数据要素驱动乡村振兴的机制与测度——基于青海的实证

Mechanism and Measurement of Rural Revitalization Driven by Data Factors—An Empirical Study Based on Qinghai Province

摘要: 本研究旨在探讨数据要素驱动西部民族地区(以青海省为例)乡村振兴的机制与测度。文章首先基于“产业兴旺、生态宜居、乡风文明、治理有效、生活富裕”五个维度构建了包含20项指标的乡村振兴评价体系。研究采用2004年至2023年的青海省时间序列数据，运用层次分析法(AHP)和熵权法相结合的方式测度乡村振兴水平。随后，通过主成分分析法(PCA)合成数字要素指标，并建立多元线性回归模型(逐步回归)，实证分析数据要素及其他控制变量对乡村振兴的影响。研究结果显示，数据要素、人均GDP增长率、财政农林支出等对乡村振兴有显著正向影响，而城镇登记失业率则呈现负向影响。最后，文章据此提出了加强数字基础设施建设、优化财政支出结构等政策建议。

Abstract: This study aims to explore the mechanism and measurement of rural revitalization driven by data factors in western ethnic minority regions (taking Qinghai Province as an example). Firstly, the paper constructs a rural revitalization evaluation system including 20 indicators based on the five dimensions of “prosperous industry, livable ecology, civilized rural customs, effective governance, and affluent life”. Using time series data of Qinghai Province from 2004 to 2023, the study measures the level of rural revitalization by combining the Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM). Subsequently, the Principal Component Analysis (PCA) is used to synthesize digital factor indicators, and a multiple linear regression model (stepwise regression) is established. Combined with heterogeneity analysis, threshold effect analysis and endogeneity treatment, the impact of data factors and other control variables on rural revitalization is empirically tested. The results show that data factors, per capita GDP growth rate, and fiscal expenditure on agriculture and forestry have significant positive impacts on rural revitalization, while the urban registered unemployment rate has a negative impact. Finally, the paper puts forward policy suggestions such as strengthening the construction of digital infrastructure and optimizing the structure of fiscal expenditure.