Consumer sentiment and household expenditure: reevaluating the forecasting equations
This paper reestimates the simple forecasting regressions in Carroll, Fuhrer, and Wilcox (1993) (CFW), which investigate the predictive power of consumer sentiment for consumption growth. Durability in the consumption categories analyzed implies that the error term may be distributed as an MA(1), indicating that ordinary least squares (OLS) estimation is inappropriate when variables lagged one period are used in the forecasting equation. I reestimate the forecasting regressions using nonlinear least squares (NLLS), explicitly accounting for a moving average error structure. In addition, I include two financial indicators as controls in the forecasting regression. These changes produce notable qualitative differences with the results obtained in CFW, and with my own results using OLS. In particular, using NLLS and financial controls, consumer attitudes appear to have little incremental forecasting power for categories of consumption other than motor vehicles.
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Eric M. Leeper, 1992. "Consumer attitudes: king for a day," Economic Review, Federal Reserve Bank of Atlanta, issue Jul, pages 1-15.
- Wilcox, David W, 1992. "The Construction of U.S. Consumption Data: Some Facts and Their Implications for Empirical Work," American Economic Review, American Economic Association, vol. 82(4), pages 922-41, September.
- Carroll, Christopher D & Fuhrer, Jeffrey C & Wilcox, David W, 1994.
"Does Consumer Sentiment Forecast Household Spending? If So, Why?,"
American Economic Review,
American Economic Association, vol. 84(5), pages 1397-1408, December.
- Christopher D. Carroll & Jeffery C. Fuhrer & David W. Wilcox, 1994. "RATS code for Does Consumer Sentiment Forecast Household Spending? If So, Why?," QM&RBC Codes 49, Quantitative Macroeconomics & Real Business Cycles.
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