Patent-based technological signals and green and digital energy start-up development: Global evidence and insights for Kazakhstan, Armenia, and Ukraine
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DOIhttp://dx.doi.org/10.21511/im.22(2).2026.25
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Article InfoVolume 22 2026, Issue #2, pp. 374–396
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Type of the article: Research Article
Abstract
Innovative marketing increasingly requires reliable market intelligence signals that reduce uncertainty, support product positioning, and guide venture financing in technology-intensive green and digital markets. This study aims to assess how patent-based technological signals shape innovative market development by predicting the formation and venture financing of green and digital energy start-ups, while also examining whether entrepreneurial market entry and funding stimulate subsequent patenting activity. The empirical analysis is based on a balanced panel of 146 countries for 2000–2023, combining IEA energy start-up and funding indicators with OECD patent data. The empirical strategy follows a sequential design: descriptive statistics and log1p transformations are used to characterize the data; Dumitrescu–Hurlin panel Granger causality tests provide the main evidence on predictive causality; and PVAR, multiple-testing corrections, PPML and TWFE models are used as complementary robustness and dynamic checks. The results show highly concentrated innovative market development: average green and digital energy start-up activity is around 7 per country-year, while the median is 0 for both indicators. The Dumitrescu–Hurlin tests reveal 69 significant relationships out of 120, with stronger evidence for patents predicting start-up formation and funding than for the reverse direction. These findings remain robust after Benjamini–Hochberg correction and after excluding numerically extreme statistics. TWFE results support the positive association between climate adaptation and ICT-mitigation patents, digital energy start-up formation and early-stage digital funding, while PVAR models provide only complementary dynamic evidence and are interpreted cautiously due to stability limitations in the main GMM specification. Country fixed effects indicate that Ukraine has a more favorable estimated structural position for digital energy start-up formation than Kazakhstan and Armenia.
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JEL Classification (Paper profile tab)O31, O34, M31, G24
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References72
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Tables5
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Figures2
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- Figure 1. Bootstrapped generalized impulse response functions for the patent–funding PVAR model
- Figure 2. Bootstrapped generalised impulse response functions for the year-demeaned green innovation PVAR model
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- Table 1. Methodological sequence and role of empirical methods
- Table 2. Dynamic panel VAR results for the green energy innovation block
- Table 3. Robustness of Dumitrescu–Hurlin panel Granger causality results to multiple testing
- Table 4. Summary of dynamic fixed-effects and PPML robustness checks
- Table 5. TWFE robustness models for digital energy start-up formation and early-stage digital energy start-up funding
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