Informational frictions lead to inefficient allocations, reducing welfare. Dynamic incentive theory offers a powerful conceptual framework to analyse the optimal design of contracts and mechanisms mitigating these inefficiencies. Its technical difficulty and abstractness, however, have limited its applications. The objective of this project is to develop new frameworks to enhance the applicability of dynamic incentive theory and address important unanswered applied questions: 1) In corporate finance, I will evaluate the quantitative relevance of dynamic contract theory. To do so, I will develop a new structural econometric framework and estimate the magnitude of dynamic incentive problems and their consequences for corporate investment and bankruptcy risk. 2) In organization theory, I will study if equilibrium choices lead to excessive complexity. I will model the link between complexity and incentives. Then, in contrast with standard dynamic contract theory, which takes the tasks of agents as given, I will endogenize agents’ tasks and their complexity. Finally I will confront this theory to new data on complexity. 3) In asset pricing, I will build a novel equilibrium framework to study the consequences of dynamic incentive constraints for relative prices and the cross section of expected returns. In addition to this positive analysis, I will delineate the normative implications of the theory for financial markets regulation. 4) In public finance, I will study whether financial transactions should be taxed. To do so, I will extend the dynamic mechanism design paradigm of “new public finance” to financial transaction taxes and compare the distortions induced by these taxes with those induced by taxes on capital or labour income. By delivering useful results on four important issues, this project will demonstrate the applicability of dynamic incentive theory. To do so it will develop novel tools by combining dynamic incentive theory with other methodologies.

The Eurozone is currently facing a sudden and sharp increase in inflation. Whether inflationary pressures will persist and what will be the cost of an eventual monetary tightening crucially depends on inflation expectations. The aim of this project is to provide theoretical and empirical support to a new channel, through which inflation may persistently shift business activity. The project sheds new light on how market prices influence consumers’ perceived inflation and how this may allow for the transmission of monetary policy even in the absence of rigidities in firms’ pricing. It shifts the focus from a traditional firm-centric to a (complementary) household-centric view of money non-neutrality. It shares the spirit of a recent trend in central banks’ efforts in getting a better appraisal of the importance of consumers’ expectations, after decades of a strict empirical focus on firms’ pricing. The project consists of five working packages (WP) based on the idea that households’ inflation perceptions, driven by actual market prices, can be a major source of the business cycle. The first WP proposes a new theory where output-inflation co-movement relies on consumers’ price hunting in response to perceived inflation, causing a counter-cyclical gap between posted and paid prices inflation. The second and third WP aim at validating the mechanism using large datasets on consumers’ spending and retail trade. The fourth presents a new model where consumers learn from inflation about future economic prospects on which all have dispersed foresight. The fifth will estimate this model on survey data. The key novelty of the project is studying, not only how expectations move market outcomes, as typical in the literature, but also how these feed-back to expectations through prices in a full circle of general equilibrium implications. As by-product, it identifies measurable empirical counterparts for incomplete information sets.

Competitive conflicts for land use between the energy and food sectors have appeared, which could be mitigated by the vertical integration of RES in farms through new circular business models. By this approach, farms will become climate neutral, optimising their production and reducing their impact on natural resources and biodiversity, on top of providing energy services to communities and diversifying their economic income. However, there is a need to identify, understand and overcome major existing barriers perceived by agricultural communities. Moreover, current initiatives do not to effectively consider and address the complex interactions and factors from the farming and RES context, thus missing to support decision making based on accurate projections, estimations and forecasts. HarvRESt will work on these needs by improving the existing knowledge and its fragmented status, which will be feed to an Agricultural Virtual Power Plant able to run different scenarios and farm configurations to determine the best operation procedures for a given RES solution. This data will be then provided to a decision support system able to weight trade-offs and key indicators to provide ad-hoc recommendations to farmers and policy makers, thus enabling the consecution of improved production rates on renewable energy, food & feed within agro communities. For the successful execution of HarvRESt and implementation of recommendations, a multi-actor approach fostering co-creation sessions together with the provision of training materials for farmers empowerment will be implemented. The full approach of HarvRESt will be supported and executed at 4 use cases representing different topologies of farms, a diversity of stakeholders and organizational structures, distinct geographical conditions and a wide variety of RES technologies. Together with HarvRESt community and mapped initiatives, the project will act as a hub for knowledge and best-practices on RES integration at farm level.

UNDERPIN addresses critical gaps in monitoring, evaluation, and learning (MEL) for climate adaptation across Europe. It will design, develop, and validate an outcome-oriented framework that enhances existing frameworks for assessing climate resilience. This framework will include operationalized process and outcome indicators to track adaptation progress at local, regional, and national levels. A major challenge is the lack of standardized indicators capturing the effectiveness of adaptation efforts. Existing frameworks often focus on processes but fail to assess long-term resilience outcomes. UNDERPIN aims to bridge this gap by developing indicators that evaluate both short-term results and long-term impacts, helping stakeholders assess how well adaptation actions reduce vulnerabilities and enhance resilience. To achieve this, UNDERPIN will review existing climate adaptation and disaster risk reduction (DRR) indicators and integrate novel data sources, including Earth observation and citizen science. The project will involve stakeholders in three pilot regions to co-create and refine the framework, ensuring practical relevance and adaptability. A user-friendly dashboard with AI and machine learning tools will provide real-time analysis at the EU and regional level, helping decision-makers track progress, identify gaps, and make data-driven decisions. A citizen science and just climate resilience lens is used throughout the different activities of UNDERPIN. By aligning with EU and global reporting standards, such as the EU Adaptation Strategy and the UNFCCC, UNDERPIN will harmonize climate adaptation monitoring across governance levels, fostering a coordinated approach to resilience-building in Europe.