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on Project, Program and Portfolio Management |
| By: | Chapman, Paul; Quang, Cuong |
| Abstract: | Recent research on the origins of risk during the planning and delivery of major projects broadly addresses two root causes: (i) complexity at the planning phase and also during project delivery, and; (ii) ‘the inside view’ at the planning phase and the associated issues of strategic misrepresentation and cognitive biases such as optimism bias. This paper presents the results of a systematic review that finds a schism in the literature showing theoretical and empirical treatment of project delivery risk polarises into considering either the effect of complexity or the inside view; rarely are they considered jointly. This work discusses the implications for theory and practice and identifies Case Based Decision Theory and Bayesian modelling, both of which are outside view techniques, as having potential to reconcile complexity and the inside view and thus provide for their joint treatment. |
| Date: | 2021–02–12 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:j9sw8&r=all |
| By: | Maximilian Mordig; Riccardo Della Vecchia; Nicol\`o Cesa-Bianchi; Bernhard Sch\"olkopf |
| Abstract: | We introduce a variant of the three-sided stable matching problem for a PhD market with students, advisors, and co-advisors. In our formalization, students have consistent (lexicographic) preferences over advisors and co-advisors, and the latter have preferences over students only (hence advisors and co-advisors are cooperative). A student must be matched to one advisor and one co-advisor, or not at all. In contrast to previous work, advisor-student and student-co-advisor pairs may not be mutually acceptable, e.g., a student may not want to work with an advisor or co-advisor and vice versa. We show that stable three-sided matchings always exist, and present the PhD algorithm, a three-sided matching algorithm with polynomial running time which uses any two-sided stable matching algorithm as matching engine. Borrowing from results on two-sided markets, we provide some approximate optimality results. We also present an extension to three-sided markets with quotas, where each student conducts several projects, and each project is supervised by one advisor and one co-advisor. As it is often the case in practice that the same student should not do more than one project with the same advisor or co-advisor, we modify our PhD algorithm for this setting by adapting the two-sided Gale--Shapley algorithm to many-to-many two-sided markets, in which the same pair can match at most once. We also generalize the three-sided market to an $n$-sided market consisting of $n-1$ two-sided markets. We extend the PhD algorithm to this multi-sided setting to compute a stable matching in polynomial time, and we discuss its extension to arbitrary quotas. Finally, we illustrate the challenges that arise when not all advisor-co-advisor pairs are compatible, and critically review the statements from [30, 29]. |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2102.11834&r=all |
| By: | Robalino, David; Romero, Jose Manuel; Walker, Ian |
| Abstract: | This paper develops a general framework to allocate subsidies to private investments in the presence of jobs-linked externalities (JLEs). JLEs emerge when wages exceed the opportunity cost of labor (labor externalities), or when there are social gains from creating better jobs for some classes of worker, such as women or youth (social externalities). Like all externalities, JLEs create a gap between private and social rates of return. Investments can be socially profitable (once the corresponding JLEs are internalized) but the private returns may be too low for the firm to go ahead. JLEs help to explain why many developing countries see insufficient investment in projects that would reallocate labor towards better jobs. The concept of JLEs is well established in economic literature, but there is a need for better operational approaches to address them. Like other externalities, JLEs can be corrected using a variety of possible subsidies (such as: grants, subsidized infrastructure, credit, training, technical assistance and tax exemptions). But doing this efficiently and at scale this requires mechanisms to (a) estimate the value of the externality and (b) discover the amount of subsidy needed to trigger the private investment. This paper shows that the optimal way to allocate subsidies to offset JLEs is through a competitive bidding process which selects projects based on the estimated amount of JLEs per dollar of subsidy. The bidding process provides an incentive to investors to reveal the subsidy needed for a project to become privately viable. The authors show that the proposed approach maximizes the jobs impacts of a given amount of fiscal resources that has been allotted to support better jobs outcomes. |
| Keywords: | social rate of return; small and medium size enterprise; share of labor in production; number of jobs; correction of market failure; Economic Rate of Retum; active labor market program; female labor force participation; business plan competition; net financial benefit; labor productivity; capital per worker; social externalities; level of employment; level of support; competitive bidding process; selection criterion; combinations of labor; total factor productivity; low labor productivity; elasticity of substitution; job creation potential; social protection system; cost of labor; job search assistance; labor market intervention; source capital; labor market reform; demand for labor; rates of return; labor market outcome; household survey data; investment in capital; interest rate subsidy; exchange rate policy; Exchange rate policies; dangerous working condition; share of profit; labor force growth; impacts on business; capital labor ratio; monte carlo simulation; number of workers; Youth in Conflict; partial risk guarantee; form of investment; share of capital; matching grant program; point of entry; SME support program; supply of labor; share of investment; privileges and immunity; social preference function; high skilled labor; unemployment benefit system; entrepreneurship support programs; domestic capital formation; private investment; financial rate; public policy; Learning and Innovation Credit; production function; fiscal resource; average cost; demand-side interventions; employment rate; opportunity cost; social value; formal sector; private investor; recent studies; private rate; market wage; job impact; labor supply; simple model; financial return; investment subsidies; young woman; expert panel; public subsidy; new job; empirical estimation; optimal allocation; firm size; young men; financial cost; weighted average; output growth; human capital; social return; labor code; minimum wage; low-skilled job; private capital; explicit subsidy; total output; firm growth; social gains; investment rate; average productivity; baseline data; wage subsidy; Wage Subsidies; market potential; outcome indicator; financial viability; environmental externality; constant term; tariff policy; increased investment; increased demand; capital input; static equilibrium; factor price; Political Economy; empirical evidence; income growth; market force; rural labor; land market; taxation system; Capital Investments; job growth; Demographic Transition; tax break; infrastructure provision; value chain; factor endowment; market demand; technological change; investment growth; capital-labor ratio; capital deepening; Macroeconomic Policy; earnings gain; random variable; Exchange Rates; government subsidy; unemployed youth; employment status; fixed budget; production technology; foregone income; net private; return increase; productivity level; social opportunities; paying job; start-up capital; capital intensity; profit to revenue; horizontal axis; paper issue; eligibility criterion; labor-intensive technology; Cash flow; managerial skill; large population; low capital; machine learning; labor-intensive production; standard error; section show; standard deviation; investment cost; virtual business; profit maximization; private information; large enterprise; low wage; labor turnover; auction mechanism; enterprise survey; aggregate employment; future research; allocation criterion; alternative subsidy; business establishment; labor demand; fiscal subsidy; fiscal envelope; public program; productivity gain; project selection; public support; knowledge spillover; risk assessment; business survival; baseline survey; predictive power; social capital; individual income; small grants; business performance; literature studies; credit market; managerial ability; financing sustainability; financing source; business management; targeted outcomes; result indicator; sales growth; negative externality; property crime; carbon emission; renewable resource |
| Date: | 2020–06–01 |
| URL: | http://d.repec.org/n?u=RePEc:wbk:jbsgrp:32113476&r=all |
| By: | Jones, D.; Louw, S.; Harvey, J. |
| Abstract: | This document has been prepared to guide practitioners on project investigation, recycling strategy selection, pavement structural design, environmental life cycle and life cycle cost assessment, mix design, and construction of in-place pavement recycling projects on flexible pavements in California. It provides information specific to California conditions to supplement the California Highway Design Manual (HDM), specification documents, and other available design guides. The main changes and updates to the 2017 version of the guide (UCPRC-GL-2017-04) include the following: • Updates to terminology used for in-place recycling • Updates to the project investigation chapter, including alignment with the new Caltrans site investigation guide, which was under review at the time of writing this guide • Updates throughout the guide to include cold central plant recycling (CCPR) • Inclusion of mechanistic-empirical design procedures (CalME) in the design chapter • Updates to the mix design chapter to align with the new California Test Method (CT-315) for mix design for partial depth recycling • Inclusion of a provisional laboratory procedure for mix designs for full-depth recycling with cement (FDR-C) • Updates to the construction chapter to align with recent specification changes |
| Keywords: | Engineering, Medicine and Health Sciences, In-place pavement recycling, partial-depth recycling, full-depth recycling, cold central plant recycling |
| Date: | 2020–12–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt54z679x4&r=all |
| By: | Volker, Jamey M.B. PhD; Handy, Susan L PhD |
| Abstract: | The National Center for Sustainable Transportation’s Induced Travel Calculator (Calculator) has generated substantial interest in the professional community as a method for estimating the additional vehicle miles traveled (VMT) induced by expanding the capacity of major roadways. The Institute of Transportation Studies at the University of California, Davis (ITS-Davis) initiated a technical assistance project to support Caltrans and others in applying the Calculator. This report: (1) provides an overview of the Calculator and the induced vehicle travel effect, (2) summarizes the results from an earlier study comparing the Calculator’s estimates with other induced travel analyses, (3) describes the technical assistance efforts and outcomes, and (4) discusses plans for future improvements to the Calculator. During the project, ITS-Davis advised Caltrans as it developed its Transportation Analysis Framework to guide transportation impact analysis for projects on the State Highway System. Caltrans published the final document in September 2020, in which it recommends that the Calculator be used where possible to estimate induced VMT. ITS-Davis also advised on efforts to apply the Calculator’s elasticity-based method to estimate induced VMT from out-of-state highway capacity expansion projects, including projects in Portland, Oregon, Washington, D.C., Kenya, and China. In a follow-up project, ITS-Davis will work with Caltrans to improve the Calculator documentation to answer questions raised by Caltrans and others, explore possible technical improvements to the Calculator, and explore opportunities for assessing the validity of the Calculator’s induced VMT estimates. |
| Keywords: | Engineering, Vehicle miles of travel, travel demand, road construction, traffic, traffic forecasting, calculators, mathematical models |
| Date: | 2021–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt2nr6q5rc&r=all |
| By: | Toshiko Matsui; Daniel Perez |
| Abstract: | In this paper, we use a variety of machine learning methods to quantify the extent to which economic and technological factors are predictive of the progression of Central Bank Digital Currencies (CBDC) within a country, using as our measure of this progression the CBDC project index (CBDCPI). We find that a financial development index is the most important feature for our model, followed by the GDP per capita and an index of the voice and accountability of the country's population. Our results are consistent with previous qualitative research which finds that countries with a high degree of financial development or digital infrastructure have more developed CBDC projects. Further, we obtain robust results when predicting the CBDCPI at different points in time. |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2102.11807&r=all |
| By: | Datta, Namita; Robinson, Danielle |
| Abstract: | This Jobs Solutions Note identifies practical solutions for development practitioners to proactively integrate gender inclusion in digital jobs programs. Based on curated knowledge and evidence for a specific topic and relevant to jobs, the Jobs Solutions Notes are not intended to be exhaustive; they provide key lessons, solutions and approaches synthesized from the experiences of the World Bank Group and partners. This Note draws from S4YE’s 2018 annual report, Digital Jobs for Youth: Young Women in the Digital Economy, highlighting new and emerging strategies to designing gender-inclusive digital jobs interventions for youth. The Note employs a nuanced definition of 'digital jobs' to enable practitioners and policy makers to develop a range of interventions tailored to specific contexts and target groups, to improve young women’s employment outcomes from digital jobs programs. |
| Keywords: | young woman; limited access to finance; youth; digital skills; labor force participation rate; income-generating opportunity; computers and the internet; project design and implementation; Fragile, Conflict & Violence; small and medium size enterprise; skill need; youth employment; skill training programs; skills and support; labor market opportunities; youth unemployment rate; self-employment and entrepreneurship; lack of content; highly skilled worker; approach to training; needs of woman; digital gender divide; availability of transport; informal labor market; barrier to woman; return on investment; private sector partner; support for entrepreneur; private sector company; women in technology; access to ict; fragile and conflict; technical skills training; creative problem solving; people with disability; Gender and ICT; opportunity for woman; civil society actor; local labor market; barriers for woman; gender mainstreaming strategy; business process outsourcing; digital economy; female entrepreneur; digital divide |
| Date: | 2020–04–29 |
| URL: | http://d.repec.org/n?u=RePEc:wbk:jbsgrp:32005465&r=all |