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"Don't know" Tells: Calculating Non-Response Bias in Firms' Inflation Expectations Using Machine Learning Techniques

Author

Listed:
  • Yosuke Uno

    (Bank of Japan)

  • Ko Adachi

    (Bank of Japan)

Abstract

This paper examines the "don't know" responses for questions concerning inflation expectations in the Tankan survey. Specifically, using machine learning techniques, we attempt to extract "don't know" responses where respondent firms are more likely to "know" in a sense. We then estimate the counterfactual inflation expectations of such respondents and examine the non-response bias based on the estimation results. Our findings can be summarized as follows. First, there is indeed a fraction of firms that respond "don't know" despite the fact that they seem to "know" something in a sense. Second, the number of such firms, however, is quite small. Third, the estimated counterfactual inflation expectations of such firms are not statistically significantly different from the corresponding official figures in the Tankan survey. Fourth and last, based on the above findings, the non-response bias in firms' inflation expectations likely is statistically negligible.

Suggested Citation

  • Yosuke Uno & Ko Adachi, 2019. ""Don't know" Tells: Calculating Non-Response Bias in Firms' Inflation Expectations Using Machine Learning Techniques," Bank of Japan Working Paper Series 19-E-17, Bank of Japan.
  • Handle: RePEc:boj:bojwps:wp19e17
    as

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    References listed on IDEAS

    as
    1. Takahiro Hirakawa & Junichiro Hatogai, 2013. "A Study of Missing Value Imputation in Business Surveys: The Case of the Short-Term Economic Survey of Enterprises in Japan (Tankan)," Bank of Japan Working Paper Series 13-E-9, Bank of Japan.
    2. Utsunomiya, Kiyohito & Sonoda, Katsurako, 2004. "Methodology for Handling Missing Values of “Short‐term Economic Survey of All Enterprises in Japan (Tankan)”," Economic Review, Hitotsubashi University, vol. 55(3), pages 217-229, July.
    3. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    4. Coibion, Olivier & Gorodnichenko, Yuriy & Kumar, Saten & Pedemonte, Mathieu, 2020. "Inflation expectations as a policy tool?," Journal of International Economics, Elsevier, vol. 124(C).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    inflation expectations; PU classification; non-response bias;
    All these keywords.

    JEL classification:

    • 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

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