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Forecasting Consumption: The Role of Consumer Confidence in Real Time with many Predictors

Kajal Lahiri (), George Monokroussos () and Yongchen Zhao ()

No 2015-02, Working Papers from Towson University, Department of Economics

Abstract: We study the role of consumer confidence in forecasting real personal consumption expenditure, and contribute to the extant literature in three substantive ways: First, we reexamine existing empirical models of consumption and consumer confidence not only at the quarterly frequency, but using monthly data as well. Second, we employ real-time data in addition to commonly used revised vintages. Third, we investigate the role of consumer confidence in a rich information context. We produce forecasts of consumption expenditures with and without consumer confidence measures using a dynamic factor model and a large, real-time, jagged-edge data set. In a robust way, we establish the important role of confidence surveys in improving the accuracy of consumption forecasts, manifesting primarily through the services component. During the recession of 2007-09, sentiment is found to have a more pervasive effect on all components of aggregate consumption - durables, non-durables and services.

Keywords: Forecasting; Consumption; Consumer Sentiment; Factor Models; Kalman Filter; Real-Time Data; Fluctuation test. (search for similar items in EconPapers)
JEL-codes: C53 E21 E27 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-for and nep-mac
Date: 2015-07, Revised 2015-07
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