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Extracting Firms' Short-Term Inflation Expectations from the Economy Watchers Survey Using Text Analysis

Author

Listed:
  • Jouchi Nakajima

    (Bank of Japan)

  • Hiroaki Yamagata

    (Bank of Japan)

  • Tatsushi Okuda

    (Bank of Japan)

  • Shinnosuke Katsuki

    (Bank of Japan)

  • Takeshi Shinohara

    (Bank of Japan)

Abstract

This paper discusses the Price Sentiment Index (PSI), a quantitative indicator of firms' outlook for general prices proposed by Otaka and Kan (2018). The PSI is developed from the textual data of the Economy Watchers Survey conducted by the Cabinet Office; it is computed by extracting firms' views from survey comments, using text analysis. In this paper, we revisit the PSI and quantitatively analyze the determinants of changes in the PSI and the relationship between the PSI and macroeconomic variables. We also address a shortcoming in the text analysis used for computing the PSI that we discover when examining the performance of the PSI since the COVID-19 outbreak. The results of our analyses show that the PSI tends to precede consumer prices by several months and that it reflects various factors affecting price developments, including demand factors associated with the business cycle and cost factors such as changes in raw materials prices and exchange rates. Our analysis suggests that the PSI is a useful monthly indicator of inflation expectations, in that it captures the price-setting stance of firms responding to the Economy Watchers Survey. While the PSI is subject to large short-term fluctuations, it can be used to complement other indicators used for the analysis of price developments such as the output gap, existing indicators of inflation expectations, and anecdotal information from various sources.

Suggested Citation

  • Jouchi Nakajima & Hiroaki Yamagata & Tatsushi Okuda & Shinnosuke Katsuki & Takeshi Shinohara, 2021. "Extracting Firms' Short-Term Inflation Expectations from the Economy Watchers Survey Using Text Analysis," Bank of Japan Working Paper Series 21-E-12, Bank of Japan.
    • Handle: RePEc:boj:bojwps:wp21e12
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    References listed on IDEAS

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    1. Olivier Coibion & Yuriy Gorodnichenko & Saten Kumar, 2018. "How Do Firms Form Their Expectations? New Survey Evidence," American Economic Review, American Economic Association, vol. 108(9), pages 2671-2713, September.
    2. Saten Kumar & Hassan Afrouzi & Olivier Coibion & Yuriy Gorodnichenko, 2015. "Inflation Targeting Does Not Anchor Inflation Expectations: Evidence from Firms in New Zealand," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 46(2 (Fall)), pages 151-225.
    3. Tomiyuki Kitamura & Masaki Tanaka, 2019. "Firms' Inflation Expectations under Rational Inattention and Sticky Information: An Analysis with a Small-Scale Macroeconomic Model," Bank of Japan Working Paper Series 19-E-16, Bank of Japan.
    4. Olivier Coibion & Yuriy Gorodnichenko & Rupal Kamdar, 2018. "The Formation of Expectations, Inflation, and the Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 56(4), pages 1447-1491, December.
    5. Haruhiko Inatsugu & Tomiyuki Kitamura & Taichi Matsuda, 2019. "The Formation of Firms' Inflation Expectations: A Survey Data Analysis," Bank of Japan Working Paper Series 19-E-15, Bank of Japan.
    6. Yosuke Uno & Saori Naganuma & Naoko Hara, 2018. "New Facts about Firms' Inflation Expectations: Short- versus Long-Term Inflation Expectations," Bank of Japan Working Paper Series 18-E-15, Bank of Japan.
    7. Angelico, Cristina & Marcucci, Juri & Miccoli, Marcello & Quarta, Filippo, 2022. "Can we measure inflation expectations using Twitter?," Journal of Econometrics, Elsevier, vol. 228(2), pages 259-277.
    8. Yosuke Uno & Saori Naganuma & Naoko Hara, 2018. "New Facts about Firms' Inflation Expectations: Simple Tests for a Sticky Information Model," Bank of Japan Working Paper Series 18-E-14, Bank of Japan.
    9. Goshima Keiichi & Ishijima Hiroshi & Shintani Mototsugu & Yamamoto Hiroki, 2021. "Forecasting Japanese inflation with a news-based leading indicator of economic activities," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(4), pages 111-133, September.
    10. Seabold,Skipper & Coppola,Andrea, 2015. "Nowcasting prices using Google trends : an application to Central America," Policy Research Working Paper Series 7398, The World Bank.
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    Cited by:

    1. De Bandt Olivier & Bricongne Jean-Charles & Denes Julien & Dhenin Alexandre & De Gaye Annabelle & Robert Pierre-Antoine, 2023. "Using the Press to Construct a New Indicator of Inflation Perceptions in France," Working papers 921, Banque de France.

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    More about this item

    Keywords

    Inflation Expectations; Machine Learning; Text Analysis; Big Data;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • 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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