arXiv subjects

Marco Ottaviani

Publications and source records attributed to Marco Ottaviani.

3 recordsLinked to original sources

arXiv2026

Information Comparison of Order Statistics, with Applications to Auctions and Voting

We compare the informativeness of order statistics in a sample of conditionally independent draws from a distribution \(F(x\mid\theta)\) as the sample size n increases. The k-th highest of n+1 draws is more accurate than the k-th highest of n if and only if the cumulative reverse hazard -\log F(x\mid\theta) is log-supermodular. Symmetrically, the k-th lowest is more accurate if and only if the cumulative hazard -\log(1-F(x\mid\theta)) is log-supermodular. Reversals are exceptional, occurring only for experiments that are, up to increasing transformations, exponential location experiments. In large samples, middle order statistics are asymptotically fully informative, while bounded lower and upper ranks require unbounded informativeness tail conditions. When full learning fails, bounded ranks converge to location experiments, and more central ranks are Blackwell more informative. Extending the analysis from scalar order statistics to blocks of selected data, we obtain multidimensional comparisons under log-supermodularity of hazard rates. The results unify and extend information-aggregation results in auctions and provide a new order-statistic approach to strategic voting.

econ.TH↗

arXiv2024

Designing Scientific Grants

This paper overviews the economics of scientific grants, focusing on the interplay between the inherent uncertainty in research, researchers' incentives, and grant design. Grants differ from traditional market systems and other science and innovation policy tools, such as prizes and patents. We outline the main economic forces specific to science, noting the limited attention given to grant funding in the economics literature. Using tools from information economics, we identify key incentive problems at various stages of the grant funding process and offer guidance for effective grant design. In the allocation stage, funders aim to select the highest-merit applications while minimizing evaluation costs. The selection rule, in turn, impacts researchers' incentives to apply and invest in their proposals. In the grant management stage, funders monitor researchers to ensure efficient use of funds. We discuss the advantages and potential pitfalls of (partial) lotteries and emphasize the effectiveness of staged grant design in promoting a productive use of grants. Beyond these broadly applicable insights, our overview highlights the need for further research on grantmaking. Understudied areas include, at the micro level, the interplay of different grant funding stages, and at the macro level, the interaction of grants with other instruments in the market for science.

econ.GN↗

arXiv2020

P-hacking in clinical trials and how incentives shape the distribution of results across phases

Clinical research should conform to high standards of ethical and scientific integrity, given that human lives are at stake. However, economic incentives can generate conflicts of interest for investigators, who may be inclined to withhold unfavorable results or even tamper with data in order to achieve desired outcomes. To shed light on the integrity of clinical trial results, this paper systematically analyzes the distribution of p-values of primary outcomes for phase II and phase III drug trials reported to the ClinicalTrials.gov registry. First, we detect no bunching of results just above the classical 5% threshold for statistical significance. Second, a density discontinuity test reveals an upward jump at the 5% threshold for phase III results by small industry sponsors. Third, we document a larger fraction of significant results in phase III compared to phase II. Linking trials across phases, we find that early favorable results increase the likelihood of continuing into the next phase. Once we take into account this selective continuation, we can explain almost completely the excess of significant results in phase III for trials conducted by large industry sponsors. For small industry sponsors, instead, part of the excess remains unexplained.

econ.GN↗