基于PMC指数模型的科技税收激励政策量化评价——以福建省为例

Quantitative Evaluation of Science and Technology Tax Incentive Policy Based on PMC Index Model--Taking Fujian Province as an Example

以福建省为研究对象,选取改革开放以来出台的14项重点科技税收激励政策进行分析,建立PMC指数模型,包括9个一级变量(政策性质、政策重点、政策时效、政策领域、激励环节、政策工具、政策评价、政策作用客体、政策公开)和37个二级变量。使用文本挖掘的方法对福建省出台的科技税收激励政策进行深入挖掘和量化评价,通过PMC数值找到科技税收激励政策的不足之处,以期为科技税收激励政策的实施和调整提供决策支持。

Taking Fujian Province as the research object,this paper selects 14 key science and technology tax incentive policies issued since 1978,and establishes PMC index model,which includes nine first-class variables,namely,policy nature,policy focus,policy effectiveness,policy areas,incentive links,policy tools,policy evaluation,policy object and policy openness,as well as 37 secondary variables.This paper uses the method of text mining to deeply excavate and quantitatively evaluate the science and technology tax incentive policy issued by Fujian Province.Through PMC value and PMC curve chart,it finds the shortcomings of tax incentive policy,and provides decision support for the implementation and adjustment of tax incentive policy.