Demographics and fluctuations in Dividend/Price
Arie E.Gozluklu and
Carlo Favero ()
No 345, Working Papers from IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University
The dynamic dividend growth model (Campbell&Shiller, 1988) linking the log dividend yield to future expected dividend growth and stock market returns has been extensively used in the literature for forecasting stock returns. The empirical evidence on the performance of the model is mixed as its strength varies with the sample choice. This model is derived on the assumption of stationary dpt, dividend-yield. The empirical validity of such hypothesis has been challenged in recent literature (Lettau&Van Nieuwerburgh, 2007) with strong evidence on a time varying mean, due to breaks, in this financial ratio. In this paper, we show that the slowly evolving mean toward which the dividend price ratio is reverting is determined by demographic factors. We also show that a forecasting model based on demographics and a demand factor as captured by excess consumption in the sense of Lettau and Ludvigson(2004) overperforms virtually all alternative models proposed in the empirical literature in the framework of the dynamic dividend growth model. Finally, we exploit the predictability of demographic factors to project the equity risk premium up to 2050.
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Our link check indicates that this URL is bad, the error code is: 500 Failed to connect to FTP server ftp.igier.uni-bocconi.it: No such host is known.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:igi:igierp:345
Ordering information: This working paper can be ordered from
Access Statistics for this paper
More papers in Working Papers from IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University via Rontgen, 1 - 20136 Milano (Italy).
Bibliographic data for series maintained by ().