Unemployment insurance and training in an equilibrium matching model with heterogeneous agents

This paper develops a joint evaluation of vocational training and unemployment insurance. This allows to analyze how these schemes complment each other from the viewpoints of labor market indicators and of welfare. For this purpose, a general equilibrium matching model is built where workers are heterogeneous and risk averse. Heterogeneity allows to look at the distribution of the effects. Job search effort and wages are endogenous in order to deal with the induced effects of these schemes. The net effect of these training programs appears to be gloomy. However, their impact on employment can be deeply affected by the design of passive policies. A declining time profile of benefit payments dominates a scheme with a constant replacement ratio. However, the optimal expected length of payment of ‘high’ benefits can vary a lot in the population. A reform that would relate this expected duration to search effort does not appear to produce substantial effects on any of the evaluation crieria. Performance indicators of the labor market and welfare criteria often vary in opposite directions after a reform. This questions the widespread focus on labor market indicators to guide the design of institutional reforms.training; unemployment insurance; sanctions; policy complementaries; wage bargaining; equilibrium unemployment; equilibrium search

Human-Machine Collaborative Optimization via Apprenticeship Scheduling

Coordinating agents to complete a set of tasks with intercoupled temporal and resource constraints is computationally challenging, yet human domain experts can solve these difficult scheduling problems using paradigms learned through years of apprenticeship. A process for manually codifying this domain knowledge within a computational framework is necessary to scale beyond the ``single-expert, single-trainee" apprenticeship model. However, human domain experts often have difficulty describing their decision-making processes, causing the codification of this knowledge to become laborious. We propose a new approach for capturing domain-expert heuristics through a pairwise ranking formulation. Our approach is model-free and does not require enumerating or iterating through a large state space. We empirically demonstrate that this approach accurately learns multifaceted heuristics on a synthetic data set incorporating job-shop scheduling and vehicle routing problems, as well as on two real-world data sets consisting of demonstrations of experts solving a weapon-to-target assignment problem and a hospital resource allocation problem. We also demonstrate that policies learned from human scheduling demonstration via apprenticeship learning can substantially improve the efficiency of a branch-and-bound search for an optimal schedule. We employ this human-machine collaborative optimization technique on a variant of the weapon-to-target assignment problem. We demonstrate that this technique generates solutions substantially superior to those produced by human domain experts at a rate up to 9.5 times faster than an optimization approach and can be applied to optimally solve problems twice as complex as those solved by a human demonstrator.Comment: Portions of this paper were published in the Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) in 2016 and in the Proceedings of Robotics: Science and Systems (RSS) in 2016. The paper consists of 50 pages with 11 figures and 4 table

Challenges for modelling interventions for future pandemics

Funding: This work was supported by the Isaac Newton Institute (EPSRC grant no. EP/R014604/1). MEK was supported by grants from The Netherlands Organisation for Health Research and Development (ZonMw), grant number 10430022010001, and grant number 91216062, and by the H2020 Project 101003480 (CORESMA). RNT was supported by the UKRI, grant number EP/V053507/1. GR was supported by Fundação para a Ciência e a Tecnologia (FCT) project reference 131_596787873. and by the VERDI project 101045989 funded by the European Union. LP and CO are funded by the Wellcome Trust and the Royal Society (grant 202562/Z/16/Z). LP is also supported by the UKRI through the JUNIPER modelling consortium (grant number MR/V038613/1) and by The Alan Turing Institute for Data Science and Artificial Intelligence. HBS is funded by the Wellcome Trust and Royal Society (202562/Z/16/Z), and the Alexander von Humboldt Foundation. DV had support from the National Council for Scientific and Technological Development of Brazil (CNPq - Refs. 441057/2020-9, 424141/2018-3, 309569/2019-2). FS is supported by the UKRI through the JUNIPER modelling consortium (grant number MR/V038613/1). EF is supported by UKRI (Medical Research Council)/Department of Health and Social Care (National Insitute of Health Research) MR/V028618/1. JPG's work was supported by funding from the UK Health Security Agency and the UK Department of Health and Social Care.Mathematical modelling and statistical inference provide a framework to evaluate different non-pharmaceutical and pharmaceutical interventions for the control of epidemics that has been widely used during the COVID-19 pandemic. In this paper, lessons learned from this and previous epidemics are used to highlight the challenges for future pandemic control. We consider the availability and use of data, as well as the need for correct parameterisation and calibration for different model frameworks. We discuss challenges that arise in describing and distinguishing between different interventions, within different modelling structures, and allowing both within and between host dynamics. We also highlight challenges in modelling the health economic and political aspects of interventions. Given the diversity of these challenges, a broad variety of interdisciplinary expertise is needed to address them, combining mathematical knowledge with biological and social insights, and including health economics and communication skills. Addressing these challenges for the future requires strong cross-disciplinary collaboration together with close communication between scientists and policy makers.Publisher PDFPeer reviewe

Economics Of Coastal Erosion And Adaptation To Sea Level Rise

This article provides a review and synthesis of geoeconomic models that are used to analyze coastal erosion management and shoreline change. We outline a generic framework for analyzing risk-mitigating and/or recreation-enhancing policy interventions within a dynamic framework, and we review literature that informs the nature and extent of net benefit flows associated with coastal management. Using stated preference analysis, we present new estimates on household preferences for shoreline erosion management, including costs associated with ecological impacts of management. Lastly, we offer some guidance on directions for future research

J-SPACE: a Julia package for the simulation of spatial models of cancer evolution and of sequencing experiments

Background: The combined effects of biological variability and measurement-related errors on cancer sequencing data remain largely unexplored. However, the spatio-temporal simulation of multi-cellular systems provides a powerful instrument to address this issue. In particular, efficient algorithmic frameworks are needed to overcome the harsh trade-off between scalability and expressivity, so to allow one to simulate both realistic cancer evolution scenarios and the related sequencing experiments, which can then be used to benchmark downstream bioinformatics methods.Result: We introduce a Julia package for SPAtial Cancer Evolution (J-SPACE), which allows one to model and simulate a broad set of experimental scenarios, phenomenological rules and sequencing settings.Specifically, J-SPACE simulates the spatial dynamics of cells as a continuous-time multi-type birth-death stochastic process on a arbitrary graph, employing different rules of interaction and an optimised Gillespie algorithm. The evolutionary dynamics of genomic alterations (single-nucleotide variants and indels) is simulated either under the Infinite Sites Assumption or several different substitution models, including one based on mutational signatures. After mimicking the spatial sampling of tumour cells, J-SPACE returns the related phylogenetic model, and allows one to generate synthetic reads from several Next-Generation Sequencing (NGS) platforms, via the ART read simulator. The results are finally returned in standard FASTA, FASTQ, SAM, ALN and Newick file formats.Conclusion: J-SPACE is designed to efficiently simulate the heterogeneous behaviour of a large number of cancer cells and produces a rich set of outputs. Our framework is useful to investigate the emergent spatial dynamics of cancer subpopulations, as well as to assess the impact of incomplete sampling and of experiment-specific errors. Importantly, the output of J-SPACE is designed to allow the performance assessment of downstream bioinformatics pipelines processing NGS data. J-SPACE is freely available at: https://github.com/BIMIB-DISCo/J-Space.jl

Effects of Equal Volume But Different Plyometric Jump Training Intensities on Components of Physical Fitness in Physically Active Young Males

Ramirez-Campillo, R, Moran, J, Drury, B, Williams, M, Keogh, JW, Chaabene, H, and Granacher, U. Effects of equal volume but different plyometric jump training intensities on components of physical fitness in physically active young males. J Strength Cond Res XX(X): 000–000, 2019—An 8-week single-blind randomized controlled trial was conducted to compare the effects of separate programs of equal volume, but different intensity, plyometric jump training (PJT), on physical fitness in healthy adults. Thirty-eight physically active males (mean age: 21.8 6 2.5 years) participated. Subjects were randomly assigned to one of 3 PJT groups or a control (CON, n = 9) according to their jump performance. Plyometric jump training was conducted at maximal (PJT-100, n = 10), high (PJT-80, n = 9), or moderate (PJT-65, n = 10) intensity within each group. Baseline and follow-up tests were performed for the assessment of countermovement jump (CMJ) height, CMJ height with arm swing (CMJA), and drop jump height from a 20-cm drop box (DJ20), linear speed (30 m), and change-of-direction speed (CODS) (the Illinois CODS test). Results revealed significant group 3 time interactions for CMJ, CMJA, DJ20, 30-m sprint, and CODS (all p , 0.001; d = 0.39–0.76). Post hoc analyses showed significant improvements in all 5 fitness measures for PJT-100 (all p , 0.01, D3.7–13.5%, d = 0.26–1.4). For PJT-80, 3 of 5 fitness tests demonstrated significant change (CMJ: p , 0.001, D5.9%, d = 0.33; CMJA: p , 0.001, D7.0%, d = 0.43; CODS: p , 0.001, D3.9%, d = 0.9), and for PJT-65, only 1 test was significant (CMJ: p , 0.05, D2.8%, d = 0.15). No significant changes were observed in CON. Except for similar gains in DJ20 and 30-m sprint in PJT-100 and PJT-80, gains in physical fitness were, in general, greater (p , 0.05) after PJT-100 vs. PJT-80 vs. PJT-65 vs. CON. Therefore, maximal PJT intensity may induce larger physical fitness gains, although high and moderate intensities may also be useful, but to a lesser exten

Modelling the interplay between human behaviour and the spread of infectious diseases: From toy models to quantitative approaches

Prevenir la propagació de malalties infeccioses és un dels reptes més grans de la humanitat. Moltes malalties es transmeten per contacte, per la qual cosa la xarxa d'interaccions humanes actua com a substrat per a la propagació. Per aquest motiu, els models epidèmics sempre inclouen, ja sigui implícita o explícitament, una descripció de com els éssers humans interactuen entre ells. Malgrat això, actualment no es disposa d’una teoria general de la interacció entre el comportament humà i la propagació d'agents. L’objectiu d’aquesta tesi és contribuir a la descripció matemàtica del comportament humà en el context de les malalties infeccioses, treballant tant amb models quantitatius com qualitatius. En el primer capítol es desenvolupen dos models qualitatius per entendre com l’adopció de mesures profilàctiques de manera dinàmica basada en el risc pot causar cicles epidèmics. En el segon capítol, considerem aspectes estàtics específics del comportament humà -homofília i patrons de contacte heterogenis- i n'analitzem les implicacions en el control d'epidèmies. En contrast amb el què es creia anteriorment, demostrem que l'homofília en l'adopció d’eines profilàctiques no sempre resulta perjudicial. A més a més, qüestionem el paradigma actual de les estratègies d'immunització basades en el risc. L'últim capítol d'aquesta tesi se centra en enfocs quantitatius per modelitzar la propagació del SARS-CoV-2, en particular la primera onada i la propagació de la variant Delta. A més dels avenços metodològics, mostrem com l’adaptació voluntària del comportament va determinar el curs de l’epidèmia més enllà de les intervencions no farmacèutiques. En conjunt, aquesta tesi revela una nova fenomenologia, afegeix proves empíriques addicionals i proporciona noves eines per analitzar com evolucionen el comportament humà i les epidèmies. La combinació d'enfocaments quantitatius i qualitatius també proporciona una via per analitzar i interpretar l’enorme quantitat de dades recopilades durant la pandèmia de SARS-CoV-2.Prevenir la propagación de enfermedades infecciosas es uno de los mayores retos de la humanidad. Muchas enfermedades se transmiten por contacto, por lo que la red de interacciones humanas actúa como sustrato para su propagación. Por esta razón, los modelos epidémicos siempre incluyen una descripción de cómo interactúan los seres humanos entre ellos. Sin embargo, actualmente no existe una teoría general de la interacción entre el comportamiento humano y la propagación de agentes. El objetivo de esta tesis es contribuir a la descripción matemática del comportamiento humano en el contexto de las enfermedades infecciosas, trabajando tanto con modelos cuantitativos como cualitativos. El primer capítulo desarrolla dos modelos cualitativos para esbozar cómo la profilaxis dinámica basada en el riesgo puede sostener ciclos epidémicos. En el segundo capítulo, consideramos aspectos estáticos específicos del comportamiento humano -homofilia y patrones de contacto heterogéneos- y analizamos sus implicaciones en el control de epidemias. En contraste con resultados anteriores, demostramos que la homofilia en la adopción de herramientas profilácticas no siempre es perjudicial. Además, cuestionamos el paradigma actual de las estrategias de inmunización basadas en el riesgo. El último capítulo de esta tesis se centra en enfoques cuantitativos para modelizar la propagación del SARS-CoV-2, en particular, la primera oleada y la propagación de la variante Delta. Además de los avances metodológicos, mostramos cómo la adaptación voluntaria del comportamiento fue capaz de determinar el curso de la epidemia más allá de las intervenciones no farmacéuticas. En conjunto, esta tesis desvela una nueva fenomenología, añade pruebas empíricas adicionales y proporciona nuevas herramientas para analizar cómo evolucionan el comportamiento humano y las epidemias. La combinación de enfoques cuantitativos y cualitativos proporciona una vía muy útil para analizar e interpretar la gran cantidad de datos recopilados durante la pandemia de SARS-CoV-2. Preventing the spread of infectious diseases is one of the greatest challenges of humanity's past, present, and foreseeable future. Many infectious diseases are transmitted upon contact, and hence the complex web of human interactions acts as a substrate for their propagation. For this reason, epidemic models always comprise, either explicitly or implicitly, a description of how humans interact. However, the quest for a general theory of the interplay between human behaviour and the spread of pathogens is far from complete. The aim of this thesis is to contribute to the mathematical description of human behaviour in the context of infectious diseases, working with both quantitative and qualitative models. The first chapter develops two qualitative toy models to outline how dynamical risk-based prophylaxis can sustain epidemic cycles. In the second chapter, we consider specific static aspects of human behaviour -- homophily and heterogeneous contact patterns -- and analyse their implications on epidemic control. In contrast to previous belief, we show that homophily in the adoption of many prophylactic tools is not always detrimental. Furthermore, we question the current paradigm of risk-based immunisation strategies and show that targeting hubs is only optimal for protection with high efficacy. The last chapter of this thesis focuses on quantitative approaches to model the spread of SARS-CoV-2, in particular, the first wave and the spread of the Delta variant. Besides the methodological advances, we add evidence of how voluntary behavioural adaptation shaped the course of the epidemic beyond non-pharmaceutical interventions. Overall, this thesis unveils new phenomenology, adds additional empirical evidence, and provides new tools to analyse how human behaviour and epidemics coevolve. The flexible blend of quantitative and qualitative approaches may also provide a pathway to analyse and interpret the vast amount of data currently collected during the SARS-CoV-2 pandemic

Grain marketing policy changes and spatial efficiency of maize and wheat markets in Ethiopia

"In the context of on-going market reform in developing countries, there is a need for an improvement in the existing methods of spatial market efficiency analysis in order to better inform the debate toward designing and implementing new grain marketing policies, institutions, and infrastructure that facilitate the emergence of a well developed and competitive grain marketing system. The standard parity bounds model (PBM), while it overcomes many weaknesses of the conventional methods of spatial market efficiency analysis, it does not allow for the test of structural changes in spatial market efficiency as a result of policy changes. In this paper, building on the standard PBM, we develop an extended parity bounds model (EPBM). The EPBM is a stochastic gradual switching model with three trade regimes. The EPBM is estimated by maximum likelihood procedure and allows for tracing the time path and structural change in spatial market efficiency conditions due to the policy changes. We applied the EPBM to analyze the effect of grain marketing policy changes on spatial efficiency of maize and wheat markets in Ethiopia. The results show that the effect of policy changes on spatial market efficiency is not significant statistically in many cases; there is high probability of spatial inefficiency in maize and wheat markets before and after the policy changes. The implication of these results is that maize and wheat markets are characterized by periodic gluts and shortages, which can undermine the welfare of producers, grain traders and consumers. It is also observed that the nature of spatial inefficiency for maize and wheat markets is different implying that the two commodities might require different policy responses in order to improve spatial market efficiency. Maize traders made losses most of the time while wheat traders made excess profits most of the time covered by the study." Authors' AbstractStochastic analysis ,structural change ,

Evaluating Impacts of Development Programs on Female Education in Afghanistan

This dissertation evaluates the effects of three development interventions on female education in Afghanistan: 1) effects of foreign military withdrawal on females’ demand for higher education; 2) impacts of PEZAK, a community-driven university entrance preparation, on student enrollment and performance in tertiary education; and 3) long-term effects of National Solidarity Program (NSP), that established gender-balanced local development councils, on female enrollment. Foreign military withdrawal increased female participation in higher education by 0.3 percentage points from a base value of 0.05 percent participation per capita. The PEZAK increased test scores by 0.17 standard deviations and had a positiveeffect on enrollment in top programs. Female students exposed to the PEZAK had a lower likelihood of enrollment in low-rank universities as compared to treated male students. In areas with favorable attitudes toward women, the NSP increased female enrollment in higher grades. In culturally conservative places, the NSP was counterproductive. Findings in this dissertation inform development policies related to women’s empowerment in conservative and fragile state settings