本文選題：Rubin因果模型 + 工具變量　； 參考：《遼寧大學》2017年碩士論文

【摘要】：教育和就業(yè)之間的問題,一直以來都是廣大學者的研究熱點。而教育投資回報率,因其不但是勞動經濟學的核心內容,還能較好地反映教育對個人收入的因果效應,使得研究者對教育投資回報率的研究興趣長盛不衰。在我國,一方面,隨著各大高等院校的不斷擴招,大學生人數比例日益增加,導致其畢業(yè)后就業(yè)形勢嚴峻。另一方面,以培養(yǎng)專業(yè)技能型人才為辦學目的的職業(yè)技術類院校社會認可度較低,招生困難,用人單位內部對應崗位存在巨大缺口。針對這一現狀,本文以中國綜合社會調查(CGSS)數據為依據,分析了技校類畢業(yè)生和大學類畢業(yè)生的個人職業(yè)收入差異情況。在模型構建上,以Rubin因果模型為基礎,為克服解釋變量內生性將工具變量法嵌入其中。根據研究個體所接受的教育水平不同將其分為處理組和控制組,其中處理組成員為技校類畢業(yè)生,包括技校和中專;控制組成員為大學類畢業(yè)生,包括大學�？坪痛髮W本科。接著,利用Stata統(tǒng)計分析軟件得到2SLS方法下工具變量估計量的輸出結果,即處理效應。在估計時,排除了可能出現自相關、異方差及弱工具變量的情況。然后,將通過估計得到的2012年和2013年技校類畢業(yè)生與大學類畢業(yè)生個人職業(yè)收入水平差異進行對比,發(fā)現2012年技校類畢業(yè)生個人職業(yè)收入水平比大學類畢業(yè)生平均低26.4%,2013年技校類畢業(yè)生比大學類畢業(yè)生平均低17.7%,二者間的收入差距呈明顯縮小趨勢。最后就研究結果所得到的結論,分析產生這種現象的原因,并就幾個方面提出對策建議。
[Abstract]:The problem between education and employment has always been a hot topic for scholars. The return on investment in education is not only the core content of labor economics, but also reflects the causal effect of education on personal income. In our country, on the one hand, with the increasing enrollment of universities and colleges, the proportion of college students is increasing day by day, which leads to the severe employment situation after graduation. On the other hand, the vocational and technical colleges with the aim of cultivating professional and technical talents are low in social recognition, difficult in recruiting students, and there is a huge gap in the corresponding positions within the employing units. In view of this situation, based on the data of China Comprehensive Social Survey (CGSS), this paper analyzes the difference of personal occupational income between technical school graduates and university graduates. On the basis of Rubin causality model, tool variable method is embedded to overcome the endogenicity of explanatory variables. According to the educational level of the individual, they are divided into treatment group and control group, in which the members of the treatment group are technical school graduates, including technical school and technical secondary school, and the control group members are university graduates, including college students and university graduates. Then, using Stata statistical analysis software, the output of tool variable estimator under 2SLS method is obtained, that is, processing effect. In the estimation, the autocorrelation, heteroscedasticity and weak tool variables are excluded. Then, the differences in the level of personal occupational income of the 2012 and 2013 technical school graduates and those of the university graduates, which were estimated, were compared. It was found that the average income level of technical school graduates in 2012 was 26.4 lower than that of college graduates, and the average income level of technical school graduates in 2013 was 17.7 lower than that of college graduates. Finally, based on the conclusions of the research, the causes of this phenomenon are analyzed, and some countermeasures are put forward.
【學位授予單位】：遼寧大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F124.7

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本文編號：2011560