Kajal Lahiri
George Monokroussos
Yongchen Zhao

forecasting consumption: the role of consumer confidence in real time with many predictors (replication data)

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 re-examine 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 dataset. 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 2007-2009, sentiment is found to have a more pervasive effect on all components of aggregate consumption: durables, non-durables and services.

Data and Resources

Suggested Citation

Lahiri, Kajal; Monokroussos, George; Zhao, Yongchen (2016): Forecasting Consumption: the Role of Consumer Confidence in Real Time with many Predictors (replication data). Version: 1. Journal of Applied Econometrics. Dataset. http://dx.doi.org/10.15456/jae.2022326.0700462975