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Forecasting with Business and Consumer Survey Data

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  • Oscar Claveria

    (Regional Quantitative Analysis Research Group, Institute of Applied Economics Research, University of Barcelona, 08034 Barcelona, Spain)

Abstract

In a context of growing uncertainty caused by the COVID-19 pandemic, the opinion of businesses and consumers about the expected development of the main variables that affect their activity becomes essential for economic forecasting. In this paper, we review the research carried out in this field, placing special emphasis on the recent lines of work focused on the exploitation of the predictive content of economic tendency surveys. The study concludes with an evaluation of the forecasting performance of quarterly unemployment expectations for the euro area, which are obtained by means of machine learning methods. The analysis reveals the potential of new analytical techniques for the analysis of business and consumer surveys for economic forecasting.

Suggested Citation

  • Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
  • Handle: RePEc:gam:jforec:v:3:y:2021:i:1:p:8-134:d:500803
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    1. Dasgupta, Susmita & Lahiri, Kajal, 1992. "A Comparative Study of Alternative Methods of Quantifying Qualitative Survey Responses Using NAPM Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 391-400, October.
    2. 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.
    3. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    4. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    5. Smith, Jeremy & McAleer, Michael, 1995. "Alternative Procedures for Converting Qualitative Response Data to Quantitative Expectations: An Application to Australian Manufacturing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 165-185, April-Jun.
    6. Altug, Sumru & Çakmaklı, Cem, 2016. "Forecasting inflation using survey expectations and target inflation: Evidence for Brazil and Turkey," International Journal of Forecasting, Elsevier, vol. 32(1), pages 138-153.
    7. James Mitchell & Richard J. Smith & Martin R. Weale, 2002. "Quantification of Qualitative Firm-Level Survey Data," Economic Journal, Royal Economic Society, vol. 112(478), pages 117-135, March.
    8. Oscar Claveria, 2018. "“A new metric of consensus for Likert scales”," AQR Working Papers 201810, University of Barcelona, Regional Quantitative Analysis Group, revised Oct 2018.
    9. Joachim Zuckarelli, 2015. "A new method for quantification of qualitative expectations," Economics and Business Letters, Oviedo University Press, vol. 4(3), pages 123-128.
    10. Junttila, Juha & Vataja, Juuso, 2018. "Economic policy uncertainty effects for forecasting future real economic activity," Economic Systems, Elsevier, vol. 42(4), pages 569-583.
    11. Bekaert, Geert & Hoerova, Marie & Lo Duca, Marco, 2013. "Risk, uncertainty and monetary policy," Journal of Monetary Economics, Elsevier, vol. 60(7), pages 771-788.
    12. Caruso, Alberto, 2018. "Nowcasting with the help of foreign indicators: The case of Mexico," Economic Modelling, Elsevier, vol. 69(C), pages 160-168.
    13. Bovi, Maurizio, 2013. "Are the representative agent’s beliefs based on efficient econometric models?," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 633-648.
    14. Meinen, Philipp & Roehe, Oke, 2017. "On measuring uncertainty and its impact on investment: Cross-country evidence from the euro area," European Economic Review, Elsevier, vol. 92(C), pages 161-179.
    15. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Using survey data to forecast real activity with evolutionary algorithms. A cross-country analysis," Journal of Applied Economics, Universidad del CEMA, vol. 20, pages 329-349, November.
    16. 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.
    17. Common, Michael S, 1985. "Testing for Rational Expectations with Qualitative Survey Data," The Manchester School of Economic & Social Studies, University of Manchester, vol. 53(2), pages 138-148, June.
    18. Kaufmann, Daniel & Scheufele, Rolf, 2017. "Business tendency surveys and macroeconomic fluctuations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 878-893.
    19. Reichlin, Lucrezia & Giannone, Domenico & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
    20. Mitchell, James & Mouratidis, Kostas & Weale, Martin, 2007. "Uncertainty in UK manufacturing: Evidence from qualitative survey data," Economics Letters, Elsevier, vol. 94(2), pages 245-252, February.
    21. Clements, Michael P. & Galvão, Ana Beatriz, 2017. "Model and survey estimates of the term structure of US macroeconomic uncertainty," International Journal of Forecasting, Elsevier, vol. 33(3), pages 591-604.
    22. Juhro, Solikin M. & Iyke, Bernard Njindan, 2020. "Consumer confidence and consumption expenditure in Indonesia," Economic Modelling, Elsevier, vol. 89(C), pages 367-377.
    23. Kapetanios, George & Marcellino, Massimiliano & Papailias, Fotis, 2016. "Forecasting inflation and GDP growth using heuristic optimisation of information criteria and variable reduction methods," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 369-382.
    24. Blaskowitz, Oliver & Herwartz, Helmut, 2011. "On economic evaluation of directional forecasts," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1058-1065, October.
    25. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    26. Pesaran, M Hashem, 1985. "Formation of Inflation Expectations in British Manufacturing Industries," Economic Journal, Royal Economic Society, vol. 95(380), pages 948-975, December.
    27. Balcombe, Kelvin, 1996. "The Carlson-Parkin method applied to NZ price expectations using QSBO survey data," Economics Letters, Elsevier, vol. 51(1), pages 51-57, April.
    28. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    29. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies," Eastern European Economics, Taylor & Francis Journals, vol. 54(2), pages 171-189, March.
    30. repec:iab:iabjlr:v:53:i:1:p:art.3 is not listed on IDEAS
    31. Kajal Lahiri & Xuguang Sheng, 2010. "Measuring forecast uncertainty by disagreement: The missing link," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 514-538.
    32. Petar Soric & Ivana Lolic, 2017. "Economic uncertainty and its impact on the Croatian economy," Public Sector Economics, Institute of Public Finance, vol. 41(4), pages 443-477.
    33. 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.
    34. Michela Nardo, 2003. "The Quantification of Qualitative Survey Data: A Critical Assessment," Journal of Economic Surveys, Wiley Blackwell, vol. 17(5), pages 645-668, December.
    35. Lahiri, Kajal & Teigland, Christie, 1987. "On the normality of probability distributions of inflation and GNP forecasts," International Journal of Forecasting, Elsevier, vol. 3(2), pages 269-279.
    36. Oscar Claveria & Ivana Lolic & Enric Monte & Salvador Torra & Petar Soric, 2020. "“Economic determinants of employment sentiment: A socio-demographic analysis for the euro area”," AQR Working Papers 2012001, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2020.
    37. Batchelor, Roy A & Orr, Adrian B, 1988. "Inflation Expectations Revisited," Economica, London School of Economics and Political Science, vol. 55(219), pages 317-331, August.
    38. Mitchell, James, 2002. "The use of non-normal distributions in quantifying qualitative survey data on expectations," Economics Letters, Elsevier, vol. 76(1), pages 101-107, June.
    39. Klein, Lawrence R. & Özmucur, Süleyman, 2010. "The use of consumer and business surveys in forecasting," Economic Modelling, Elsevier, vol. 27(6), pages 1453-1462, November.
    40. Binding, Garret & Dibiasi, Andreas, 2017. "Exchange rate uncertainty and firm investment plans evidence from Swiss survey data," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 1-27.
    41. Jan Marc Berk, 1999. "Measuring inflation expectations: a survey data approach," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1467-1480.
    42. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    43. Christian Dreger & Konstantin Arkadievich Kholodilin, 2013. "Forecasting Private Consumption by Consumer Surveys," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(1), pages 10-18, January.
    44. Batchelor, R. A., 1981. "Aggregate expectations under the stable laws," Journal of Econometrics, Elsevier, vol. 16(2), pages 199-210, June.
    45. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.
    46. Dovern, Jonas, 2015. "A multivariate analysis of forecast disagreement: Confronting models of disagreement with survey data," European Economic Review, Elsevier, vol. 80(C), pages 16-35.
    47. 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.
    48. Binder, Carola Conces, 2015. "Whose expectations augment the Phillips curve?," Economics Letters, Elsevier, vol. 136(C), pages 35-38.
    49. Rina Rosenblatt-Wisch & Rolf Scheufele, 2015. "Quantification and characteristics of household inflation expectations in Switzerland," Applied Economics, Taylor & Francis Journals, vol. 47(26), pages 2699-2716, June.
    50. Sarah Gelper & Christophe Croux, 2010. "On the Construction of the European Economic Sentiment Indicator," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(1), pages 47-62, February.
    51. Domenico Giannone & Lucrezia Reichlin & David Small, 2008. "Nowcasting: the real time informational content of macroeconomic data releases," ULB Institutional Repository 2013/6409, ULB -- Universite Libre de Bruxelles.
    52. 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.
    53. Stephen Bruestle & W. Mark Crain, 2015. "A mean-variance approach to forecasting with the consumer confidence index," Applied Economics, Taylor & Francis Journals, vol. 47(23), pages 2430-2444, May.
    54. Petar Sorić, 2018. "Consumer confidence as a GDP determinant in New EU Member States: a view from a time-varying perspective," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(2), pages 261-282, May.
    55. Frieder Mokinski & Xuguang (Simon) Sheng & Jingyun Yang, 2015. "Measuring Disagreement in Qualitative Expectations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(5), pages 405-426, August.
    56. Ivana Lolić & Petar Sorić, 2018. "A critical re-examination of the Carlson–Parkin method," Applied Economics Letters, Taylor & Francis Journals, vol. 25(19), pages 1360-1363, November.
    57. Das, Abhiman & Lahiri, Kajal & Zhao, Yongchen, 2019. "Inflation expectations in India: Learning from household tendency surveys," International Journal of Forecasting, Elsevier, vol. 35(3), pages 980-993.
    58. Ulrike Malmendier & Stefan Nagel, 2016. "Learning from Inflation Experiences," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(1), pages 53-87.
    59. Santiago Pinto & Pierre-Daniel Sarte & Robert Sharp, 2020. "The Information Content and Statistical Properties of Diffusion Indexes," International Journal of Central Banking, International Journal of Central Banking, vol. 16(4), pages 47-99, September.
    60. Tutsirai Sakutukwa & Hee-Seung Yang, 2018. "The role of uncertainty in forecasting employment by skill and industry," Applied Economics Letters, Taylor & Francis Journals, vol. 25(18), pages 1288-1291, October.
    61. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
    62. O Claveria & E Pons & J Surinach, 2006. "Quantification of Expectations. Are They Useful for Forecasting Inflation?," Economic Issues Journal Articles, Economic Issues, vol. 11(2), pages 19-38, September.
    63. Fishe, Raymond P. H. & Lahiri, Kajal, 1981. "On the estimation of inflationary expectations from qualitative responses," Journal of Econometrics, Elsevier, vol. 16(1), pages 89-102, May.
    64. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Assessment of the effect of the financial crisis on agents’ expectations through symbolic regression," Applied Economics Letters, Taylor & Francis Journals, vol. 24(9), pages 648-652, May.
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    1. Petar Soric & Enric Monte & Salvador Torra & Oscar Claveria, 2022. "“Density forecasts of inflation using Gaussian process regression models”," AQR Working Papers 202207, University of Barcelona, Regional Quantitative Analysis Group, revised Jul 2022.
    2. Sergey V. Arzhenovskiy, 2024. "Forecasting GDP Dynamics Based on the Bank of Russia’s Enterprise Monitoring Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 1, pages 31-44, February.

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