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Imputing rent in consumption measures, with an application to consumption poverty in Canada, 1997-2009

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  • Sam Norris
  • Krishna Pendakur

Abstract

We consider two econometric problems in the measurement of poverty, both relating to rent imputation. First, we account for quality differences correlated with selection into owneroccupied versus rental tenure. This correction increases estimated household consumption by 5% over uncorrected estimates and decreases estimated poverty rates quite dramatically. Second, we propose that measurement error induced by the imputation be corrected by imputing a consumption distribution, rather than a consumption level, for each household. This correction increases estimated poverty rates slightly. We use our methods to measure consumption poverty in Canada, and find that the imputation strategy used influences the patterns observed. For example, measured poverty among the elderly barely declines when one uses our methods, in contrast to the almost 6 percentage point reduction we find using traditional methods. In our assessment of the overtime evolution of consumption poverty, we find that substantial progress has been made on overall poverty and on child poverty, but that poverty among the elderly hardly changed.

Suggested Citation

  • Sam Norris & Krishna Pendakur, 2013. "Imputing rent in consumption measures, with an application to consumption poverty in Canada, 1997-2009," Canadian Journal of Economics, Canadian Economics Association, vol. 46(4), pages 1537-1570, November.
  • Handle: RePEc:cje:issued:v:46:y:2013:i:4:p:1537-1570
    DOI: 10.1111/caje.12054
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    Cited by:

    1. Rahul Deb & Yuichi Kitamura & John K H Quah & Jörg Stoye, 2023. "Revealed Price Preference: Theory and Empirical Analysis," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(2), pages 707-743.
    2. Chen, Feifei & Qiu, Huanguang & Zhang, Jun, 2022. "Energy consumption and income of the poor in rural China: Inference for poverty measures," Energy Policy, Elsevier, vol. 163(C).
    3. Serena Yu, 2016. "Retiree Welfare and the 2009 Pension Increase: Impacts from an Australian Experiment," The Economic Record, The Economic Society of Australia, vol. 92(296), pages 67-80, March.
    4. Sam Norris & Krishna Pendakur, 2015. "Consumption inequality in Canada, 1997 to 2009," Canadian Journal of Economics, Canadian Economics Association, vol. 48(2), pages 773-792, May.
    5. Krishna Pendakur, 2018. "Welfare analysis when people are different," Canadian Journal of Economics, Canadian Economics Association, vol. 51(2), pages 321-360, May.
    6. Lidia Ceriani & Sergio Olivieri & Marco Ranzani, 2023. "Housing, imputed rent, and household welfare," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 21(1), pages 131-168, March.
    7. Yanfeng Chen & Qingjie Xia & Xiaolin Wang, 2021. "Consumption and Income Poverty in Rural China: 1995–2018," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 29(4), pages 63-88, July.
    8. Carlos Felipe Balcázar & Lidia Ceriani & Sergio Olivieri & Marco Ranzani, 2017. "Rent‐Imputation for Welfare Measurement: A Review of Methodologies and Empirical Findings," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(4), pages 881-898, December.
    9. Li, Lianyou & Song, Ze & Ma, Chao, 2015. "Engel curves and price elasticity in urban Chinese Households," Economic Modelling, Elsevier, vol. 44(C), pages 236-242.

    More about this item

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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