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Lost in translation: What do Engel curves tell us about the cost of living?

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  • Ingvild Almås
  • Timothy K.M. Beatty
  • Thomas F. Crossley
Abstract
The Hamilton method for estimating CPI bias is simple, intuitive, and has been widely adopted. We show that the method conflates CPI bias with variation in cost of-living growth across income levels. Assuming a single price index across the income distribution is not consistent with the downward sloping Engel curves that are necessary to implement the method. We suggest an approach that disentangles genuine CPI bias from differences caused by comparing changes in the cost of living across income levels– non-homotheticity. For the period Hamilton studies, this yields substantially lower estimates of CPI bias and therefore implies lower income growth.

Suggested Citation

  • Ingvild Almås & Timothy K.M. Beatty & Thomas F. Crossley, 2019. "Lost in translation: What do Engel curves tell us about the cost of living?," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-09, Economic Statistics Centre of Excellence (ESCoE).
    • Handle: RePEc:nsr:escoed:escoe-dp-2019-09
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    Cited by:

    1. David Atkin & Benjamin Faber & Thibault Fally & Marco Gonzalez-Navarro, 2024. "Measuring Welfare and Inequality with Incomplete Price Information," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 139(1), pages 419-475.
    2. Ingvild Almås & Timothy K.M. Beatty & Thomas F. Crossley, 2018. "Lost in Translation: What do Engel Curves Tell us about the Cost of Living?," CESifo Working Paper Series 6886, CESifo.
    3. Andrew Dabalen & Isis Gaddis & Nga Thi Viet Nguyen, 2020. "CPI Bias and its Implications for Poverty Reduction in Africa," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(1), pages 13-44, March.
    4. Marcel Fafchamps & Aditya Shrinivas, 2022. "Risk Pooling and Precautionary Saving in Village Economies," NBER Working Papers 30128, National Bureau of Economic Research, Inc.
    5. Emi Nakamura & Jón Steinsson & Miao Liu, 2016. "Are Chinese Growth and Inflation Too Smooth? Evidence from Engel Curves," American Economic Journal: Macroeconomics, American Economic Association, vol. 8(3), pages 113-144, July.
    6. Ligon, Ethan, 2017. "Estimating household welfare from disaggregate expenditures," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt5gc4h1fm, Department of Agricultural & Resource Economics, UC Berkeley.
    7. Hartmut Egger & Simone Habermeyer, 2019. "Nonhomothetic Preferences and Rent Sharing in an Open Economy," Working Papers 184, Bavarian Graduate Program in Economics (BGPE).
    8. Chen,Xiaomeng & Mungai,Rose & Nakamura,Shohei & Pearson,Thomas Patrick & Wambile,Ayago Esmubancha & Yoshida,Nobuo, 2020. "How Useful is CPI Price Data for Spatial Price Adjustment in Poverty Measurement? : A Case from Ghana," Policy Research Working Paper Series 9388, The World Bank.
    9. Ingvild Almas & Ashild Johnsen, 2018. "The cost of a growth miracle - reassessing price and poverty trends in China," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 30, pages 239-264, October.

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    More about this item

    Keywords

    Inflation; CPI-bias; Hamilton Method; Engel Curves;
    All these keywords.

    JEL classification:

    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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