Paper title: Venture Capital as a Catalyst for Accelerating Innovation: Empirical Evidence from Bangladesh
Abstract: Bangladesh’s ambition to become a knowledge-based, high-income economy by 2041 hinges on enhancing total factor productivity through innovation. With prior studies offering limited empirical evidence specific to its emerging VC ecosystem, this study examines the role of venture capital (VC) funding in driving innovation, proxied by patent applications, in Bangladesh over a 29-year period (1995–2023). Using data from VentureXpert, the World Bank, and Bangladesh’s Department of Patents, Designs and Trademarks, we employ Negative Binomial regression and Autoregressive Distributed Lag (ARDL) models to analyze short- and long-run relationships between VC funding and innovation, while taking a vector of macroeconomic variables (GDP, market capitalization, domestic credit) as control. Negative Binomial Regression results indicate that domestic credit influences patenting, while VC funding shows a positive but insignificant effect. The ARDL model confirms a long-run equilibrium relationship, with GDP positively impacting patenting, but VC’s long-run effect remains insignificant, supporting the hypothesis that VC prioritizes non-technological innovations in Bangladesh’s weak innovation ecosystem. Aligning with Schmookler’s demand-pull hypothesis and Romer’s endogenous growth theory, these results suggest VC fosters market-driven innovations (e.g., Pathao, 10 Minute School) rather than patent-intensive R&D. Policy recommendations include strengthening regulatory frameworks, promoting non-technological innovation, and enhancing financial intermediation to bolster Bangladesh’s innovation ecosystem and support its economic growth objectives. Keywords: Venture Capital, Innovation, ARDL Model, Negative Binomial Regression
