Financing green entrepreneurs under limited commitment

IF 1.9 3区经济学 Q2 ECONOMICS

Journal of Economic Dynamics & Control Pub Date : 2024-08-12 DOI:10.1016/j.jedc.2024.104930

Alain Bensoussan , Benoit Chevalier-Roignant , Nam Nguyen , Alejandro Rivera

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Abstract

Risk-averse entrepreneurs interact with financiers to fund their projects. Projects can be operated under green or dirty technologies. We explore the role of limited commitment in determining the adoption of green technologies when governments enact carbon taxes and/or directed investment subsidies. We show that entrepreneurial (respectively, financier) limited commitment makes it more (less) costly for governments to encourage green technology adoption. Because green technologies are still at an early stage, the cash flows they generate are back-loaded. Entrepreneurial limited commitment forces consumption to increase over time, thereby undermining risk-sharing and making dirty technologies more attractive. By contrast, under financier limited commitment, the possibility that front-loaded dirty technologies become obsolete forces consumption to decrease over time, thereby impairing risk-sharing and making green technologies more attractive. We also show that carbon taxes (directed technology subsidies) are more cost-effective when entrepreneurs (financiers) display limited commitment.

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在承诺有限的情况下为绿色企业家融资

规避风险的企业家与金融家互动，为他们的项目提供资金。项目可以采用绿色技术或肮脏技术。我们探讨了当政府颁布碳税和/或定向投资补贴时，有限承诺在决定绿色技术采用中的作用。我们的研究表明，企业家（分别是融资者）的有限承诺使政府鼓励采用绿色技术的成本更高（更低）。由于绿色技术仍处于早期阶段，它们所产生的现金流是后负荷的。企业家有限承诺迫使消费随着时间的推移而增加，从而削弱了风险分担，使肮脏技术更具吸引力。与此相反，在融资者有限承诺的情况下，前期的肮脏技术可能会过时，这就迫使消费随时间推移而减少，从而影响风险分担，使绿色技术更具吸引力。我们还表明，当企业家（融资者）表现出有限承诺时，碳税（定向技术补贴）更具成本效益。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Economic Dynamics & Control ECONOMICS-

CiteScore

3.10

自引率

10.50%

发文量

199

期刊介绍： The journal provides an outlet for publication of research concerning all theoretical and empirical aspects of economic dynamics and control as well as the development and use of computational methods in economics and finance. Contributions regarding computational methods may include, but are not restricted to, artificial intelligence, databases, decision support systems, genetic algorithms, modelling languages, neural networks, numerical algorithms for optimization, control and equilibria, parallel computing and qualitative reasoning.