We study regulation of a bureaucratic provider of a public good in the presence of moral hazard and adverse selection. By bureaucratic we mean that it values output in itself, and not only profit. Three different financing systems are studied - cost reimbursement, prospective payment, and the optimal contract. In all cases, the output level increases with the bureaucratic bias. We find that the optimal contract is linear in cost (fixed payment plus partial cost-reimbursement). A stronger preference for high output reduces the tendency of the firm to announce a high cost (adverse selection), allowing a more powered incentive scheme (a lower fraction of the costs is reimbursed), which alleviates the problem of moral hazard.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Publisher Info
Paper provided by Universidade do Porto, Faculdade de Economia do Porto in its series FEP Working Papers with number
304.
Find related papers by JEL classification: D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information H41 - Public Economics - - Publicly Provided Goods - - - Public Goods H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
This paper has been announced in the following NEP Reports:
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Did you know? Citation analysis on IDEAS includes online papers that are freely accessible and whose text could be automatically analyzed, currently about 210000 papers.