Solving Euler equations via two-stage nonparametric penalized splines
Yongmiao Hong () and
Journal of Econometrics, 2021, vol. 222, issue 2, 1024-1056
This study proposes a novel estimation-based approach to solving asset pricing models for both stationary and time-varying observations. Our method is robust to misspecification errors while inheriting a closed-form solution. By representing the Euler equation into a well-posed integral equation of the second kind, we propose a penalized two-stage nonparametric estimation method and establish its optimal convergence under mild conditions. With the merit of penalized splines, our estimate is less sensitive to the spline setting and we also design a fast data-driven algorithm to effectively tune the key smoother, i.e. the penalty amount. Our approach exhibits excellent finite sample performance. Using the US data from 1947 to 2017, we reinvestigate the return predictability and find that the estimated implied dividend yield significantly predicts lower future cash flows and higher interest rates at short horizons.
Keywords: Euler equation; Nonparametric penalized splines; Two-stage regression; Return predictability; Implied price–dividend ratios (search for similar items in EconPapers)
JEL-codes: C1 C3 C4 C5 E1 G12 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
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:eee:econom:v:222:y:2021:i:2:p:1024-1056
Access Statistics for this article
Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson
More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().