高校科技投入与产出动态关系及效率演进  

Dynamic Relationship Between Scientific and Technological Input and Output and Its Efficiency Evolution in Universities

作　　者：汪树坤 WANG Shu-kun(Xiamen University,Xiamen 361005,China)

机构地区：[1]厦门大学,福建厦门361005

出　　处：《黑龙江高教研究》2025年第2期54-61,共8页Heilongjiang Researches on Higher Education

摘　　要：运用面板向量自回归(PVAR)模型和超效率SBM模型,选取2007—2017年30所研究型大学和53所非研究型大学科技投入与产出的数据,使用PVAR模型分析两类大学科技投入与产出的动态关系并运用超效率SBM模型对其投入与产出效率进行测算。研究发现,研究型大学与非研究型大学的货币资本投入与产出存在正向影响,但这种影响并不具有持续性,高校科技产出主要依赖货币资本的投入,最大促进作用分别存在1年和2年的滞后期,且只在短期内显著。引入滞后期测度出的科技投入与产出效率表明,高校科技投入与产出效率整体水平较低,研究型大学明显高于非研究型大学。研究为科学认识高校科技投入与产出规律和进一步提高高校科技投入与产出效率提供新的参考视角。Using Panel Vector Autoregression(PVAR)and Super-Efficiency SBM models,this study analyzes the dynamic rela-tionship between science and technology inputs and outputs at 30 research universities and 53 non-research universities from 2007 to 2017.The study employs the PVAR model to examine these dynamics and the Super-Efficiency SBM model to evaluate input-output efficiency.Findings indicate that monetary capital inputs positively affect outputs at both types of universities,though the impact is not sustained over time.The greatest promotional effects on technological outputs occur with a lag of one and two years,respectively,and are significant only in the short term.Efficiency analysis,incorporating lagged measures of technology inputs and outputs,reveals that overall university science and technology input-output efficiency is low,with research universities performing significantly better than non-research universities.This research offers new perspectives for understanding the patterns of university science and technology in-puts and outputs and for enhancing efficiency.

关 键 词：高校科技投入与产出 PVAR模型 超效率SBM模型 动态演进 

分 类 号：G40-054[文化科学—教育学原理]