Modeling Conditional Yield Densities
针对农作物产量数据有限导致参数模型难以验证的问题，本文提出一种半参数估计方法，其理论性质和模拟结果能提高实证分析的可靠性。
Given the increasing interest in agricultural risk, many have sought improved methods to characterize conditional crop‐yield densities. While most have postulated the Beta as a flexible alternative to the Normal, others have chosen nonparametric methods. Unfortunately, yield data tends not to be sufficiently abundant to invalidate many reasonable parametric models. This is problematic because conclusions from economic analyses, which require estimated conditional yield densities, tend not to be invariant to the modeling assumption. We propose a semiparametric estimator that, because of its theoretical properties and our simulation results, enables one to empirically proceed with a higher degree of confidence.