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Forecasting inflation with consumer survey data – application of multi-group confirmatory factor analysis to elimination of the general sentiment factor

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Abstract

This paper (1) examines the properties of survey based households’ inflation expectations and investigates their forecasting performance. With application of the individual data from the State of the Households’ Survey (50 quarters between 1997Q4 and 2010Q1) it was shown that inflation expectations were affected by the consumer sentiment. Multi-Group Confirmatory Factor Analysis (MGCFA) was employed to verify whether a set of proxies provides a reliable basis for measurement of two latent phenomena – consumer sentiment and inflation expectations. Following the steps proposed by Davidov (2008) and Steenkamp and Baumgartner (1998), it appeared that it was possible to specify and estimate a MGCFA model with partial measurement invariance. Thus it was possible to eliminate the influence of consumer sentiment on inflation expectations and at the same time to obtain individually corrected answers concerning the inflation expectations. Additionally, it was shown that the linear relation between consumer sentiment and inflation expectations was stable over time. As a by-product of analysis, it was possible to show that respondents during the financial crisis were much less consistent in their answers to the questions of the consumer questionnaire. In the next step of the analysis, data on inflation expectations were applied to modelling and forecasting inflation. It was shown that with respect to standard ARIMA processes, inclusion of the information on the inflation expectations significantly improved the in-sample and out-of-sample forecasting performance of the time-series models. Especially out-of-sample performance was significantly better as the average absolute error in forecasts of headline and core inflation was reduced by half. It was also shown that models with inflation expectations based on the CFA method (after elimination of the consumer sentiment factor) provided better in-sample forecasts of inflation. Nevertheless, it was not confirmed for the out-of-sample forecasts. (1) Project financed by the National Bank of Poland. Polish title of the project: "Prognozowanie inflacji na podstawie danych koniunktury gospodarstw domowych. Zastosowanie konfirmacyjnej analizy czynnikowej dla wielu grup do oczyszczenia prognoz inflacji z czynnika ogólnego nastroju gospodarczego."

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  • Piotr Białowolski, 2011. "Forecasting inflation with consumer survey data – application of multi-group confirmatory factor analysis to elimination of the general sentiment factor," NBP Working Papers 100, Narodowy Bank Polski.
    • Handle: RePEc:nbp:nbpmis:100
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    References listed on IDEAS

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    1. Carroll, Christopher D & Fuhrer, Jeffrey C & Wilcox, David W, 1994. "Does Consumer Sentiment Forecast Household Spending? If So, Why?," American Economic Review, American Economic Association, vol. 84(5), pages 1397-1408, December.
    2. Rolf Scheufele, 2011. "Are Qualitative Inflation Expectations Useful to Predict Inflation?," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2011(1), pages 29-53.
    3. Henry, Olan T. & Shields, Kalvinder, 2004. "Is there a unit root in inflation?," Journal of Macroeconomics, Elsevier, vol. 26(3), pages 481-500, September.
    4. Cukierman, Alex & Meltzer, Allan H, 1986. "A Theory of Ambiguity, Credibility, and Inflation under Discretion and Asymmetric Information," Econometrica, Econometric Society, vol. 54(5), pages 1099-1128, September.
    5. Bharat Trehan, 2015. "Survey Measures of Expected Inflation and the Inflation Process," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(1), pages 207-222, February.
    6. Roberto Golinelli & Renzo Orsi, 2002. "Modelling Inflation in EU Accession Countries: The Case of the Czech Republic, Hungary and Poland," Eastward Enlargement of the Euro-zone Working Papers wp09, Free University Berlin, Jean Monnet Centre of Excellence, revised 01 Aug 2002.
    7. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423, September.
    8. Friedman, Milton, 1977. "Nobel Lecture: Inflation and Unemployment," Journal of Political Economy, University of Chicago Press, vol. 85(3), pages 451-472, June.
    9. R. Golinelli & R. Orsi, 2001. "Hungary and Poland," Working Papers 424, Dipartimento Scienze Economiche, Universita' di Bologna.
    10. Steenkamp, Jan-Benedict E M & Baumgartner, Hans, 1998. "Assessing Measurement Invariance in Cross-National Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(1), pages 78-90, June.
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    Cited by:

    1. Murillo Garza José Antonio & Sánchez-Romeu Paula, 2012. "Testing the Predictive Power of Mexican Consumers' Inflation Expectations," Working Papers 2012-13, Banco de México.

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    More about this item

    Keywords

    Inflation expectations; Inflation forecasts; Confirmatory Factor Analysis;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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