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Physical activity, leisure-time, cognition and academic grades: Connections and causal effects in Chinese students

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  • Guan, Jing
  • Tena, J.D.

Abstract

Academic achievement and positive leisure activities are traditionally considered significant determinants of economic growth and human capital accumulation. This paper estimates the impact of physical activity on academic outcome and time allocation to 25 different types of leisure activity by Chinese adolescents. We use structural equation models (SEM) to explore the channels of this transmission. Our results suggest that physical exercise not only exerts a positive direct effect on academic outcome but also increases (decreases) students' time devoted to activities that are positively (negatively) correlated with academic outcome. All the effects are statistically significant but modest at the individual level. Our findings are robust to different exercise frequencies and academic outcome indicators based on students' self-assessment, academic scores, and cognitive tests.

Suggested Citation

  • Guan, Jing & Tena, J.D., 2022. "Physical activity, leisure-time, cognition and academic grades: Connections and causal effects in Chinese students," Journal of Asian Economics, Elsevier, vol. 78(C).
    • Handle: RePEc:eee:asieco:v:78:y:2022:i:c:s1049007821001512
    DOI: 10.1016/j.asieco.2021.101423
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    More about this item

    Keywords

    Structural equation models; Leisure-time activities; Academic performance; Physical; Activity; Instrumental variables;
    All these keywords.

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • Z20 - Other Special Topics - - Sports Economics - - - General
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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