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Measuring the Distributions of Public Inflation Perceptions and Expectations in the UK

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  • Murasawa, Yasutomo

Abstract

The Bank of England/GfK NOP Inflation Attitudes Survey asks individuals about their inflation perceptions and expectations in eight ordered categories with known boundaries except for an indifference limen. With enough categories for identification, one can fit a mixture distribution to such data, which can be multi-modal. Thus Bayesian analysis of a normal mixture model for interval data with an indifference limen is of interest. This paper applies the No-U-Turn Sampler (NUTS) for Bayesian computation, and estimates the distributions of public inflation perceptions and expectations in the UK during 2001Q1--2015Q4. The estimated means are useful for measuring information rigidity.

Suggested Citation

  • Murasawa, Yasutomo, 2017. "Measuring the Distributions of Public Inflation Perceptions and Expectations in the UK," MPRA Paper 76244, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:76244
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    File URL: https://mpra.ub.uni-muenchen.de/76244/1/MPRA_paper_76244.pdf
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    References listed on IDEAS

    as
    1. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1295-1328.
    2. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    3. Yasutomo Murasawa, 2013. "Measuring Inflation Expectations Using Interval-Coded Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(4), pages 602-623, August.
    4. Christophe Biernacki, 2007. "Degeneracy in the Maximum Likelihood Estimation of Univariate Gaussian Mixtures for Grouped Data and Behaviour of the EM Algorithm," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(3), pages 569-586.
    5. Akira Terai, 2010. "Estimating the distribution of inflation expectations," Economics Bulletin, AccessEcon, vol. 30(1), pages 315-329.
    6. Charles F. Manski, 2004. "Measuring Expectations," Econometrica, Econometric Society, vol. 72(5), pages 1329-1376, September.
    7. repec:ebl:ecbull:v:30:y:2010:i:1:p:315-329 is not listed on IDEAS
    8. Olivier Armantier & Wändi Bruine de Bruin & Simon Potter & Giorgio Topa & Wilbert van der Klaauw & Basit Zafar, 2013. "Measuring Inflation Expectations," Annual Review of Economics, Annual Reviews, vol. 5(1), pages 273-301, May.
    9. Koichiro Kamada & Jouchi Nakajima & Shusaku Nishiguchi, 2015. "Are Household Inflation Expectations Anchored in Japan?," Bank of Japan Working Paper Series 15-E-8, Bank of Japan.
    10. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
    11. Alston, C.L. & Mengersen, K.L., 2010. "Allowing for the effect of data binning in a Bayesian Normal mixture model," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 916-923, April.
    12. Geweke, John, 2007. "Interpretation and inference in mixture models: Simple MCMC works," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3529-3550, April.
    13. David G. Blanchflower & Conall MacCoille, 2009. "The formation of inflation expectations: an empirical analysis for the UK," NBER Working Papers 15388, National Bureau of Economic Research, Inc.
    14. Michela Nardo, 2003. "The Quantification of Qualitative Survey Data : A Critical Assessment," Journal of Economic Surveys, Wiley Blackwell, vol. 17(5), pages 645-668, December.
    15. Manski, Charles F. & Molinari, Francesca, 2010. "Rounding Probabilistic Expectations in Surveys," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 219-231.
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    More about this item

    Keywords

    Bayesian; Indifference limen; Information rigidity; Interval data; Normal mixture; No-U-turn sampler;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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