Nowcasting del PIB de México usando modelos de factores y ecuaciones puente
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 forecastsis statistically b...
| Auteur principal: | |
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| Format: | Online |
| Langue: | anglais |
| Éditeur: |
El Colegio de México, A.C.
2020
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| Sujets: | |
| Accès en ligne: | https://estudioseconomicos.colmex.mx/index.php/economicos/article/view/402 |
| Institution: |
Estudios Económicos |
| authentication_code | dc |
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| _version_ | 1844256703987580928 |
| author | Gálvez-Soriano, Oscar de J. |
| author_facet | Gálvez-Soriano, Oscar de J. |
| author_sort | Gálvez-Soriano, Oscar de J. |
| category_str_mv |
"Bolivia", "hyperinflation", "economic crisis", "Bolivia", "hiperinflación", "crisis económica"
|
| collection | OJS |
| description | 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 forecastsis statistically better than the rest of the models under consideration, according to the Diebold-Mariano accuracy test. Using real-time 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. |
| format | Online |
| id | oai:oai.estudioseconomicos.colmex.mx:article-402 |
| index_str_mv | CONAHCYT LATINDEX PKP Index DORA Redalyc Scielo México Handbook of Latin American Studies (HLAS) JSTOR Dialnet HAPI Ulrich’s International Periodicals Directory Google Scholar IBSS Gale OneFile: Informe Académico Global Issues in Context InfoTracCustom Cengage Learning EconLit Índice bibliográfico Publindex RePEc The Journal of Economic Literature |
| journal | Estudios Económicos |
| language | eng |
| publishDate | 2020 |
| publisher | El Colegio de México, A.C. |
| record_format | ojs |
| Terms_governing_use_and_reproduction_note | Copyright (c) 2020 Estudios Económicos de El Colegio de México |
| data_source_entry/ISSN | Estudios Económicos de El Colegio de México; 70-vol. 35, no. 2, july-december, 2020; 213-265 Estudios Económicos de El Colegio de México; 70-vol. 35, núm. 2, julio-diciembre, 2020; 213-265 0186-7202 0188-6916 |
| spelling | oai:oai.estudioseconomicos.colmex.mx:article-4022023-05-19T03:10:11Z Nowcasting Mexico's quarterly GDP using factor models and bridge equations Nowcasting del PIB de México usando modelos de factores y ecuaciones puente Gálvez-Soriano, Oscar de J. forecasting state space model principal component analysis monetary policy Kalman filter Diebold-Mariano test C32 C38 C53 E52 pronósticos modelos de estado espacio análisis de componentes principales política monetaria filtro de Kalman prueba de Diebold-Mariano C32 C38 C53 E52 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 forecastsis statistically better than the rest of the models under consideration, according to the Diebold-Mariano accuracy test. Using real-time 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. Se evalúan cinco modelos de Nowcasting: un modelo de factores dinámicos (MFD), dos ecuaciones puente (BE) y dos basados en componentes principales (PCA). Los resultados indican que el promedio de los pronósticos de las BE es estadísticamente mejor que el del resto de los modelos considerados, de acuerdo con la prueba de precisión de pronósticos de Diebold-Mariano. Utilizando información en tiempo real, se encuentra que el promedio de las BE es más preciso que la mediana de los pronósticos de los analistas encuestados por Bloomberg, que la mediana de los especialistas que responden la encuesta de expectativas del Banco de México y que la estimación oportuna del PIB publicada por el INEGI. El Colegio de México, A.C. 2020-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf text/xml https://estudioseconomicos.colmex.mx/index.php/economicos/article/view/402 10.24201/ee.v35i2.402 Estudios Económicos de El Colegio de México; 70-vol. 35, no. 2, july-december, 2020; 213-265 Estudios Económicos de El Colegio de México; 70-vol. 35, núm. 2, julio-diciembre, 2020; 213-265 0186-7202 0188-6916 eng https://estudioseconomicos.colmex.mx/index.php/economicos/article/view/402/510 https://estudioseconomicos.colmex.mx/index.php/economicos/article/view/402/518 Copyright (c) 2020 Estudios Económicos de El Colegio de México |
| spellingShingle | forecasting state space model principal component analysis monetary policy Kalman filter Diebold-Mariano test C32 C38 C53 E52 pronósticos modelos de estado espacio análisis de componentes principales política monetaria filtro de Kalman prueba de Diebold-Mariano C32 C38 C53 E52 Gálvez-Soriano, Oscar de J. Nowcasting del PIB de México usando modelos de factores y ecuaciones puente |
| title | Nowcasting del PIB de México usando modelos de factores y ecuaciones puente |
| title_alt | Nowcasting Mexico's quarterly GDP using factor models and bridge equations |
| title_full | Nowcasting del PIB de México usando modelos de factores y ecuaciones puente |
| title_fullStr | Nowcasting del PIB de México usando modelos de factores y ecuaciones puente |
| title_full_unstemmed | Nowcasting del PIB de México usando modelos de factores y ecuaciones puente |
| title_short | Nowcasting del PIB de México usando modelos de factores y ecuaciones puente |
| title_sort | nowcasting del pib de mexico usando modelos de factores y ecuaciones puente |
| topic | forecasting state space model principal component analysis monetary policy Kalman filter Diebold-Mariano test C32 C38 C53 E52 pronósticos modelos de estado espacio análisis de componentes principales política monetaria filtro de Kalman prueba de Diebold-Mariano C32 C38 C53 E52 |
| topic_facet | forecasting state space model principal component analysis monetary policy Kalman filter Diebold-Mariano test C32 C38 C53 E52 pronósticos modelos de estado espacio análisis de componentes principales política monetaria filtro de Kalman prueba de Diebold-Mariano C32 C38 C53 E52 |
| url | https://estudioseconomicos.colmex.mx/index.php/economicos/article/view/402 |
| work_keys_str_mv | AT galvezsorianooscardej nowcastingmexicosquarterlygdpusingfactormodelsandbridgeequations AT galvezsorianooscardej nowcastingdelpibdemexicousandomodelosdefactoresyecuacionespuente |