OAW

A Theory of BOT Concession Contracts

Auriol, Emmanuelle and Picard, Pierre M. (2011) A Theory of BOT Concession Contracts. TSE Working Paper, n. 11-228, Toulouse

WarningThere is a more recent version of this item available.
[img]
Preview
Text
Download (303kB) | Preview
Official URL: http://tse-fr.eu/pub/24307

Abstract

In this paper, we discuss the choice for build-operate-and-transfer (BOT) concessions when governments and firm managers do not share the same information regarding the operation characteristics of a facility. We show that larger shadow costs of public funds and larger information asymmetries entice governments to choose BOT concessions. This result stems from a trade-o¤ between the government’s shadow costs of financing the construction and the operation of the facility and the excessive usage price that the consumer may face during the concession period. The incentives to choose BOT concessions increase as a function of ex-ante informational asymmetries between governments and potential BOT concession holders and with the possibility of transferring the concession cost characteristics to public firms at the termination of the concession.

Item Type: Monograph (Working Paper)
Language: English
Date: 25 March 2011
Place of Publication: Toulouse
Uncontrolled Keywords: Public-private-partnership, privatization, adverse selection, regulation, natural monopoly, infrastructure, facilities
JEL codes: D83 - Search; Learning; Information and Knowledge; Communication; Belief
L33 - Comparison of Public and Private Enterprises; Privatization; Contracting Out
L43 - Legal Monopolies and Regulation or Deregulation
L51 - Economics of Regulation
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Institution: Université Toulouse 1 Capitole
Site: UT1
Date Deposited: 18 Jan 2012 06:03
Last Modified: 02 Oct 2019 23:01
OAI ID: oai:tse-fr.eu:24307
URI: http://publications.ut-capitole.fr/id/eprint/3506

Available Versions of this Item

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year