Centre dedocumentation
scientifique

Decentralized markets and the emergence of housing wealth inequality / Omar A. Guerrero in Computers, Environment and Urban Systems, vol 84 (November 2020)  

Public [article]  inComputers, Environment and Urban Systems > vol 84 (November 2020) . - n° 101541 Titre : Decentralized markets and the emergence of housing wealth inequality Type de document : Article/Communication Auteurs : Omar A. Guerrero, Auteur Année de publication : 2020 Article en page(s) : n° 101541 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse socio-économique [Termes IGN] bien immobilier [Termes IGN] coefficient de Gini [Termes IGN] évaluation foncière [Termes IGN] inégalité [Termes IGN] logement [Termes IGN] marché foncier [Termes IGN] modèle orienté agent [Termes IGN] patrimoine immobilier [Termes IGN] propriété foncière [Termes IGN] Royaume-Uni Résumé : (auteur) Recent studies suggest that the traditional determinants of housing wealth are insufficient to explain its current inequality levels. Thus, they argue that efforts should focus on understanding institutional factors. From the perspective of complex adaptive systems, institutions are more than the ‘the rules of the game’, they also consider the interaction protocols or the ‘algorithm’ through which agents engage in socioeconomic activities. By viewing markets as complex adaptive systems, I develop a model that allows estimating how much housing wealth inequality is attributable to the market institution. It combines virtues from two different modeling traditions: (1) the microeconomic foundations from overlapping-generation models and (2) the explicit interaction protocols of agent-based models. Overall, the model generates prices and housing inequality endogenously and from bottom-up; without needing to impose assumptions about the aggregate behavior of the market (such as market equilibrium). It accounts for economic and institutional factors that are important to housing consumption decisions (e.g., wages, consumption of goods, non-labor income, government transfers, taxes, etc.). I calibrate the model with the British Wealth and Assets Survey at the level of each individual household (i.e., ~25 million agents). By performing counter-factual simulations that control for data heterogeneity, I estimate that, in the United Kingdom, the decentralized protocol interaction of the housing market contributes with one to two thirds of the Gini coefficient. I perform policy experiments and compare the outcomes between an expansion in the housing stock, a sales tax, and an inheritance tax. The results raise concerns about the limitations of traditional policies and call for a careful re-examination of housing wealth inequality. Numéro de notice : A2020-711 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2020.101541 date de publication en ligne : 26/08/2020 En ligne : https://doi.org/10.1016/j.compenvurbsys.2020.101541 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96268 [article]

Using OpenStreetMap data and machine learning to generate socio-economic indicators / Daniel Feldmeyer in ISPRS International journal of geo-information, vol 9 n° 9 (September 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 9 (September 2020) . - 16 p. Titre : Using OpenStreetMap data and machine learning to generate socio-economic indicators Type de document : Article/Communication Auteurs : Daniel Feldmeyer, Auteur ; Claude Meisch, Auteur ; Holger Sauter, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 16 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] Allemagne [Termes IGN] apprentissage automatique [Termes IGN] arbre aléatoire [Termes IGN] base de données spatiotemporelles [Termes IGN] changement climatique [Termes IGN] chômage [Termes IGN] classification par réseau neuronal [Termes IGN] collectivité territoriale [Termes IGN] données localisées des bénévoles [Termes IGN] données socio-économiques [Termes IGN] inégalité [Termes IGN] limite administrative [Termes IGN] modèle de régression [Termes IGN] modèle de simulation [Termes IGN] OpenStreetMap Résumé : (auteur) Socio-economic indicators are key to understanding societal challenges. They disassemble complex phenomena to gain insights and deepen understanding. Specific subsets of indicators have been developed to describe sustainability, human development, vulnerability, risk, resilience and climate change adaptation. Nonetheless, insufficient quality and availability of data often limit their explanatory power. Spatial and temporal resolution are often not at a scale appropriate for monitoring. Socio-economic indicators are mostly provided by governmental institutions and are therefore limited to administrative boundaries. Furthermore, different methodological computation approaches for the same indicator impair comparability between countries and regions. OpenStreetMap (OSM) provides an unparalleled standardized global database with a high spatiotemporal resolution. Surprisingly, the potential of OSM seems largely unexplored in this context. In this study, we used machine learning to predict four exemplary socio-economic indicators for municipalities based on OSM. By comparing the predictive power of neural networks to statistical regression models, we evaluated the unhinged resources of OSM for indicator development. OSM provides prospects for monitoring across administrative boundaries, interdisciplinary topics, and semi-quantitative factors like social cohesion. Further research is still required to, for example, determine the impact of regional and international differences in user contributions on the outputs. Nonetheless, this database can provide meaningful insight into otherwise unknown spatial differences in social, environmental or economic inequalities. Numéro de notice : A2020-663 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9090498 date de publication en ligne : 21/08/2020 En ligne : https://doi.org/10.3390/ijgi9090498 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96139 [article]

Measuring differential access to facilities between population groups using spatial Lorenz curves and related indices / Gordon A. Cromley in Transactions in GIS, Vol 23 n° 6 (November 2019)  

Public [article]  inTransactions in GIS > Vol 23 n° 6 (November 2019) . - pp 1332 - 1351 Titre : Measuring differential access to facilities between population groups using spatial Lorenz curves and related indices Type de document : Article/Communication Auteurs : Gordon A. Cromley, Auteur Année de publication : 2019 Article en page(s) : pp 1332 - 1351 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] accessibilité [Termes IGN] coefficient de Gini [Termes IGN] commerce [Termes IGN] courbe de Lorenz [Termes IGN] distribution spatiale [Termes IGN] équipement collectif [Termes IGN] inégalité [Termes IGN] Ohio (Etats-Unis) [Termes IGN] population [Termes IGN] segmentation [Termes IGN] service public [Termes IGN] sociologie [Termes IGN] système d'information géographique Résumé : (auteur) Access to certain types of facilities can promote health and well‐being. When population and facilities are not uniformly distributed across the landscape, inequities in accessibility may occur. Current research into GIS‐based accessibility measures has focused primarily on spatial inequities between different geographic locations but not directly on differences in accessibility between subgroups of the population. The research presented here develops a new method for measuring differential accessibility to facilities between various segments of the population. The method extends concepts and techniques in spatial point pattern analysis that account for the spatial structure of demand and its relationship to supply. In this approach, the traditional Lorenz curve and its associated indices, the Gini coefficient and the dissimilarity index, which are used to measure inequality, are recast in spatial terms for measuring differences in accessibility between population subgroups. An analysis of spatial accessibility to grocery stores in Akron, OH illustrates the value of the spatial Lorenz curve and its associated indices compared to other methods. Numéro de notice : A2019-567 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12577 date de publication en ligne : 06/10/2019 En ligne : https://onlinelibrary.wiley.com/doi/10.1111/tgis.12577 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94419 [article]

Mapping inequality in London : a different approach / M. Green in Cartographic journal (the), vol 49 n° 3 (August 2012)  

Public [article]  inCartographic journal (the) > vol 49 n° 3 (August 2012) . - pp 247 - 255 Titre : Mapping inequality in London : a different approach Type de document : Article/Communication Auteurs : M. Green, Auteur Année de publication : 2012 Article en page(s) : pp 247 - 255 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] carte thématique [Termes IGN] inégalité [Termes IGN] Londres [Termes IGN] pauvreté [Termes IGN] représentation cartographique Résumé : (Auteur) Maps provide an effective means of distributing ideas simply, creating a format where spatial data can be easily understood. However, a lot of people are not aware where administrative boundaries lie, limiting their appeal for educating the public on important issues such as poverty and inequality. This paper seeks to utilize a well-known cartographic map design, the London Underground map, to aid data dissemination of the complex issues surrounding inequality and deprivation in London. A discussion of the relevance of this approach to researching inequality in London, as well as how this fits in with previous approaches to mapping poverty is provided. An example using the recent release of the Indices of Multiple Deprivation 2010 shows the usefulness of this design. Numéro de notice : A2012-539 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1179/1743277412Y.0000000018 date de publication en ligne : 22/11/2013 En ligne : https://doi.org/10.1179/1743277412Y.0000000018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31985 [article]

Réservation

Réserver ce document

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
030-2012031	RAB	Revue	Centre de documentation	En réserve 3L	Disponible

Mathématiques, enseignement supérieur technique, 1. 1, Analyse, cours et exercices / Elie Azoulay (1985)

Public Titre de série : Mathématiques, enseignement supérieur technique, 1 Titre : 1, Analyse, cours et exercices Type de document : Guide/Manuel Auteurs : Elie Azoulay, Auteur ; Jean Avignant, Auteur Editeur : Boston, New York, ... : McGraw-Hill Année de publication : 1985 Importance : 286 p. Format : 15 x 22 cm ISBN/ISSN/EAN : 978-2-7042-1064-0 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Analyse mathématique [Termes IGN] fonction exponentielle [Termes IGN] fonction hyperbolique [Termes IGN] inégalité [Termes IGN] intégrale [Termes IGN] primitive [Termes IGN] série de Taylor [Termes IGN] variable Numéro de notice : 55661A Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE Nature : Manuel de cours Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=48349

Réservation

Réserver ce document

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
55661-01A	23.30	Livre	Centre de documentation	En réserve 1L	Disponible