文章基本信息

标题：Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations
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作者：Oscar Claveria
期刊名称：Journal for Labour Market Research
电子版ISSN：2510-5027
出版年度：2019
卷号：53
期号：1
页码：1-10
DOI：10.1186/s12651-019-0253-4
出版社：Springer
摘要：This study aims to refine unemployment forecasts by incorporating the degree of consensus in consumers’ expectations. With this objective, we first model the unemployment rate in eight European countries using the step-wise algorithm proposed by Hyndman and Khandakar (J Stat Softw 27(3):1–22, 2008 ). The selected optimal autoregressive integrated moving average (ARIMA) models are then used to generate out-of-sample recursive forecasts of the unemployment rates, which are used as benchmark. Finally, we replicate the forecasting experiment including as predictors both an indicator of unemployment, based on the degree of agreement in consumer unemployment expectations, and a measure of disagreement based on the dispersion of expectations. In both cases, we obtain an improvement in forecast accuracy in most countries. These results reveal that the degree of agreement in consumers’ expectations contains useful information to predict unemployment rates, especially for the detection of turning points.
关键词：Unemployment; Forecasting; Leading indicator; Economic tendency surveys; Consumer expectations; C51; C52; C53; D12; E24