我国省际人才流动对经济增长的贡献研究

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我国省际人才集聚对经济增长的贡献是当前研究的热点问题之一。通过对跨省人才流动与经济增长的关系进行深入探讨和分析，可以更好地了解人才引进对于不同省市经济发展的影响，为制定相应的政策提供依据。本次测算旨在通过统计数据和模型分析，揭示不同人才类型、数量、流向对于我国经济增长的实质性贡献，为完善人才引进政策、促进区域经济协调发展提供科学依据。同时，通过对人才的流动、技能结构等方面的深入了解，也为人力资源的合理配置提供参考，有助于推动我国区域经济协调发展。

我国省际人才集聚对经济增长的贡献测算

贺勇，廖诺，张紫君

(广东工业大学管理学院，广东 广州510520)

摘要：构建“人才集聚-人才资本-经济增长”(T-C-E)的人才经济价值转化链，测算人才集聚对我国省际区域经济增长的贡献作用。首先计算1990-我国大陆31个省（市、自治区）的平均人才集聚度和人才资本水平；然后基于扩展柯布-道格拉斯生产函数计算我国省际区域人才资本对经济增长的贡献率，并采用聚类算法构建“人才集聚度-人才经济贡献率”矩阵进行分析。研究结果表明：我国省际区域的人才集聚水平存在较大差异，北京市人才集聚水平最高，其平均集聚度达到24.75%，青海省人才集聚度最低，其平均人才集聚度仅为1.7%；人才集聚水平不同，其区域的人才资本对经济增长的贡献存在显着差异，其中，北京等九个区域的人才资本贡献率超过35%，宁夏等八个区域的人才资本贡献率低于10%；总体而言，人才集聚水平较高的区域，其对经济增长的贡献也较高，但两者之间并不具有严格的正向关系。

关键词：人才集聚；人才资本；经济增长；经济贡献率

主要研究结论：本文构建T-C-E人才经济价值转换链，分别计算了中国31个省际区域的人才集聚度、人才资本与人才资本的经济贡献率，得到人才集聚度-人才资本贡献率矩阵进行分析，得出以下结论：

第一、我国31个省市自治区的人才集聚度水平差异较大，人才分布不均衡。从平均人才集聚度来看，北京市和上海市的人才集聚度最高，其平均集聚度分别达到24.75%和17.02%。人才集聚度最低为青海省，其平均人才集聚度仅为1.70%。

第二、省际区域的人才资本对经济增长的贡献存在显着差异。其中，北京、天津等9个区域的人才资本贡献率超过35%，这些区域人才资本对经济增长作用显着。宁夏、安徽等8个区域的人才资本贡献率则低于10%，这些区域的人才资本对经济增长的贡献作用不够凸显。17个区域的基础人力资本贡献率为负，说明这些区域的基础人力资本呈降低趋势。

第三、通过人才集聚度-人才资本贡献率矩阵分析，高人才集聚度容易产生高的经济增长贡献，中等人才集聚度可能产生高、中、低的人才资本贡献，低人才集聚度产生中、低的经济增长贡献。总体而言，人才集聚水平较高的区域，其对经济增长的贡献也较相对较高，但两者之间并不呈现严格的正向关系。

Estimation of the contribution of talent aggregation on economic growth in provincial regions of China

He Yong，Liao Nuo， Zhang Zijun

(School of Management, Guangdong University of Technology, Guangzhou 510520, Guangdong, China）

Abstract:As an important resource, talent has become a core element in economic growth. In the 30 years of China’s reform and opening up, the role of human resources in local economic growth mainly reflects its regional aggregation. For example, Beijing, Shanghai and some other provincial regions have always maintained the leading position of economic growth, mainly relying on the high level of talent aggregation. Talent resources are the essence of human resources with high-level knowledge and skill. They are the core of human resources and play a key role in promoting science and technology progress and economic growth. The key role is derived from the capital of talent resources, namely talent capital. Based on the theory of human capital and the specific practice in China, many scholars have carried out groundbreaking research on the theoretical system of talent aggregation and talent capital. They have carried out fruitful exploration on the relationship between talent aggregation and economic growth, as well as talent capital and economic growth. However, the research on talent aggregation and economic growth is not deep enough, which is only through qualitative description or correlation analysis of the time series to show the positive relationship. The research on the internal mechanism is lacking. The following issues should be solved. Why does talent aggregation have a positive effect on economic growth? What is the transmission path from talent aggregation to economic growth? In addition, the existing literature mainly focuses on the analysis of the contribution of talent aggregation on economic growth in a single region, and there lacks comprehensive comparative studies on multiple regions.

This paper takes talent capital as a bridge and constructs the "T-C-E" talent economic value conversion chain, namely "talent aggregation-talent capital-economic growth", and uses Shultz model and the extended Cobb-Douglas production function to calculate the talent aggregation, talent capital and the contribution rate to economic growth in 31 provincial regions inChina from 1990 to . The clustering algorithm is adopted to construct the matrix of talent aggregation to the contribution rate of talent capital, to further analyze the mutual relationship. The corresponding policy implications are put forward according to the research results. Regarding to the "T-C-E" talent-economy conversion chain, in the talent aggregation-talent capital (T-C) calculation model, using the Shultz model of the education year method, the product of education years and productivity is used as the weight value, and then the number of people educated in different levels and the weight value are sum-weighted to obtain the total human capital stock. In the talent capital-economic growth (C-E) calculation model, the extended C-D function of human capital is used to simultaneously calculate the economic contribution rate of talent capital and the contribution rate of basic human capital and fixed capital to economic growth. Through the above methods, the talent aggregation, talent capital and the economic contribution rate of talent capital in 31 provincial regions of China are calculated. The matrix of talent aggregation-talent capital contribution rate is analyzed and the following conclusions are put forward:

First, the level of talent aggregation in 31 provincial regions in China is quite different, and the distribution of talents is uneven. From the perspective of talent aggregation, Beijing and Shanghai have the highest level of talent aggregation, with a mean value of 24.75% and 17.02% respectively. Qinghai has the lowest level of talent aggregation, and its mean value is only 1.70%. Second, there are significant differences in the contribution of talent capital on economic growth among provincial regions. The economic contribution rates of talent capital in 9 regions, such as Beijing and Tianjin, are more than 35%. The talent capital of these regions has a significant effect on economic growth. The contribution rates of talent capital in 8 regions, such as Ningxia and Anhui, are less than 10%, and in these regions, the contribution of talent capital to economic growth is not significant enough. The economic contribution rate of basic human capital has shown negative value in 17 regions, indicating that the basic human capital in these regions is decreasing along the years. Third, through the analysis on the matrix of talent aggregation-talent capital contribution rate, it indicates that, high-level talent aggregation tends to generate high economic growth contribution, medium-level talent aggregation may produce high, medium and low economic contribution, and low-level talent aggregation will generate low economic contribution. In general, regions with higher-level talent aggregation tend to have a relatively higher contribution rate to economic growth, but there is no strict positive relationship between them.

From the above conclusions, the following policy suggestions are proposed: first, in order to improve the economic contribution rate of talent capital, every provincial region should keep enhancing the talent aggregation, increasing the intensity of talent introduction and personnel training, to enhance the stock of talent capital. The policy of prioritizing human capital investment should be implemented, and higher education and on-the-job training should be developed vigorously to improve the quality of employed people. Second, talent resources should be rationally allocated, and the efficacy of human resources should take into effect fully. Government should promote the transformation of human resources into talent capital, to increase the stock of talent capital. Under the same level of talent aggregation, there are differences in the economic contribution of talent capital. When every region pays attention to the level of talent aggregation, it is also necessary to pay attention to talent capital, especially the high-end talents. Third, each region should coordinate the proportion of talent capital and fixed capital. There is a reasonable proportion between fixed capital and human capital in economic growth. Under this proportion, the economic output could have the highest growth rate. When increasing the investment of fixed capital, all regions should increase the investment and aggregation of human capital, in order to better promote the pattern transformation of economic growth.

Keywords:talent aggregation; talent capital; economic growth; economic contribution rate

引用本文：贺勇,廖诺,张紫君.我国省际人才集聚对经济增长的贡献测算[J].科研管理,,40(11):247-256.

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