Different covariate balance weighting methods have been proposed by researchers from different perspectives to estimate the treatment effects.This paper gives a brief review of the covariate balancing propensity score...Different covariate balance weighting methods have been proposed by researchers from different perspectives to estimate the treatment effects.This paper gives a brief review of the covariate balancing propensity score method by Imai and Ratkovic(2014),the stable balance weighting procedure by Zubizarreta(2015),the calibration balance weighting approach by Chan,et al.(2016),and the integrated propensity score technique by Sant’Anna,et al.(2020).Simulations are conducted to illustrate the finite sample performance of both the average treatment effect and quantile treatment effect estimators based on different weighting methods.Simulation results show that in general,the covariate balance weighting methods can outperform the conventional maximum likelihood estimation method while the performance of the four covariate balance weighting methods varies with the data generating processes.Finally,the four covariate balance weighting methods are applied to estimate the treatment effects of the college graduate on personal annual income.展开更多
Rock-fill dykes are often damaged caused by rapid flow currents in a mountainriver. Based on the relationship between the rock size on cover layer and its incipient velocity,it is found that rock weight is directly pr...Rock-fill dykes are often damaged caused by rapid flow currents in a mountainriver. Based on the relationship between the rock size on cover layer and its incipient velocity,it is found that rock weight is directly proportional to the 6th-9th power of incipient velocity,and 50% increase of the velocity may result in about 40 times increase of the rock weight.Therefore, it is inappropriate to improve the stability of rock-fill dykes by simply increasing therock weight. Some new measures should be used to reach this purpose.展开更多
基金the National Natural Science Foundation of China under Grant Nos.71631004 and 72033008the National Science Foundation for Distinguished Young Scholars under Grant No.71625001the Science Foundation of Ministry of Education of China under Grant No.19YJA910003。
文摘Different covariate balance weighting methods have been proposed by researchers from different perspectives to estimate the treatment effects.This paper gives a brief review of the covariate balancing propensity score method by Imai and Ratkovic(2014),the stable balance weighting procedure by Zubizarreta(2015),the calibration balance weighting approach by Chan,et al.(2016),and the integrated propensity score technique by Sant’Anna,et al.(2020).Simulations are conducted to illustrate the finite sample performance of both the average treatment effect and quantile treatment effect estimators based on different weighting methods.Simulation results show that in general,the covariate balance weighting methods can outperform the conventional maximum likelihood estimation method while the performance of the four covariate balance weighting methods varies with the data generating processes.Finally,the four covariate balance weighting methods are applied to estimate the treatment effects of the college graduate on personal annual income.
文摘Rock-fill dykes are often damaged caused by rapid flow currents in a mountainriver. Based on the relationship between the rock size on cover layer and its incipient velocity,it is found that rock weight is directly proportional to the 6th-9th power of incipient velocity,and 50% increase of the velocity may result in about 40 times increase of the rock weight.Therefore, it is inappropriate to improve the stability of rock-fill dykes by simply increasing therock weight. Some new measures should be used to reach this purpose.
