Truncation bias corrections in patent data: Implications for recent research on innovation

Nishant Dass, Vikram Nanda and Steven Chong Xiao

Journal of Corporate Finance, 2017, vol. 44, issue C, 353-374

Abstract: We review the effectiveness of various adjustment methods in correcting the truncation-bias in patents data and the implications for existing studies. The NBER patents-database was recently updated, extending the sample from 2006 to 2010. The updated sample is largely free of truncation-bias over the period covered by the NBER-2006 sample, allowing us to evaluate the bias-adjustment methods. We find that existing adjustments perform poorly towards the end of NBER-2006 sample. We re-examine multiple studies from the recent literature on innovation and show that findings based on the last few years of NBER-2006 data are not supported in the updated patents-database.

Keywords: Innovation; Patents; NBER patent data; Truncation bias; Stock liquidity (search for similar items in EconPapers)
JEL-codes: G14 G30 O30 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (44)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S092911991730161X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:corfin:v:44:y:2017:i:c:p:353-374

DOI: 10.1016/j.jcorpfin.2017.03.010

Access Statistics for this article

Journal of Corporate Finance is currently edited by A. Poulsen and J. Netter

More articles in Journal of Corporate Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().