The approximate solution of finite‐horizon discrete‐choice dynamic programming models
研究了有限期离散选择动态规划模型估计的计算负担问题，详细描述了Keane和Wolpin的插值方法，重新计算了其质量诊断，并揭示了计算时间与估计精度之间的权衡。
Summary The estimation of finite‐horizon discrete‐choice dynamic programming (DCDP) models is computationally expensive. This limits their realism and impedes verification and validation efforts. Keane and Wolpin ( Review of Economics and Statistics , 1994, 76 (4), 648–672) propose an interpolation method that ameliorates the computational burden but introduces approximation error. I describe their approach in detail, successfully recompute their original quality diagnostics, and provide some additional insights that underscore the trade‐off between computation time and the accuracy of estimation results.