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Do returns to education depend on how and whom you ask?

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  • Serneels, Pieter
  • Beegle, Kathleen
  • Dillon, Andrew

Abstract

Returns to education remain an important parameter of interest in economic analysis. A large literature estimates these returns, often carefully addressing issues such as selection into wage employment and endogeneity in terms of completed schooling. There has been much less exploration of whether the estimates of Mincerian returns depend on how information about wage work is collected. Relying on a survey experiment in Tanzania, this paper finds that estimates of the returns to education vary by questionnaire design, but not by whether the information on employment and wages is self-reported or collected by a proxy respondent. The differences derived from questionnaire type are substantial, varying from higher returns of 5 percentage points among the most well educated men to 16 percentage points among the least well educated women. These differences are at magnitudes similar to the bias in ordinary least squares estimation, which receives considerable attention in the literature. The findings demonstrate that survey design matters in the estimation of returns to schooling and that care is needed in comparing across contexts and over time, particularly if the data are generated through different surveys.

Suggested Citation

  • Serneels, Pieter & Beegle, Kathleen & Dillon, Andrew, 2017. "Do returns to education depend on how and whom you ask?," Economics of Education Review, Elsevier, vol. 60(C), pages 5-19.
  • Handle: RePEc:eee:ecoedu:v:60:y:2017:i:c:p:5-19
    DOI: 10.1016/j.econedurev.2017.07.010
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    2. Livini Donath & Oliver Morrissey & Trudy Owens, 2021. "Does the pay period matter in estimating returns to schooling? Evidence from East Africa," Discussion Papers 2021-01, University of Nottingham, CREDIT.
    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. Nikolov, Plamen & Jimi, Nusrat & Chang, Jerray, 2020. "The Importance of Cognitive Domains and the Returns to Schooling in South Africa: Evidence from Two Labor Surveys," Labour Economics, Elsevier, vol. 65(C).
    5. 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.
    6. Koolwal, Gayatri B., 2021. "Improving the measurement of rural women's employment: Global momentum and survey priorities," World Development, Elsevier, vol. 147(C).
    7. 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.
    8. Rebecca Pietrelli & Marco d’Errico & Kate Dassesse, 2021. "Measuring household food security through surveys: Do the characteristics of the enumerators matter?," Development Policy Review, Overseas Development Institute, vol. 39(6), pages 911-925, November.
    9. Fitzpatrick, Anne, 2023. "Which price is right? A comparison of three standard approaches to measuring prices," Journal of Development Economics, Elsevier, vol. 163(C).
    10. Livini Donath & Oliver Morrissey & Trudy Owens, 2023. "Benefits of enhanced access to education in Tanzania," Development Policy Review, Overseas Development Institute, vol. 41(3), May.
    11. Fiala, Nathan & Masselus, Lise, 2022. "Whom to ask? Testing respondent effects in household surveys," Ruhr Economic Papers 935, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

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    More about this item

    Keywords

    Returns to education; Survey design; Field experiment; Development; Tanzania;
    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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