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Ana Beatriz Galvão
Researcher at University of Warwick
Publications - 71
Citations - 1849
Ana Beatriz Galvão is an academic researcher from University of Warwick. The author has contributed to research in topics: Monetary policy & Inflation. The author has an hindex of 18, co-authored 68 publications receiving 1588 citations. Previous affiliations of Ana Beatriz Galvão include Queen Mary University of London & European University Institute.
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Macroeconomic forecasting with mixed-frequency data: forecasting output growth in the United States
TL;DR: In this article, a mixed data-frequency sampling (MIDAS) approach was used to predict U.S. real output growth, and the results showed that the use of monthly data on the current quarter leads to significant improvement in forecasting current and next quarter output growth.
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Forecasting US output growth using leading indicators: an appraisal using MIDAS models
TL;DR: When real-time vintage data is used, leading indicators are found to have significant predictive ability, and this is further enhanced by the use of monthly data on the quarter at the time the forecast is made.
Journal ArticleDOI
Communicating uncertainty about facts, numbers and science.
Anne Marthe van der Bles,Sander van der Linden,Alexandra L. J. Freeman,James Mitchell,Ana Beatriz Galvão,Lisa Zaval,David Spiegelhalter +6 more
TL;DR: This interdisciplinary review structures and summarizes current practice and research across domains, combining a statistical and psychological perspective, and develops a framework for uncertainty communication in which three objects of uncertainty—facts, numbers and science—and two levels of uncertainty: direct and indirect are identified.
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Quantile forecasts of daily exchange rate returns from forecasts of realized volatility
TL;DR: In this paper, the authors calculate and evaluate quantile forecasts of the daily exchange rate returns of five currencies, including the Canadian dollar, and use the empirical distribution of predicted standardized returns with both rolling and recursive samples.
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Macroeconomic forecasting with mixed frequency data: Forecasting US output growth
TL;DR: In this paper, a mixed data-frequency sampling (MIDAS) approach is compared to other ways of making use of monthly data to predict quarterly output growth, and it is shown that the use of such data on the current quarter leads to a signi cant improvement in forecasting current and next quarter output growth.