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Are Two Cheap, Noisy Measures Better Than One Expensive, Accurate One?

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  • Martin Browning
  • Thomas Crossley

Abstract

1. Survey responses are always subject to measurement error. In general surveys (and especially longitudinal surveys), there are severe constraints on the time that can be spent eliciting a less noisy response for any target variable. In this paper we consider when it may be better to consider multiple noisy measures of the target measure rather than improving the reliability of a single measure. 2. The Kotlarski result states that if the measurement errors in two measures of the same target variable are mutually independent and independent of the true value then we can recover the entire distribution of the quantity of interest, up to location. 3. We consider designing surveys to deliver measurement error with desirable properties. This shifts the emphasis from reliability (the signal to noise ratio for any given measure) to the joint properties of the multiple measures. 4. To illustrate our ideas, we consider a concrete example: the measurement of consumption inequality. A small simulation study suggests that the approach we propose has promise. The next step in this research agenda is experiments in survey data collection.
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Suggested Citation

  • Martin Browning & Thomas Crossley, 2009. "Are Two Cheap, Noisy Measures Better Than One Expensive, Accurate One?," American Economic Review, American Economic Association, vol. 99(2), pages 99-103, May.
  • Handle: RePEc:aea:aecrev:v:99:y:2009:i:2:p:99-103
    Note: DOI: 10.1257/aer.99.2.99
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    References listed on IDEAS

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    1. Martin Browning & Thomas F. Crossley & Guglielmo Weber, 2003. "Asking consumption questions in general purpose surveys," Economic Journal, Royal Economic Society, vol. 113(491), pages 540-567, November.
    2. Richard Blundell & Luigi Pistaferri & Ian Preston, 2004. "Imputing consumption in the PSID using food demand estimates from the CEX," IFS Working Papers W04/27, Institute for Fiscal Studies.
    3. Martin Browning & Mette Gørtz, 2012. "Spending Time and Money within the Household," Scandinavian Journal of Economics, Wiley Blackwell, vol. 114(3), pages 681-704, September.
    4. Menno Pradhan, 2009. "Welfare Analysis with a Proxy Consumption Measure: Evidence from a Repeated Experiment in Indonesia," Fiscal Studies, Institute for Fiscal Studies, vol. 30(Special I), pages 391-417, December.
    5. Richard Blundell & Ian Preston, 1998. "Consumption Inequality and Income Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 113(2), pages 603-640.
    6. Erich Battistin & Richard Blundell & Arthur Lewbel, 2009. "Why Is Consumption More Log Normal than Income? Gibrat's Law Revisited," Journal of Political Economy, University of Chicago Press, vol. 117(6), pages 1140-1154, December.
    7. Susanne M. Schennach, 2004. "Estimation of Nonlinear Models with Measurement Error," Econometrica, Econometric Society, vol. 72(1), pages 33-75, January.
    8. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics,in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843 Elsevier.
    9. Cutler, David M & Katz, Lawrence F, 1992. "Rising Inequality? Changes in the Distribution of Income and Consumption in the 1980's," American Economic Review, American Economic Association, vol. 82(2), pages 546-551, May.
    10. Martin Browning & Thomas Crossley, 2009. "Are Two Cheap, Noisy Measures Better Than One Expensive, Accurate One?," American Economic Review, American Economic Association, vol. 99(2), pages 99-103, May.
    11. Li, Tong & Vuong, Quang, 1998. "Nonparametric Estimation of the Measurement Error Model Using Multiple Indicators," Journal of Multivariate Analysis, Elsevier, vol. 65(2), pages 139-165, May.
    12. Skinner, Jonathan, 1987. "A superior measure of consumption from the panel study of income dynamics," Economics Letters, Elsevier, vol. 23(2), pages 213-216.
    13. Naeem Ahmed & Matthew Brzozowski & Thomas Crossley, 2006. "Measurement errors in recall food consumption data," IFS Working Papers W06/21, Institute for Fiscal Studies.
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    Cited by:

    1. John Sabelhaus & David Johnson & Stephen Ash & Thesia Garner & John S. Greenlees & Steven W. Henderson & David Swanson, 2012. "Is the Consumer Expenditure Survey representative by income?," Finance and Economics Discussion Series 2012-36, Board of Governors of the Federal Reserve System (U.S.).
    2. John Sabelhaus & David Johnson & Stephen Ash & David Swanson & Thesia I. Garner & John Greenlees & Steve Henderson, 2014. "Is the Consumer Expenditure Survey Representative by Income?," NBER Chapters,in: Improving the Measurement of Consumer Expenditures, pages 241-262 National Bureau of Economic Research, Inc.
    3. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2012. "Measuring Economic Growth from Outer Space," American Economic Review, American Economic Association, vol. 102(2), pages 994-1028, April.
    4. Martin Browning & Thomas Crossley, 2009. "Are Two Cheap, Noisy Measures Better Than One Expensive, Accurate One?," American Economic Review, American Economic Association, vol. 99(2), pages 99-103, May.
    5. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers CWP41/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Thomas F. Crossley & Joachim K. Winter, 2014. "Asking Households about Expenditures: What Have We Learned?," NBER Chapters,in: Improving the Measurement of Consumer Expenditures, pages 23-50 National Bureau of Economic Research, Inc.
    7. Tilottama Ghosh & Sharolyn J. Anderson & Christopher D. Elvidge & Paul C. Sutton, 2013. "Using Nighttime Satellite Imagery as a Proxy Measure of Human Well-Being," Sustainability, MDPI, Open Access Journal, vol. 5(12), pages 1-32, November.
    8. Corrado, L. & Weeks, M., 2010. "Identification Strategies in Survey Response Using Vignettes," Cambridge Working Papers in Economics 1031, Faculty of Economics, University of Cambridge.
    9. repec:eee:chieco:v:46:y:2017:i:c:p:208-228 is not listed on IDEAS
    10. Doppelhofer, G. & Moe Hansen, O-P. & Weeks, M., 2017. "Determinants of long-term economic growth redux: A Measurement Error Model Averaging (MEMA) approach," Cambridge Working Papers in Economics 1702, Faculty of Economics, University of Cambridge.
    11. Orazio Attanasio & Erik Hurst & Luigi Pistaferri, 2014. "The Evolution of Income, Consumption, and Leisure Inequality in the United States, 1980–2010," NBER Chapters,in: Improving the Measurement of Consumer Expenditures, pages 100-140 National Bureau of Economic Research, Inc.
    12. Keshav Dogra & Olga Gorbachev, 2016. "Consumption Volatility, Liquidity Constraints and Household Welfare," Economic Journal, Royal Economic Society, vol. 126(597), pages 2012-2037, November.
    13. Doppelhofer, Gernot & Hansen, Ole-Petter Moe & Weeks, Melvyn, 2016. "Determinants of long-term economic Growth redux: A Measurement Error Model Averaging (MEMA) approach," Discussion Paper Series in Economics 19/2016, Norwegian School of Economics, Department of Economics.
    14. Orazio Attanasio & Erik Hurst & Luigi Pistaferri, 2012. "The Evolution of Income, Consumption, and Leisure Inequality in The US, 1980-2010," NBER Working Papers 17982, National Bureau of Economic Research, Inc.

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    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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