IDEAS home Printed from https://ideas.repec.org/a/vrs/offsta/v38y2022i3p733-765n7.html

Timely Estimates of the Monthly Mexican Economic Activity

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/jos-2022-0033
    Download Restriction: no
    File URL: https://libkey.io/10.2478/jos-2022-0033?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ali, Umair & Herbst, Chris M. & Makridis, Christos A., 2021. "The impact of COVID-19 on the U.S. child care market: Evidence from stay-at-home orders," Economics of Education Review, Elsevier, vol. 82(C).
    2. 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.
    3. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Makridis, Christos A. & Wang, Tao, 2024. "Learning from Friends in a Pandemic: Social networks and the macroeconomic response of consumption," European Economic Review, Elsevier, vol. 169(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Francisco Corona & Graciela Gonz'alez-Far'ias & Jes'us L'opez-P'erez, 2021. "A nowcasting approach to generate timely estimates of Mexican economic activity: An application to the period of COVID-19," Papers 2101.10383, arXiv.org.
    2. Claudio Morana, 2010. "Heteroskedastic Factor Vector Autoregressive Estimation of Persistent and Non Persistent Processes Subject to Structural Breaks," ICER Working Papers - Applied Mathematics Series 36-2010, ICER - International Centre for Economic Research.
    3. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    4. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    5. Yi‐Chiuan Wang & Jyh‐Lin Wu, 2015. "Fundamentals and Exchange Rate Prediction Revisited," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(8), pages 1651-1671, December.
    6. Harbatkin, Erica & Strunk, Katharine O. & McIlwain, Aliyah, 2023. "School turnaround in a pandemic: An examination of the outsized implications of COVID-19 on low-performing turnaround schools, districts, and their communities," Economics of Education Review, Elsevier, vol. 97(C).
    7. Holmes, Mark & Grimes, Arthur, 2005. "Is there long-run convergence of regional house prices in the UK?," Motu Working Papers 292891, Motu Economic and Public Policy Research.
    8. Beland, Louis-Philippe & Brodeur, Abel & Haddad, Joanne & Mikola, Derek, 2020. "Covid-19, Family Stress and Domestic Violence: Remote Work, Isolation and Bargaining Power," GLO Discussion Paper Series 571, Global Labor Organization (GLO).
    9. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    10. Reese, Simon, 2015. "Asymptotic Inference in the Lee-Carter Model for Modelling Mortality Rates," Working Papers 2015:16, Lund University, Department of Economics.
    11. Morana, Claudio, 2007. "Multivariate modelling of long memory processes with common components," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 919-934, October.
    12. Barigozzi, Matteo & Trapani, Lorenzo, 2020. "Sequential testing for structural stability in approximate factor models," Stochastic Processes and their Applications, Elsevier, vol. 130(8), pages 5149-5187.
    13. Nuno Cassola & Claudio Morana, 2008. "Modeling Short-Term Interest Rate Spreads in the Euro Money Market," International Journal of Central Banking, International Journal of Central Banking, vol. 4(4), pages 1-37, December.
    14. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
    15. Luya Wang & Zheng Li & Qi Li, 2023. "A Tale of Two Policies: Examining Treatment Effects on Housing Prices in Shenzhen, China," Annals of Economics and Finance, Society for AEF, vol. 24(2), pages 277-288, November.
    16. Jushan Bai & Josep Lluís Carrion‐i‐Silvestre, 2013. "Testing panel cointegration with unobservable dynamic common factors that are correlated with the regressors," Econometrics Journal, Royal Economic Society, vol. 16(2), pages 222-249, June.
    17. Herrerias, M.J., 2013. "The environmental convergence hypothesis: Carbon dioxide emissions according to the source of energy," Energy Policy, Elsevier, vol. 61(C), pages 1140-1150.
    18. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).
    19. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Papers 2111.11506, arXiv.org.
    20. Roman Matkovskyy, 2016. "Arbitrary temporal heterogeneity in time of European countries panel model," Economics Bulletin, AccessEcon, vol. 36(1), pages 576-587.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:offsta:v:38:y:2022:i:3:p:733-765:n:7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.