Stephen Billington

Abstract: In 1794, the British State intervened in the patent system by introducing the Navy proviso, a legal proviso targeted at select patents compelling the patentee to supply their invention to the State on terms set by state-appointed adjudicators. This study employs new patent and archival data to examine the proviso’s origins, administration, and which […]

Abstract: We examine how the design of the patent system shapes firms’ access to finance. We exploit a UK reform that introduced substantive examination into the patent application process, improving the quality of information available to investors about the value of firms’ innovation. Using a newly compiled dataset of officially listed corporations, we find that […]

Abstract: The history of industrial revolutions provides valuable insights into how patents and patenting systems influence innovation. It also reveals the extent to which inventors have relied on other ways to protect their ideas, including secrecy, sharing and showcasing them at international exhibitions. Cite as: Stephen Billington, Alan Hanna, Joe Lane, What can we learn […]

Abstract: Did the outbreak of the French Revolutionary and Napoleonic Wars influence technical change during the Industrial Revolution? We address this question by investigating an instance of state intervention into the market for inventions from 1793-1820: the introduction of a new proviso into British patents compelling inventors to supply the military, and also attracting military […]

Abstract: A recent re-evaluation of patenting during the British Industrial Revolution argues patentees were responsive to demand-side conditions. This view does not consider supply-side factors, such as a patentee’s skill or access to financial resources, as an alternative mechanism. I exploit a rich dataset of patentee occupations to investigate the role a patentee’s economic or […]

Abstract: Innovation researchers currently make use of various patent classification schemas, which are hard to replicate. Using machine learning techniques, we construct a transparent, replicable and adaptable patent taxonomy, and a new automated methodology for classifying patents. We contrast our new schema with existing ones using a long-run historical patent dataset. We find quantitative analyses […]