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Financial Conditions Indicators for Brazil

Author

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  • Wagner Piazza Gaglianone
  • Waldyr Dutra Areosa

Abstract

In this paper, we propose a methodology to construct a Financial Conditions Indicator (FCI) based on Brave and Butters (2011) and Aramonte et al. (2013). The main idea is to use a selected set of economic and financial time series and aggregate their information content into a single index that summarizes the overall financial conditions of the economy. This approach can be further employed to forecast economic activity. An empirical exercise for Brazil is provided to illustrate the methodology, in which a modified IS-type equation (substituting the interest rate by the FCI) is employed to point forecast the output gap. In addition, a standard quantile regression technique (e.g. Koenker, 2005) is used to construct density forecasts and generate fan charts of future economic activity. A risk analysis is conducted within this setup in order to compute conditional probabilities of the output growth to be above/below a given scenario

Suggested Citation

  • Wagner Piazza Gaglianone & Waldyr Dutra Areosa, 2016. "Financial Conditions Indicators for Brazil," Working Papers Series 435, Central Bank of Brazil, Research Department.
  • Handle: RePEc:bcb:wpaper:435
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    References listed on IDEAS

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    Cited by:

    1. Simone Auer, 2017. "A Financial Conditions Index for the CEE economies," Temi di discussione (Economic working papers) 1145, Bank of Italy, Economic Research and International Relations Area.

    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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