A two-step indirect inference approach to estimate the long-run risk asset pricing model
提出两步间接推断法，分离估计长期风险模型的宏观经济动态与投资者偏好参数，并用美国数据重新评估该模型解释实体经济与金融市场的能力。
Abstract The long-run consumption risk model provides a theoretically appealing explanation for prominent asset pricing puzzles, but its intricate structure presents a challenge for econometric analysis. This paper proposes a two-step indirect inference approach that disentangles the estimation of the model’s macro-economic dynamics and the investor’s preference parameters. A Monte Carlo study explores the feasibility and efficiency of the estimation strategy. We apply the method to recent U.S. data and provide a critical re-assessment of the long-run risk model’s ability to reconcile the real economy and financial markets. This two-step indirect inference approach is potentially useful for the econometric analysis of other prominent consumption-based asset pricing models that are equally difficult to estimate.