Financial infrastructure and new business density in transition economies: Resource dependence and the structural role of transport connectivity

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Type of the article: Research Article

Abstract
In transition economies, the contribution of financial and transport infrastructure to new firm formation remains a first-order public-finance question. This paper examines how financial infrastructure and air connectivity relate to new business density across 28 transition economies over 2010–2024, and whether resource dependence moderates the relative contribution of branch-density and credit-volume channels (FDI and gross fixed capital formation serve as secondary benchmarks). Two-way fixed-effects panel regressions on an unbalanced panel of 28 transition economies (420 country-years as the maximal frame; the primary new-business-density model is identified on 249 complete cases from 24 economies), complemented by pooled OLS and between-effects estimators, are estimated for the three outcomes. Within countries, ATM penetration is the financial-infrastructure indicator most consistently associated with entrepreneurial activity (β = 0.011); trade openness is positive (β = 0.006) but does not survive relaxing the air-restricted sample. The relative contribution of bank branches versus domestic credit shifts with resource-rent intensity (branches × R = +0.016; credit × R = −0.011) − a pattern directionally stable across specifications but resting on the interaction design, a small complete-case panel, and a static moderator, its branch leg particularly sensitive to sample composition; the reversal is therefore read as suggestive rather than definitive. Air-passenger connectivity is a structural between-country correlate of entrepreneurship (between-effects β = +0.310) but not a within-country driver. New business density is more fully explained than the secondary outcomes (within-R2 = 0.26 versus 0.14 and 0.09); conclusions are therefore drawn for firm entry rather than for the investment-and-entrepreneurial ecosystem.

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    • Figure 1. Marginal effects of bank branches per 100,000 adults (panel a) and domestic credit (% GDP) (panel b) on ln(new business density), across the empirical range of centered ln(1 + resource rents % GDP)
    • Table 1. Variable definitions, operational measurement, and sources
    • Table 2. Descriptive statistics, 28 transition economies, 2010–2024
    • Table 3. New business density regressions − pooled OLS, between effects, fixed effects
    • Table 4. New business density with resource-dependence moderation (FE, country-and-year)
    • Table 5. Robustness checks of the D3 moderation specification
    • Table 6. Robustness of the moderation to excluding the air-transport variables
    • Table А1. Country sample
    • Table B1. Correlation matrix
    • Table C1. FDI net inflows (% GDP), Hungary excluded
    • Table D1. Gross fixed capital formation (% GDP)
    • Table E1. Marginal effects of bank branches and domestic credit on ln(NBD)
    • Table F1. Country-years available and contribution to the estimation sample, by economy
    • Table F2. Full-sample versus complete-case descriptive statistics
    • Conceptualization
      Vugar Nazarov, Jamal Hajiyev, Vasif Ahadov, Aziz İskandarov
    • Formal Analysis
      Vugar Nazarov, Jamal Hajiyev, Vasif Ahadov
    • Methodology
      Vugar Nazarov, Jamal Hajiyev, Vasif Ahadov, Aziz İskandarov
    • Resources
      Vugar Nazarov, Shabnem Dadaşova
    • Supervision
      Vugar Nazarov, Jamal Hajiyev, Aziz İskandarov
    • Validation
      Vugar Nazarov, Vasif Ahadov, Shabnem Dadaşova
    • Writing – original draft
      Vugar Nazarov, Jamal Hajiyev, Vasif Ahadov, Aziz İskandarov, Shabnem Dadaşova, Farid Aghababazade, Mayıl Zalıyev
    • Writing – review & editing
      Vugar Nazarov, Jamal Hajiyev, Vasif Ahadov, Aziz İskandarov, Shabnem Dadaşova, Farid Aghababazade, Mayıl Zalıyev
    • Funding acquisition
      Jamal Hajiyev, Vasif Ahadov
    • Project administration
      Jamal Hajiyev, Vasif Ahadov
    • Software
      Aziz İskandarov, Farid Aghababazade, Mayıl Zalıyev
    • Data curation
      Shabnem Dadaşova, Farid Aghababazade, Mayıl Zalıyev
    • Investigation
      Shabnem Dadaşova, Farid Aghababazade, Mayıl Zalıyev
    • Visualization
      Shabnem Dadaşova, Farid Aghababazade, Mayıl Zalıyev