IDEAS home Printed from https://ideas.repec.org/a/zbw/ifweej/201625.html
   My bibliography  Save this article

Does uncertainty affect non-response to the European Central Bank's survey of professional forecasters?

Author

Listed:
  • López-Pérez, Víctor

Abstract

This paper explores how changes in macroeconomic uncertainty have affected the decision to reply to the European Central Bank's Survey of Professional Forecasters (ECB's SPF). The results suggest that higher (lower) aggregate uncertainty increases (reduces) non-response to the survey. This effect is statistically and economically significant. Therefore, the assumption that individual ECB's SPF data are missing at random may not be appropriate. Moreover, the forecasters that perceive more individual uncertainty seem to have a lower likelihood of replying to the survey. Consequently, measures of uncertainty computed from individual ECB's SPF data could be biased downwards.

Suggested Citation

  • López-Pérez, Víctor, 2016. "Does uncertainty affect non-response to the European Central Bank's survey of professional forecasters?," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-47.
  • Handle: RePEc:zbw:ifweej:201625
    DOI: 10.5018/economics-ejournal.ja.2016-25
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.5018/economics-ejournal.ja.2016-25
    Download Restriction: no

    File URL: https://www.econstor.eu/bitstream/10419/147299/1/871004801.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.5018/economics-ejournal.ja.2016-25?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. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54, January.
    2. Baker, Scott R. & Bloom, Nicholas, 2013. "Does uncertainty reduce growth? Using disasters as natural experiments," LSE Research Online Documents on Economics 121906, London School of Economics and Political Science, LSE Library.
    3. Glas, Alexander & Hartmann, Matthias, 2016. "Inflation uncertainty, disagreement and monetary policy: Evidence from the ECB Survey of Professional Forecasters," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 215-228.
    4. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    5. Adina Popescu & Frank Rafael Smets, 2010. "Uncertainty, Risk-taking, and the Business Cycle in Germany," CESifo Economic Studies, CESifo Group, vol. 56(4), pages 596-626, December.
    6. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    7. Wooldridge, Jeffrey M., 1995. "Selection corrections for panel data models under conditional mean independence assumptions," Journal of Econometrics, Elsevier, vol. 68(1), pages 115-132, July.
    8. Geoff Kenny & Thomas Kostka & Federico Masera, 2014. "How Informative are the Subjective Density Forecasts of Macroeconomists?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(3), pages 163-185, April.
    9. Maritta Paloviita & Matti Viren, 2014. "Inflation and output growth uncertainty in individual survey expectations," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(1), pages 69-81, February.
    10. Jaewoo Lee & Pau Rabanal & Damiano Sandri, 2010. "U.S. Consumption after the 2008 Crisis," IMF Staff Position Notes 2010/01, International Monetary Fund.
    11. Mr. Jaewoo Lee & Mr. Pau Rabanal & Mr. Damiano Sandri, 2010. "U.S. Consumption after the 2008 Crisis," IMF Staff Position Notes 2010/001, International Monetary Fund.
    12. Wooldridge, Jeffrey M., 2007. "Inverse probability weighted estimation for general missing data problems," Journal of Econometrics, Elsevier, vol. 141(2), pages 1281-1301, December.
    13. Haddow, Abigail & Hare, Chris & Hooley, John & Shakir, Tamarah, 2013. "Macroeconomic uncertainty: what is it, how can we measure it and why does it matter?," Bank of England Quarterly Bulletin, Bank of England, vol. 53(2), pages 100-109.
    14. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    15. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Density characteristics and density forecast performance: a panel analysis," Empirical Economics, Springer, vol. 48(3), pages 1203-1231, 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. Saygin Sahinoz & Evren Erdogan Cosar, 2020. "Quantifying uncertainty and identifying its impacts on the Turkish economy," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(2), pages 365-387, May.
    2. Elisa Giuliani & Federica Nieri & Andrea Vezzulli, 2019. "BEST IN CLASS BUT BIG WRONGDOERS: Exploring the financial performance and human rights infringe ments nexus in large emerging country companies," Discussion Papers 2019/250, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    3. Chris Redl, 2018. "Macroeconomic Uncertainty in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 86(3), pages 361-380, September.
    4. Rodrigo Cerda & Álvaro Silva & José Tomás Valente, 2018. "Impact of economic uncertainty in a small open economy: the case of Chile," Applied Economics, Taylor & Francis Journals, vol. 50(26), pages 2894-2908, June.
    5. Enrico Fabrizi & Chiara Mussida, 2020. "Assessing poverty persistence in households with children," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(4), pages 551-569, December.
    6. Mecikovsky, Ariel & Meier, Matthias, 2014. "Do plants freeze upon uncertainty shocks?," EconStor Preprints 100662, ZBW - Leibniz Information Centre for Economics.
    7. Gieseck Arne & Largent Yannis, 2016. "The Impact of Macroeconomic Uncertainty on Activity in the Euro Area," Review of Economics, De Gruyter, vol. 67(1), pages 25-52, May.
    8. Adriaan Kalwij, 2015. "Two tests for strict exogeneity in a correlated random effects panel data Tobit model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(2), pages 115-125, May.
    9. Đặng, Rey & Houanti, L’Hocine & Reddy, Krishna & Simioni, Michel, 2020. "Does board gender diversity influence firm profitability? A control function approach," Economic Modelling, Elsevier, vol. 90(C), pages 168-181.
    10. Redl, Chris, 2020. "Uncertainty matters: Evidence from close elections," Journal of International Economics, Elsevier, vol. 124(C).
    11. Johannes Geyer, 2011. "The Effect of Health and Employment Risks on Precautionary Savings," SOEPpapers on Multidisciplinary Panel Data Research 408, DIW Berlin, The German Socio-Economic Panel (SOEP).
    12. Pouliakas, Konstantinos & Panos, Georgios & Zangelidis, Alexandros, 2009. "The Inter-Related Dynamics of Dual Job Holding, Human Capital and Occupational Choice," MPRA Paper 16859, University Library of Munich, Germany.
    13. Widenhorn, Andreas & Salhofer, Klaus, 2014. "Differentiation in demand with different food retail formats," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182777, European Association of Agricultural Economists.
    14. Cesa-Bianchi, Ambrogio & Pesaran, M. Hashem & Rebucci, Alessandro, 2014. "Uncertainty and Economic Activity: A Global Perspective," IDB Publications (Working Papers) 6605, Inter-American Development Bank.
    15. Claeys, Peter & Vašíček, Bořek, 2019. "Transmission of uncertainty shocks: Learning from heterogeneous responses on a panel of EU countries," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 62-83.
    16. Ambrogio Cesa-Bianchi & M Hashem Pesaran & Alessandro Rebucci & Stijn Van Nieuwerburgh, 2020. "Uncertainty and Economic Activity: A Multicountry Perspective," The Review of Financial Studies, Society for Financial Studies, vol. 33(8), pages 3393-3445.
    17. Badi H. Baltagi & Peter Egger & Michael Pfaffermayr, 2014. "Panel Data Gravity Models of International Trade," CESifo Working Paper Series 4616, CESifo.
    18. Alexander Glas & Matthias Hartmann, 2022. "Uncertainty measures from partially rounded probabilistic forecast surveys," Quantitative Economics, Econometric Society, vol. 13(3), pages 979-1022, July.
    19. Aleksey Oshchepkov & Anna Shirokanova, 2020. "Multilevel Modeling For Economists: Why, When And How," HSE Working papers WP BRP 233/EC/2020, National Research University Higher School of Economics.
    20. López-Pérez, Víctor, 2016. "Does uncertainty affect non-response to the European Central Bank's survey of professional forecasters?," Economics Discussion Papers 2016-29, Kiel Institute for the World Economy (IfW Kiel).

    More about this item

    Keywords

    Non-response; uncertainty; Survey of Professional Forecasters; European Central Bank;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions

    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:zbw:ifweej:201625. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/iwkiede.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.