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Nowcasting Using Firm-Level Survey Data; Tracking UK Output Fluctuations and Recessionary Events

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  • Alex Botsis
  • Kevin Lee

Abstract

Survey data on actual past and expected future output movements are often available in a more timely manner than official statistics. We quantify qualitative survey data from the UK’s Confederation of British Industry to generate nowcasts on output growth of the whole economy and the sectors of Manufacturing and Services. Implementing model weighting techniques, we find that a weighted model that combines the survey responses, expected and realized, with an AR(1) is the most accurate one for the period before the pandemic. Survey-based data can improve the accuracy, relatively to an AR(1), of out of-sample nowcasts of the aggregate monthly growth of the GVA. At the sectoral level, this is the case only for Manufacturing. During the pandemic we cannot however draw safe conclusions. Finally, we make suggestions about future use and improvement of the survey-based qualitative data.

Suggested Citation

  • Alex Botsis & Kevin Lee, 2022. "Nowcasting Using Firm-Level Survey Data; Tracking UK Output Fluctuations and Recessionary Events," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-20, Economic Statistics Centre of Excellence (ESCoE).
    • Handle: RePEc:nsr:escoet:escoe-tr-20
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    panel data; firm data; nowcasting; quantification methods; survey data;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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