主管:中国科学院
主办:中国优选法统筹法与经济数学研究会
   中国科学院科技战略咨询研究院

中国管理科学 ›› 2023, Vol. 31 ›› Issue (3): 228-237.doi: 10.16381/j.cnki.issn1003-207x.2022.0446

• 论文 • 上一篇    

组群结构视角下异质性消费者的识别及成因分析

任燕燕, 李东霖   

  1. 山东大学经济学院,山东 济南250100
  • 收稿日期:2022-03-04 修回日期:2022-07-03 发布日期:2023-04-03
  • 通讯作者: 李东霖(1996-),男(汉族),辽宁大连人,山东大学经济学院,博士研究生,研究方向:计量经济学、复杂网络,Email:donglinli1996@163.com. E-mail:donglinli1996@163.com
  • 基金资助:
    国家社会科学基金资助项目(21BTJ046);山东省自然科学基金资助项目(ZR2020MG035);山东省社会科学基金资助项目(18CZKJ19)

Identification and Cause Analysis of Heterogeneous Consumers from the Perspective of Group Structure

REN Yan-yan, LI Dong-lin   

  1. School of Economics, Shandong University, Jinan 250100, China
  • Received:2022-03-04 Revised:2022-07-03 Published:2023-04-03
  • Contact: 李东霖 E-mail:donglinli1996@163.com

摘要: 本文依据两期消费决策模型,利用CFPS家庭数据构建具有组群结构的面板结构模型,基于C-lasso方法根据数据自身特征,引入信息准则验证组群结构的存在,并确定组群数量和调整参数,从而实现对异质性消费者的自动识别。与传统方法和机器学习中的聚类方法相比,本文提出的方法的信息准则值较小,说明对异质性消费者的识别具有更高的精确度。实证结果表明,我国消费者可以划分为两个组群,而不同组群消费者的暂时性收入变化和家庭资产对消费的影响存在差异,家庭资产、受教育水平和城乡类别在不同组群消费者之间亦存在显著差异,这也验证了上述识别方法的科学性和客观性。此外,研究发现,家庭资产不同的流动性配置是导致消费者异质性的原因。

关键词: 面板结构模型;C-lasso方法;组群结构;异质性消费者;家庭资产流动性

Abstract: The identification of heterogeneous consumers provides a reference for the formulation and evaluation of macroeconomic policies aimed at releasing the consumption potential of residents. However, in the current related studies, there is no objective automatic identification of heterogeneous consumers through the characteristics of data. In this paper, based on the two-stage consumption decision model, a panel structure model with group structure is constructed using the micro data form China Family Panel Studies (CFPS). Based on the C-Lasso method, information criterion is introduced to verify the existence of group structure, and the number of groups and tuning parameters are determined, so as to realize the automatic identification of heterogeneous consumers according to the characteristics of data. The empirical results show that: (1) Chinese consumers can be divided into two groups. Compared with the traditional method and the clustering method in machine learning, the information criterion value of the proposed method is smaller, indicating a higher accuracy in identifying heterogeneous consumers. (2) There are differences in the effects of temporary income changes and household assets on consumption among different groups of consumers, shows that the identification method is scientific and objective. For the group with higher household assets, temporary income change and illiquid assets significantly promote consumption, but liquid assets to inhibited consumption; The temporary income changes and illiquidity assets of the group with lower household assets significantly inhibited consumption, while liquid assets promoted consumption. (3) There are significant differences in household assets, education level and urban and rural categories among different groups of consumers. The group with higher household assets has longer years of education and has a higher proportion of urban household registration. The group with lower household assets has shorter schooling years and had a higher proportion of rural household registration. (4) Different liquidityof household assets allocation may be the cause of consumer heterogeneity. A new idea and method for automatic identification of heterogeneous consumer group structure is proposed, which provides a reference for the formulation and evaluation of macroeconomic policies to release the consumption potential of different types of consumers.

Key words: panelstructuremodel; C-lasso; groupstructures; heterogeneousconsumers; householdasset liquidity

中图分类号: