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Autore principale: Oscar de J. Gálvez-Soriano
Natura: Artículo científico
Lingua:en
Pubblicazione: El Colegio de México, A.C. 2020
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Accesso online:https://www.redalyc.org/articulo.oa?id=59763958002
https://www.redalyc.org/journal/597/59763958002/
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Sommario:
  • Nowcasting Mexico’s quarterly GDP using factor models and bridge equations Oscar de J. Gálvez-Soriano Economía y Finanzas Diebold Forecasting Mariano test Kalman filter monetary policy I evaluate five nowcasting models that I used to forecast Mexico’s quarterly GDP in the short run: a dynamic factor model (DFM), two bridge equation (BE) models and two models based on principal components analysis (PCA). The results indicate that the average of the two BE forecasts is statistically better than the rest of the models under consideration, according to the Diebold-Mariano accuracy test. Using realtime information, I show that the average of the BE models is also more accurate than the median of the forecasts provided by the analysts surveyed by Bloomberg, the median of the experts who answer Banco de México’s Survey of Professional Forecasters and the rapid GDP estimate released by INEGI. 2020 artículo científico 0188-6916 https://www.redalyc.org/articulo.oa?id=59763958002 https://www.redalyc.org/journal/597/59763958002/ https://www.redalyc.org/journal/597/59763958002/html/ https://www.redalyc.org/journal/597/59763958002/59763958002.epub https://www.redalyc.org/journal/597/59763958002/movil 10.24201/ee.v35i2.402 en http://www.redalyc.org/revista.oa?id=597 Estudios Económicos application/pdf El Colegio de México, A.C. Estudios Económicos (México) Num.2 Vol.35