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Nonresponse Imputations and Related Measurement Issues in the CPI for Shelter

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Shelter is the largest component of US consumer price index (CPI) inflation; therefore, the accuracy of shelter inflation is critical for the accuracy of overall CPI inflation. Nonresponse in the BLS Housing Survey, which underpins the measurement of CPI shelter inflation, has increased since 2000 and now represents roughly 40 percent of total observations. Missing rent data are currently imputed using a class-mean approach based on rent tier, potentially resulting in biased imputations, as we find that nonresponse is correlated with factors beyond rent tier. We study alternative simple imputation methods based on variables correlated with both nonresponse and rent growth, including structure type and tenure length. A simple model demonstrates that alternative methods could yield sharply different index biases. However, in practice, we find that these alternative methods yield similar shelter inflation indexes, suggesting that any index bias may be modest.

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  • Lara Loewenstein & Hugh Montag & Randal J. Verbrugge, 2026. "Nonresponse Imputations and Related Measurement Issues in the CPI for Shelter," Working Papers 26-13, Federal Reserve Bank of Cleveland.
    • Handle: RePEc:fip:fedcwq:103314
    DOI: 10.26509/frbc-wp-202613
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    1. Randal Verbrugge & Alan Dorfman & William Johnson & Fred Marsh III & Robert Poole & Owen Shoemaker, 2017. "Determinants of Differential Rent Changes: Mean Reversion versus the Usual Suspects," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 45(3), pages 591-627, July.
    2. Brian Adams & Lara Loewenstein & Hugh Montag & Randal Verbrugge, 2024. "Disentangling Rent Index Differences: Data, Methods, and Scope," American Economic Review: Insights, American Economic Association, vol. 6(2), pages 230-245, June.
    3. Adams, Brian & Verbrugge, Randal, 2025. "Location, location, structure type: Rent divergence within neighborhoods," Journal of Housing Economics, Elsevier, vol. 69(C).
    4. Theodore M. Crone & Leonard I. Nakamura & Richard Voith, 2010. "Rents Have Been Rising, Not Falling, in the Postwar Period," The Review of Economics and Statistics, MIT Press, vol. 92(3), pages 628-642, August.
    5. Randal Verbrugge & Saeed Zaman, 2024. "Post‐COVID inflation dynamics: Higher for longer," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 871-893, July.
    6. Richard Ashley & Randal Verbrugge, 2025. "The intermittent Phillips curve: Finding a stable (but persistence‐dependent) Phillips curve model specification," Economic Inquiry, Western Economic Association International, vol. 63(3), pages 926-944, July.
    7. Tim Erickson & Ariel Pakes, 2011. "An Experimental Component Index for the CPI: From Annual Computer Data to Monthly Data on Other Goods," American Economic Review, American Economic Association, vol. 101(5), pages 1707-1738, August.
    8. Charles Hokayem & Christopher Bollinger & James P. Ziliak, 2015. "The Role of CPS Nonresponse in the Measurement of Poverty," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 935-945, September.
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    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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