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Boom de crédito en Uruguay: Identificación y Anticipación

Author

Listed:
  • María Victoria Landaberry

    (Banco Central del Uruguay)

Abstract

In this paper we review the most used methodologies for the identification of credit boom episodes as ex post identification threshold techniques that can be used to identify episodes in Uruguay between 1985 and 2018. We estimate a Bayesian Model Average (BMA) that allows the identification and early prediction of credit booms based on the interrelation between these episodes and the macroeconomic aggregates. Considering the evolution of GDP, private consumption, investment, public spending, imports, exports, the exchange rate, the terms of trade, the current account and the capital account and financial information as a percentage of GDP, it is possible to determine the probability of being in an episode of credit boom up to two quarters in advance. Following this methodology, 3 episodes are identified, from the second quarter of 2000 to the first quarter of 2003, from the fourth quarter of 2008 to the second quarter of 2010 and from the second quarter of 2012 to the third quarter of 2015.

Suggested Citation

  • María Victoria Landaberry, 2019. "Boom de crédito en Uruguay: Identificación y Anticipación," Documentos de trabajo 2019001, Banco Central del Uruguay.
    • Handle: RePEc:bku:doctra:2019001
    as

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    File URL: https://www.bcu.gub.uy/Estadisticas-e-Indicadores/Documentos%20de%20Trabajo/01.2019.pdf
    File Function: First version, 2019
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Early warning indicator; Credit Booms; financial stability; Uruguay;
    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
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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