not automatically establish that the transition has been socially inclusive. India’s informal and unincorporated economy remains deeply embedded in the country’s employment and production structure. The Ministry of Statistics and Programme Implementation (MoSPI, 2025a, 2025b) reported that the informal sector contributed about 45% of GDP in FY 2022–23 and that the unincorporated non-agricultural sector employed more than 12 crore workers in 2023–24. These figures indicate that formalisation in India remains a live developmental transition rather than a completed administrative outcome.

The distinction is especially important for small and rural enterprises. Roy and Khan (2021) argue that digitised tax systems in developing countries can produce premature formalisation when low-capability firms are drawn into compliance systems before they possess the organisational, financial, or digital readiness needed to absorb them. Their core insight is that formal registration and digital visibility should not be conflated with substantive developmental inclusion.

Indian evidence also points in this direction. In an enterprise-level study of MSMEs, Ghosh (2022) found that 81.5% of surveyed firms identified compliance and paperwork as a major burden, 58.6% reported blocked working capital, and average employment per firm fell from 20 to 16.6 workers in the post-GST period. These findings show that GST can affect firms not only through accounting obligations but also through liquidity compression, business reorganisation, and labour adjustment.

Theoretically, this problem may be understood through the literature on tax thresholds, informality, and compliance partitions. Kanbur and Keen (2014) demonstrate that tax design can create non-linear compliance costs that affect smaller firms disproportionately. Complementing this perspective, the International Labour Organization’s Recommendation No. 204 emphasises that transition from the informal to the formal economy should improve rights, security, and productive opportunity rather than merely expand administrative control (International Labour Organization [ILO], 2015).

Against this backdrop, the present paper asks whether GST has produced inclusive formalisation for rural enterprise clusters or induced formalisation under conditions of capability deficit. The paper focuses on Kanakapura Taluk in Karnataka and examines three sectoral clusters—silk, dairy, and granite-linked enterprises—because they differ in labour intensity, perishability, documentation dependence, and market hierarchy. By shifting the analytical lens from macro-fiscal outcomes to the enterprise-level process of formalisation, the paper contributes a cluster-sensitive model of induced formalisation under capability constraints.

2. Statement of the problem

The central problem examined in this study is the possibility that GST has generated a capability–compliance mismatch for rural informal and semi-formal enterprises. The design of GST presumes regular digital filing, invoice matching, documentary discipline, and sufficient liquidity to withstand lags in tax adjustment and payment cycles. Yet many small enterprises continue to operate through delayed settlements, relationship-based credit, family labour, local intermediation, and low-cost bookkeeping. When such enterprises are drawn into compliance-intensive supply chains through input tax credit dependency or buyer pressure, the transition may be experienced less as enabling formalisation and more as administrative and financial strain (Ghosh, 2022; Roy & Khan, 2021).

The problem is therefore not formalisation in the abstract, but formalisation without adequate capability support. This may translate into blocked working capital, higher dependence on accountants or intermediaries, reduced operational flexibility, labour retrenchment, and weaker market security. In policy terms, the issue is whether a digitised tax regime can produce statistically visible formalisation while simultaneously undermining the social and productive basis of rural livelihoods.

3. Research gap

A first gap lies in the imbalance between macro-fiscal assessments of GST and micro-level enterprise evidence. Official statistics document improvements in collections and taxpayer expansion, but these indicators do not explain how low-capability firms experience the transition to compliance-intensive taxation in sectorally specific rural contexts (Ministry of Finance, 2025; MoSPI, 2025a, 2025b).

A second gap is conceptual. Existing scholarship has identified themes such as premature formalisation, compliance burden, and tax threshold effects, but relatively few studies have integrated GST institutional pressure, formalisation stress, organisational capability, livelihood outcomes, and social equity into one coherent framework. Ghosh (2022) and Roy and Khan (2021) provide the foundation, but cluster-based empirical work in rural Indian settings remains limited.

A third gap concerns the distinction between consumption-side distribution and production-side inclusion. Even if GST may appear progressive or manageable from a household-consumption perspective, that does not settle whether production-side formalisation has been equitable for small rural enterprises. The present study addresses this gap by examining enterprise survival, employment, and market access within rural clusters.

4. Objectives of the study

• To examine how GST institutional mechanisms create formalisation pressure for rural informal and semi-formal enterprises.

• To analyse the mediating role of compliance burden, working-capital stress, and supply-chain restructuring in the GST-induced formalisation process.

• To assess how organisational capability, particularly digital literacy and enterprise size, moderates enterprise adjustment to GST.

• To evaluate the consequences of GST-induced formalisation for rural livelihoods, including employment, wage pressure, and enterprise stability.

• To examine whether GST-driven formalisation produces unequal socio-economic outcomes across rural enterprise clusters and socially vulnerable groups.

5. Scope of the study

The topical scope of this paper is limited to GST-induced formalisation and its implications for rural livelihoods and social equity. The geographical scope is Kanakapura Taluk in Karnataka, treated as a rural-cluster setting suitable for examining enterprise adaptation under GST. The sectoral scope covers silk, dairy, and granite-linked enterprise activity, chosen because these clusters embody different combinations of labour intensity, perishability, documentation dependence, and market structure. The analytical scope is enterprise-centred but livelihood-sensitive, examining business-level variables such as compliance burden and working-capital stress alongside socio-economic outcomes such as employment contraction, wage pressure, and market inclusion.

6. Literature review and theoretical foundation

The theoretical foundation of the paper rests on three interlinked streams of scholarship. The first is the literature on tax thresholds, informality, and compliance design. Kanbur and Keen (2014) show that tax systems generate behavioural partitions and that the cost of compliance can become disproportionately burdensome for firms operating near threshold boundaries. This perspective is important because it frames tax architecture as a determinant of enterprise behaviour rather than treating compliance as a purely moral or administrative choice.

The second is the literature on digitised taxation and premature formalisation. Roy and Khan (2021) argue that digital tax regimes in developing countries can create forms of formalisation that are premature in relation to enterprise capability. This helps explain why increased registration or visibility should not automatically be interpreted as inclusive institutional progress.

The third is the literature on inclusive transition from informality to formality, reflected both in ILO Recommendation No. 204 and in enterprise-level empirical work such as Ghosh (2022). This stream emphasises that formalisation should be judged by whether workers and firms gain security, resilience, and productive opportunity, not merely by whether they enter administrative databases. In the Indian GST context, this literature provides the conceptual basis for analysing compliance not only as a fiscal process but also as a distributive and developmental event.

Together, these streams support the central proposition of this paper: GST should be analysed as an institutional compliance regime whose consequences depend on how tax design interacts with enterprise capability, liquidity, and market embeddedness.

Table 1. Literature synthesis and conceptual anchors

Source: Compiled by the author from the cited literature.

7. GST-Induced Formalisation and Equity (GIFE) framework

The GST-Induced Formalisation and Equity (GIFE) framework proposed in this paper explains how GST can generate uneven outcomes in rural enterprise ecosystems. At the first stage, GST institutional reform acts as the exogenous force. This includes digital return filing, invoice matching, input tax credit dependency, and documentation requirements that influence whether firms can transact credibly within formal supply chains. The reform is therefore treated not merely as a tax event, but as a change in the institutional terms of market participation.

At the second stage, GST generates a formalisation process that may be enabling for some firms but stressful for others. This mediating process includes compliance burden, working-capital blockage, dependence on accountants or intermediaries, pressure to transact with registered counterparties, and the weakening of earlier trust-based practices. Ghosh’s (2022) evidence on paperwork burden, blocked credit, and labour adjustment directly supports this logic, while Roy and Khan (2021) strengthen the interpretation by showing that digitised taxation can formalise enterprises in ways that are institutionally deep but economically premature.

At the third stage, the effect of this formalisation process is shaped by organisational capability, especially digital literacy and enterprise size. Firms with stronger buffers, better connectivity, and easier access to professional support may be able to absorb compliance more effectively, whereas low-capability firms may experience the same requirements as coercive or exclusionary. Finally, the framework captures two broad categories of dependent outcomes: rural livelihoods and social equity. Livelihood effects include employment reduction, wage pressure, and enterprise instability, while equity effects include unequal market access and the possibility that low-capability or socially disadvantaged actors bear a disproportionate share of the transition cost.

Fig. 1:GST-Induced Formalisation and Equity (GIFE) Framework

Source: Author’s theoretical model, based on the conceptual framework developed for this study.

8. Hypotheses development

H1. GST institutional reform positively influences the GST-induced formalisation process.

Digital filing, invoice matching, and input-tax-credit dependency increase the importance of documentary compliance and formal vendor relationships. As these mechanisms become embedded in commercial exchange, enterprises face stronger pressure to adopt formal routines (Kanbur & Keen, 2014; Ministry of Finance, 2025).

H2. The GST-induced formalisation process negatively affects rural livelihoods.

When firms are compelled to comply before they possess adequate capability, the burden may be transmitted through working-capital stress, labour compression, and operational instability (Ghosh, 2022; Roy & Khan, 2021).

H3. The GST-induced formalisation process negatively affects social equity.

If compliance adaptation depends on digital literacy, liquidity, and access to intermediaries, the burdens of adjustment are unlikely to be evenly distributed. Low-capability and socially weaker enterprises are more likely to face exclusionary outcomes (Roy & Khan, 2021; ILO, 2015).

H4. Organisational capability weakens the positive relationship between GST institutional reform and the GST-induced formalisation process.

Digital literacy, enterprise scale, and access to administrative support can reduce the strain associated with GST adaptation; capability should therefore moderate the intensity of formalisation stress (Roy & Khan, 2021).

H5. Organisational capability weakens the negative effects of the GST-induced formalisation process on rural livelihoods and social equity.

Where firms possess stronger capability, the downstream consequences of compliance stress should be less severe, while low-capability enterprises are more vulnerable to employment loss, wage suppression, and market exclusion (ILO, 2015; Roy & Khan, 2021).

9. Methodology

This study adopts an explanatory sequential mixed-methods orientation, with the quantitative component serving as the primary empirical basis and the qualitative logic embedded in the cluster-tracing design used to interpret the observed enterprise dynamics. Sequential explanatory designs are appropriate when the researcher seeks first to identify numeric patterns and then to use contextual understanding to explain how and why those patterns arise (Creswell, 2009; Ivankova et al., 2006). In practical terms, the paper is quantitatively led but qualitatively informed.

The empirical setting is Kanakapura Taluk, Karnataka, chosen as a rural-cluster context where agriculture-linked, artisanal, and mineral-linked enterprise systems coexist. The study focuses on silk, dairy, and granite-linked activities because these sectors represent different combinations of labour intensity, perishability, market dependence, and documentation burden. This sectoral diversity strengthens the paper’s ability to examine whether GST-induced formalisation is experienced uniformly or unevenly across production systems.

The target population comprises micro and small enterprises and own-account units operating within the selected Kanakapura-linked clusters. Since informal and semi-formal enterprises often lack a complete official directory, the design uses purposive cluster identification followed by targeted snowballing. This is methodologically defensible because the study seeks to trace supply-chain relationships rather than draw a strict probability sample from a fully enumerated population.

The observed enterprise dataset contains 120 cases, balanced evenly across three sectors: milk (n = 40), silk (n = 40), and granite (n = 40). The sample also captures social category, digital literacy, employment before and after GST, compliance-cost strain, working-capital blockage, forced formalisation pressure, and annual turnover. The unit of analysis is the enterprise, with the preferred respondent being the proprietor, manager, contractor, or principal decision-maker with knowledge of compliance practices, labour use, and turnover conditions.

Primary data consist of the observed enterprise dataset and the questionnaire structure developed around the GIFE framework. Secondary sources are used for contextual triangulation and include official GST statistics, unincorporated-sector employment evidence, and the normative framework of ILO Recommendation No. 204. The instrument combines nominal variables (sector and social category), ratio variables (turnover and employment counts), and Likert-scale variables capturing digital literacy, compliance-cost strain, working-capital blockage, and forced formalisation pressure.

The analysis proceeds in two layers. The first and primary layer uses the observed enterprise dataset for descriptive statistics, paired pre–post comparisons, one-way sector comparisons, and exploratory regression analysis. The second layer is a supplementary structural illustration. A separate Python-based SEM script exists in the project files, but that script generates a fictitious 200-case dataset before estimating the model. Accordingly, the SEM results are used only as theory-consistent support and not as the paper’s sole empirical proof. This distinction is essential for publication integrity.

Table 2. Observed sample structure

Source: Author’s computation from the observed enterprise dataset (gst_research_data.csv).

Table 3. Construct operationalisation

Source: Developed by the author from the theoretical model and project notes.

10. Results

The empirical analysis is based on an observed dataset of 120 rural enterprise respondents, evenly distributed across milk, silk, and granite-linked clusters. The social composition of the sample consists of 55 OBC respondents, 41 Dalit respondents, and 24 General-category respondents, which is relevant to the equity dimension of the GIFE framework because the study is explicitly concerned with whether the burden of formalisation is socially uneven.

Across the full sample, the mean score for digital literacy was 2.64 on a five-point scale, suggesting only modest digital capability among respondents. At the same time, the mean values for compliance-cost strain (M = 4.00), working-capital blockage (M = 3.97), and forced formalisation pressure (M = 4.00) indicate that GST-related transition pressures were perceived as high across the sample. The mean annual turnover was ₹29.52 lakhs, indicating that the study is largely capturing lower-scale and moderate-scale rural enterprise activity rather than large-firm behaviour.

Most importantly, the sample shows a visible decline in employment from the pre-GST period to the post-GST period. Mean employment fell from 14.48 workers per enterprise before GST to 11.23 workers after GST, indicating an average reduction of 3.26 workers per enterprise. In rural enterprise contexts, this magnitude is substantively important because it reflects reduced labour absorption and heightened livelihood vulnerability.

Table 4. Descriptive statistics of key study variables (N = 120)

Source: Author’s computation from the observed enterprise dataset (gst_research_data.csv).

A paired-sample t-test was conducted to determine whether the observed reduction in employment from the pre-GST to the post-GST period was statistically significant. The result was highly significant, t(119) = 8.11, p < .001, with a paired-effect size of Cohen’s d = 0.74. This indicates a moderate-to-strong effect and supports the GIFE framework’s central claim that GST-induced formalisation pressure is not merely administrative in its consequences; it can be associated with tangible livelihood contraction at the enterprise level.

Table 5. Paired-sample t-test for pre- and post-GST employment

Source: Author’s computation from the observed enterprise dataset (gst_research_data.csv).

Separate paired-sample tests were then conducted for each sector. In the granite cluster, mean employment fell from 15.08 to 10.75, a reduction of 4.33 workers per enterprise, t(39) = 7.10, p < .001, d = 1.12. In the milk cluster, mean employment fell from 14.63 to 11.78, a reduction of 2.85 workers, t(39) = 3.38, p = .002, d = 0.53. In the silk cluster, mean employment declined from 13.75 to 11.15, a reduction of 2.60 workers, t(39) = 4.38, p < .001, d = 0.69. These findings show that labour contraction is not confined to one cluster but is a broad-based post-GST pattern across all three sectors.

Table 6. Sector-wise pre- and post-GST employment comparison

Source: Author’s computation from the observed enterprise dataset (gst_research_data.csv).

Fig.2:Mean employment before and after GST by sector

Source: Author’s computation from the observed enterprise dataset (gst_research_data.csv).

To assess whether the three sectors differed significantly in the intensity of post-GST stress, one-way ANOVA was performed across the main observed variables. The ANOVA for post-GST employment was not significant, F(2,117) = 1.14, p = .322. Similarly, the ANOVA for employment reduction was not significant, F(2,117) = 1.82, p = .167. Compliance-cost strain was also not significantly different across sectors, F(2,117) = 1.46, p = .236, suggesting that paperwork and compliance burden were high across all sectors rather than concentrated in only one.

By contrast, working-capital blockage showed a statistically significant sectoral difference, F(2,117) = 3.18, p = .045. The highest mean was observed in the silk sector (M = 4.23), followed by milk (M = 3.85) and granite (M = 3.83). Although post hoc Tukey comparisons did not individually cross the .05 threshold, the omnibus result suggests that liquidity strain is the most cluster-sensitive channel of distress in the observed dataset.

Table 7. Sector-wise means and ANOVA results

Source: Author’s computation from the observed enterprise dataset (gst_research_data.csv).

Fig.3:Working-capital blockage by sector

Source: Author’s computation from the observed enterprise dataset (gst_research_data.csv).

An exploratory multiple regression model was estimated with employment reduction as the dependent variable and forced formalisation pressure, compliance-cost strain, working-capital blockage, digital literacy, and annual turnover as predictors. The model yielded very low explained variance (R² = .003), and none of the individual predictors reached statistical significance. A second model added sector dummies for milk and silk, with granite as the reference category. This marginally improved model fit to R² = .035, but the overall model remained non-significant, F(7,112) = 0.58, p = .772.

This result should be interpreted carefully. It does not negate the finding of statistically significant employment contraction; rather, it suggests that the observed reduction is likely shaped by multiple interacting and unmeasured contextual factors—including seasonality, demand fluctuation, informal subcontracting patterns, family labour substitution, and commodity-market volatility—that are not fully captured by the available predictors.

Table 8. Exploratory regression models predicting employment reduction

Source: Author’s computation from the observed enterprise dataset (gst_research_data.csv).

A supplementary SEM output was also available in the project files. However, this result must be interpreted with caution because it was generated from a separate model-support dataset rather than directly estimated from the observed 120-enterprise field dataset. Therefore, it is best used as a structural illustration of the GIFE framework, not as the paper’s sole empirical proof.

Within that supplementary model, the path from GST Institutional Pressure (GIP) to Compliance Burden (CB) was strong and significant (β = 0.682, p < .001). The path from Compliance Burden to Socio-Economic Impact (SEI) was also significant (β = 0.389, p < .001), while the direct path from GST Institutional Pressure to Socio-Economic Impact remained significant (β = 0.308, p = .002). Taken together, these coefficients suggest a partial mediation structure in which GST affects socio-economic outcomes both directly and indirectly through compliance burden.

Table 9. Supplementary structural model estimates (illustrative only)

Source: Author’s compilation from the supplementary SEM output (sem_estimates.csv). Note: This table is presented only as a theory-consistent structural illustration and not as the primary field-estimated model.

11. Discussion

The findings strongly support the central intuition of the GIFE framework. The most robust empirical result is the statistically significant decline in employment after GST across the full sample and within each sector. This suggests that GST-era transition pressures are associated with reduced labour absorption in rural enterprises, even if the exact enterprise-level predictors of this reduction cannot be fully isolated using the observed regression model.

Much of the policy debate around GST has focused on collections, compliance deepening, and administrative integration. The present results indicate that a production-side analysis yields a more complex picture. The enterprises in the sample reported high levels of compliance burden, working-capital blockage, and forced formalisation pressure, while simultaneously showing a decline in average employment. This pattern is consistent with the literature on premature formalisation (Roy & Khan, 2021) and with Ghosh’s (2022) evidence that GST can generate business strain through paperwork burden, liquidity compression, and labour adjustment.

A particularly important finding is that working-capital blockage, rather than compliance burden in general, shows the clearest sectoral differentiation. The silk sector recorded the highest mean level of working-capital stress, and the omnibus ANOVA result for this variable was statistically significant. This suggests that liquidity blockage may be the most cluster-sensitive mechanism through which GST-induced formalisation is transmitted. Sectors that rely on cyclical procurement, delayed payment, or multi-stage value chains appear especially vulnerable when compliance requires earlier documentation and cash-flow discipline.

The results also support the idea that GST-induced formalisation is broad-based rather than isolated. Digital literacy, compliance-cost strain, and forced formalisation pressure did not significantly differ across sectors, implying that the institutional compliance environment is widely felt across clusters. What varies is not necessarily the existence of the burden, but the form in which it is converted into distress.

The exploratory regression models did not explain employment reduction well, but this should not be read as a contradiction. Rather, it points to the complexity of livelihood outcomes in rural enterprise systems. Employment adjustment is likely influenced by several contextual variables not fully captured in the dataset. This reinforces the value of a mixed-methods and cluster-sensitive approach: a narrow linear model cannot by itself capture the full logic of induced formalisation.

The supplementary SEM results, while not primary empirical evidence, reinforce the theoretical coherence of this interpretation. The significant path from GST Institutional Pressure to Compliance Burden, and from Compliance Burden to Socio-Economic Impact, supports the proposition that GST’s effects are not exhausted by tax administration alone. Instead, GST appears to function as an institutional restructuring force that changes the conditions of market participation, liquidity management, and labour survival.

12. Hypothesis-wise interpretation

H1: Broadly supported conceptually and illustratively.

The observed enterprise dataset shows high mean levels of forced formalisation pressure and compliance burden across all sectors, while the supplementary structural model reports a strong path from GST Institutional Pressure to Compliance Burden.

H2: Supported.

The observed data show significant pre–post employment decline overall and within each sector, indicating that GST-era formalisation pressures are associated with adverse livelihood consequences.

H3: Partially supported.

The observed dataset does not provide a full latent equity scale, but the social composition of the sample, combined with high burden indicators and the market-exclusion logic embedded in the supplementary SEM, suggests that equity-related risks are plausible and consistent with the model.

H4: Not conclusively tested.

Digital literacy was measured in the observed dataset, but the available sample and structure do not support a fully specified moderation test of the theoretical relationship.

H5: Not conclusively tested.

The current data are suggestive but insufficient for a strong moderation claim. This remains a valuable direction for future field-based structural estimation.

13. Theoretical implications

The paper extends the GST debate from a macro-fiscal success narrative to a micro-institutional transition perspective. Formalisation should not be conflated with registration growth alone.

It advances the concept of GST-induced formalisation as distinct from generic formalisation. The findings suggest that firms may enter or adapt to formal compliance structures not through organic capability growth, but through coercive commercial necessity.

The paper also links formalisation to social equity and livelihood outcomes. This is theoretically important because it integrates tax policy, informal-sector transition, and rural development within a single explanatory framework and operationalises the spirit of ILO Recommendation No. 204 in a concrete Indian policy setting.

14. Practical and policy implications

For policymakers, the findings suggest that formalisation cannot be treated as inclusion by default. If GST-induced compliance deepening leads to employment contraction and liquidity stress in rural clusters, complementary support mechanisms become essential. These may include sector-sensitive working-capital support, simplified return procedures for micro-enterprises, cluster-level digital handholding, and targeted relief for labour-intensive sectors.

For GST administration, the results indicate that working-capital blockage is a critical pain point. Improving refund timelines, easing documentation frictions, and reducing the cash-flow mismatch embedded in compliance cycles could make formalisation more sustainable.

For MSME and rural development agencies, the evidence suggests that digital capability should be treated as an institutional support issue rather than a purely private firm-level problem. Training, assisted compliance cells, cluster-based facilitation desks, and vernacular digital support mechanisms could substantially improve enterprise adaptation.

15. Limitations and future research directions

This study has several limitations. First, the primary observed dataset is limited to 120 enterprises in one rural cluster region. While analytically useful, the findings should not be generalised to all of India without caution.

Second, the design is not a strict probability sample and therefore prioritises cluster relevance over population representativeness. Third, the regression models explain only a small share of employment reduction, indicating that additional contextual variables should be incorporated in future work.

Fourth, the observed dataset contains strong enterprise indicators but not a full latent multi-item scale battery for every theoretical construct. This limits the extent to which moderation and mediation can be field-estimated. Fifth, the supplementary SEM is illustrative rather than primary evidence. Future research should estimate the full GIFE model on a larger real-field dataset using validated scales and field-based SEM.

Conclusion

This paper set out to examine whether GST has produced inclusive formalisation or induced a capability–compliance mismatch for rural enterprises. Using a cluster-based analysis of milk, silk, and granite-linked enterprises in Kanakapura, Karnataka, the study finds that post-GST employment declined significantly across the sample and within each sector. It also finds that compliance burden is widespread, while working-capital blockage emerges as the most cluster-sensitive mechanism of strain.

Taken together, these findings suggest that GST should not be understood solely as a successful tax reform measured by revenue and registrations. In rural enterprise systems, GST also operates as an institutional restructuring force that can deepen formal visibility while leaving capability constraints unresolved. The result is not necessarily inclusive formalisation, but in many cases induced formalisation under conditions of uneven preparedness.

The broader implication is clear: formalisation must be judged not only by whether firms enter compliance systems, but by whether they can survive, adapt, and participate with dignity and viability after entering them. That is the central contribution of the GIFE framework and the main policy lesson of this paper.

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