A new metric of consensus for Likert-type questionnaires: An application to forecast the unemployment rate using the degree of agreement in consumer expectations

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A new metric of consensus for Likert-type questionnaires: An application to forecast the unemployment rate using the degree of agreement in consumer expectations

Authors
Type
Conference
Journal
39th International Symposium on Forecasting
Publication Date
Jun 14, 2019
Source
MyScienceWork
License
Green

Abstract

In this study we present a metric of consensus for Likert-type scales. The statistic gives the level of agreement obtained as the percentage of consensus among respondents. The proposed analytical framework allows to construct a positional indicator that gives the degree of agreement for each item and for any given number of reply options. In order to assess the performance of the proposed metric of consensus we first design a simulation experiment in which compare the sampling distribution of the percentage of agreement for three and for five response alternatives, finding that the distribution of the statistic for three reply options shows a higher level of granularity and dispersion. This notion is further confirmed when computing the evolution of the metric for consumers' unemployment expectations. We conduct an iterated forecasting experiment to test whether the inclusion of the degree of agreement in households' expectations improves out-of-sample forecast accuracy of the unemployment rate in eight European countries. We find evidence that the level of consensus among households contains useful information to predict unemployment rates in most countries. The obtained results show the potential of agreement metrics to track the evolution of economic variables.

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