生产率增长是宏观经济研究的一个重要议题。采用经典估计贝叶斯平均(bACE)方法,引入模型的不确定性,在上万次回归的基础上,对众多影响生产率的解释变量按其重要性进行分类和排序。研究发现:在事先列出的16个可能的解释变量中,fdI进入程度、进口依存度、出口依存度、专科以上学历人数占从业人数的比率、相邻地区的生产率(空间邻居变量)以及市场化程度对TfP增长的解释能力最强,并且都具有良好的稳健性。fdI金额、进口额、出口额以及前一期研发投入等四个变量对TfP增长也有一定的解释能力。但各变量在我国东、中、西部地区的影响力存在显著差异。The growth of TFP is an important issue of macro-economics.By using Bayesian Averaging of Classical Estimates(BACE)approach,this paper introduces model uncertainty to classify and order all potential explanatory variables of TFP according to their explanatory ability after thousands of regression.The main conclusions are as follows: of 16 ex-given potential explanatory variables,degree of FDI entry,importation dependence,exportation dependence,human capital level,neighbor region's TFP,the mature degree of market are the most important and robust variables.Another four variables-volume of FDI,import volume,export volume,and former R&D investment also have some explanatory ability.But,their effects on east,middle and west China are different.教育部人文社科基金资助项目“劳动力供给内生化条件下的财政政策与经济增长:理论模型、实证检验与政策模拟”(10YJC790402);博士后科学基金资助项目“我国技术创新与技术进步的推动因素、实现路径与政策选择”(20110490851
