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Good Grades for Hard Work? A Lab-in-the-Field Study of Effort and Educational Inequality

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Abstract

Despite its importance for status attainment and meritocracy, measuring effort remains elusive, often relying on indirect proxies or unreliable self-reports. This study examines how objective (cognitive effort, CogEff) and subjective (teacher-perceived effort, TpEff) measures of student effort contribute to educational inequality. We examine the predictive capacity of effort for educational performance and test the mediating and moderating roles of effort in the relationship between parental socioeconomic status (SES) and school grades. Drawing on original, representative "lab-in-the-field" data from 1,270 fifth-graders in Spain and Germany, who performed three different incentivized real-effort tasks engaging various executive functions, four key findings emerge. First, both CogEff and TpEff predict grade point average (GPA), with TpEff having a powerful effect, more predictive even than IQ or parental SES. Second, effort—especially TpEff—is unequally distributed by parental SES and explains a substantial share of the SES-based GPA gap, on par with IQ. Third, roughly half of the GPA gap by social origin remains unexplained even after accounting for academic merit (IQ + effort). Fourth, while grading returns to CogEff are independent of SES, high-SES students are significantly less penalized for low TpEff than low-SES peers. Overall, effort predicts academic success and shapes educational (in)equality. High-SES students show higher average effort and can afford to be perceived as lazy, while hardworking low-SES students can overcome disadvantage through greater returns to teacher-perceived effort. We discuss the findings' implications for student agency, educational inequality, and fair evaluations.

Suggested Citation

  • Carlos J. Gil-Hernández & Alberto Palacios-Abad & Jonas Radl, 2025. "Good Grades for Hard Work? A Lab-in-the-Field Study of Effort and Educational Inequality," Econometrics Working Papers Archive 2025_09, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  • Handle: RePEc:fir:econom:wp2025_09
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    File URL: https://labdisia.disia.unifi.it/wp_disia/2025/wp_disia_2025_09.pdf
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    JEL classification:

    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement

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