voprecotestВопросы экономикиVoprosy Ekonomiki0042-8736Voprosy Ekonomiki, NP10.32609/0042-8736-2020-1-127-144voprecotest-2382Research ArticleМЕТОДОЛОГИЯ ЭКОНОМИЧЕСКОГО АНАЛИЗАMETHODOLOGY OF ECONOMIC ANALYSISИзмерение доходов населения: варианты оценки смещенияMeasurement of population income: Variants of estimating biaseshttps://orcid.org/0000-0002-0994-4388ЧеркашинаТ. Ю.CherkashinaT. Yu.

Черкашина Татьяна Юрьевна, к.  соц.  н., вед. н. с. 

завкафедрой общей социологии экономического факультета

Candidate of Sociological Sciences, Senior ResearcherDepartment of Social Problems

Head of the Department “General Sociology”

touch241@yandex.ruИнститут экономики и организации промышленного производства Сибирского отделения РАН; Новосибирский национальный исследовательский государственный университетРоссияInstitute of Economics and Industrial engineering of the ­Siberian Branch of the RAS; Novosibirsk State UniversityRussian Federation20202712201901127144Copyright © Voprosy Ekonomiki, NP, 20202020Voprosy Ekonomiki, NPVoprosy Ekonomiki, NPhttps://www.vopreco.ru/jour/about/submissions#copyrightNoticehttps://www.vopreco.ru/jour/article/view/2382

Доход — один из самых явных и часто используемых показателей экономического статуса и уровня жизни. Для социологов и экономистов основными источниками данных о доходах являются обследования домохозяйств и индивидов, к которым все чаще добавляются административные данные. Сопоставление данных из разных источников или полученных в опросах с помощью разных методик позволяет оценить смещение, источники ошибок, хотя и демонстрирует отсутствие «идеальных» данных о доходах. Обзор зарубежных исследований по этой проблеме дополняется примером расчетов по данным Российского мониторинга экономического положения и здоровья населения (РМЭЗ) НИУ ВШЭ: сравнивается композиционная величина индивидуальных доходов, рассчитанная как сумма отдельных видов поступлений, и общая величина личных доходов, сообщенная респондентами. Первое измерение индивидуальных доходов оказалось более консистентным и содержательно определенным, меньше подвержено ошибке измерения, но дает более низкие значения индивидуальных доходов. Отличия суммарных личных доходов, которые сообщают респонденты, от расчетной суммы поступлений обусловлены не столько неточностью суммирования и округления, сколько «концептуальными» особенностями понимания личных доходов частью респондентов. Такие сравнения необходимы для понимания ограничений различных измерений доходов, обоснованного и рефлексируемого выбора конкретных показателей.

Income is one of the most obvious and frequently used indicators of economic status and living standards. Surveys of households and individuals are the main sources of income data for sociologists and economists. Administrative data is added to them on a growing scale. Comparison of data obtained from different sources or surveys using different methods allows us to estimate biases, sources of errors, and demonstrates the absence of “ideal” income data in general. The review of foreign studies on this problem is supplemented by an example of calculations on data from the The Russia Longitudinal Monitoring Survey — Higher School of Economics (RLMS—HSE): we compare the compositional individual income, calculated as the sum of types of income, and the total personal income reported by respondents. The first measurement of individual incomes has turned out to be more consistent and definite, less prone to measurement error, but gives lower values of individual incomes. The differences of the total personal income reported by respondents and compositional individual income are due not so much to the inaccuracy of the summation and rounding as to “conceptual” features of understanding of personal income by some respondents. Such comparisons are necessary in order to understand the limitations of various measurements of income, grounded and reflexive choice of its specific indicators.

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Improving the measurement of consumer expenditures. Chicago: University of Chicago Press, pp. 289—307. http://doi.org/10.7208/chicago/9780226194714.003.0011Bollinger C. R., Hirsch B. T. (2013). Is earnings nonresponse ignorable? Review of Economics and Statistics, Vol. 95, No. 2, pp. 407—416. https://doi.org/10.1162/ REST_a_00264Jansen W., Verhoeven W.-J., Robert P., Dessens J. (2013). The long and short of asking questions about income: A comparison using data from Hungary. Quality and Quantity, Vol. 47, No. 4, pp. 1957—1969. https://doi.org/10.1007/s11135-011-9636-5Bollinger C. R., Hirsch B. T. (2013). Is earnings nonresponse ignorable? Review of Economics and Statistics, Vol. 95, No. 2, pp. 407—416. https://doi.org/10.1162/ REST_a_00264Meyer B. D., Mok W. K. C., Sullivan J. X. (2015). Household surveys in crisis. Journal of Economic Perspectives. Vol. 29, No. 4, pp. 1—29. https://doi.org/10.1257/jep.29.4.199Davern M., Rodin H., Beebe T. J., Call K. T. (2005). 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Income, program participation, poverty, and financial vulnerability: Research and data needs. Journal of Economic and Social Measurement, Vol. 40, No. 1-4, pp. 27—68. https://doi.org/10.3233/JEM-150397Hariri J. G., Lassen D. D. (2017). Income and outcomes: Social desirability bias distorts measurements of the relationship between income and political behavior. Public Opinion Quarterly, Vol. 81, No. 2, pp. 564—576. https://doi.org/10.1093/poq/nfw044Kim C., Tamborini C. R. (2014). Response error in earnings: An analysis of the survey of income and program participation matched with administrative data. Sociological Methods & Research, Vol. 43, No. 1, pp. 39—72. https://doi.org/10.1177/0049124112460371Kim C., Tamborini C. R. (2014). Response error in earnings: An analysis of the survey of income and program participation matched with administrative data. Sociological Methods & Research, Vol. 43, No. 1, pp. 39—72. https://doi.org/10.1177/0049124112460371Kim C., Tamborini C. R. (2014). Response error in earnings: An analysis of the survey of income and program participation matched with administrative data. Sociological Methods & Research, Vol. 43, No. 1, pp. 39—72. https://doi.org/10.1177/0049124112460371Kim C., Tamborini C. R. (2014). Response error in earnings: An analysis of the survey of income and program participation matched with administrative data. Sociological Methods & Research, Vol. 43, No. 1, pp. 39—72. https://doi.org/10.1177/0049124112460371Kreiner C. T., Lassen D. D., Leth-Petersen S. (2015). Measuring the accuracy of survey responses using administrative register data: Evidence from Denmark. In: C. D. Carroll, T. F. Crossley, J. Sabelhaus (ed.). Improving the measurement of consumer expenditures. Chicago: University of Chicago Press, pp. 289—307. http://doi.org/10.7208/chicago/9780226194714.003.0011Kreiner C. T., Lassen D. D., Leth-Petersen S. (2015). Measuring the accuracy of survey responses using administrative register data: Evidence from Denmark. In: C. D. Carroll, T. F. Crossley, J. Sabelhaus (ed.). Improving the measurement of consumer expenditures. Chicago: University of Chicago Press, pp. 289—307. http://doi.org/10.7208/chicago/9780226194714.003.0011Kreiner C. T., Lassen D. D., Leth-Petersen S. (2015). Measuring the accuracy of survey responses using administrative register data: Evidence from Denmark. In: C. D. Carroll, T. F. Crossley, J. Sabelhaus (ed.). Improving the measurement of consumer expenditures. Chicago: University of Chicago Press, pp. 289—307. http://doi.org/10.7208/chicago/9780226194714.003.0011Kreiner C. T., Lassen D. D., Leth-Petersen S. (2015). Measuring the accuracy of survey responses using administrative register data: Evidence from Denmark. In: C. D. Carroll, T. F. Crossley, J. Sabelhaus (ed.). Improving the measurement of consumer expenditures. Chicago: University of Chicago Press, pp. 289—307. http://doi.org/10.7208/chicago/9780226194714.003.0011Jansen W., Verhoeven W.-J., Robert P., Dessens J. (2013). The long and short of asking questions about income: A comparison using data from Hungary. Quality and Quantity, Vol. 47, No. 4, pp. 1957—1969. https://doi.org/10.1007/s11135-011-9636-5Jansen W., Verhoeven W.-J., Robert P., Dessens J. (2013). The long and short of asking questions about income: A comparison using data from Hungary. Quality and Quantity, Vol. 47, No. 4, pp. 1957—1969. https://doi.org/10.1007/s11135-011-9636-5Jansen W., Verhoeven W.-J., Robert P., Dessens J. (2013). The long and short of asking questions about income: A comparison using data from Hungary. Quality and Quantity, Vol. 47, No. 4, pp. 1957—1969. https://doi.org/10.1007/s11135-011-9636-5Jansen W., Verhoeven W.-J., Robert P., Dessens J. (2013). The long and short of asking questions about income: A comparison using data from Hungary. Quality and Quantity, Vol. 47, No. 4, pp. 1957—1969. https://doi.org/10.1007/s11135-011-9636-5Meyer B. D., Mok W. K. C., Sullivan J. X. (2015). Household surveys in crisis. Journal of Economic Perspectives. Vol. 29, No. 4, pp. 1—29. https://doi.org/10.1257/jep.29.4.199Meyer B. D., Mok W. K. C., Sullivan J. X. (2015). Household surveys in crisis. Journal of Economic Perspectives. Vol. 29, No. 4, pp. 1—29. https://doi.org/10.1257/jep.29.4.199Meyer B. D., Mok W. K. C., Sullivan J. X. (2015). Household surveys in crisis. Journal of Economic Perspectives. Vol. 29, No. 4, pp. 1—29. https://doi.org/10.1257/jep.29.4.199Meyer B. D., Mok W. K. C., Sullivan J. X. (2015). Household surveys in crisis. Journal of Economic Perspectives. Vol. 29, No. 4, pp. 1—29. https://doi.org/10.1257/jep.29.4.199Micklewright J., Schnepf S.V. (2010). How reliable are income data collected with a single question? Journal of the Royal Statistical Society. Series A: Statistics in Society, Vol. 173, No. 2, pp. 409—429. https://doi.org/10.1111/j.1467-985X.2009.00632.xMicklewright J., Schnepf S.V. (2010). How reliable are income data collected with a single question? Journal of the Royal Statistical Society. Series A: Statistics in Society, Vol. 173, No. 2, pp. 409—429. https://doi.org/10.1111/j.1467-985X.2009.00632.xMicklewright J., Schnepf S.V. (2010). How reliable are income data collected with a single question? Journal of the Royal Statistical Society. Series A: Statistics in Society, Vol. 173, No. 2, pp. 409—429. https://doi.org/10.1111/j.1467-985X.2009.00632.xMicklewright J., Schnepf S.V. (2010). How reliable are income data collected with a single question? Journal of the Royal Statistical Society. Series A: Statistics in Society, Vol. 173, No. 2, pp. 409—429. https://doi.org/10.1111/j.1467-985X.2009.00632.xMoore J., Stinson L. L., Welniak Jr. E. J. (2000). Income measurement error in surveys. 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The authors declare that there are no conflicts of interest present.