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A note on the predictive power of survey data in nowcasting euro area GDP

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  • Kurz-Kim, Jeong-Ryeol

Abstract

This paper investigates the trade-off between timeliness and quality in nowcasting practices. This trade-off arises when the frequency of the variable to be nowcast, such as GDP, is quarterly, while that of the underlying panel data is monthly; and the latter contains both survey and macroeconomic data. These two categories of data have different properties regarding timeliness and quality: the survey data are timely available (but might possess less predictive power), while the macroeconomic data possess more predictive power (but are not timely available because of their publication lags). In our empirical analysis, we use a modified dynamic factor model which takes three refinements for the standard dynamic factor model of Stock and Watson (2002) into account, namely mixed frequency, pre-selections and co-integration among the economic variables. Our main finding from a historical nowcasting simulation based on euro area GDP is that the predictive power of the survey data depends on the economic circumstances, namely, that survey data are more useful in tranquil times, and less so in times of turmoil.

Suggested Citation

  • Kurz-Kim, Jeong-Ryeol, 2018. "A note on the predictive power of survey data in nowcasting euro area GDP," Discussion Papers 10/2018, Deutsche Bundesbank.
    • Handle: RePEc:zbw:bubdps:102018
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    References listed on IDEAS

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    More about this item

    Keywords

    nowcasting; dynamic factor model; mixed frequency; pre-selections; co-integration; survey data; trade-off between timeliness and quality; turmoil and tranquility;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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