606 research outputs found

    i-FRAME – Assessing impacts of social policy innovation in the EU: Proposed methodological framework to evaluate socio-economic returns on investment of social policy innovations

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    This report presents the final proposal for developing a methodological framework to assess the impacts generated by social policy innovations which promote social investment in the EU, in short i-FRAME. This framework has the objective to provide a structured approach that shall serve as a comprehensive framework for conducting analysis of the economic and social returns on investments of social policy innovations. It also aims to act as a guide to gather insights into replicability and transferability of initiatives which promote social investment across the EU. The report outlines the reviewed and improved theoretical and methodological approach developed by the JRC with help from external experts, and validated by testing the operational components proposed on a number of case studies and scenarios of use. After outlining the conceptual and methodological approach underpinning the i-FRAME (V1.0), the report discusses the proposal for building its operational components according to a structured theoretical framework of a dynamic simulation model for social impact assessment (V1.5). The final proposal for i-FRAME (V2.0) and an overview of the operational components for its implementation are then presented discussing the key elements that should be developed to build a comprehensive i-FRAME Web-Platform and simulator for social impact assessment. Conclusions are then offered in terms of implications for policy and directions for future research. These were drawn after consulting experts from different research disciplines, practitioners and representatives of relevant stakeholders and policymakers, and they include .recommendations for further developing the operational components proposed, paving the way towards building the i-FRAME (V3.0) and beyond.JRC.B.4-Human Capital and Employmen

    Foundations of GAM Research. Methodological Guidelines for Designing and Conducting Research that Combines Games and Agent-based Models

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    This thesis presents the development of the games and agent-based model methodology and provides methodological guidelines for using GAM research, i.e., combining games and agent-based models in research. GAM research is rooted in complexity sciences and transdisciplinary research, offering valuable insights into complex, adaptable systems. GAM research has particular relevance in decision-making and complex-system management, thus fostering collaboration among scientists and non-academics from various disciplines. It is an engaging platform for data collection and stakeholder processes, thus enriching causal explanations. It should be noted that GAM research has the potential to overcome the limitations of traditional methods by facilitating hypothesis testing with simulation-based observations of human behaviours. Investigations in GAM research can change how social science addresses pressing global challenges. The immersive nature of games combined with agent-based models offers an innovative approach that attracts diverse participants, making it a promising tool for science that reaches beyond the classic academic spheres. As a comprehensive handbook, this thesis offers researchers inspiration and references for conducting GAM research across diverse application domains. This thesis presents an assessment of the state of research that combines games and agent-based models and proposes a structured approach to making progress in this field. Addressing the lack of a standardised methodology, this thesis is aimed at improving research practices, transparency, and replicability . Practical advice is provided for guiding researchers through designing and conducting GAM research, thus promoting rigorous and comprehensive studies

    An Exploratory Study of Value Added Services

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    Purpose: Using data from 104 countries over a six-year period (2009-2014), this study proposes a value-added predictor in service industries based on the eight indicators of the prosperity index, namely economy, entrepreneurship and opportunity, governance, education, health, safety and security, personal freedom, and social capital. Design/methodology/approach: The fuzzy-set qualitative comparative analysis (fsQCA) and complexity theory, a relatively novel approach for developing and testing the conceptual model, are used for asymmetric modelling of value added in service industries, and the predictive validity of the proposed configural model is tested. Findings: Apart from advancing method and theory, this study simulates causal conditions (i.e., recipes) leading to both high and low scores of the value added of services. The configural conditions indicating a high/low level of value added in service industries can be used as a guiding strategy for marketers, investors and policy makers. Originality/value: An analysis of worldwide data provides complex models demonstrating both how to regulate country conditions to achieve a high value-added score and select a foreign country for investment that offers a high level of value added service

    Risk and vulnerability analysis in society’s proactive emergency management: Developing methods and improving practices

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    Risk and vulnerability analyses can play important roles in the society’s proactive emergency management. This thesis addresses two ways of improving the analysis of risk and vulnerability analysis in this context. First, by developing methods for risk and vulnerability analysis of technical infrastructure networks and emergency response systems. Secondly, by aiming to improve practises related to RVA through an evaluation of Swedish municipal RVAs and an empirical study of how various disaster characteristics affect people judgments of disaster seriousness. The research has to a large extent been carried out by using a design research approach developed in the thesis

    Education and optimal dynamic taxation: The role of income-contingent student loans

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    We study Pareto optimal tax and education policies when human capital upon labor market entry is endogenous and individuals face wage uncertainty. Though optimal labor distortions are history-dependent, i.e. depend on income and education, simple policy instruments can yield the desired distortions: a single nonlinear labor income tax schedule combined with income-contingent loans. To take themodel to the (US) data, we simplify the model to a binary education decision (graduating from college or not). We find that for lowand intermediate incomes the labor supply decision of college graduates should be distorted more heavily than for individuals without a college degree. As a consequence, the optimal student loan repayment schedule increases in income for this range. This result holds along the Pareto frontier. We compare the second best to a situation where loan repayment is restricted to be independent from income and find significant welfare gains.Optimal dynamic taxation, education, implementation

    Net reductions or spatiotemporal displacement of intentional wildfires in response to arrests? : evidence from Spain

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    Research to date has not examined how the impacts of arrests manifest across space and time in environmental crimes. We evaluate whether arrests reduce or merely spatiotemporally displace intentional illegal outdoor firesetting. Using municipality-level daily wildfire count data from Galicia, Spain, from 1999 to 2014, we develop daily spatiotemporal ignition count models of agricultural, non-agricultural and total intentional illegal wildfires as functions of spatiotemporally lagged arrests, the election cycle, seasonal and day indicators, meteorological factors and socioeconomic variables. We find evidence that arrests reduce future intentional illegal fires across space in subsequent time periods.This research was partly funded by Project ECO2017–89274-R MINECO/AEI/FEDER, UES

    The Greek crisis in focus: austerity, recession and paths to recovery

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