Macroeconomic nowcasting using Google probabilities

Koop, Gary and Onorante, Luca; Jeliazkov, Ivan and Tobias, Justin L., eds. (2019) Macroeconomic nowcasting using Google probabilities. In: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A. Advances in Econometrics, 40A (1). Emerald Publishing Limited, pp. 17-40. ISBN 9781789732412 (https://doi.org/10.1108/S0731-90532019000040A003)

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Abstract

Many recent papers have investigated whether data from internet search engines such as Google can help improve nowcasts or short-term forecasts of macroeconomic variables. These papers construct variables based on Google searches and use them as explanatory variables in regression models. We add to this literature by nowcasting using dynamic model selection (DMS) methods which allow for model switching between time-varying parameter regression models. This is potentially useful in an environment of coe¢ cient instability and over-parameterization which can arise when forecasting with Google variables. We extend the DMS methodology by allowing for the model switching to be controlled by the Google variables through what we call ìGoogle probabilitiesî: instead of using Google variables as regressors, we allow them to determine which nowcasting model should be used at each point in time. In an empirical exercise involving nine major monthly US macroeconomic variables, we Önd DMS methods to provide large improvements in nowcasting. Our use of Google model probabilities within DMS often performs better than conventional DMS.

ORCID iDs

Koop, Gary ORCID logoORCID: https://orcid.org/0000-0002-6091-378X and Onorante, Luca; Jeliazkov, Ivan and Tobias, Justin L.
  • Item type:Book Section
    ID code:66415
    Dates:
    Date
    Event
    30 August 2019
    Published
    5 November 2018
    Accepted
    Notes:Copyright © Chapter 12 is in the Public Domain. All other chapters and editorial matter © Emerald 2019 Koop, G. and Onorante, L. (2019), "Macroeconomic Nowcasting Using Google Probabilities ☆ ", Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A (Advances in Econometrics, Vol. 40A), Emerald Publishing Limited, Leeds, pp. 17-40. https://doi.org/10.1108/S0731-90532019000040A003
    Subjects:Social Sciences > Economic Theory
    Department:Strathclyde Business School > Economics
    Depositing user: Pure Administrator
    Date deposited:18 Dec 2018 12:55
    Last modified:13 Nov 2024 01:28
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/66415
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