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Timely Estimates of the Monthly Mexican Economic Activity

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  • Corona Francisco

    (Instituto Nacional de Estadistica y Geografia, Research Department, Av. Adolfo López Mateos 160, Col. San Ángel Inn, AlcaldíaÁlvaro Obregón, 01060, CDMX, Mexico.)

  • 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.)

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.

Suggested Citation

  • Corona Francisco & González-Farías Graciela & López-Pérez Jesús, 2022. "Timely Estimates of the Monthly Mexican Economic Activity," Journal of Official Statistics, Sciendo, vol. 38(3), pages 733-765, September.
    • Handle: RePEc:vrs:offsta:v:38:y:2022:i:3:p:733-765:n:7
    DOI: 10.2478/jos-2022-0033
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    References listed on IDEAS

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    1. Valentina Aprigliano & Lorenzo Bencivelli, 2013. "Ita-coin: a new coincident indicator for the Italian economy," Temi di discussione (Economic working papers) 935, Bank of Italy, Economic Research and International Relations Area.
    2. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
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