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Do Returns to Education Depend on How and Who You Ask?

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  • Serneels, Pieter

    (University of East Anglia)

  • Beegle, Kathleen

    (World Bank)

  • Dillon, Andrew

    (Michigan State University)

Abstract

Returns to education remain an important parameter of interest in economic analysis. A large literature estimates returns to education in the labor market, often carefully addressing issues such as selection, both into wage employment and in terms of completed schooling. There has been much less exploration whether estimated returns are robust to survey design. Specifically, do returns to education differ depending on how information about wage work is collected? Using a survey experiment in Tanzania, this paper investigates whether survey methods matter for estimating mincerian returns to education. Results show that estimated returns vary by questionnaire design, but not by whether the information on employment and wages is self-reported or collected by a proxy respondent (another household member). The differences due to questionnaire type are substantial varying from 6 percentage points higher returns to education for the highest educated men, to 14 percentage points higher for the least educated women, after allowing for non-linearity and endogeneity in the estimation of these parameters. These differences are of similar magnitudes as the bias in OLS estimation, which receives considerable attention in the literature. The findings underline that survey design matters for the estimation of structural parameters, and that care is needed when comparing across contexts and over time, in particular when data is generated by different surveys.

Suggested Citation

  • Serneels, Pieter & Beegle, Kathleen & Dillon, Andrew, 2016. "Do Returns to Education Depend on How and Who You Ask?," IZA Discussion Papers 10002, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp10002
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    Cited by:

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    2. Kilic,Talip & Van den Broeck,Goedele & Koolwal,Gayatri B. & Moylan,Heather G., 2020. "Are You Being Asked ? Impacts of Respondent Selection on Measuring Employment," Policy Research Working Paper Series 9152, The World Bank.
    3. Joachim De Weerdt & John Gibson & Kathleen Beegle, 2020. "What Can We Learn from Experimenting with Survey Methods?," Annual Review of Resource Economics, Annual Reviews, vol. 12(1), pages 431-447, October.
    4. Plamen Nikolov & Nusrat Jimi, 2018. "What factors drive individual misperceptions of the returns to schooling in Tanzania? Some lessons for education policy," Applied Economics, Taylor & Francis Journals, vol. 50(44), pages 4705-4723, September.

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    More about this item

    Keywords

    returns to education; survey design; field experiment; development; Africa;
    All these keywords.

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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