Abstract: At national level, using gross expenditure on R&D (GERD) and researchers in full-time equivalents (RFTE) as S&T (scientific and technical) input, with high cited papers and triadic patents as S&T output respectively, it is revealed that C-D production function, CES production function and VES production function show strong correlations between S&T input and paper output, but show relatively weak explanatory ability to the data variation of S&T input and patent output. Based on the analysis of output elasticity and returns to scale, it is pointed out that neither excess input of GERD nor that of RFTE is conducive to increasing paper output or patent output and that model select also plays an important role. For improving the performance of scale, it is suggested to adjust dynamically S&T input referring to the equation φEGERD+ψERFTE=1 on the premise of grasping the specific relationship between paper output and patent output.

摘要： 在国家层面以R&D支出和科研人员全时当量代表科技投入，分别以高被引论文和三方专利代表科技产出，实证研究结果表明C-D、CES和VES生产函数均能较好地揭示科技投入与论文产出的关联，而对科技投入与专利产出数据的解释能力相对较弱。在分析要素产出弹性EGERD、ERFTE与规模报酬m的基础上，指出R&D经费投入过量或科研人员投入过量均不利于提高论文产出或专利产出，同时模型选择也至关重要。建议在把握论文产出与专利产出具体关系的前提下，参照等式φEGERD+ψERFTE=1动态调整科技投入量从而提高规模绩效。