The influence of macro-financial conditions on consumer spending through sentiment.
Description
This paper studies how U.S. financial conditions affect consumer spending directly and through consumer sentiment. Using monthly data from January 2007 through July 2024, it combines autoregressive distributed lag modeling, bootstrapped mediation analysis, and vector autoregression to separate direct macro-financial effects from the sentiment channel.
The results show a long-run relationship among financial conditions, sentiment, and spending. Roughly one-fifth to one-quarter of the total effect of financial conditions on spending operates through consumer sentiment, and financial conditions become an increasingly important driver of sentiment and consumption over time.
What this paper contributes.
Connects financial conditions to spending through sentiment.
The analysis treats consumer sentiment as a transmission mechanism rather than only a coincident macro indicator.
Uses complementary time-series methods.
ARDL, mediation, and VAR models are used to distinguish long-run relationships, indirect effects, and dynamic feedback.
Quantifies the sentiment pathway.
The mediation estimates indicate that about 21-24 percent of the financial-conditions effect on spending runs through sentiment.
Reframes macroeconomic assessment.
Policy analysis that ignores sentiment can misread the timing and persistence of spending responses during financial instability.