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A Cautionary Note on Using Industry Affiliation to Predict Income

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  • Jörn-Steffen Pischke
  • Hannes Schwandt

Abstract

Many literatures investigate the causal impact of income on economic outcomes, for example in the context of intergenerational transmission or well-being and health. Some studies have proposed to use employer wage differentials and in particular industry affiliation as an instrument for income. We demonstrate that industry affiliation is correlated with fixed individual characteristics, specifically parents' education and own height, conditional on the covariates typically controlled for in these studies. These results suggest that there is selection into industries based on unobservables. As a result the exclusion restriction in many IV studies of this type is likely violated.

Suggested Citation

  • Jörn-Steffen Pischke & Hannes Schwandt, 2012. "A Cautionary Note on Using Industry Affiliation to Predict Income," NBER Working Papers 18384, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:18384
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    Citations

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    Cited by:

    1. Kaiser, Caspar, 2018. "People do not adapt to income changes: A re-evaluation of the dynamic effects of (reference) income on life satisfaction with GSOEP and UKHLS data," MPRA Paper 89867, University Library of Munich, Germany.
    2. Eleftherios Giovanis, 2019. "Worthy to lose some money for better air quality: applications of Bayesian networks on the causal effect of income and air pollution on life satisfaction in Switzerland," Empirical Economics, Springer, vol. 57(5), pages 1579-1611, November.
    3. Kaiser, Caspar, 2020. "People do not adapt. New analyses of the dynamic effects of own and reference income on life satisfaction," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 494-513.
    4. Abel Brodeur & Sarah Flèche, 2019. "Neighbors' Income, Public Goods, and Well‐Being," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 65(2), pages 217-238, June.
    5. Ambrey, Christopher L. & Fleming, Christopher M., 2014. "The causal effect of income on life satisfaction and the implications for valuing non-market goods," Economics Letters, Elsevier, vol. 123(2), pages 131-134.
    6. Levinson, Arik, 2012. "Valuing public goods using happiness data: The case of air quality," Journal of Public Economics, Elsevier, vol. 96(9-10), pages 869-880.
    7. NI Bin & KATO Hayato & LIU Yang, 2020. "Does It Matter Where You Invest? The Impact of FDI on Domestic Job Creation and Destruction," Discussion papers 20008, Research Institute of Economy, Trade and Industry (RIETI).
    8. Clingingsmith, David, 2016. "Negative Emotions, Income, and Welfare: Casual Estimates from the PSID," SocArXiv fae4x, Center for Open Science.
    9. Nattavudh Powdthavee & Warn N. Lekfuangfu & Mark Wooden, 2013. "The Marginal Income Effect of Education on Happiness: Estimating the Direct and Indirect Effects of Compulsory Schooling on Well-Being in Australia," Melbourne Institute Working Paper Series wp2013n16, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    10. Ambrey, Christopher L. & Fleming, Christopher M. & Chan, Andrew Yiu-Chung, 2014. "Estimating the cost of air pollution in South East Queensland: An application of the life satisfaction non-market valuation approach," Ecological Economics, Elsevier, vol. 97(C), pages 172-181.
    11. Clingingsmith, David, 2016. "Negative emotions, income, and welfare: Causal estimates from the PSID," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 1-19.
    12. Ambrey, Christopher L. & Chan, Andrew Yiu-Chung & Fleming, Christopher M., 2013. "Estimating the cost of air pollution in South East Queensland: An application of the life satisfaction non-market valuation approach," 2013 Conference (57th), February 5-8, 2013, Sydney, Australia 152133, Australian Agricultural and Resource Economics Society.
    13. Matthew Manning & Christopher M. Fleming & Christopher L. Ambrey, 2016. "Life Satisfaction and Individual Willingness to Pay for Crime Reduction," Regional Studies, Taylor & Francis Journals, vol. 50(12), pages 2024-2039, December.
    14. Sebastian Himmler & Jannis Stöckel & Job van Exel & Werner B. F. Brouwer, 2021. "The value of health—Empirical issues when estimating the monetary value of a quality‐adjusted life year based on well‐being data," Health Economics, John Wiley & Sons, Ltd., vol. 30(8), pages 1849-1870, August.
    15. Hannes Schwandt, 2018. "Wealth Shocks and Health Outcomes: Evidence from Stock Market Fluctuations," American Economic Journal: Applied Economics, American Economic Association, vol. 10(4), pages 349-377, October.
    16. repec:cep:sticar:case/96 is not listed on IDEAS
    17. Clingingsmith, David, 2017. "Negative Emotions, Income, and Welfare: Causal Estimates from the PSID," SocArXiv q2mxt, Center for Open Science.
    18. Eleftherios Giovanis & Oznur Ozdamar & Sahizer Samuk, 2021. "Health status and willingness-to-pay estimates for the benefits of improved recycling rates: evidence from Great Britain," SN Business & Economics, Springer, vol. 1(1), pages 1-28, January.
    19. Sebastian Himmler & Jannis Stöckel & Job van Exel & Werner Brouwer, 2020. "The Value of Health - Empirical Issues when Estimating the Monetary Value of a QALY Based on Well-Being," SOEPpapers on Multidisciplinary Panel Data Research 1101, DIW Berlin, The German Socio-Economic Panel (SOEP).
    20. Vendrik, Maarten C.M., 2013. "Adaptation, anticipation and social interaction in happiness: An integrated error-correction approach," Journal of Public Economics, Elsevier, vol. 105(C), pages 131-149.

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    More about this item

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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