How Informative are Aggregated Inflation Expectations? Evidence from the ECB Survey of Professional Forecasters

Oinonen, Sami; Paloviita, Maritta

doi:10.2139/ssrn.2784182

Cited by 2 publications

(2 citation statements)

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“…The ex-post nature of the latter approach has generated a strand of research that looks for ways to approximate economic uncertainty ex-ante. Most of this research makes use of quantitative expectations made by professional forecasters (Clements and Galvão 2017;Dovern et al 2012;Krüger and Nolte 2016;Lahiri and Sheng 2010;Oinonen and Paloviita 2017). Jo and Sekkel (2019) used the forecast errors of consensus survey forecasts of various economic indicators to capture a real-time measure of uncertainty surrounding subjective forecasts.…”

Section: Introductionmentioning

confidence: 99%

On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables

Clavería

2020

J Bus Cycle Res

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We analyse the effects of aggregating the level of disagreement in survey-based expectations. With this aim, we construct several indicators based on two metrics of disagreement: the standard deviation of the balance and a geometric measure of discrepancy. We use data from business and consumer surveys in eleven European countries and the Euro Area. We evaluate the dynamic response of economic growth to shocks in agents' uncertainty gauged by the discrepancy measures in a bivariate vector autoregressive framework. We find that while the effect on economic activity to a shock in aggregate discrepancy is always negative for firms' disagreement, the effect to consumers' disagreement is positive in all countries except Italy. To shed some light regarding the effect of aggregating disagreement both across variables and economic agents on forecast accuracy, we also examine the predictive performance of the discrepancy indicators, using them to generate out-of-sample forecasts of economic growth. We do not find evidence that the aggregation of disagreement improves forecast accuracy. These findings are especially relevant when using cross-sectional dispersion of survey-based expectations of firms and households.

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Section: Introductionmentioning

confidence: 99%

On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables

Clavería

2020

J Bus Cycle Res

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“…Disagreement measures based on survey expectations make use of prospective information, as agents are asked about the expected future evolution of a wide range of variables. While most studies rely on quantitative macroeconomic expectations made by professional forecasters (Lahiri and Sheng 2010;Oinonen and Paloviita 2017), an alternative source of survey expectations are business and consumer tendency surveys (Claveria, 2020(Claveria, , 2021Binding and Dibiasi 2017;Das et al 2019;Shainoz and Cosar 2020). See Grimme et al (2014) for the evaluation of a combination of different types of measures.…”

Section: Introductionmentioning

confidence: 99%

Evolution of Business and Consumer Uncertainty in the Midst of the COVID-19 Pandemic. a Sector Analysis in 32 European Countries

Clavería

2020

SSRN Journal

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This paper examines the evolution of business and consumer uncertainty amid the coronavirus pandemic in 32 European countries and the European Union (EU). Since uncertainty is not directly observable, we approximate it using the geometric discrepancy indicator of Claveria et al. (2019). This approach allows us quantifying the proportion of disagreement in business and consumer expectations of 32 countries. We have used information from all monthly forward-looking questions contained in Joint Harmonised Programme of Business and Consumer Surveys conducted by the European Commission (EC): the industry survey, the service survey, the retail trade survey, the building survey and the consumer survey. First, we have calculated a discrepancy indicator for each of the 17 survey questions analysed, which allows us to approximate the proportion of uncertainty about different aspects of economic activity, both form the demand and the supply sides of the economy. We then use these indicators to calculate disagreement indices at the sector level. We graphic the evolution of the degree of uncertainty in the main economic sectors of the analysed economies up to June 2020. We observe marked differences, both across variables, sectors and countries since the inception of the COVID-19 crisis. Finally, by adding the sectoral indicators, an indicator of business uncertainty is calculated and compared with that of consumers. Again, we find substantial differences in the evolution of uncertainty between managers and consumers. This analysis seeks to offer a global overview of the degree of economic uncertainty in the midst of the coronavirus crisis at the sectoral level.

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How Informative are Aggregated Inflation Expectations? Evidence from the ECB Survey of Professional Forecasters

Cited by 2 publications

References 10 publications

On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables

On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables

Evolution of Business and Consumer Uncertainty in the Midst of the COVID-19 Pandemic. a Sector Analysis in 32 European Countries

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