The determinants of contractual choice for private involvement in infrastructure projects in the United States

Reliance on private partners to help provide infrastructure investment and service delivery is increasing in the United States. Numerous studies have examined the determinants of the degree of private participation in infrastructure projects as governed by contract type. We depart from this simple public/private dichotomy by examining a rich set of contractual arrangements. We utilize both municipal and state-level data on 472 projects of various types completed between 1985 and 2008. Our estimates indicate that infrastructure characteristics, particularly those that reflect stand alone versus network characteristics, are key factors influencing the extent of private participation. Fiscal variables, such as a jurisdiction’s relative debt level, and basic controls, such as population and locality of government, increase the degree of private participation, while a greater tax burden reduces private participation

Recovery Risk and Labor Costs in Public-Private Partnerships : Contractual Choice in the US Water industry

We use an ordered logistic model to empirically examine the factors that explain varying degrees of private involvement in the U.S. water sector through public-private partnerships. Our estimates suggest that a variety of factors help explain greater private participation in this sector. We find that the risk to private participants regarding cost recovery is an important driver of private participation. The relative cost of labor is also a key factor in determining the degree of private involvement in the contract choice. When public wages are high relative to private wages, private participation is viewed as a source of cost savings. We thus find two main drivers of greater private involvement: one encouraging private participation by reducing risk, and another encouraging government to seek out private participation in lowering costs

Strong versus Weak Vertical Integration: Contractual Choice and PPPs in the United States

Public-Private-Partnerships are long-term, relational contracts between a public-sector sponsor and a private partner to deliver infrastructure projects across a range of economic sectors. Efficiency gains may derive from risk transfer and bundling different tasks within a single contract. We study the factors explaining the scope of bundling. We focus on the choice between weak vertical integration, which includes operational tasks alone or construction tasks alone, versus strong vertical integration, which involves the combination of operational and construction tasks. We utilize a new data set that includes 553 PPPs concluded in the U.S. between 1985 and 2013

How Much Vertical Integration? Contractual Choice and Public-Private Partnerships in the United States

Efficiency gains in Public-Private Partnerships derive from risk transfer and the bundling of different tasks. We study the factors that explain bundling in single contracts. We focus on the choice between integrating operational tasks alone or construction tasks alone, versus vertically integrating both operational and construction tasks. We analyze a new data set that includes 553 PPPs that were concluded in the United States. We find evidence that some financial variables play a role in bundling decisions. In addition, market size and the type of economic sectors involved, are also important drivers of contract choice and bundling decisions

Do public-private partnership enabling laws increase private investment in transportation infrastructure?

The use of public-private partnerships, or PPPs, is an important development in U.S. infrastructure delivery. PPPs are detailed contracts between a public-sector project sponsor and a private-sector provider that bundle together key delivery services. PPPs represent an important middle ground between pure-public project delivery and complete privatization. As of 2016, thirty-five U.S. states had enacted PPP enabling laws. Those laws define the broad institutional framework surrounding a PPP agreement. They address such questions as the mixing of public- and private-sector funds, the treatment of unsolicited PPP proposals, and the need for prior legislative approval of PPP contracts, among other issues. We provide the first comprehensive empirical assessment of the impact of those laws on a state's utilization of private investment. We analyze the overall effect of a state having a PPP enabling law while controlling for a variety of factors. A law's average impact represents an almost six-fold increase relative to the average percentage of PPP investment prior to enactment in treated states. We then assess the impact of PPP enabling-law provisions. We develop an expert-informed weighted index reflecting the degree to which a state's law is encouraging or discouraging of private investment. We find that PPP provisions that empower PPPs, such as exemptions from property taxes and from extant procurement laws, as well as confidentiality protections, successfully attract PPP investment

Do public-private partnership enabling laws increase private investment in infrastructure [WP]

Rising use of public-private partnerships, or PPPs, is an important development in U.S. infrastructure delivery. PPPs are detailed contracts between a public-sector infrastructure project sponsor and a private-sector provider that bundle delivery services. PPPs represent a middle ground between pure-public project delivery and complete privatization. As of 2016, thirty-five U.S. states had enacted PPP enabling laws. That legislation defines the broad institutional framework surrounding a PPP agreement. It addresses such questions as the mixing of public- and private-sector funds, the treatment of unsolicited PPP proposals, and need for prior legislative approval of PPP contracts, among other key issues. We provide the first thorough empirical assessment of the impact of PPP enabling laws on a state’s utilization of private investment. We analyze the overall effect of having a PPP enabling law while controlling for a variety of factors, including the state’s indebtedness, its broad political disposition, union membership, per-capita income, and other variables. We then assess the impact of thirteen individual PPP enabling-law provisions. We develop an expert-informed weighted index reflecting the degree to which a state’s law is encouraging or discouraging of private investment. We find that more favorable PPP enabling laws increase private investment: when our favorability index increases by one-tenth, the proportion of infrastructure investment delivered via PPP in a state increases by 0.5-0.6. We find that PPP enabling-law provisions allowing unsolicited proposals and the comingling of public and private funds are particularly important in attracting private investment

CDK-dependent nuclear localization of B-Cyclin Clb1 promotes FEAR activation during meiosis I in budding yeast

Cyclin-dependent kinases (CDK) are master regulators of the cell cycle in eukaryotes. CDK activity is regulated by the presence, post-translational modification and spatial localization of its regulatory subunit cyclin. In budding yeast, the B-cyclin Clb1 is phosphorylated and localizes to the nucleus during meiosis I. However the functional significance of Clb1's phosphorylation and nuclear localization and their mutual dependency is unknown. In this paper, we demonstrate that meiosis-specific phosphorylation of Clb1 requires its import to the nucleus but not vice versa. While Clb1 phosphorylation is dependent on activity of both CDK and polo-like kinase Cdc5, its nuclear localization requires CDK but not Cdc5 activity. Furthermore we show that increased nuclear localization of Clb1 during meiosis enhances activation of FEAR (Cdc Fourteen Early Anaphase Release) pathway. We discuss the significance of our results in relation to regulation of exit from meiosis I

Reuse of design pattern measurements for health data

Research using health data is challenged by its heterogeneous nature, description and storage. The COVID-19 outbreak made clear that rapid analysis of observations such as clinical measurements across a large number of healthcare providers can have enormous health benefits. This has brought into focus the need for a common model of quantitative health data that enables data exchange and federated computational analysis. The application of ontologies, Semantic Web technologies and the FAIR principles is an approach used by different life science research projects, such as the European Joint Programme on Rare Diseases, to make data and metadata machine readable and thereby reduce the barriers for data sharing and analytics and harness health data for discovery. Here, we show the reuse of a pattern for measurements to model diverse health data, to demonstrate and raise visibility of the usefulness of this pattern for biomedical research

Determining population structure among Argentinian jaguars (Panthera onca)

The jaguar (Panthera onca) is the largest felid in America and the most emblematic South American predator. This carnivore species holds a high environmental importance in all ecosystems it inhabits for its apex predator role. Jaguar populations have suffered an important decline over the last century and today this species is considered as critically endangered in Argentina. Ensuring the sustainability of theremaining jaguar populations demands a high degree of knowledge about the current state of their genetic variability levels and a description of population structure is essential, especially to allow rational translocation and reintroduction actions. The first jaguar reference genome was released in2017 (Figueiro et al. 2017) by the Jaguar Genome Project, a consortium we integrate.With the aim of generating useful resources and information for the jaguar genetics and conservation from the genomic perspective, we carried out the whole genome sequencing of 9 jaguar samples using Illumina 2500 NSG technology. Here we present the first results obtained from these 9 genomescompared to the reference. We performed a population structure analysis in order to estimate the optimal number of populations present in our data and a Multiple Correspondece Analysis (MCA) clustering of our samples based on over 280.000 homozygous variable positions in their genomes. Theestimation of the optimal number of populations present among our samples resulted in 6, according to the Structure analysis. However, the MCA clustering analysis only revealed 5 groups of individuals. The main genetic cluster of animal obtained is integrated by captive animals from zoos and natural reserves and surprisingly a Paraguayan male. Apart from this central group, a wild Argentinian sample from Misiones (a province in the north-east of the country) was located. Also, an animal of Uruguayan origin and the reference, built from a Brazilian animal, located in individual clusters.More work including heterozygous variable position analysis will be performed to better describe the genetic variability among the sequenced jaguar genomes and accurately describe the current genetic situation and population structure of this species in Argentinian territory.Fil: Pisciottano, Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Tarifa Reischle, Inti Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Pegueroles Queralt, Cinta. Centro de Regulación Genómica; España. Universitat Pompeu Fabra; EspañaFil: Willis, Jesse R.. Centro de Regulación Genómica; EspañaFil: Julca Chavez, Irene Consuelo. Centro de Regulación Genómica; España. Universitat Pompeu Fabra; EspañaFil: Gabaldón, Toni. Centro de Regulación Genómica; España. Institució Catalana de Recerca i Estudis Avançats ; EspañaFil: Saragueta, Patricia Esther. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; ArgentinaExploring Genomic Landscapes EMBO WorkshopSan Pedro de AtacamaChileEMBOCenter for Genomic Regulatio