Endogenous Price Commitment, Sticky and Leadership Pricing: Evidence from the Italian Petrol Market

This article studies dynamic pricing strategies in the Italian gasoline market before and after the market leader unilaterally announced its commitment to adopt a sticky-pricing policy. Using daily Italian firm level prices and weekly average EU prices, we show that the effect of the new policy was twofold. First, it facilitated price alignment and coordination on price changes. After the policy change, the observed pricing pattern shifted from cost-based to sticky-leadership pricing. Second, using a dif-in-dif estimation and a synthetic control group, we show that the causal effect of the new policy was to significantly increase prices through sticky-leadership pricing. Our paper highlights the importance of price-commitment by a large firm in order to sustain (tacit) collusion

Actions Speak Louder than Words: Econometric Evidence to Target Tacit Collusion in Oligopolistic Markets

Tacit collusion reduces welfare comparably to explicit collusion but remains mostly unaddressed by antitrust enforcement which greatly depends on evidence of explicit communication. We propose to target specific elements of firms’ behavior that facilitate tacit collusion by providing quantitative evidence that links these actions to an anticompetitive market outcome. We apply our approach to incidents on the Italian gasoline market where the market leader unilaterally announced its commitment to a policy of sticky pricing and large price changes which facilitated price alignment and coordination of price changes. Antitrust policy has to distinguish such active promotion of a collusive strategy from passive (best response) alignment. Our results imply the necessity of stronger legal instruments which target unilateral conduct that aims at bringing about collusion

Open Access to Research Data: Strategic Delay and the Ambiguous Welfare Effects of Mandatory Data Disclosure

Mandatory data disclosure is an essential feature for credible empirical work but comes at a cost: First, authors might invest less in data generation if they are not the full residual claimants of their data after their first publication. Second, authors might "strategically delay" the time of submission of papers in order to fully exploit their data in subsequent research. We analyze a three-stage model of publication and data disclosure. We derive exact conditions for positive welfare effects of mandatory data disclosure. However, we find that the transition to mandatory data disclosure has negative welfare properties if authors delay strategically

Open Access to Data: An Ideal Professed but not Practised

We provide evidence for the status quo in economics with respect to data sharing using a unique data set with 488 hand-collected observations randomly taken from researchers' academic webpages. Out of the sample, 435 researchers (89.14%) neither have a data&code section nor indicate whether their data is available. We find that 8.81% of researchers share some of their data whereas only 2.05% fully share. We run an ordered probit regression to relate the decision of researchers to share to their observable characteristics. We find that three predictors are positiv and significant across specifications: being full professor, working at a higher-ranked institution and personal attitudes towards sharing as indicated by sharing other material such as lecture slides

Open Access to Data: An Ideal Professed but not Practised

We provide evidence for the status quo in economics with respect to data sharing using a unique data set with 488 hand-collected observations randomly taken from researchers' academic webpages. Out of the sample, 435 researchers (89.14%) neither have a data&code section nor indicate whether their data is available. We find that 8.81% of researchers share some of their data whereas only 2.05% fully share. We run an ordered probit regression to relate the decision of researchers to share to their observable characteristics. We find that three predictors are positiv and significant across specifications: being full professor, working at a higher-ranked institution and personal attitudes towards sharing as indicated by sharing other material such as lecture slides

Leading-effect vs. Risk-taking in Dynamic Tournaments: Evidence from a Real-life Randomized Experiment

Two 'order effects' may emerge in dynamic tournaments with information feedback. First, participants adjust effort across stages, which could advantage the leading participant who faces a larger 'effective prize' after an initial victory (leading-effect). Second, participants lagging behind may increase risk at the final stage as they have 'nothing to lose' (risk-taking). We use a randomized natural experiment in professional two-game soccer tournaments where the treatment (order of a stage-specific advantage) and team characteristics, e.g. ability, are independent. We develop an identification strategy to test for leading-effects controlling for risk-taking. We find no evidence of leading-effects and negligible risk-taking effects

Intellectual Property, Open Science and Research Biobanks

In biomedical research and translational medicine, the ancient war between exclusivity (private control over information) and access to information is proposing again on a new battlefield: research biobanks. The latter are becoming increasingly important (one of the ten ideas changing the world, according to Time magazine) since they allow to collect, store and distribute in a secure and professional way a critical mass of human biological samples for research purposes. Tissues and related data are fundamental for the development of the biomedical research and the emerging field of translational medicine: they represent the “raw material” for every kind of biomedical study. For this reason, it is crucial to understand the boundaries of Intellectual Property (IP) in this prickly context. In fact, both data sharing and collaborative research have become an imperative in contemporary open science, whose development depends inextricably on: the opportunities to access and use data, the possibility of sharing practices between communities, the cross-checking of information and results and, chiefly, interactions with experts in different fields of knowledge. Data sharing allows both to spread the costs of analytical results that researchers cannot achieve working individually and, if properly managed, to avoid the duplication of research. These advantages are crucial: access to a common pool of pre-competitive data and the possibility to endorse follow-on research projects are fundamental for the progress of biomedicine. This is why the "open movement" is also spreading in the biobank's field. After an overview of the complex interactions among the different stakeholders involved in the process of information and data production, as well as of the main obstacles to the promotion of data sharing (i.e., the appropriability of biological samples and information, the privacy of participants, the lack of interoperability), we will firstly clarify some blurring in language, in particular concerning concepts often mixed up, such as “open source” and “open access”. The aim is to understand whether and to what extent we can apply these concepts to the biomedical field. Afterwards, adopting a comparative perspective, we will analyze the main features of the open models – in particular, the Open Research Data model – which have been proposed in literature for the promotion of data sharing in the field of research biobanks. After such an analysis, we will suggest some recommendations in order to rebalance the clash between exclusivity - the paradigm characterizing the evolution of intellectual property over the last three centuries - and the actual needs for access to knowledge. We argue that the key factor in this balance may come from the right interaction between IP, social norms and contracts. In particular, we need to combine the incentives and the reward mechanisms characterizing scientific communities with data sharing imperative