加速居民太阳能发电系统的普及：基于动态结构模型的政策分析
Accelerating the Adoption of Residential Solar Power Systems: Policy Analysis using a Dynamic Structural Model
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中文总结 AI 辅助
该研究构建居民光伏扩散动态结构模型，利用奥斯汀家庭数据估计模型，模拟反事实政策发现有限期回扣等策略可提升光伏采用与减排效果。
中文摘要 AI 辅助
问题定义：太阳能发电是能源组合的战略组成部分，旨在满足日益增长的需求并减少碳排放。政府和市政当局通过前期回扣和税收抵免鼓励家庭采用光伏（PV）系统。有限的预算需要基于原则、数据驱动的政策，这些政策需考虑采用的驱动因素以及激励措施对采用率的影响。方法与结果：我们开发了一个基于前瞻性家庭采用决策的居民光伏扩散动态结构模型，这些家庭权衡现在安装与未来安装之间的经济利弊。采用决策取决于投资回报和相邻采用者的影响。该模型按房屋价值和城市化水平对家庭进行细分，纳入未观测到的异质性，并捕捉时空安装动态。我们使用贝叶斯方法和德克萨斯州奥斯汀市详细的家庭层面数据估计该模型。在样本外测试中，它比同期替代模型更准确地预测安装量。我们在光伏扩散的动态均衡中模拟反事实政策，以评估回扣设计。该框架还可用于研究其他耐用技术的采用。管理启示：有限期提供的回扣比长期、成本更高的计划能产生更多的采用量和减排量。这一反直觉结果源于前瞻性行为、相邻影响以及回扣到期前的加速采用。我们还评估了分阶段削减和按家庭细分的差异化回扣。两步削减优于多次小幅削减。地理差异化可改善政策绩效，而按房屋价值差异化相比统一回扣几乎没有优势。
英文摘要
Problem definition: Solar electricity generation is a strategic component of energy portfolios designed to meet growing demand and reduce carbon emissions. Governments and municipalities encourage household photovoltaic (PV) adoption through upfront rebates and tax credits. Limited budgets require principled, data-driven policies that account for the drivers of adoption and the effects of incentives on adoption rates. Methodology/results: We develop a dynamic structural model of residential PV diffusion based on adoption decisions by forward-looking households that weigh the economic trade-offs between installing now and later. Adoption depends on return on investment and influence from neighboring adopters. The model segments households by home value and urbanization level, incorporates unobserved heterogeneity, and captures spatiotemporal installation dynamics. We estimate the model using Bayesian methods and detailed household-level data from Austin, Texas. In out-of-sample tests, it predicts installations more accurately than contemporary alternatives. We simulate counterfactual policies within the dynamic equilibrium of PV diffusion to evaluate rebate designs. The framework can also be adapted to study the adoption of other durable technologies. Managerial implications: A rebate offered for a limited period generates more adoption and emissions reductions than a prolonged, costlier program. This counterintuitive result arises from forward-looking behavior, neighbor influence, and accelerated adoption before the rebate expires. We also evaluate phased reductions and rebates differentiated by household segment. A two-step reduction outperforms multiple small reductions. Geographic differentiation improves policy performance, whereas differentiation by home value offers little advantage over a uniform rebate.
发表机构
- Lally School of Management, Rensselaer Polytechnic Institute（伦斯勒理工学院拉里管理学院）
- McCombs School of Business, The University of Texas at Austin（德克萨斯大学奥斯汀分校麦库姆斯商学院）
- LBJ School of Public Affairs, The University of Texas at Austin（德克萨斯大学奥斯汀分校LBJ公共事务学院）
机构由 AI 辅助整理，请以论文原文为准。
