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A new consensus-based unemployment indicator

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  • Oscar Claveria

Abstract

In this study we present a novel approach to measure the level of consensus among agents’ expectations. The proposed framework allows us to design a positional indicator that gives the percentage of agreement between survey expectations. While other aggregation methods such as the balance, which is constructed as the difference between the percentages of respondents giving positive and negative replies, explicitly omit the neutral information, the proposed metric allows synthesizing the information coming from all response categories, including the percentage of respondents who do not expect any change. In order to assess the performance of the proposed measure of consensus, we compare its ability to track the evolution of unemployment to that of the balance in eight European countries. With this aim, we scale both measures to generate one-period ahead forecasts of the unemployment rate. We find that the consensus-based unemployment indicator outperforms the balance in all countries except Denmark and Sweden, which suggests that the level of agreement among agents’ expectations is a good predictor of unemployment.

Suggested Citation

  • Oscar Claveria, 2019. "A new consensus-based unemployment indicator," Applied Economics Letters, Taylor & Francis Journals, vol. 26(10), pages 812-817, June.
    • Handle: RePEc:taf:apeclt:v:26:y:2019:i:10:p:812-817
    DOI: 10.1080/13504851.2018.1497846
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    Cited by:

    1. 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(1), pages 1-3.
    2. Blanchflower, David G. & Bryson, Alex, 2021. "The Economics of Walking About and Predicting Unemployment," GLO Discussion Paper Series 922, Global Labor Organization (GLO).
    3. Oscar Claveria & Enric Monte & Salvador Torra, 2020. "Spectral analysis of business and consumer survey data," IREA Working Papers 202006, University of Barcelona, Research Institute of Applied Economics, revised May 2020.
    4. Oscar Claveria, 2020. "“Measuring and assessing economic uncertainty”," AQR Working Papers 2012003, University of Barcelona, Regional Quantitative Analysis Group, revised Jul 2020.
    5. Martin Kenyeres & Jozef Kenyeres, 2023. "Distributed Average Consensus Algorithms in d-Regular Bipartite Graphs: Comparative Study," Future Internet, MDPI, vol. 15(5), pages 1-24, May.
    6. Petar Soric & Oscar Claveria, 2021. ""Employment uncertainty a year after the irruption of the covid-19 pandemic"," IREA Working Papers 202112, University of Barcelona, Research Institute of Applied Economics, revised May 2021.
    7. Oscar Claveria, 2020. "Business and consumer uncertainty in the face of the pandemic: A sector analysis in European countries," Papers 2012.02091, arXiv.org.
    8. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    9. Blanchflower, David G. & Bryson, Alex, 2023. "Labour Market Expectations and Unemployment in Europe," IZA Discussion Papers 15905, Institute of Labor Economics (IZA).
    10. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.

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