A Reassessment of Likelihood Approximation by Integration on Sparse Grids
重新评估了稀疏网格积分在随机系数离散选择模型中近似选择概率的效果，发现其在高方差或不同方差结构下可能失效，且对截面混合Logit的适用性受备选项数量影响。
ABSTRACT This paper revisits sparse grid integration proposed in the literature for approximating integrals that occur as choice probabilities in random coefficient discrete choice models. First, we successfully replicate their main findings for the panel mixed logit. Second, for higher variances and for a different structure of the variances of the random coefficients, in certain cases, we fail to replicate the original results. Third, for the important special case of cross‐sectional mixed logit, replication of the original results is successful when the number of alternatives is moderate but fails otherwise.