Volume 18, Issue 3

Healthcare treatment can be considered a credence good; that is, the patient may not always be able to infer quality ex ante nor observe it ex post. In this article, we study the allocation of liability among two physicians for joint damage under two liability regimes: strict liability and the negligence rule. The credence characteristic implies that the patient imperfectly detects treatment error. We find that the negligence rule is more deterrent than strict liability if the probability of detection of treatment error by the patient is high. If the probability of detection is low, both liability regimes are equivalent. An efficient allocation rule should be based on the degree of substitutability between the precaution levels of the physicians and the probability that the patient detects treatment error.

The value of an unlisted company is a contentious issue. This is because investors value marketability and liquidity, but vacillate on the appropriate percentage discount that needs to be applied for the valuation of a private company. As more companies find it easier to remain private, a better understanding of this discount is increasingly important. The extant discount studies are mainly derived from financial and transactional data. They provide reliable averages using large sample sizes, but present few determinants to explain the wide ranges in the observations. Our research is based on a unique, alternative data source that complements existing studies by tapping into rich contextual information. Specifically, we examine court decisions that determine the appropriate discount and relate this percentage to an important characteristic of a private company: its “open” character, i.e. its willingness to accept outside shareholders or partners in the venture. We find that open and closed companies differ in value 6.5%. Our conclusions hold after controlling for known determinants of the discount. Our results impact valuation approaches and present real-world application for the owners and managers of private companies who may consider opening ownership to third parties.

Highly influential recent work by Benartzi et al. (2017) argues—using comparisons of effectiveness and costs—that behavioral interventions (or nudges) offer more cost-effective means than traditional regulatory instruments for changing individual behavior to achieve desirable policy goals. Based on this finding, these authors further conclude that governments and other organizations should increase their investments in nudging to supplement traditional interventions. Yet a closer look at Benartzi et al.’s (2017) own data and analysis reveals that they variously exclude and include key cost elements to the benefit of behavioral instruments over traditional ones and overstate the utility of cost-effectiveness analysis for policy selection. Once these methodological shortcomings are corrected, a reassessment of key policies evaluated by the authors reveals that nudges do not consistently outperform traditional interventions, neither under cost-effectiveness analysis nor under the methodologically required cost-benefit analysis. These illustrative findings demonstrate that governments concerned with social welfare cannot simply assume the superiority of behavioral instruments and should strive instead to conduct cost-benefit analyses of competing interventions, including nudges, to identify the most efficient of the available instruments.

In this paper, Data Envelopment Analysis (DEA) is used to calculate the technical efficiency and the Malmquist Total Factor Productivity Index (MPI) of the municipal (JM) and circuit courts (JC) of the ordinary jurisdiction of the Colombian criminal justice system, from 2012 to 2016. The results show an average technical inefficiency of 16, 9% for de JCs, and 17.3% for JMs. Additionally, we find a total factor productivity (TFP) decline for these courts of 24 and 44%, respectively. Although both components of the MPI registered average values lower than one, the decrease in TFP is mainly driven by the decline in the technical change component.