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Quantifying Qualitative Survey Data with Panel Data Structure

Author

Listed:
  • Alexandros Botsis
  • Christoph Gortz
  • Plutarchos Sakellaris
Abstract
We develop a novel methodology to quantify forecasts based on qualitative survey data. The methodology is generally applicable when quantitative information is available on the realization of the forecasted variable, for example from firm balance sheets. The method can be applied to a wide range of panel datasets, including qualitative surveys on firm-level forecasts or household expectations. As an application, we employ a panel of Greek manufacturing firms and quantify firms’ forecast errors of own sales growth. In this context, we conduct a variety of exercises to demonstrate the methodology’s validity and accuracy.

Suggested Citation

  • Alexandros Botsis & Christoph Gortz & Plutarchos Sakellaris, 2024. "Quantifying Qualitative Survey Data with Panel Data Structure," CAMA Working Papers 2024-21, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:camaaa:2024-21
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    File URL: https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2024-03/21_2024_botsis_gortz_sakellaris.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    expectations; firm data; forecast errors; survey data;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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