IDEAS home Printed from https://ideas.repec.org/p/bdr/borrec/1202.html

Aporte de las expectativas de empresarios al pronóstico de las variables macroeconómicas

Author

Listed:
  • María Alejandra Hernández-Montes
  • Ramón Hernández-Ortega
  • Jonathan Alexander Muñoz-Martínez

Abstract

Este documento evalúa el aporte de las expectativas de los empresarios, capturadas a través de las encuestas del Banco de la República y Fedesarrollo, a los pronósticos de las principales variables macroeconómicas: inflación, desempleo, empleo y crecimiento económico. Este aporte se evalúa mediante la comparación de los errores de pronóstico de uno a cuatro trimestres de dos modelos econométricos anidados. Los resultados sugieren que las expectativas de los empresarios reducen de manera importante el error de pronóstico de la inflación y del crecimiento económico, mientras que los aportes al pronóstico del empleo y el desempleo son limitados. **** ABSTRAC: In this paper we evaluate the contribution of business expectations from surveys of Banco de la República and Fedesarrollo, to the forecasts of the main macroeconomic variables: inflation, unemployment, employment and economic growth. We make this assessment by comparing one to four quarters ahead forecast errors of two nested models econometrics. The results suggest that the expectations of businessmen could have information that improves forecasts of economic growth and inflation and have other lower contributions to employment and unemployment predictions.

Suggested Citation

  • María Alejandra Hernández-Montes & Ramón Hernández-Ortega & Jonathan Alexander Muñoz-Martínez, 2022. "Aporte de las expectativas de empresarios al pronóstico de las variables macroeconómicas," Borradores de Economia 1202, Banco de la Republica de Colombia.
    • Handle: RePEc:bdr:borrec:1202
    DOI: 10.32468/be.1202
    as

    Download full text from publisher

    File URL: https://doi.org/10.32468/be.1202
    Download Restriction: no
    File URL: https://libkey.io/10.32468/be.1202?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. Boriss Siliverstovs, 2009. "Evaluating short-run forecasting properties of the KOF employment indicator for Switzerland in real time," KOF Working papers 09-226, KOF Swiss Economic Institute, ETH Zurich.
    2. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    3. Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 51(54), pages 5802-5816.
    4. Matheson, Troy D., 2010. "An analysis of the informational content of New Zealand data releases: The importance of business opinion surveys," Economic Modelling, Elsevier, vol. 27(1), pages 304-314, January.
    5. Robert Lehmann & Antje Weyh, 2016. "Forecasting Employment in Europe: Are Survey Results Helpful?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 81-117, September.
    6. Martinsen, Kjetil & Ravazzolo, Francesco & Wulfsberg, Fredrik, 2014. "Forecasting macroeconomic variables using disaggregate survey data," International Journal of Forecasting, Elsevier, vol. 30(1), pages 65-77.
    7. Claveria, Oscar & Pons, Ernest & Ramos, Raul, 2007. "Business and consumer expectations and macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 47-69.
    8. Stock, James H. & Watson, Mark, 2011. "Dynamic Factor Models," Scholarly Articles 28469541, Harvard University Department of Economics.
    9. Hanssens, Dominique M & Vanden Abeele, Pierre M, 1987. "A Time-Series Study of the Formation and Predictive Performance of EEC Production Survey Expectations," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 507-519, October.
    10. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
    11. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
    12. Ximena Chavarro-Sanchez & Deicy Cristiano-Botia & Jose E. Gomez-Gonzalez & Carlos Huertas-Campos Eliana Gonz�lez-Molano, 2015. "Evaluaci�n de la transmisi�n de la tasa de inter�s de referencia a las tasas de inter�s del sistema financiero," Borradores de Economia 12625, Banco de la Republica.
    13. González-Molano, Eliana Rocío & Jalil-Barney, Munir Andrés & Romero-Chamorro, José Vicente, 2011. "Inflación y expectativas de inflación en Colombia," Chapters, in: López Enciso, Enrique & Ramírez Giraldo, María Teresa (ed.), Formación de precios y salarios en Colombia, tomo II, volume 2, chapter 13, pages 491-519, Banco de la Republica de Colombia.
    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. Robert Lehmann & Antje Weyh, 2016. "Forecasting Employment in Europe: Are Survey Results Helpful?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 81-117, September.
    2. Inna S. Lola & Anton Manukov, 2020. "Forecasting Employment In Small Businesses In Russia: The Relevance Of Business Tendency Surveys," HSE Working papers WP BRP 113/STI/2020, National Research University Higher School of Economics.
    3. Euler Pereira G. de Mello & Francisco Marcos R. Figueiredo, 2014. "Assessing the Short-term Forecasting Power of Confidence Indices," Working Papers Series 371, Central Bank of Brazil, Research Department.
    4. 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.
    5. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    6. Robert Lehmann, 2023. "The Forecasting Power of the ifo Business Survey," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 43-94, March.
    7. repec:iab:iabjlr:v:53:i:1:p:art.3 is not listed on IDEAS
    8. Chris Heaton & Natalia Ponomareva & Qin Zhang, 2020. "Forecasting models for the Chinese macroeconomy: the simpler the better?," Empirical Economics, Springer, vol. 58(1), pages 139-167, January.
    9. Knut Are Aastveit & Anne Sofie Jore & Francesco Ravazzolo, 2014. "Forecasting recessions in real time," Working Paper 2014/02, Norges Bank.
    10. Carlos A. Medel, 2018. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," International Economic Journal, Taylor & Francis Journals, vol. 32(3), pages 331-371, July.
    11. repec:iab:iabjlr:v:53:p:art.03 is not listed on IDEAS
    12. Claveria, Oscar, 2019. "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 53, pages 1-003.
    13. Carlos Medel, 2017. "Forecasting Chilean inflation with the hybrid new keynesian Phillips curve: globalisation, combination, and accuracy," Journal Econom a Chilena (The Chilean Economy), Central Bank of Chile, vol. 20(3), pages 004-050, December.
    14. Oscar Claveria, 2019. "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 53(1), pages 1-10, December.
    15. R. Lehmann & K. Wohlrabe, 2017. "Experts, firms, consumers or even hard data? Forecasting employment in Germany," Applied Economics Letters, Taylor & Francis Journals, vol. 24(4), pages 279-283, February.
    16. In Choi & Hanbat Jeong, 2020. "Differencing versus nondifferencing in factor‐based forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 728-750, September.
    17. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
    18. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
    19. Nason, Guy P. & Palasciano, Henry Antonio, 2026. "Forecasting UK consumer price inflation with RaGNAR: Random generalised network autoregressive processes," International Journal of Forecasting, Elsevier, vol. 42(1), pages 181-202.
    20. Bespalova, Olga, 2018. "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper 117706, University Library of Munich, Germany.
    21. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    22. Robert Lehmann, 2021. "Forecasting exports across Europe: What are the superior survey indicators?," Empirical Economics, Springer, vol. 60(5), pages 2429-2453, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:bdr:borrec:1202. 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: Clorith Angélica Bahos Olivera (email available below). General contact details of provider: https://edirc.repec.org/data/brcgvco.html .

    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.