Nicola Dimitri

Best Value for Money in Procurement

Recent years witnessed a gradual change on how to evaluate successful procurement, in both the private ad the public sector. Indeed from a price-only criterion for measuring success, decisions shifted to a multi-criteria approach where various dimensions of quality, as well as price, are considered. The most common way to express such shift is to say that procurement should deliver “best value for money” (BVM). That is, to award the contract, both monetary and non-monetary components of an offer are to be considered. Whether in competitive bidding or negotiations BVM is typically formalized by a scoring formula, namely a rule for assigning dimensionless numbers to different elements of an offer, often expressed in different units of measurement. The contract would then be awarded according to the total score obtained by an offer. This paper discusses the notion of BVM and some typical forms of scoring rules, as a way to formalize the procurer’s preferences.

An assessment of R&D productivity in the pharmaceutical industry

Recent reports suggest that R&D productivity in the pharmaceutical industry can be strengthened by reducing costs both in the early phase and, mostly, in the clinical phase of drug discovery. However, a cost-benefit probabilistic analysis reveals that despite high costs, the clinical phase shows healthy productivity, whereas the early phase, particularly lead optimization, exhibits very low productivity.

Efficiency and equilibrium in the electronic mail game; the general case

In the Email Game (Amer. Econom. Rev. 79 (1989) 385) noisy information channels may prevent risky-efficient coordination, even when the game is almost common knowledge. In this paper, we show that this is the case whenever message failure probabilities are not sufficiently different. Quite intuitively, the extent of the difference is governed by the game payoffs, and in particular by the mixed Nash Equilibrium strategy of one of the two games to be played. This is because, conditionally to having observed ones type, a players beliefs on the opponents choices are governed by the reliability of communication channels.

R&D investments for neglected diseases can be sensitive to the economic goal of pharmaceutical companies.

A fundamental problem with neglected diseases is how to induce pharmaceutical companies to invest resources for developing effective treatments. A recent debate focused on the role of economic incentives represented by monetary transfers to the firms. In this article I focus on the economic goals of pharmaceutical companies, as determinants for R&D effort. In particular, within a stylized framework, the work compares expected profit and expected productivity maximization, arguing that the former in general induces higher R&D investments than the latter. Therefore, as it is currently the case, when pharmaceutical firms focus on productivity, appropriate economic incentives might be needed for them to invest in R&D for neglected diseases.

Time discounting and time consistency

Time discounting is the phenomenon that a desired result in the future is perceived as less valuable than the same result now. Economic theories can take this psychological fact into account in several ways. In the economic literature the most widely used type of additive time discounting is exponential discounting . In exponential discounting, the fall of valuation depends by a constant factor on the length of the delay period. It is well known, however, that exponential time discounting often does not describe well how people actually behave. Most people are averse to short delays in gratification now, while their future selves may not mind a bit of extra waiting. This behaviour can be described well by non-exponential discounting functions such as hyperbolic discounting . In hyperbolic discounting, valuations fall rapidly for small delay periods, but the fall gets slower for longer delay periods. Hyperbolic discounting captures phenomena such as procrastination, addiction and in general inconsistency over time. This chapter investigates whether forms of non-exponential discounting, in particular close to the so called Quasi-Hyperbolic model, could also be characterized in terms of dynamically consistent choices when individuals discount the welfare of future selves as well as their payoffs.

Pricing pharmaceutical compounds under development

The pharmaceutical industry is facing a decline in R&D productivity [1,2], owing to increased attrition rates of compounds across developing phases and increased development costs. These reasons may not be independent of each other, because increased attrition may increase R&D costs. Smaller companies seem to concentrate on developing molecules in the early stages that they then sell to larger companies. This way of sharing risks of failure among firms has created a ‘market’ for compounds under development.

Generating realistic data sets for combinatorial auctions

We consider the generation of realistic data sets for combinatorial auctions. This problem has been recognized as central to enhance the contribution of the computer science community to the field. We put forward the notions of structure and budget as main guidelines towards the generation of succinct and realistic input data. We describe a computational framework for the analysis of existing algorithms against realistic benchmarks, and use it in the context of two real world scenarios, i.e., real estate and railroad track auctions. The results of this analysis suggest that the obstacles to using (one round) combinatorial auctions in real world applications might be of an economic nature rather than a computational one.

R&D incentives for neglected diseases.

Neglected diseases are typically characterized as those for which adequate drug treatment is lacking, and the potential return on effort in research and development (R&D), to produce new therapies, is too small for companies to invest significant resources in the field. In recent years various incentives schemes to stimulate R&D by pharmaceutical firms have been considered. Broadly speaking, these can be classified either as ‘push’ or ‘pull’ programs. Hybrid options, that include push and pull incentives, have also become increasingly popular. Supporters and critics of these various incentive schemes have argued in favor of their relative merits and limitations, although the view that no mechanism is a perfect fit for all situations appears to be widely held. For this reason, the debate on the advantages and disadvantages of different approaches has been important for policy decisions, but is dispersed in a variety of sources. With this in mind, the aim of this paper is to contribute to the understanding of the economic determinants behind R&D investments for neglected diseases by comparing the relative strength of different incentive schemes within a simple economic model, based on the assumption of profit maximizing firms. The analysis suggests that co-funded push programs are generally more efficient than pure pull programs. However, by setting appropriate intermediate goals hybrid incentive schemes could further improve efficiency.

Global burden and investment for neglected diseases

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On the stage division mechanism in pharmaceuticals development processes

This paper contributes to the understanding of a recent trend taking place in the pharmaceutical industry, whereby large companies develop a meaningful number of alliances with smaller firms, to share stages of drug development processes. Small firms tend to operate in earlier stages and intuitively, this may suggest that this is because they are more efficient, or more willing, than larger firms to take such early risk. In exchange, larger firms would afford the higher development costs of later phases. In this article we argue that the intuition appears correct if large companies have enough resources to develop in-house all potentially interesting projects, but not necessarily so when they are resource constrained.