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Nowcasting Mexican GDP

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  • Alberto Caruso

Abstract

In this paper I study the flow of conjunctural data relevant to assess the state of theMexican economy. I reconstruct the flow of releases that are most frequently monitored bymarket participants, economic commentators and policy makers. Given the close linkages withthe US economy, I take into account both US and Mexican data. Following the literature onnowcasting, I jointly analyse these data in a model that is continuously updated as new data getreleased. The model can be used to assess the current macroeconomic conditions (predictingthe present) of the Mexican economy and to evaluate the importance of each macroeconomicdata release. I find that the model produces forecasts whose accuracy is similar to that ofinstitutional and judgemental forecasts, and I document the importance of considering US data.

Suggested Citation

  • Alberto Caruso, 2015. "Nowcasting Mexican GDP," Working Papers ECARES ECARES 2015-40, ULB -- Universite Libre de Bruxelles.
    • Handle: RePEc:eca:wpaper:2013/219871
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    Cited by:

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    2. Bragoli, Daniela & Modugno, Michele, 2017. "A now-casting model for Canada: Do U.S. variables matter?," International Journal of Forecasting, Elsevier, vol. 33(4), pages 786-800.
    3. Francisco Corona & Graciela González-Farías & Pedro Orraca, 2017. "A dynamic factor model for the Mexican economy: are common trends useful when predicting economic activity?," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 26(1), pages 1-35, December.
    4. Bragoli, Daniela, 2017. "Now-casting the Japanese economy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 390-402.
    5. Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017. "Nowcasting BRIC+M in real time," International Journal of Forecasting, Elsevier, vol. 33(4), pages 915-935.
    6. Abel Rodríguez Tirado & Marcelo Delajara & Federico Hernández Álvarez, 2016. "Nowcasting Mexico’s Short-Term GDP Growth in Real-Time: A Factor Model versus Professional Forecasters," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Fall 2016), pages 167-182, October.
    7. Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
    8. Bhadury, Soumya & Ghosh, Saurabh & Kumar, Pankaj, 2019. "Nowcasting GDP Growth Using a Coincident Economic Indicator for India," MPRA Paper 96007, University Library of Munich, Germany.
    9. Modugno, Michele & Soybilgen, Barış & Yazgan, Ege, 2016. "Nowcasting Turkish GDP and news decomposition," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1369-1384.
    10. Oguzhan Cepni & I. Ethem Guney & Norman R. Swanson, 2020. "Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 18-36, January.
    11. Daniela Bragoli & Jack Fosten, 2018. "Nowcasting Indian GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(2), pages 259-282, April.
    12. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.

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