IDEAS home Printed from https://ideas.repec.org/a/wly/canjec/v46y2013i4p1537-1570.html
   My bibliography  Save this article

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

Author

Listed:
  • 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 owner‐occupied 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 over‐time 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. Les auteurs considèrent deux problèmes économétriques dans la mesure de la pauvreté, tous deux reliés à l'imputation du loyer. D'abord, on prend en compte les différences de qualité liées au choix entre logement occupé par son propriétaire et logement locatif. La correction accroît le niveau de consommation des ménages de 5% par rapport aux estimations non‐corrigées, et diminue les taux de pauvreté estimés de manière dramatique. Ensuite, on suggère que l'erreur de mesure introduite par l'imputation soit corrigée en dérivant une distribution de consommation plutôt qu'un niveau de consommation pour chaque ménage. Cette correction augmente la pauvreté estimée un peu. Les auteurs utilisent leurs méthodes pour mesurer la pauvreté de consommation au Canada, et découvrent que la stratégie d'imputation utilisée influence les patterns observés. Par exemple, la pauvreté mesurée chez les aînés diminue à peine quand on utilise leurs méthodes, contrairement à la diminution de presque 6% que proposent les méthodes traditionnelles. Dans leur évaluation de l’évolution de la pauvreté de consommation dans le temps, ils découvrent qu'on a fait des progrès substantiels pour ce qui est de la pauvreté en général et de la pauvreté des enfants, mais que la pauvreté chez les aînés n'a à peu près pas changé.

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/Revue canadienne d'économique, John Wiley & Sons, vol. 46(4), pages 1537-1570, November.
  • Handle: RePEc:wly:canjec:v:46:y:2013:i:4:p:1537-1570
    DOI: 10.1111/caje.12054
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/caje.12054
    Download Restriction: no

    File URL: https://libkey.io/10.1111/caje.12054?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Blundell, Richard & Robin, Jean Marc, 1999. "Estimation in Large and Disaggregated Demand Systems: An Estimator for Conditionally Linear Systems," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(3), pages 209-232, May-June.
    2. Matthew Brzozowski & Thomas F. Crossley, 2011. "Viewpoint: Measuring the well‐being of the poor with income or consumption: a Canadian perspective," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 44(1), pages 88-106, February.
    3. Browning, Martin & Meghir, Costas, 1991. "The Effects of Male and Female Labor Supply on Commodity Demands," Econometrica, Econometric Society, vol. 59(4), pages 925-951, July.
    4. Arthur Lewbel & Krishna Pendakur, 2009. "Tricks with Hicks: The EASI Demand System," American Economic Review, American Economic Association, vol. 99(3), pages 827-863, June.
    5. Jean-Marc Robin, 1999. "[Econometrics of systems of demand] [Econométrie des systèmes de demande]," Post-Print hal-02688894, HAL.
    6. Bruce D. Meyer & James X. Sullivan, 2011. "Viewpoint: Further results on measuring the well-being of the poor using income and consumption," Canadian Journal of Economics, Canadian Economics Association, vol. 44(1), pages 52-87, February.
    7. Kevin Milligan, 2008. "The Evolution of Elderly Poverty in Canada," Canadian Public Policy, University of Toronto Press, vol. 34(s1), pages 79-94, November.
    8. Krishna Pendakur, 2001. "Consumption Poverty in Canada, 1969 to 1998," Canadian Public Policy, University of Toronto Press, vol. 27(2), pages 125-149, June.
    9. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Krishna Pendakur, 2018. "Welfare analysis when people are different," Canadian Journal of Economics, Canadian Economics Association, vol. 51(2), pages 321-360, May.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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).
    8. 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.
    9. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mickaël Beaud & Thierry Blayac & Patrice Bougette & Soufiane Khoudmi & Philippe Mahenc & Stéphane Mussard, 2013. "Estimation du coût d'opportunité des fonds publics pour l'économie française," Working Papers halshs-01077141, HAL.
    2. Laura Blow & Valérie Lechene & Peter Levell, 2014. "Using the CE to Model Household Demand," NBER Chapters, in: Improving the Measurement of Consumer Expenditures, pages 141-178, National Bureau of Economic Research, Inc.
    3. Knobel, Alexander (Кнобель, Александр) & Chentsov, Alexander (Ченцов, Александр), 2018. "The Impact of Exchange Rates and Their Volatility on Russia's Foreign Trade, Taking into Account its Membership in EAEU [Влияние Обменных Курсов И Их Волатильности На Внешнюю Торговлю России С Учет," Working Papers 061824, Russian Presidential Academy of National Economy and Public Administration.
    4. Sam Norris & Krishna Pendakur, 2015. "Consumption inequality in Canada, 1997 to 2009," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 48(2), pages 773-792, May.
    5. Xavier Labandeira & José M. Labeaga & Miguel Rodríguez, 2006. "A Residential Energy Demand System for Spain," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 87-112.
    6. Andr'es Ram'irez-Hassan & Alejandro L'opez-Vera, 2021. "Semi-parametric estimation of the EASI model: Welfare implications of taxes identifying clusters due to unobserved preference heterogeneity," Papers 2109.07646, arXiv.org.
    7. Cherchye, Laurens & De Rock, Bram & Vermeulen, Frederic, 2012. "Economic well-being and poverty among the elderly: An analysis based on a collective consumption model," European Economic Review, Elsevier, vol. 56(6), pages 985-1000.
    8. Mauro Vigani & Hasan Dudu & Gloria Solano-Hermosilla, 2019. "Estimation of food demand parameters in Ethiopia: A Quadratic Almost Ideal Demand System (QUAIDS) approach," JRC Research Reports JRC117125, Joint Research Centre.
    9. Beznoska, Martin, 2019. "Do couples pool their income? Evidence from demand system estimation for Germany," Discussion Papers 2019/3, Free University Berlin, School of Business & Economics.
    10. Haag, Berthold R. & Hoderlein, Stefan & Pendakur, Krishna, 2009. "Testing and imposing Slutsky symmetry in nonparametric demand systems," Journal of Econometrics, Elsevier, vol. 153(1), pages 33-50, November.
    11. Belan, Pascal & Gauthier, Stéphane & Laroque, Guy, 2008. "Optimal grouping of commodities for indirect taxation," Journal of Public Economics, Elsevier, vol. 92(7), pages 1738-1750, July.
    12. Rodrigo Lluberas, 2018. "Life‐Cycle Expenditure and Retirees’ Cost of Living," Fiscal Studies, John Wiley & Sons, vol. 39(3), pages 385-415, September.
    13. Pothen, Frank & Tovar Reaños, Miguel Angel, 2018. "The Distribution of Material Footprints in Germany," Ecological Economics, Elsevier, vol. 153(C), pages 237-251.
    14. Diego Comin & Danial Lashkari & Martí Mestieri, 2021. "Structural Change With Long‐Run Income and Price Effects," Econometrica, Econometric Society, vol. 89(1), pages 311-374, January.
    15. Francesca Parodi, 2023. "Taxation of Consumption and Labor Income: A Quantitative Approach," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(4), pages 177-216, October.
    16. Hanna Lindström, 2022. "The Swedish consumer market for organic and conventional milk: A demand system analysis," Agribusiness, John Wiley & Sons, Ltd., vol. 38(3), pages 505-532, July.
    17. Lindström, Hanna, 2021. "The Swedish consumer market for organic and conventional milk: A demand system analysis," Umeå Economic Studies 998, Umeå University, Department of Economics.
    18. Caillavet, France & Fadhuile, Adelaide & Nichèle, Véronique, 2014. "Taxing animal foods for sustainability: environmental, nutritional and social perspectives in France," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182863, European Association of Agricultural Economists.
    19. Lenis Saweda O. Liverpool‐Tasie & Awa Sanou & Thomas Reardon & Ben Belton, 2021. "Demand for Imported versus Domestic Fish in Nigeria," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 782-804, September.
    20. Zsombor Cseres-Gergely & Gyorgy Molnar & Tibor Szabo, 2017. "Expenditure responses, policy interventions and heterogeneous welfare effects in Hungary during the 2000s," CERS-IE WORKING PAPERS 1704, Institute of Economics, Centre for Economic and Regional Studies.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:canjec:v:46:y:2013:i:4:p:1537-1570. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1540-5982 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.