基于分位数回归的城市居民体育消费研究——以北京市第3次群众体育调查数据为例

A Research on Urban Residents' Sport Consumption Based on Quantile Regression——Based on the Third Beijing Mass Sports Survey Data

采用问卷调查法、数理统计法等,对北京市3 304名户籍居民进行整群分层随机入户调查。调查内容包括体育培训、体育信息、体育赛事、体育健身、体育器材设备、运动服装鞋帽等费用;使用一般线性回归模型(OLS)、分位数回归模型(QR)分析不同特征居民的体育消费水平现状及差异。结果显示:性别、婚姻、年龄、收入、地域、工作类型对体育消费有影响,在体育消费30%、40%、50%、60%、70%、80%、90%分位数有显著性差异。提示,相比一般线性回归,分位数回归能更精准地反映不同自变量的不同分布对因变量的影响。

Using the methods of questionnaires and mathematical statistics, the research conducted a stratified random household survey of 3 304 residents in Beijing, to investigate the costs of physical training, sport information, sports events, physical fitness, sports facilities, as well as sports shoes and clothing among the respondents. Then the general linear regression model （OLS） and quantile regression （QR） are used to analyze the status quo and the differences of sport consumption among residents with different characteristics. The results show that the gender, marriage, age, income, regions and types of work have influences on their sport consumption, with the significant differences in 30%, 40%, 50%, 60%, 70%, 80% and 90% quantiles, respectively. The results indicate that quantile regression is more accurate than general linear regression in reflecting the influence of different distribution of independent variables on dependent variables.