Skip to main content
SpringerLink
Log in

On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables

  • Research Paper
  • Published:
Journal of Business Cycle Research Aims and scope Submit manuscript

Abstract

We analyse the effects of aggregating the level of disagreement in survey-based expectations. With this aim, we construct several indicators based on two metrics of disagreement: the standard deviation of the balance and a geometric measure of discrepancy. We use data from business and consumer surveys in eleven European countries and the Euro Area. We evaluate the dynamic response of economic growth to shocks in agents’ uncertainty gauged by the discrepancy measures in a bivariate vector autoregressive framework. We find that while the effect on economic activity to a shock in aggregate discrepancy is always negative for firms’ disagreement, the effect to consumers’ disagreement is positive in all countries except Italy. To shed some light regarding the effect of aggregating disagreement both across variables and economic agents on forecast accuracy, we also examine the predictive performance of the discrepancy indicators, using them to generate out-of-sample forecasts of economic growth. We do not find evidence that the aggregation of disagreement improves forecast accuracy. These findings are especially relevant when using cross-sectional dispersion of survey-based expectations of firms and households.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Availability of Data and Material

The datasets used and/or analysed during the current study are: The Joint Harmonised EU Consumer Survey conducted by the European Commission, which can be freely downloaded at: https://ec.europa.eu/info/business-economy-euro/indicators-statistics/economic-databases/business-and-consumer-surveys_en. Gross Domestic Product provided by Eurostat at: https://ec.europa.eu/eurostat/web/national-accounts/data/main-tables.

References

  • Alessandri, P., & Mumtaz, H. (2019). Financial regimes and uncertainty shocks. Journal of Monetary Economics, 101, 31–46.

    Google Scholar 

  • Alexopoulos, M., & Cohen, J. (2015). The power of print: Uncertainty shocks, markets, and the economy. International Review of Economics and Finance, 40, 8–28.

    Google Scholar 

  • Altig, D., Barrero, J. M., Bloom, N., Davis, S. J., Meyer, B. H., & Parker, N. (2020). Surveying business uncertainty. Journal of Econometrics. (forthcoming).

  • Atalla, T., Joutz, F., & Pierru, A. (2016). Does disagreement among oil price forecasters reflect volatility? Evidence form the ECB surveys. International Journal of Forecasting, 32(4), 1178–1192.

    Google Scholar 

  • Bachmann, R., Carstensen, K., Lautenbacher, S., & Schneider, M. (2018). Uncertainty and change: Survey evidence of firms’ subjective beliefs. Technical Report.

  • Bachmann, R., Carstensen, K., Lautenbacher, S., & Schneider, M. (2020). Uncertainty is more than risk—Survey evidence on Knightian and Bayesian firms. Technical Report.

  • Bachmann, R., Elstner, S., & Sims, E. R. (2013). Uncertainty and economic activity: Evidence from business survey data. American Economic Journal: Macroeconomics, 5(2), 217–249.

    Google Scholar 

  • Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. Quarterly Journal of Economics, 131(4), 1593–1636.

    Google Scholar 

  • Basu, S., & Bundick, B. (2017). Uncertainty shocks in a model of effective demand. Econometrica, 85(3), 937–958.

    Google Scholar 

  • Bekaert, G., Hoerova, M., & Lo Duca, M. (2013). Risk, uncertainty and monetary policy. Journal of Monetary Economics, 60(7), 771–788.

    Google Scholar 

  • Binding, G., & Dibiasi, A. (2017). Exchange rate uncertainty and firm investment plans evidence from Swiss survey data. Journal of Macroeconomics, 51, 1–27.

    Google Scholar 

  • Bloom, N. (2009). The impact of uncertainty shocks. Econometrica, 77(3), 623–685.

    Google Scholar 

  • Caldara, D., Fuentes-Albero, C., Gilchrist, S., & Zakrajšek, E. (2016). The macroeconomic impact of financial and uncertainty shocks. European Economic Review, 88, 185–207.

    Google Scholar 

  • Carriero, A., Clark, T. E., & Marcellino, M. (2018). Measuring uncertainty and its impact on the economy. Review of Economics and Statistics, 100(5), 799–815.

    Google Scholar 

  • Cascaldi-Garcia, D., Sarisoy, C., Londono, J. M., Rogers, J., Datta, D., Ferreira, T., et al. (2020). What is certain about uncertainty?. International Finance Discussion Papers 1294. Washington: Board of Governors of the Federal Reserve

  • Castelnuovo, E. (2019). Domestic and global uncertainty: A survey and some new results. CESifo Working Paper Series 7900.

  • Cerda, R., Silva, A., & Valente, J. T. (2018). Impact of economic uncertainty in a small open economy: The case of Chile. Applied Economics, 50(26), 2894–2908.

    Google Scholar 

  • Charles, A., Darné, O., & Tripier, F. (2018). Uncertainty and the macroeconomy: Evidence from an uncertainty composite indicator. Applied Economics, 50(10), 1093–1107.

    Google Scholar 

  • Chuliá, H., Guillén, M., & Uribe, J. M. (2017). Measuring uncertainty in the stock market. International Review of Economics and Finance, 48, 18–33.

    Google Scholar 

  • Claveria, O. (2018). A new metric of consensus for Likert scales. IREA Working Papers 2018/21. University of Barcelona, Institute of Applied Economics Research (IREA).

  • Claveria, O. (2019). A new consensus-based unemployment indicator. Applied Economics Letters, 26(10), 812–817.

    Google Scholar 

  • Claveria, O. (2020). Uncertainty indicators based on expectations of business and consumer surveys. Empirica. (forthcoming).

  • Claveria, O., Monte, E., & Torra, S. (2019). Economic uncertainty: A geometric indicator of discrepancy among experts’ expectations. Social Indicators Research, 193(1), 91–114.

    Google Scholar 

  • Clements, M., & Galvão, A. B. (2017). Model and survey estimates of the term structure of US macroeconomic uncertainty. International Journal of Forecasting, 33(3), 591–604.

    Google Scholar 

  • Crespo, J., Huber, F., & Onorante, L. (2017). The macroeconomic effects of international uncertainty shocks. WU Working Paper Series 245.

  • Dibiasi, A., & Iselin, D. (2019). Measuring Knightian uncertainty. KOF Working Papers 456.

  • Dibiasi, A., & Sarferaz, S. (2020). Measuring macroeconomic uncertainty: A cross-country analysis. KOF Working Papers 479, 1–44.

  • Diebold, F. X., & Mariano, R. (1995). Comparing predictive accuracy. Journal of Business and Economic Statistics, 13(3), 253–263.

    Google Scholar 

  • Dovern, J., Fritsche, U., & Slacalek, J. (2012). Disagreement among forecasters in G7 countries. Review of Economic and Statistics, 94(4), 1081–1096.

    Google Scholar 

  • European Commission. (2020). Business and consumer surveys. https://ec.europa.eu/info/business-economy-euro/indicators-statistics/economic-databases/business-and-consumer-surveys_en. Accessed 3 Sep 2020.

  • Eurostat. (2020). Database. https://ec.europa.eu/eurostat/web/national-accounts/data/main-tables. Accessed 3 Sep 2020.

  • Girardi, A., & Reuter, A. (2017). New uncertainty measures for the euro area using survey data. Oxford Economic Papers, 69(1), 278–300.

    Google Scholar 

  • Glas, A. (2020). Five dimensions of the uncertainty—Disagreement linkage. International Journal of Forecasting, 36(2), 607–627.

    Google Scholar 

  • Glocker, C., & Hölzl, W. (2019). Assessing the economic content of direct and indirect business uncertainty measures. WIFO Working Paper 576/2019.

  • Gupta, R., Lau, C. K. M., & Wohar, M. E. (2019). The impact of US uncertainty on the Euro area in good and bad times: Evidence from a quantile structural vector autoregressive model. Empirica, 46(2), 353–368.

    Google Scholar 

  • Hailemariam, A., & Smyth, R. (2019). What drives volatility in natural gas prices? Energy Economics, 80, 731–742.

    Google Scholar 

  • Harvey, D. I., Leybourne, S. J., & Newbold, P. (1997). Testing the equality of prediction mean squared errors. International Journal of Forecasting, 13(2), 281–291.

    Google Scholar 

  • Hauzenberger, N., Böck, M., Pfarrhofer, M., Stelzer, A., & Zens, G. (2018). Implications of macroeconomic volatility in the Euro area. ArXiv preprint, 1801, 02925.

    Google Scholar 

  • Istiak, K., & Serletis, A. (2018). Economic policy uncertainty and real output: Evidence from the G7 countries. Applied Economics, 50(39), 4222–4233.

    Google Scholar 

  • Jo, S., & Sekkel, R. (2019). Macroeconomic uncertainty through the lens of professional forecasters. Journal of Business & Economic Statistics, 37(3), 436–446.

    Google Scholar 

  • Junttila, J., & Vataja, J. (2018). Economic policy uncertainty effects for forecasting future real economic activity. Economic Systems, 42(4), 569–583.

    Google Scholar 

  • Jurado, K., Ludvigson, S., & Ng, S. (2015). Measuring uncertainty. American Economic Review, 105(3), 1177–1216.

    Google Scholar 

  • Knight, F. (1921). Risk, uncertainty, and profit. Boston: Houghton Mifflin.

    Google Scholar 

  • Kozeniauskas, N., Orlik, A., & Veldkamp, L. (2016). The common origin of uncertainty shocks. NBER Working Paper 22384. National Bureau of Economic Research (NBER).

  • Krüger, F., & Nolte, I. (2016). Disagreement versus uncertainty: Evidence from distribution forecasts. Journal of Banking & Finance, Supplement, 72, S172–S186.

    Google Scholar 

  • Lahiri, K., & Sheng, X. (2010). Measuring forecast uncertainty by disagreement: The missing link. Journal of Applied Econometrics, 25(4), 514–538.

    Google Scholar 

  • Meinen, P., & Roehe, O. (2017). On measuring uncertainty and its impact on investment: Cross-country evidence from the euro area. European Economic Review, 92, 161–179.

    Google Scholar 

  • Mokinski, F., Sheng, X., & Yang, J. (2015). Measuring disagreement in qualitative expectations. Journal of Forecasting, 34(5), 405–426.

    Google Scholar 

  • Morikawa, M. (2019). Uncertainty over production forecasts: An empirical analysis using monthly quantitative survey data. Journal of Macroeconomics, 60, 163–179.

    Google Scholar 

  • Oinonen, S., & Paloviita, M. (2017). How informative are aggregated inflation expectations? Evidence from the ECB Survey of Professional Forecasters. Journal of Business Cycle Research, 13(2), 139–163.

    Google Scholar 

  • Ozturk, E. O., & Sheng, X. S. (2018). Measuring global and country-specific uncertainty. Journal of International Money and Finance, 88, 276–295.

    Google Scholar 

  • Paloviita, M., & Viren, M. (2014). Inflation and output growth uncertainty in individual survey expectations. Empirica, 41(1), 69–81.

    Google Scholar 

  • Poncela, P., & Senra, E. (2017). Measuring uncertainty and assessing its predictive power in the euro area. Empirical Economics, 53(1), 165–182.

    Google Scholar 

  • Rossi, B., & Sekhposyan, T. (2015). Macroeconomic uncertainty indices based on nowcast and forecast error distributions. American Economic Review, 105(5), 650–655.

    Google Scholar 

  • Rossi, B., & Sekhposyan, T. (2017). Macroeconomic uncertainty indices for the euro area and its individual member countries. Empirical Economics, 53(1), 41–62.

    Google Scholar 

  • Rossi, B., Sekhposyan, T., & Souprez, M. (2020). Understanding the sources of macroeconomic uncertainty. Barcelona GSE Working Paper 920. Barcelona Graduate School of Economics (GSE).

  • Sahinoz, S., & Cosar, E. E. (2019). Quantifying uncertainty and identifying its impacts on the Turkish economy. Empirica, 47(2), 365–387.

    Google Scholar 

  • Sorić, P., & Lolić, I. (2017). Economic uncertainty and its impact on the Croatian economy. Public Sector Economics, 41(4), 443–477.

    Google Scholar 

  • Yıldırım-Karaman, S. (2017). Uncertainty shocks, central bank, characteristics and business cycles. Economic Systems, 41(3), 379–388.

    Google Scholar 

  • Zarnowitz, V., & Lambros, L. A. (1987). Consensus and uncertainty in economic prediction. Journal of Political Economy, 95(3), 591–621.

    Google Scholar 

Download references

Funding

This research received no financial support.

Author information

Authors and Affiliations

  1. AQR-IREA, University of Barcelona, Diagonal, 690, 08034, Barcelona, Spain

    Oscar Claveria

Authors
  1. Oscar Claveria
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Oscar Claveria.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Code Availability

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

Figure 6 contains the evolution of the disagreement indicators presented in Sect. 2 computed with the geometric indicator of discrepancy (G).

Fig. 6
figure 6figure 6figure 6

Evolution of disagreement indicators (2003:01–2020:08)

Full size image

Table 5 presents the results of the estimation of the VAR models.

Table 5 Estimation of VAR models
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Claveria, O. On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables. J Bus Cycle Res 17, 1–26 (2021). https://doi.org/10.1007/s41549-020-00050-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41549-020-00050-2

Keywords

JEL Classification

Search

Navigation