Government Debt and the Returns to Innovation
Mariano Massimiliano Croce,
Thiên Tung Nguyen,
Steve Raymond and
No 12617, CEPR Discussion Papers from C.E.P.R. Discussion Papers
Elevated levels of government debt raise concerns about their effects on long-term growth prospects. Using the cross section of US stock returns, we show that (i) high-R&D firms are more exposed to government debt and pay higher expected returns than low-R&D firms; and (ii) higher levels of the debt-to-GDP ratio predict higher risk premia for high-R&D firms. Furthermore, rises in the cost of capital for innovation-intensive firms predict declines in subsequent productivity and economic growth. We propose a production-based asset pricing model with endogenous innovation and fiscal policy shocks that can rationalize key aspects of the empirical evidence. Our study highlights a novel and distinct risk channel shaping the link between government debt and future growth.
Keywords: Cross Section of Stock Returns; Fiscal Uncertainty; Government Debt; Government Debt; growth; predictability; R&D (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ino, nep-knm and nep-sbm
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed
Downloads: (external link)
CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at email@example.com
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:cpr:ceprdp:12617
Ordering information: This working paper can be ordered from
http://www.cepr.org/ ... rs/dp.php?dpno=12617
Access Statistics for this paper
More papers in CEPR Discussion Papers from C.E.P.R. Discussion Papers Centre for Economic Policy Research, 33 Great Sutton Street, London EC1V 0DX.
Bibliographic data for series maintained by ().