Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/rbz/wpaper/11058.html
   My bibliography  Save this paper

Firm level expectations and macroeconomic conditions underpinnings and disagreement

Author

Listed:
  • Monique Reid
  • Pierre Siklos
Abstract
There is abundant evidence that financial analysts inflation expectations differ in economically important ways from those of non-financial specialists. As a result, there is an increasing demand for firm-level data to more accurately capture the views of price setters. The unusually rich firm-level survey data from South Africa allow us to explore some of the ways in which the expectations of firms differ from those of other groups surveyed. We focus specifically on forecast disagreement, which can offer insights into the level of uncertainty reflected in the data and the degree to which expectations are anchored. We find that the divergence in inflation forecasts among respondents is partly explained by differences in how respondents believe the broader macroeconomy is evolving. The effect of aggregating the data in different ways is also considered. When we construct a new measure of macroeconomic disagreement that combines all the variables being forecast, we are able to see that forecasters responded sharply in early 2020 as the COVID-19 pandemic emerged.

Suggested Citation

  • Monique Reid & Pierre Siklos, 2024. "Firm level expectations and macroeconomic conditions underpinnings and disagreement," Working Papers 11058, South African Reserve Bank.
    • Handle: RePEc:rbz:wpaper:11058
    as

    Download full text from publisher

    File URL: https://www.resbank.co.za/content/dam/sarb/publications/working-papers/2024/firm-level-expectations-and-macroeconomic-conditions-underpinnings-and-disagreement.pdf
    File Function: Revision
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2022. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling, volume 43, pages 29-50, Emerald Group Publishing Limited.
    2. Òscar Jordà & Moritz Schularick & Alan M. Taylor, 2017. "Macrofinancial History and the New Business Cycle Facts," NBER Macroeconomics Annual, University of Chicago Press, vol. 31(1), pages 213-263.
    3. Henry Kaiser, 1958. "The varimax criterion for analytic rotation in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 23(3), pages 187-200, September.
    4. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
    5. Michael P. Clements & Ana Beatriz Galvão, 2014. "Measuring Macroeconomic Uncertainty: US Inflation and Output Growth," ICMA Centre Discussion Papers in Finance icma-dp2014-04, Henley Business School, University of Reading.
    6. Coibion, Olivier & Gorodnichenko, Yuriy & Kumar, Saten & Pedemonte, Mathieu, 2020. "Inflation expectations as a policy tool?," Journal of International Economics, Elsevier, vol. 124(C).
    7. N. Nergiz Dincer & Barry Eichengreen, 2014. "Central Bank Transparency and Independence: Updates and New Measures," International Journal of Central Banking, International Journal of Central Banking, vol. 10(1), pages 189-259, March.
    8. Carlos Capistr¡N & Allan Timmermann, 2009. "Disagreement and Biases in Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 365-396, March.
    9. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    10. 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.
    11. Binder, Carola Conces, 2015. "Whose expectations augment the Phillips curve?," Economics Letters, Elsevier, vol. 136(C), pages 35-38.
    12. Jonas Dovern & Matthias Hartmann, 2017. "Forecast performance, disagreement, and heterogeneous signal-to-noise ratios," Empirical Economics, Springer, vol. 53(1), pages 63-77, August.
    13. Jitmaneeroj, Boonlert & Lamla, Michael J. & Wood, Andrew, 2019. "The implications of central bank transparency for uncertainty and disagreement," Journal of International Money and Finance, Elsevier, vol. 90(C), pages 222-240.
    14. Reid, Monique & Siklos, Pierre & Plessis, Stan Du, 2021. "What drives household inflation expectations in South Africa? Demographics and anchoring under inflation targeting," Economic Systems, Elsevier, vol. 45(3).
    15. Glas, Alexander, 2020. "Five dimensions of the uncertainty–disagreement linkage," International Journal of Forecasting, Elsevier, vol. 36(2), pages 607-627.
    16. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    17. Strohsal, Till & Melnick, Rafi & Nautz, Dieter, 2016. "The time-varying degree of inflation expectations anchoring," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 62-71.
    18. Ruttachai Seelajaroen & Pornanong Budsaratragoon & Boonlert Jitmaneeroj, 2020. "Do monetary policy transparency and central bank communication reduce interest rate disagreement?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 368-393, April.
    19. Robert Rich & Joseph Tracy, 2021. "A Closer Look at the Behavior of Uncertainty and Disagreement: Micro Evidence from the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(1), pages 233-253, February.
    20. R?diger Bachmann & Steffen Elstner & Eric R. Sims, 2013. "Uncertainty and Economic Activity: Evidence from Business Survey Data," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(2), pages 217-249, April.
    21. Michael P. Clements, 2015. "Do US Macroeconomic Forecasters Exaggerate their Differences?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(8), pages 649-660, December.
    22. Christopher D. Carroll, 2003. "Macroeconomic Expectations of Households and Professional Forecasters," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(1), pages 269-298.
    23. Monique B. Reid & Pierre L. Siklos, 2022. "How Firms and Experts View The Phillips Curve: Evidence from Individual and Aggregate Data from South Africa," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 58(12), pages 3355-3376, September.
    24. Constantin Bürgi & Tara M. Sinclair, 2021. "What does forecaster disagreement tell us about the state of the economy?," Applied Economics Letters, Taylor & Francis Journals, vol. 28(1), pages 49-53, January.
    25. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.
    26. Gianna Boero & Jeremy Smith & Kenneth F. Wallis, 2015. "The Measurement and Characteristics of Professional Forecasters' Uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1029-1046, November.
    27. Guido Schultefrankenfeld, 2020. "Appropriate monetary policy and forecast disagreement at the FOMC," Empirical Economics, Springer, vol. 58(1), pages 223-255, January.
    28. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    29. Strohsal, Till & Winkelmann, Lars, 2015. "Assessing the anchoring of inflation expectations," Journal of International Money and Finance, Elsevier, vol. 50(C), pages 33-48.
    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. Pierre L. Siklos, 2016. "Forecast Disagreement and the Inflation Outlook: New International Evidence," IMES Discussion Paper Series 16-E-03, Institute for Monetary and Economic Studies, Bank of Japan.
    2. Siklos, Pierre, 2017. "What Has Publishing Inflation Forecasts Accomplished? Central Banks And Their Competitors," LCERPA Working Papers 0098, Laurier Centre for Economic Research and Policy Analysis, revised 01 Apr 2017.
    3. Conrad, Christian & Lahiri, Kajal, 2023. "Heterogeneous expectations among professional forecasters," ZEW Discussion Papers 23-062, ZEW - Leibniz Centre for European Economic Research.
    4. Kose, M. Ayhan & Matsuoka, Hideaki & Panizza, Ugo & Vorisek, Dana, 2019. "Inflation Expectations: Review and Evidence," CEPR Discussion Papers 13601, C.E.P.R. Discussion Papers.
    5. Gaurav Kumar Singh & Tathagata Bandyopadhyay, 2024. "Determinants of disagreement: Learning from inflation expectations survey of households," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 326-343, March.
    6. Fernandes, Cecilia Melo, 2021. "ECB communication as a stabilization and coordination device: evidence from ex-ante inflation uncertainty," Working Paper Series 2582, European Central Bank.
    7. Ruttachai Seelajaroen & Pornanong Budsaratragoon & Boonlert Jitmaneeroj, 2020. "Do monetary policy transparency and central bank communication reduce interest rate disagreement?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 368-393, April.
    8. Beckmann, Joscha & Czudaj, Robert L., 2023. "Perceived monetary policy uncertainty," Journal of International Money and Finance, Elsevier, vol. 130(C).
    9. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.
    10. repec:zbw:bofrdp:2022_005 is not listed on IDEAS
    11. Beckmann, Joscha & Czudaj, Robert L., 2024. "Uncertainty Shocks and Inflation: The Role of Credibility and Expectation Anchoring," MPRA Paper 119971, University Library of Munich, Germany.
    12. Czudaj, Robert L., 2022. "Heterogeneity of beliefs and information rigidity in the crude oil market: Evidence from survey data," European Economic Review, Elsevier, vol. 143(C).
    13. Li, You & Tay, Anthony, 2021. "The role of macroeconomic and policy uncertainty in density forecast dispersion," Journal of Macroeconomics, Elsevier, vol. 67(C).
    14. Glas, Alexander, 2020. "Five dimensions of the uncertainty–disagreement linkage," International Journal of Forecasting, Elsevier, vol. 36(2), pages 607-627.
    15. Ambrocio, Gene, 2020. "Inflationary household uncertainty shocks," Bank of Finland Research Discussion Papers 5/2020, Bank of Finland.
    16. Claveria, Oscar, 2022. "Global economic uncertainty and suicide: Worldwide evidence," Social Science & Medicine, Elsevier, vol. 305(C).
    17. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.
    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. Ambrocio, Gene, 2020. "Inflationary household uncertainty shocks," Research Discussion Papers 5/2020, Bank of Finland.
    20. Petar Soric & Oscar Claveria, 2021. "“Employment uncertainty a year after the irruption of the covid-19 pandemic”," AQR Working Papers 202104, University of Barcelona, Regional Quantitative Analysis Group, revised May 2021.
    21. Paul Hubert, 2014. "FOMC Forecasts as a Focal Point for Private Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(7), pages 1381-1420, October.

    More about this item

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

    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:rbz:wpaper:11058. 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: Jessica VanWyk (email available below). General contact details of provider: https://edirc.repec.org/data/rbagvza.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.