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Financial condition indices for emerging market economies: Can Google help?

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  • Ferriani, Fabrizio
  • Gazzani, Andrea

Abstract

We compare alternative approaches to construct financial condition indices (FCIs) for major emerging market economies (EMEs). We further test whether measures of web-search intensity for keywords related to financial tensions can complement the informative content of traditional financial variables. We find that an index constructed as a simple average of key financial variables augmented with data from google searches outperforms several alternative definitions of FCIs to explain business cycle fluctuations and capital flows episodes. These results survive when controlling for proxies of the global financial cycle, highlighting that local financial markets conditions are important for the macroeconomic performance in EMEs.

Suggested Citation

  • Ferriani, Fabrizio & Gazzani, Andrea, 2022. "Financial condition indices for emerging market economies: Can Google help?," Economics Letters, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:ecolet:v:216:y:2022:i:c:s0165176522001410
    DOI: 10.1016/j.econlet.2022.110528
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    More about this item

    Keywords

    Financial condition index; Emerging markets; Google search; Principal component analysis; VAR; Quantile regressions;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F30 - International Economics - - International Finance - - - General
    • G01 - Financial Economics - - General - - - Financial Crises
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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