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RESEARCH PAPER
Consensus in Business Tendency Surveys: Comparison of Alternative Measures
 
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SGH Warsaw School of Economics, Poland
 
 
Submission date: 2023-08-01
 
 
Final revision date: 2023-09-28
 
 
Acceptance date: 2023-10-18
 
 
Publication date: 2023-12-29
 
 
Corresponding author
Emilia Tomczyk   

SGH Warsaw School of Economics, Poland
 
 
GNPJE 2023;316(4):17-29
 
KEYWORDS
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ABSTRACT
In this article, we aim to compare various methods of evaluating consensus in qualitative business surveys in which respondents express expectations on the ordered scale. A reliable method of measuring degree of consensus would provide researchers with valuable information, offering a leading indicator of respondent sentiment. However, there is no single generally accepted mathematical measure applicable to evaluating agreement among respondents. Several approaches are mentioned in previous studies, including indicators based on statistical dispersion, Shannon entropy, and multi-dimensional simplex. We present measures of consensus defined in literature and discuss their advantages and limitations. We then employ these indicators to expectations expressed in Polish business tendency survey in manufacturing, and compare results across various economic variables. In several cases, we find patterns in the behavior of measures of consensus: expected prices are characterized by the highest degree of consensus among respondents, and expected production and orders – by the lowest degree of consensus. We also find linkages between the degree of consensus and degree of optimism among respondents as measured by the balance statistic for prices, employment, and general business conditions.
 
REFERENCES (15)
1.
Adamowicz E., Walczyk K. [2017], Zaburzenia cykliczności aktywności gospodarczej w Polsce w świetle wyników badania koniunktury gospodarczej IRG SGH, Prace i Materiały Instytutu Rozwoju Gospodarczego SGH, 101.
 
2.
Bachmann R., Elstner S., Sims E. R. [2013], Uncertainty and Economic Activity: Evidence from Business Survey Data, American Economic Journal: Macroeconomics, American Economic Association, 5 (2): 217–249.
 
3.
Claveria O. [2019], Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations, Journal for Labour Market Research, 53 (3): 1–10.
 
4.
Claveria O., Monte E., Torra S. [2019], Economic Uncertainty: A Geometric Indicator of Discrepancy Among Experts’ Expectations, Social Indicators Research, 143: 95–114.
 
5.
Conflitti C. [2011], Measuring Uncertainty and Disagreement in the European Survey of Professional Forecasters, ECARES (Université libre de Bruxelles) Working Paper.
 
6.
Daly A. J., Baetens J. M., De Baets B. [2018], Ecological Diversity: Measuring the Unmeasurable, Mathematics, 6/7 (119), https://doi.org/10.3390/math60....
 
7.
D’Amico S., Orphanides A. [2008], Uncertainty and Disagreement in Economic Forecasting, Finance and Economics Discussion Series No. 2008–56, Divisions of Research & Statistics and Monetary Affairs, Federal Reserve Board, Washington, D. C.
 
8.
Kowalczyk B., Tomczyk E. [2008], Rationality of Expectations of Industrial Enterprises – Analysis Based on Business Tendency Surveys with Item Non-response, Bank i Kredyt, 8: 3–11.
 
9.
Kowalczyk B., Tomczyk E. [2010], Influence of non-response in business tendency surveys on properties of expectations, Statistics in Transition (New Series), 11 (2): 403–422.
 
10.
Krüger F., Nolte I. [2016], Disagreement versus uncertainty: Evidence from distribution forecasts, Journal of Banking and Finance, 72: S172 – S186.
 
11.
Tastle W. J., Wierman M. J. [2006], Consensus and dissention: A measure of ordinal dispersion, International Journal of Approximate Reasoning, 45: 531–545.
 
12.
Tomczyk E. [2011], Application of measures of entropy, information content and dissimilarity of structures to business tendency survey data, Przegląd Statystyczny, 58 (1–2): 88–101.
 
13.
Tomczyk E. [2023], Dynamics of survey expectations and assessments before and during the pandemic: entropy and dissimilarity measures applied to business tendency survey data, Statistic in Transition (New Series), 24 (2): 185–199.
 
14.
Wójciak M. [2015], Metody oceny zgodności opinii ekspertów na potrzeby badania foresight, Studia Ekonomiczne, 220: 58–77.
 
15.
Zarnowitz V., Lambros L. A. [1987], Consensus and Uncertainty in Economic Prediction, Journal of Political Economy, 95 (3): 591–621.
 
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