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on Project, Program and Portfolio Management |
| By: | Benoît Faivre-Dupaigre; Emmanuel Fourmann |
| Abstract: | Project economic analysis (PEA) aims to evaluate ex-ante the various impacts of a project on all stakeholders, beyond its mere financial profitability. Long used by donors, it has come in for a lot of criticism (complexity, cost, technocracy). And, as aid practices have evolved, it has gradually given way to other approaches. Yet, in the current context, EAF remains a valuable tool for informing decisions, structuring debates, comparing options and integrating social, economic and environmental issues. This article outlines a number of avenues and recommendations for revitalizing PEA, with the aim of making public investment more profitable, inclusive and sustainable. |
| JEL: | Q |
| Date: | 2025–04–24 |
| URL: | https://d.repec.org/n?u=RePEc:avg:wpaper:en18027 |
| By: | Bluhm, Richard; Dreher, Axel; Fuchs, Andreas; Parks, Bradley C.; Strange, Austin M.; Tierney, Michael J. |
| Abstract: | This paper studies the causal effect of transport infrastructure on the spatial distribution of economic activity within subnational regions across a large number of developing countries. To do so, we introduce a new global dataset of geolocated Chinese grant- and loan-financed development projects from 2000 to 2014 and combine it with measures of spatial concentration based on remotely sensed data. We find that Chinese financed transportation projects decentralize economic activity within regions, as measured by a spatial Gini coefficient, by 2.2 percentage points. The treatment effects are particularly strong in regions that are less developed, more urbanized, and located closer to cities. |
| Keywords: | Development finance, Transport costsInfrastructure, Foreign aid, Spatial concentration, China |
| JEL: | F35 R11 R12 P33 O18 O19 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:ifwkie:318203 |
| By: | Lee, Seungjin; Mazarei Saadabadi, Kasra; Martinez-Morales, Alfredo A. |
| Abstract: | This white paper evaluates the feasibility of solar-powered bike paths in California, integrating renewable energy generation with sustainable transportation. Drawing on global case studies—including Germany’s solar cycle path roofing project, the Netherlands’ SolaRoad, and South Korea’s solar-integrated bike path—the study highlights the environmental, economic, and technical benefits of these systems. A conceptual case study along the Santa Ana River Trail in Riverside, California, modeled a 1 megawatt solar bike path capable of producing 2, 022, 041 kilowatt-hours (kWh) annually and offsetting 734 metric tons of carbon dioxide emissions. The analysis used advanced tools like PVWatts (a solar energy output estimation tool), System Advisor Model (SAM), and Jobs and Economic Development Impact (JEDI) to assess energy production, financial viability, and job creation. The Riverside project demonstrated a levelized cost of energy of 12.64 cents per kWh and job creation of 20.4 construction jobs and 0.2 operational jobs, confirming financial feasibility for pilot-scale projects. However, challenges such as high upfront costs, maintenance demands, and regulatory complexities must be addressedthrough modular designs and streamlined permitting processes. Key recommendations include leveraging public-private partnerships, prioritizing equity in project siting to benefit underserved communities, and initiating pilot projects in high-visibility areas to demonstrate feasibility and catalyze adoption. Solar bike paths represent a scalable solution to advance California’s climate goals, integrating renewable energy with urban infrastructure to create a cleaner, more equitable future. View the NCST Project Webpage |
| Keywords: | Engineering, GIS, solar bike paths, geospatial analysis, ArcGIS, System Advisor Model, JEDI model, PVWatts, renewable energy analysis |
| Date: | 2025–06–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsdav:qt97k9r1f0 |
| By: | Bernhardt, Dan (Department of Economics, University of Illinois and Department of Economics, University of Warwick); Hwang, Ilwoo (Department of Economics, Seoul National University); Krasa, Stefan (Department of Economics, University of Illinois) |
| Abstract: | We modify a canonical two-agent bargaining game with investments in a joint project, by allowing agents to also invest in outside options that improve their bargaining positions. Absent outside options, it is well known that equal bargaining power maximizes output. However, this is no longer true when investment in outside options is possible and the joint-project technology exhibits stronger substitutability than Cobb-Douglas. When this is so, equal bargaining power minimizes project output while maximizing total investment in unused outside options. Paradoxically, when inputs are suffciently strong substitutes, starting at equal bargaining power, each agent would gain from reductions in their own bargaining power. |
| Keywords: | Bargaining ; bargaining power ; outside option ; hold-up problem JEL Codes: C78 ; D25 ; L24 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:warwec:1559 |
| By: | Yuan, Yating (University of Warwick) |
| Abstract: | A principal incentivizes a team of agents to work on a joint project. Building on Winter (2004), this paper explores a simple mechanism where agents choose between two public messages, collaborate and ‘monopolize’, and the message profile decides their bonus upon team success. The principal minimizes the total payment while ensuring full effort in outcomes that survive Iterative Elimination of Weakly Dominated Strategies. The optimal mechanism reaches the first-best payment, leaving no rent for strategic uncertainty. Unlike previous results (Winter, 2004; Halac et al., 2021; Cavounidis and Ghosh, 2021), the optimal bonus allocation is neither discriminatory nor private. Thus, effciency need not come at the cost of fairness or transparency. |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:warwec:1561 |
| By: | Mafrur, Rischan |
| Abstract: | The convergence of blockchain and artificial intelligence (AI) has led to the emergence of AI-based tokens, which are cryptographic assets designed to power decentralized AI platforms and services. This paper provides a comprehensive review of leading AI-token projects, examining their technical architectures, token utilities, consensus mechanisms, and underlying business models. We explore how these tokens operate across various blockchain ecosystems and assess the extent to which they offer value beyond traditional centralized AI services. Based on this assessment, our analysis identifies several core limitations. From a technical perspective, many platforms depend extensively on off-chain computation, exhibit limited capabilities for on-chain intelligence, and encounter significant scalability challenges. From a business perspective, many models appear to replicate centralized AI service structures, simply adding token-based payment and governance layers without delivering truly novel value. In light of these challenges, we also examine emerging developments that may shape the next phase of decentralized AI systems. These include approaches for on-chain verification of AI outputs, blockchain-enabled federated learning, and more robust incentive frameworks. Collectively, while emerging innovations offer pathways to strengthen decentralized AI ecosystems, significant gaps remain between the promises and the realities of current AI-token implementations. Our findings contribute to a growing body of research at the intersection of AI and blockchain, highlighting the need for critical evaluation and more grounded approaches as the field continues to evolve. |
| Date: | 2025–05–08 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:yrzj5_v1 |