671 research outputs found

    Functional Labour Market Areas for Chile

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    Administrative areas are arbitrarily designed and do not necessarily reflect the geographical patterns of socio-economic and labour market activity. Labour market areas (LMAs) are required to analyse spatial labour market activity and provide a framework to guide spatially-explicit employment policy development. This resource describes a data source of a set of recently created labour market areas for Chile.</jats:p

    Changing post-school pathways and outcomes: Melbourne and regional students

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    A Generalisable Data Fusion Framework to Infer Mode of Transport Using Mobile Phone Data

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    Cities often lack up-to-date data analytics to evaluate and implement transport planning interventions to achieve sustainability goals, as traditional data sources are expensive, infrequent, and suffer from data latency. Mobile phone data provide an inexpensive source of geospatial information to capture human mobility at unprecedented geographic and temporal granularity. This paper proposes a method to estimate updated mode of transportation usage in a city, with novel usage of mobile phone application traces to infer previously hard to detect modes, such as bikes and ride-hailing/taxi. By using data fusion and matrix factorisation, we integrate socioeconomic and demographic attributes of the local resident population into the model. We tested the method in a case study of Santiago (Chile), and found that changes from 2012 to 2020 in mode of transportation inferred by the method are coherent with expectations from domain knowledge and the literature, such as ride-hailing trips replacing mass transport.Comment: 19 pages, 8 figure

    Interregional migration efficiency in adjusting regional labour markets in Chile

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    The objective of the article is to re-review the interregional migration process in Chile according to Aroca & Hewings (2002), using up-dated data of 1992 and 2002 from CENSO of population and housing in a probability model probit. Additionally, analyse the efficiency of the interregional migration process in terms of equalising regional salaries and unemployment rates. The results show that signal labour markets are less important for explaining the probability to migrate related to others regional characteristics and the migration process is inefficient to adjust regional markets. The results are consistent with previous findings.Migración Intrarregional; Empleo; Desempleo; Salarios; Utilidad

    A Major Uplift

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    This editorial describes improvements REGION implemented in the first months of 2022. Although they are not directly visible to authors or readers, they are important for the quality of the journal and for the visibility of the articles published in REGION.</jats:p

    Internal Migration Intensity and Impact in Europe

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    Globally, internal migrants outnumber international migrants by 4 to 1 (Bell et al 2015) and recent years have seen significant progress in understanding internal migration in a comparative framework. The IMAGE project (Internal Migration Around the GlobE) developed a rigorous framework for cross-national comparisons of internal migration, involving (1) a suite of statistical indicators, (2) methods to generate estimates where comparable metrics are not collected directly, and (3) a global repository of internal migration data. The Aggregate Crude Migration Intensity (ACMI) captures the intensity of internal migration measuring all changes of address in a given interval. The Migration Effectiveness Index (MEI), which ranges from 0 to 100, quantifies the degree of balance between flows and counterflows, with low values indicating largely reciprocal exchanges between regions, while high values suggest strongly directional flows. Together, intensity and effectiveness drive the redistributive impact of migration on national populations.</p

    Using Twitter Data to Monitor Immigration Sentiment

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    This repository contains the relevant data and code to replicate the analysis and results reported in the paper "Using Twitter Data to Monitor Immigration Sentiment", forthcoming in A practitioner Guide Book to be published by International Organization for Migration.</p
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