IDEAS home Printed from https://ideas.repec.org/p/cte/derepe/3004.html

Un nuevo indicador semanal y mensual de actividad basado en el consumo de energía eléctrica

Author

Listed:
  • Cancelo, José Ramón
  • Espasa, Antoni

Abstract

La falta de información mensual o trimestral sobre el PIB obliga a utilizar una serie de indicadores parciales para el seguimiento a corto plazo de la actividad. De entre ellos destaca el consumo de energía eléctrica; sin embargo, la evolución de esta magnitud aparece muy distorsionada por las condiciones metereológicas y de calendario. En este trabajo se propone utilizar la información contenida en un modelo de predicción diaria del consumo eléctrico para estimar una serie diaria depurada de la demanda diferencial debida a estos factores; por agregación de dicha serie diaria corregida se obtienen indicadores más fiables de actividad semanal y mensual.

Suggested Citation

  • Cancelo, José Ramón & Espasa, Antoni, 1991. "Un nuevo indicador semanal y mensual de actividad basado en el consumo de energía eléctrica," DE - Documentos de Trabajo. Economía. DE 3004, Universidad Carlos III de Madrid. Departamento de Economía.
  • Handle: RePEc:cte:derepe:3004
    as

    Download full text from publisher

    File URL: https://e-archivo.uc3m.es/rest/api/core/bitstreams/6b0f83a3-de1b-47b8-b110-3fb3d5200a62/content
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zellner, Arnold & Palm, Franz, 1974. "Time series analysis and simultaneous equation econometric models," Journal of Econometrics, Elsevier, vol. 2(1), pages 17-54, May.
    Full references (including those not matched with items on IDEAS)

    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. Anna Mikusheva & Mikkel Sølvsten, 2025. "Linear regression with weak exogeneity," Quantitative Economics, Econometric Society, vol. 16(2), pages 367-403, May.
    2. Cubadda, Gianluca & Hecq, Alain & Palm, Franz C., 2009. "Studying co-movements in large multivariate data prior to multivariate modelling," Journal of Econometrics, Elsevier, vol. 148(1), pages 25-35, January.
    3. Kapetanios, G. & Pagan, A. & Scott, A., 2007. "Making a match: Combining theory and evidence in policy-oriented macroeconomic modeling," Journal of Econometrics, Elsevier, vol. 136(2), pages 565-594, February.
    4. Wilms, Ines & Rombouts, Jeroen & Croux, Christophe, 2021. "Multivariate volatility forecasts for stock market indices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 484-499.
    5. Pauwels, Koen H., 2018. "Modeling Dynamic Relations Among Marketing and Performance Metrics," Foundations and Trends(R) in Marketing, now publishers, vol. 11(4), pages 215-301, November.
    6. Boswijk, H. Peter & Franses, Philip Hans & van Dijk, Dick, 2010. "Cointegration in a historical perspective," Journal of Econometrics, Elsevier, vol. 158(1), pages 156-159, September.
    7. Jean‐Paul Chavas & Giorgia Rivieccio & Salvatore Di Falco & Giovanni De Luca & Fabian Capitanio, 2022. "Agricultural diversification, productivity, and food security across time and space," Agricultural Economics, International Association of Agricultural Economists, vol. 53(S1), pages 41-58, November.
    8. Cubadda, G. & Hecq, A.W. & Palm, F.C., 2007. "Studying co-movements in large multivariate models without multivariate modelling," Research Memorandum 032, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    9. Brown, Stephen J. & Hiraki, Takato & Arakawa, Kiyoshi & Ohno, Saburo, 2009. "Risk premia in international equity markets revisited," Pacific-Basin Finance Journal, Elsevier, vol. 17(3), pages 295-318, June.
    10. Gianluca Cubadda & Alain Hecq & Antonio Riccardo, 2018. "Forecasting Realized Volatility Measures with Multivariate and Univariate Models: The Case of The US Banking Sector," CEIS Research Paper 445, Tor Vergata University, CEIS, revised 30 Oct 2018.
    11. Tripathi, Ashutosh K. & Mishra, Ashok K., 2023. "Impact of Agricultural Policies on Wheat Market Prices: Evidence from India," 2023 Annual Meeting, July 23-25, Washington D.C. 335623, Agricultural and Applied Economics Association.
    12. Giacomo Sbrana, 2012. "Aggregation and marginalization of GARCH processes: some further results," METRON, Springer;Sapienza Università di Roma, vol. 70(2), pages 165-172, August.
    13. Javier Moreno & Jaime H. Beltrán & Leovardo Mata, 2019. "Efectos de corto y largo plazo de los programas de condonación de créditos fiscales en la recaudación del Impuesto al Valor Agregado," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 14(1), pages 113-128, Enero-Mar.
    14. Yin, Runsheng & Baek, Jungho, 2004. "The US-Canada softwood lumber trade dispute: what we know and what we need to know," Forest Policy and Economics, Elsevier, vol. 6(2), pages 129-143, March.
    15. Chevillon, Guillaume & Hecq, Alain & Laurent, Sébastien, 2018. "Generating univariate fractional integration within a large VAR(1)," Journal of Econometrics, Elsevier, vol. 204(1), pages 54-65.
    16. Zha, Tao, 1999. "Block recursion and structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 90(2), pages 291-316, June.
    17. Cubadda, Gianluca & Triacca, Umberto, 2011. "An alternative solution to the Autoregressivity Paradox in time series analysis," Economic Modelling, Elsevier, vol. 28(3), pages 1451-1454, May.
    18. Dong Wan Shin & Sahadeb Sarkar, 1995. "Estimation Of The Multivariate Autoregressive Moving Average Having Parameter Restrictions And An Application To Rotational Sampling," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(4), pages 431-444, July.
    19. Mala Raghavan & George Athanasopoulos & Param Silvapulle, 2009. "VARMA models for Malaysian Monetary Policy Analysis," Monash Econometrics and Business Statistics Working Papers 6/09, Monash University, Department of Econometrics and Business Statistics.

    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:cte:derepe:3004. 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: Ana Poveda (email available below). General contact details of provider: http://www.eco.uc3m.es/ .

    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.