Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method

Lahiri, Kajal; Zhao, Yongchen

doi:10.1016/j.ijforecast.2014.06.003

Cited by 30 publications

(2 citation statements)

References 35 publications

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“…The qualitative nature of survey results has often lead to quantify agents' responses making use of survey indicators, such as the balance statistic. See Lahiri and Zhao (2015) for an appraisal of alternative measures of economic expectations.…”

Section: Introductionmentioning

confidence: 99%

“…Expectations forecasts can then be used to predict business cycle turning points (Qi, 2001;Diebold and Rudebusch, 1989), to quantify business survey data (Lahiri and Zhao, 2015;Breitung, and Schmeling, 2013;Claveria et al, 2006;Mitchell, 2002;Mitchell et al, 2002), and as explanatory variables in quantitative forecasts models (Lui et al, 2011;Graff, 2010;Mitchell et al, 2005;Claveria et al, 2007Claveria et al, , 2010Parigi and Schlitzer, 1995;Biart and Praet, 1987). Recently, Dees et al (2013) empirically assesses the link between the consumer sentiment indicator and consumer expenditures in the United States and the Euro Area.…”

Section: Introductionmentioning

confidence: 99%

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A self-organizing map analysis of survey-based agents׳ expectations before impending shocks for model selection: The case of the 2008 financial crisis

Clavería

Monte

Porras

2016

International Economics

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A self-organizing map analysis of survey-based agents' expectations before impending shocks for model selection: The case of the 2008 financial crisis ABSTRACT By means of Self-Organizing Maps we cluster fourteen European countries according to the most suitable way to model their agents' expectations. Using the financial crisis of 2008 as a benchmark, we distinguish between those countries that show a progressive anticipation of the crisis and those where sudden changes in expectations occur. We compare the forecasting performance of Artificial Neural Networks to that of three different time series models and find that neural networks outperform time series models when there are brisk changes in expectations before impending shocks. Conversely, in countries where expectations show a smooth transition towards recession, ARIMA models outperform neural networks. This result demonstrates the usefulness of clustering techniques for selecting the most appropriate method to forecast expectations according to their behaviour.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A self-organizing map analysis of survey-based agents׳ expectations before impending shocks for model selection: The case of the 2008 financial crisis

Clavería

Monte

Porras

2016

International Economics

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Measuring Disagreement in Qualitative Expectations

Mokinski

Sheng

Yang

2015

Journal of Forecasting

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We assess how well measures of disagreement in qualitative survey expectations reflect disagreement in corresponding quantitative expectations. We consider a variety of measures, belonging to two categories: measures of dispersion in nominal and ordinal variables and measures based on the probability approach of Carlson and Parkin (Economica, 1975; 42, 123–138). Using data from two household surveys that collect both qualitative and quantitative inflation expectations, we find that the probability approaches with time‐varying categorization thresholds and either a piecewise uniform or t distribution perform best and the resulting disagreement estimates are highly correlated with the benchmark. Copyright © 2015 John Wiley & Sons, Ltd.

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Uncertainty and disagreement of inflation expectations: Evidence from household‐level qualitative survey responses

Zhao

2021

Journal of Forecasting

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We propose a procedure that jointly estimates expectation, uncertainty, and disagreement using a flexible hierarchical ordered response model and individual‐level qualitative data. Based on the Michigan survey of US consumers, our results reveal how their inflation expectations and the associated uncertainty are affected by various factors, including their perceptions of economic conditions, recollections of relevant news reports, and sociodemographic characteristics. An examination of the dynamics of inflation uncertainty and disagreement produces evidence in support of using the latter as a proxy of the former. However, our results also highlight important episodes (such as the start of the COVID pandemic) in which the two series diverge.

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Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method

Cited by 30 publications

References 35 publications

A self-organizing map analysis of survey-based agents׳ expectations before impending shocks for model selection: The case of the 2008 financial crisis

A self-organizing map analysis of survey-based agents׳ expectations before impending shocks for model selection: The case of the 2008 financial crisis

Measuring Disagreement in Qualitative Expectations

Uncertainty and disagreement of inflation expectations: Evidence from household‐level qualitative survey responses

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