Data Revisions and Out-of-Sample Stock Return Predictability

Lettau and Ludvigson (2001) find that the consumption-wealth ratio (cay) constructed from revised data is a strong predictor of stock market returns. This paper shows that its out-ofsample forecasting power becomes substantially weaker if cay is estimated using information available at the time of forecast. The difference, which mainly reflects periodic revisions in consumption and labor income data, is consistent with the conjecture that cay is a theoretically motivated variable. That is, revised data outperform real-time data because the former have smaller measurement errors. Nevertheless, practitioners should be cautious when they need to use real-time cay as a forecasting variable.