The biggest problem in the world as well as in Turkey is to increase efficiency of human capital, which can only be achieved by educating all people in accordance with their capacities and demands. And, the biggest pr...The biggest problem in the world as well as in Turkey is to increase efficiency of human capital, which can only be achieved by educating all people in accordance with their capacities and demands. And, the biggest problem in education is finance. In order for everybody to have education, there is a need to develop a finance system which will help overcome the financial problems faced by households or individuals. For this purpose, the participatory, payable, profitable, and potent （4p＇s） insured education system model （IESM） is developed. This paper focuses on principles of the IESM and the analyses of frequency and variance by categories （one-way ANOVA）.展开更多
This paper is concerned with inference of panel data varying-coefficient partially linear models with a one-way error structure. The model is a natural extension of the well-known panel data linear model （due to Balt...This paper is concerned with inference of panel data varying-coefficient partially linear models with a one-way error structure. The model is a natural extension of the well-known panel data linear model （due to Baltagi 1995） to the setting of semiparametric regressions. The authors propose a weighted profile least squares estimator （WPLSE） and a weighted local polynomial estimator （WLPE） for the parametric and nonparametric components, respectively. It is shown that the WPLSE is asymptotically more efficient than the usual profile least squares estimator （PLSE）, and that the WLPE is also asymptotically more efficient than the usual local polynomial estimator （LPE）. The latter is an interesting result. According to Ruckstuhl, Welsh and Carroll （2000） and Lin and Carroll （2000）, ignoring the correlation structure entirely and ＂pretending＂ that the data are really independent will result in more efficient estimators when estimating nonparametric regression with longitudinal or panel data. The result in this paper shows that this is not true when the design points of the nonparametric component have a closeness property within groups. The asymptotic properties of the proposed weighted estimators are derived. In addition, a block bootstrap test is proposed for the goodness of fit of models, which can accommodate the correlations within groups illustrate the finite sample performances of the Some simulation studies are conducted to proposed procedures.展开更多
文摘The biggest problem in the world as well as in Turkey is to increase efficiency of human capital, which can only be achieved by educating all people in accordance with their capacities and demands. And, the biggest problem in education is finance. In order for everybody to have education, there is a need to develop a finance system which will help overcome the financial problems faced by households or individuals. For this purpose, the participatory, payable, profitable, and potent （4p＇s） insured education system model （IESM） is developed. This paper focuses on principles of the IESM and the analyses of frequency and variance by categories （one-way ANOVA）.
基金supported by the Leading Academic Discipline Program211 Project for Shanghai University of Finance and Economics (the 3rd phase) (No.B803)the Shanghai Leading Academic Discipline Project (No.B210)
文摘This paper is concerned with inference of panel data varying-coefficient partially linear models with a one-way error structure. The model is a natural extension of the well-known panel data linear model （due to Baltagi 1995） to the setting of semiparametric regressions. The authors propose a weighted profile least squares estimator （WPLSE） and a weighted local polynomial estimator （WLPE） for the parametric and nonparametric components, respectively. It is shown that the WPLSE is asymptotically more efficient than the usual profile least squares estimator （PLSE）, and that the WLPE is also asymptotically more efficient than the usual local polynomial estimator （LPE）. The latter is an interesting result. According to Ruckstuhl, Welsh and Carroll （2000） and Lin and Carroll （2000）, ignoring the correlation structure entirely and ＂pretending＂ that the data are really independent will result in more efficient estimators when estimating nonparametric regression with longitudinal or panel data. The result in this paper shows that this is not true when the design points of the nonparametric component have a closeness property within groups. The asymptotic properties of the proposed weighted estimators are derived. In addition, a block bootstrap test is proposed for the goodness of fit of models, which can accommodate the correlations within groups illustrate the finite sample performances of the Some simulation studies are conducted to proposed procedures.
