Costly sequential experimentation and project valuation with an application to health technology assessment

Jacco J.J. Thijssen and Daniele Bregantini

Journal of Economic Dynamics and Control, 2017, vol. 77, issue C, 202-229

Abstract: We study the optimal investment/abandonment decision for a project, where costly sequential experimentation provides information about its true profitability. We derive the optimal decision rule by appropriately extending the Bayesian framework of sequential hypothesis testing. The optimal decision time takes the form of the first exit time of a particular inaction region. We find that increased noise in the observations lowers the value of the project, and that the effect on the expected time at which a decision is taken is ambiguous. Delays in observations affect both project value and the inaction region. The model is illustrated with a health technology assessment application using data on standard versus robot-assisted laporascopic prostatectomy.

Keywords: Sequential experimentation; Optimal stopping; Health technology assessment (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0165188917300246
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:dyncon:v:77:y:2017:i:c:p:202-229

DOI: 10.1016/j.jedc.2017.01.016

Access Statistics for this article

Journal of Economic Dynamics and Control is currently edited by J. Bullard, C. Chiarella, H. Dawid, C. H. Hommes, P. Klein and C. Otrok

More articles in Journal of Economic Dynamics and Control from Elsevier
Bibliographic data for series maintained by Catherine Liu ().