ACTIVEResearch Project

Credit Constraints and Innovation Investment

Develops a dynamic general equilibrium model integrating Schumpeterian growth theory with real business cycle dynamics. Explores how credit market imperfections affect entrepreneurial innovation decisions through a venture capital financing structure. The model features patient households providing seed funding to credit-constrained entrepreneurs who invest in quality-ladder R&D. Examines the tension between the Arrow replacement effect and financing constraints in determining optimal innovation investment, with implications for understanding why R&D patterns deviate from theoretical predictions.

§ Project Resources
§ Key Findings

Key Findings

  1. 001

    Credit constraints bind for entrepreneurs: Patient households provide seed funding but entrepreneurs face borrowing limits that restrict optimal R&D investment

  2. 002

    Quality ladder innovation generates endogenous growth: R&D expenditure creates probabilistic quality improvements with cost increasing in technological sophistication

  3. 003

    Venture capital structure affects innovation dynamics: The equity-sharing arrangement between patient households and entrepreneurs creates different incentives compared to standard debt financing

  4. 004

    Arrow replacement effect modified: Credit constraints can override the standard result that incumbents have lower innovation incentives than entrants

Credit Constraints and Innovation Investment
Correlation structure for output, consumption, investment, and R&D in the model and data.
§ Methodology

Methodology

  1. 001

    Two-agent DSGE model: Patient households (high β) and impatient entrepreneurs (low β) with different time preferences

  2. 002

    Schumpeterian quality ladder: Innovation increases sectoral quality levels by factor λ with probability η(z^E_t)

  3. 003

    Credit market friction: Entrepreneurs can only borrow against expected firm value, creating financing constraints

  4. 004

    Endogenous mark-ups: Monopolistic competition with price mark-ups determined by number of firms per sector

  5. 005

    Calibration to business cycle moments: Model parameters chosen to match stylized facts about R&D and output volatility

§ Implications

Implications

  1. 001

    Financial development matters for growth: Improving access to credit for entrepreneurs can boost aggregate innovation and long-run growth

  2. 002

    Venture capital policy: Policies supporting equity financing may be more effective than debt market interventions for innovation

  3. 003

    Cyclical innovation patterns: Credit constraints can explain why R&D behaves differently from theoretical predictions during business cycles

  4. 004

    Firm size and innovation: The model suggests optimal firm size depends on the balance between financing constraints and market power effects

Rev. 05.2026email@pedroserodio.comLondon, United Kingdom
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