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

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  • Serneels,Pieter Maria
  • Beegle,Kathleen G.
  • Dillon,Andrew S.

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, into wage employment and in terms of completed schooling. There has been much less exploration of 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. The 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 Maria & Beegle,Kathleen G. & Dillon,Andrew S., 2016. "Do returns to education depend on how and who you ask ?," Policy Research Working Paper Series 7747, The World Bank.
    • Handle: RePEc:wbk:wbrwps:7747
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    1. is not listed on IDEAS
    2. Ambler, Kate & Herskowitz, Sylvan & Maredia, Mywish K., 2021. "Are we done yet? Response fatigue and rural livelihoods," Journal of Development Economics, Elsevier, vol. 153(C).
    3. Talip Kilic & Goedele Van den & Gayatri Koolwal & Heather Moylan, 2023. "Are You Being Asked? Impacts of Respondent Selection on Measuring Employment in Malawi," Journal of African Economies, Centre for the Study of African Economies, vol. 32(5), pages 495-522.
    4. 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.
    5. repec:lic:licosd:41819 is not listed on IDEAS
    6. Ambler, Kate & Herskowitz, Sylvan & Maredia, Mywish K., "undated". "Rural Labor and Long Recall Loss," Staff Paper Series 316616, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    7. 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).
    8. 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.
    9. Koolwal, Gayatri B., 2021. "Improving the measurement of rural women's employment: Global momentum and survey priorities," World Development, Elsevier, vol. 147(C).
    10. 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.
    11. 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.
    12. Fitzpatrick, Anne, 2023. "Which price is right? A comparison of three standard approaches to measuring prices," Journal of Development Economics, Elsevier, vol. 163(C).
    13. Josefine Durazo & Valentina Costa & Amparo Palacios-Lopez & Isis Gaddis, 2021. "Employment and Own-Use Production in Household Surveys," World Bank Publications - Reports 37310, The World Bank Group.
    14. Masselus, Lise & Fiala, Nathan, 2024. "Whom to ask? Testing respondent effects in household surveys," Journal of Development Economics, Elsevier, vol. 168(C).
    15. 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.
    16. 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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    Keywords

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    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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