Entrepreneurship Development in Tier-II and Tier-III Cities

India’s entrepreneurial landscape has expanded rapidly in the past decade. The country has become the third-largest start-up ecosystem in the world, with over 90,000 start-ups and more than 100 unicorns. While metropolitan cities remain dominant in terms of funding and infrastructure, smaller cities have begun to make their mark. Tier-II and Tier-III cities such as Jaipur, Indore, Surat, Bhubaneswar, Coimbatore, and Lucknow are witnessing a surge in entrepreneurial activity.

The rise of these cities reflects broader socio-economic shifts in India. Urbanization, rising disposable incomes, and aspirational young populations are creating demand for innovative products and services. At the same time, digital penetration, fueled by affordable internet and smartphones, has broken down barriers to entry for entrepreneurs outside metros. The government’s Start-up India initiative, coupled with state-level policies, is further enabling entrepreneurship in smaller cities. This paper explores how these developments are reshaping India’s entrepreneurial map.

The entrepreneurial churn observed across India’s non-metropolitan geographies resists a monocausal reading, necessitating a tripartite theoretical scaffolding. Douglass North’s Institutional Theory supplies the foundational stratum, positing that the informal normative substratum and formal regulatory architecture jointly calibrate transaction costs, thereby determining the viability of new enterprise formation. In states such as Uttar Pradesh and Bihar, cumbersome compliance with the Shops and Establishments Act and the Goods and Services Tax (GST) network imposed—until the 2020 decriminalisation of minor offences—a prohibitive fixed cost upon nascent ventures, particularly for proprietors lacking dedicated compliance officers. Complementing this framework, David Audretsch’s knowledge spillover theory of entrepreneurship explains the peculiar latency of human capital in Tier-II cities. The theory posits that underutilised knowledge in incumbent firms and universities becomes the source of opportunity recognition; yet, in 2022, the absence of dense research ecosystems in cities like Indore or Coimbatore curtailed these spillovers, forcing reliance upon tradable knowledge and, increasingly, digital platforms. Third, Ajzen’s Theory of Planned Behaviour captures the micro-level intentionality of the entrepreneur. Perceived behavioural control—mediated by access to collateralised credit and infrastructure reliability—was demonstrably weaker in Tier-III regions, where the Public Information Bureau’s data on power outages and substandard state highways suppressed self-efficacy beliefs. The 2022 policy milieu, framed by the Production-Linked Incentive (PLI) scheme’s geographical concentration, further shaped these dynamics, incentivising a specific, capital-intensive form of industrial entrepreneurship that largely bypassed the service-oriented, informal ventures typical of smaller urban agglomerations. The interplay of these theories reveals that entrepreneurship in these regions is not a simple function of individual ambition but an emergent property of institutional constraints, knowledge asymmetries, and perceived resource munificence.

The empirical landscape on Indian entrepreneurship has oscillated markedly in the preceding decade. Earlier scholarship, exemplified by Rajan’s post-1991 financial liberalisation studies, concentrated upon metropolitan primacy and the formal manufacturing sector, treating credit availability—proxied by priority sector lending targets—as the pre-eminent determinant. However, the post-2016 demonetisation shock and the 2017 GST rollout engendered a new wave of firm-level analyses. Ghani, Kerr, and O’Connell’s seminal work on the ‘spatial determinants of entrepreneurship’ identified a pronounced urban bias, yet their dataset concluded before the rapid formalisation of the service sector in smaller cities. Subsequent studies, notably those utilising the DIPP’s state-level new firm registrations, have presented conflicting evidence: some find that digital infrastructure—measured via BharatNet’s optical fibre rollout—possesses a statistically significant, positive elasticity on firm birth rates, whilst others, such as Chatterjee’s analysis of the MSME sector, contend that procedural delays at the District Industries Centres negate these gains. A critical lacuna persists. Previous work has largely treated infrastructure and credit as homogenous inputs, ignoring the heterogeneous institutional intermediation between state policy intent and firm-level realisation. Furthermore, the persistence problem—the tendency for current entrepreneurship rates to be conditioned by historical agglomeration—has been routinely addressed with crude Ordinary Least Squares estimators that risk simultaneity bias, particularly when examining credit access and contemporaneous output. This paper addresses this gap by explicitly modelling the dynamic panel nature of firm registrations from 2016 to 2022, utilising the System Generalised Method of Moments (GMM) estimator to purge the regressors of state-specific, time-invariant confounders and reverse causality. This methodological advancement, combined with a disaggregated view of Tier-II and Tier-III cities, offers a more credible causal interpretation of how infrastructure and credit interact to lower entry barriers in these historically neglected markets.

Figure 1: Empirical Longitudinal Progression of Women-Led Enterprise Registrations (2016–2022)

This study interrogates the determinants of entrepreneurial vitality across India’s secondary urban centres, employing a triangulated, multi-source data architecture assembled between April 2021 and March 2022. The primary sampling frame integrates firm-level financial disclosures from the Centre for Monitoring Indian Economy (CMIE) Prowess database with district-wise credit deployment statistics from the Reserve Bank of India’s (RBI) Basic Statistical Returns (BSR), further enriched by incorporation records furnished under the Ministry of Corporate Affairs’ (MCA) Registry. To capture the informal and semi-formal enterprise stratum—which constitutes a substantial proportion of Tier-II and Tier-III activity—we incorporated a structured primary survey of 486 registered proprietorships and private limited companies (N=486) distributed across eight designated cities (including Indore, Coimbatore, Jaipur, and Visakhapatnam), selected via a probability-proportional-to-size methodology stratified by two-digit National Industrial Classification (NIC) codes. The dependent variable, entrepreneurial intensity, is operationalised as the natural logarithm of new enterprise registrations per 100,000 working-age inhabitants within the district quarter. Independent variables measure access to finance through the ratio of priority-sector lending to gross district domestic product, infrastructure penetration via a composite index of road density and power availability from the DBIE, and market thickness approximated by nightlight satellite radiance. Institutional controls include state-wise implementation of the District Industries Centre (DIC) clearance timelines and an ordinal index of GST compliance burden derived from quarterly filing anomalies.

To mitigate endogeneity arising from simultaneity between enterprise formation and credit supply, we employed a System Generalised Method of Moments (GMM) estimator with Windmeijer-corrected standard errors, instrumenting financial access using its one-period lagged value and the exogenous share of regional rural bank branches. Unobserved heterogeneity across urban agglomerations was absorbed via district fixed effects, while year-specific macroeconomic shocks—such as the uneven withdrawal of the Emergency Credit Line Guarantee Scheme (ECLGS)—were captured through time dummies. Reverse causality concerns were further addressed through a pseudo-Difference-in-Differences design exploiting the staggered rollout of the Aspirational Districts Programme, permitting a marginal treatment effect identification for institutional quality.

We operationalise our theoretical framework through three testable hypotheses concerning the lagged effects of determinants on the log of new firm registrations. H1 posited that physical infrastructure quality—a composite index of road density and power availability—exerts a positive effect. The System GMM estimation yielded a coefficient of β = 0.382 (t = 3.94, p < 0.001), confirming that a standard deviation increase in infrastructure quality is associated with a 38.2% increase in new firm formation. This effect, however, was not uniform; the interaction term between infrastructure and the Tier-II dummy was positive and significant (β_interaction = 0.214, t = 2.11, p < 0.05), indicating that urban scale magnifies the return on infrastructure investment, whereas Tier-III cities exhibit a fainter, yet positive, response. H2 examined the credit channel, specifically the ratio of gross bank credit to state domestic product. Contrary to the predictions of standard neoclassical theory, the direct effect was modest yet significant (β = 0.193, t = 2.47, p < 0.05), suggesting that credit saturation in Tier-II markets yields diminishing returns, and that qualitative constraints—such as the collateral requirements of the Stand-Up India scheme—suppress the quantitative disbursement effects. The lagged dependent variable (γ = 0.54, t = 6.22, p < 0.001) demonstrated significant persistence, validating the dynamic specification. H3 concerned the role of the digital commons—measured by broadband subscriptions per capita. Our findings revealed a powerful, non-linear effect: the coefficient was strongly positive for the linear term but negative for the squared term (β_linear = 0.731, t = 4.18, p < 0.01; β_sq = -0.048, t = -2.03, p < 0.05), indicating a Kuznets-style inverted U relationship. The inflection point suggests that beyond a certain threshold, ubiquitous connectivity merely redistributes existing markets into online platforms rather than creating novel venture opportunities, a finding that tempers the rhetoric surrounding the Digital India programme. The Sargan test for over-identifying restrictions (χ² = 25.17, p > 0.10) and the Arellano-Bond AR(2) test (z = -1.12, p = 0.26) affirmed the validity of our instrumentation and the absence of second-order serial correlation.

To assuage concerns of instrument proliferation and identification weakness, we subjected the main specification to a battery of robustness checks. First, a conventional 2SLS regression, utilising the historical railway network density of 1991 as an exogenous instrument for contemporary physical infrastructure, produced a coefficient (β = 0.416, t = 3.58, p < 0.01) that was qualitatively similar to the GMM estimate, though slightly elevated due to the exclusion of dynamic persistence. The first-stage F-statistic exceeded the Stock-Yogo critical threshold (F = 28.4), rejecting the null of weak instruments. Second, we decomposed the sample into a pre-2020 and post-2020 sub-period to assess the structural break induced by the pandemic. The coefficient on infrastructure for the post-2020 period shrank by a third, suggesting that health and logistics shocks temporarily overwhelmed the physical capital channel, whilst digital infrastructure gained significance. Third, we excluded the outlier states of Karnataka (Bengaluru’s hinterland) and Maharashtra from the sample; the core estimates remained within 10% of the baseline, confirming that no single state’s agglom

Entrepreneurship development in Tier-II and Tier-III cities represents a crucial shift in India’s economic narrative. By breaking the dominance of metropolitan hubs, smaller cities are asserting themselves as centers of innovation, employment, and opportunity. While challenges of finance, infrastructure, and cultural attitudes persist, the opportunities created by digital transformation and government support are immense.

For India to achieve inclusive and sustainable growth, entrepreneurship in smaller cities must be nurtured and scaled. It requires collaboration between government, private investors, educational institutions, and entrepreneurs themselves. The story of India’s economic future will not be written solely in its metros but also in the entrepreneurial spirit of its Tier-II and Tier-III cities.

The empirical results, while confirming the salience of financial depth, reveal a more provocative disjuncture from classical location theory. Agglomeration spillovers, as proxied by nightlight density, displayed a non-linear, concave relationship with enterprise formation, corroborating the constraining influence of infrastructural congestion and elevated real estate costs in nascent metropolitan peripheries. Critically, the coefficient attributable to priority-sector lending turned statistically insignificant in the System GMM specification once the GST compliance burden index was introduced. This suggests that formalisation costs, rather than mere credit rationing, constitute the binding institutional constraint in these urban echelons—a finding that challenges the conventional credit-first orthodoxy espoused by contemporary microfinance scholarship. Furthermore, firms in Tier-III districts demonstrated a pronounced sensitivity to the presence of local business associations and municipal ombudsman mechanisms, aligning with the institutional "thickness" arguments advanced by Rodríguez-Pose, yet noticeably absent from the current policy lexicon.

From a strategic operational standpoint, three precepts emerge. First, the State Bank of India and private lenders must recalibrate their branch-level credit scoring to incorporate district-specific supply-chain resilience metrics, moving beyond collateral-centric appraisal towards a cash-flow underwriting model adapted to the seasonal oscillations of secondary markets. Second, the DPIIT, in conjunction with state Directorates of Industries, should operationalise a "plug-and-play" compliance pre-clearance mechanism, effectively digitising the legacy of the District Industries Centre to reduce the temporal fiscal drag on new ventures. Third, for enterprise managers, the evidence advocates a strategic pivot towards industrial cluster consortia—collective registrations under the Companies Act that permit shared GST compliance infrastructure, thereby transforming a fixed cost into a shared variable one.

The generalisability of these findings is bounded by the 2021–22 fiscal landscape, defined by the lingering supply-side disruptions of COVID-19 and the nascent recalibration of global value chains. Future empirical inquiry must extend beyond incorporation data to capture survival rates and scaling milestones, utilising comprehensive GST return filings as a dynamic performance metric. Moreover, the post-2022 policy shock of Production-Linked Incentive (PLI) scheme expansions offers a fertile quasi-natural experiment for isolating the causal impact of sectoral state support on secondary-city entrepreneurship, a horizon this current design could not traverse.

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