Uncertainty indicators based on expectations of business and consumer surveys
In this study we evaluate the dynamic response of different macroeconomic variables to shocks in agents' perception of three dimensions of uncertainty (economic, inflation and employment). First, we apply a geometric indicator to compute the proportion of disagreement in business and consumer e...
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:2445/176750 |
| Acceso en línea: | https://hdl.handle.net/2445/176750 |
| Access Level: | acceso abierto |
| Palabra clave: | Incertesa Indicadors econòmics Enquestes de consum Inflació Uncertainty Economic indicators Consumer surveys Inflation |
| Sumario: | In this study we evaluate the dynamic response of different macroeconomic variables to shocks in agents' perception of three dimensions of uncertainty (economic, inflation and employment). First, we apply a geometric indicator to compute the proportion of disagreement in business and consumer expectations of eight European countries and the Euro Area. Next, we use a bivariate vector autoregressive framework to estimate the impulse response functions to innovations in disagreement. While we find an adverse reaction in unemployment rates to shocks in discrepancy, results differ markedly between disagreement in business and in consumer surveys with regard to economic growth and inflation: shocks to manufacturing production discrepancy lead to a decrease in economic activity, as opposed to shocks to consumer economic discrepancy; and the opposite in the case of a shock in the perception of price uncertainty. Finally, we perform a forecasting exercise to assess the predictive performance of the disagreement indicators for different time horizons, obtaining more accurate out-of-sample recursive forecasts of economic growth with the indicators of discrepancy of manufacturing firms and, of unemployment with the indicators of consumer discrepancy. When compared to recursive autoregressive predictions used as a benchmark, we find that vector autoregressions with industry discrepancy tend to outperform the benchmark in more cases that models with indicators of consumer discrepancy. |
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