nep-ppm New Economics Papers
on Project, Program and Portfolio Management
Issue of 2021‒06‒28
six papers chosen by
Arvi Kuura
Tartu Ülikool

  1. Measuring the AI content of government-funded R&D projects: A proof of concept for the OECD Fundstat initiative By Izumi Yamashita; Akiyoshi Murakami; Stephanie Cairns; Fernando Galindo-Rueda
  2. Finding transport projects with high value for money : what are the socio-geographic determinants? By Jussila Hammes, Johanna; Volden, Gro Holst; Welde, Morten; Börjesson, Maria; Odeck, James
  3. Connective Financing - Chinese Infrastructure Projects and the Diffusion of Economic Activity in Developing Countries By Bluhm, Richard; Dreher, Axel; Fuchs, Andreas; Parks, Brad; Strange, Austin; Tierney, Michael J.
  4. Funding Risky Research By Chiara Franzoni; Paula Stephan; Reinhilde Veugelers
  5. Signaling and Discrimination in Collaborative Projects By Paula Onuchic ⓡ; Debraj Ray
  6. What Matters for Private Investment Financing in Renewable Energy Globally and in Asia? By Azhgaliyeva, Dina; Beirne, John; Mishra, Ranjeeta

  1. By: Izumi Yamashita; Akiyoshi Murakami; Stephanie Cairns; Fernando Galindo-Rueda
    Abstract: This report presents the results of a proof of concept for a new analytical infrastructure (“Fundstat”) for analysing government funding of R&D at the project level, exploiting the wealth of text-based information about funded projects. Reflecting the growth in popularity of artificial intelligence (AI) and the OECD Council Recommendation on AI’s emphasis on R&D investment, the report focuses on analysing government investments into AI-related R&D. Using text mining tools, it documents the creation of a list of key terms used to identify AI-related R&D projects contained in 13 funding databases from eight OECD countries and the EU, provides estimates for the total number and volume of government R&D funding, and characterises their AI funding portfolio. The methods and findings developed in this study also serve as a prototype for a new distributed mechanism capable of measuring and analysing government R&D support across key OECD priority areas and topics.
    Keywords: artificial intelligence, government funding, research and development
    Date: 2021–06–28
  2. By: Jussila Hammes, Johanna (Swedish National Road & Transport Research Institute (VTI)); Volden, Gro Holst (NTNU – Norwegian University of Science and Technology, 7491 Trondheim, Norway); Welde, Morten (NTNU – Norwegian University of Science and Technology, 7491 Trondheim, Norway); Börjesson, Maria (Swedish National Road & Transport Research Institute (VTI)); Odeck, James (Swedish National Road & Transport Research Institute (VTI))
    Abstract: We use cost-benefit data from 1052 projects in Norway and Sweden to analyse ex ante factors that can explain which characteristics of transport infrastructure projects explain high value for money. The aim is to identify characteristics that can be used in assessments of projects before a cost-benefit analysis is feasible. We find that in Norway, road toll financing is a good indicator of high value projects, especially in the poorer municipalities. In Sweden, co-financing serves to raise investment volumes, but tends to lead to worse value for money. In Sweden, congestion seems to be the biggest problem in medium-income municipalities, while there are traffic safety benefits to be obtained in the rural areas. A higher initial capacity on a link raises both benefits and costs, and costs are higher in more densely populated areas in both countries. We find diminishing economies of scale in Norway and increasing economies of scale in Sweden.
    Keywords: CBA; Transport infrastructure planning; Value for money
    JEL: R40 R42
    Date: 2021–06–16
  3. By: Bluhm, Richard; Dreher, Axel; Fuchs, Andreas; Parks, Brad; Strange, Austin; Tierney, Michael J.
    Abstract: This paper studies the causal effect of transport infrastructure on the spatial concentration of economic activity. Leveraging a new global dataset of geo-located Chinese government-financed projects over the period from 2000 to 2014 together with measures of spatial inequality based on remotely-sensed data, we analyze the effects of transport projects on the spatial distribution of economic activity within and between regions in a large number of developing countries. We find that Chinese-financed transportation projects reduce spatial concentration within but not between regions. In line with land use theory, we document a range of results which are consistent with a relocation of activity from city centers to their immediate periphery. Transport projects decentralize activity particularly strongly in regions that are more urbanized, located closer to the coast, and less developed.
    Keywords: China; Development finance; foreign aid; infrastructure; spatial concentration; transport costs
    JEL: F15 F35 O18 O19 P33 R11 R12
    Date: 2020–05
  4. By: Chiara Franzoni; Paula Stephan; Reinhilde Veugelers
    Abstract: The speed with which Covid-19 vaccines were developed and their high-performance underlines how much society depends on the pace of scientific research and how effective science can be. This is especially the case for vaccines based on the new designer mRNA technology. We draw on this exceptional moment for science to reflect on whether the government funding system is sufficiently supportive of research needed for key breakthroughs, and whether the system of funding encourages sufficient risk-taking to induce scientists to explore transformative research paths. We begin with a discussion of the challenges faced by scientists who did pioneering-research related to mRNA-based drugs in getting support for research. We describe measures developed to distinguish risky from non-risky research and their citation footprint. We review empirical work suggesting that funding is biased against risky research and provide a framework for thinking about why principal investigators, panelists and funding agencies may eschew risky research. We close with a discussion of interventions that government agencies and universities could follow if they wish to avoid a bias against risk.
    JEL: I23 O31 O38
    Date: 2021–06
  5. By: Paula Onuchic ⓡ; Debraj Ray
    Abstract: We propose a model of collaborative work in pairs. Each potential partner draws an idea from a distribution that depends on their unobserved ability. The partners then choose to combine their ideas, or work separately. These decisions are based on the intrinsic value of their projects, but also on signaling payoffs, which depend on the public’s assessment of individual contributions to joint work. In equilibrium, collaboration strategies both justify and are justified by public assessments. When partners are symmetric, equilibria with symmetric collaborative strategies are often fragile, in a sense made precise in the paper. In such cases, asymmetric equilibria exist: upon observing a collaborative outcome, the public ascribes higher credit to one of the partners based on payoff-irrelevant “identities.” Such favored identities do receive a higher payoff relative to their disfavored counterparts conditional on collaborating, but may receive lower overall expected payoff. Finally, we study a policy that sometimes (but not always) clarifies the ordinal ranking of partners’ contributions, and find that such disclosures can be Pareto-improving and reduce the scope for discrimination across payoff-irrelevant identities.
    JEL: D70 D82 J71
    Date: 2021–06
  6. By: Azhgaliyeva, Dina (Asian Development Bank Institute); Beirne, John (Asian Development Bank Institute); Mishra, Ranjeeta (Asian Development Bank Institute)
    Abstract: We examine the drivers of private investment in renewable energy by source of funding for 13 global economies over the period 2008 to 2018, with a focus on a sub-panel of Asian economies. Using a seemingly unrelated regression model, we provide a first quantitative estimate of the effect of government renewable energy policies on private investments across different sources of financing. Our results indicate that feed-in-tariffs (FITs) have the greatest overall effect in Asia on driving private investment in renewable energy, particularly from asset finance compared with other funding sources. The impact of FITs in Asia is also greater than that of the global sample. The impact of FITs is amplified in the presence of lower regulatory quality, which may be related to ease of market entry. We also find an important role in Asia for government expenditure on research and development in stimulating private investment. The magnitudes of the effects in Asia are broadly in line with the overall global sample. Finally, we find that technology costs, are less elastic on private investment in Asia compared with globally in affecting private investment in renewable energy across all funding sources, which may be related to the prevailing strong cost competitiveness of Asian economies in renewable energy provision.
    Keywords: private investment; public investment; renewable energy; green investment; feed-in tariff
    JEL: O30 O38 Q28 Q42
    Date: 2021–06–20

This nep-ppm issue is ©2021 by Arvi Kuura. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.