Timely Estimates of the Monthly Mexican Economic Activity

Francisco Corona, González-Farías Graciela () and López-Pérez Jesús ()
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González-Farías Graciela: Centro de Investigación en Matemáticas, A.C., Guanajuato, Guanajuato, Mexico.
López-Pérez Jesús: Instituto Nacional de Estadistica y Geografia, Research Department, Av. Adolfo López Mateos 160, Col. San Ángel Inn, AlcaldíaÁlvaro Obregón, 01060, CDMX, Mexico.

Journal of Official Statistics, 2022, vol. 38, issue 3, 733-765

Abstract: In this article, we present a new approach based on dynamic factor models (DFMs) to perform accurate nowcasts for the percentage annual variation of the Mexican Global Economic Activity Indicator (IGAE), the commonly used variable as an approximation of monthly GDP. The procedure exploits the contemporaneous relationship of the timely traditional macroeconomic time series and nontraditional variables as Google Trends with respect to the IGAE. We evaluate the performance of the approach in a pseudo real-time framework, which includes the pandemic of COVID-19, and conclude that the procedure obtains accurate estimates, for one and two-steps ahead, above all, given the use of Google Trends. Another contribution for economic nowcasting is that the approach allows to disentangle the key variables in the DFM by estimating the confidence interval for the factor loadings, hence allows to evaluate the statistical significance of the variables in the DFM. This approach is used in official statistics to obtain preliminary and accurate estimates for IGAE up to 40 days before the official data release.

Keywords: Dynamic factor models; global mexican economic activity indicator; google trends; nowcasts; pseudo real-time (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:38:y:2022:i:3:p:733-765:n:7

DOI: 10.2478/jos-2022-0033

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