系统工程理论与实践
繫統工程理論與實踐
계통공정이론여실천
Systems Engineering—Theory & Practice
2014年
4期
892~898
,共null页
工具变量估计 模型选取 模拟退火
工具變量估計 模型選取 模擬退火
공구변량고계 모형선취 모의퇴화
instrumental variables estimation; model selection; simulated annealing
工具变量估计是解决模型内生性问题的基本方法，但其有限样本表现对工具变量的选取十分敏感．近年来，对于“多工具变量”模型，文献中提出了基于近似最小均方误差的工具变量选取方法来解决这一问题，但这些方法或依赖于工具变量的排序，或受限于工具变量的数目．本文采用基于模拟退火算法的工具变量选取方法很好地克服了这些缺陷．Monte Carlo模拟结果表明该算法有效可行．
工具變量估計是解決模型內生性問題的基本方法，但其有限樣本錶現對工具變量的選取十分敏感．近年來，對于“多工具變量”模型，文獻中提齣瞭基于近似最小均方誤差的工具變量選取方法來解決這一問題，但這些方法或依賴于工具變量的排序，或受限于工具變量的數目．本文採用基于模擬退火算法的工具變量選取方法很好地剋服瞭這些缺陷．Monte Carlo模擬結果錶明該算法有效可行．
공구변량고계시해결모형내생성문제적기본방법，단기유한양본표현대공구변량적선취십분민감．근년래，대우“다공구변량”모형，문헌중제출료기우근사최소균방오차적공구변량선취방법래해결저일문제，단저사방법혹의뢰우공구변량적배서，혹수한우공구변량적수목．본문채용기우모의퇴화산법적공구변량선취방법흔호지극복료저사결함．Monte Carlo모의결과표명해산법유효가행．
Instrumental variables estimation provides a general solution to the problem of an endogenous explanatory variable, but the finite sample properties of instrumental variable estimators are sensitive to the choice of instruments. In recent years, several approaches based on minimizing the approximate mean square error have been proposed in the literature for the models with many instruments. However, these methods either depend on the order of the instruments or are limited by the number of instruments. In this paper, the selection method of instruments based on simulated annealing algorithm is proposed to solve these problems. Monte Carlo simulations have demonstrated the effectiveness of the proposed algorithm.
