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dc.contributor.authorSobieraj, Janusz
dc.contributor.authorMetelski, Dominik Igor
dc.date.accessioned2022-03-29T12:30:04Z
dc.date.available2022-03-29T12:30:04Z
dc.date.issued2022-02-07
dc.identifier.citationSobieraj, J.; Metelski, D. Private Renting vs. Mortgage Home Buying: Case of British Housing Market—A Bayesian Network and Directed Acyclic Graphs Approach. Buildings 2022, 12, 189. [https://doi.org/10.3390/buildings12020189]es_ES
dc.identifier.urihttp://hdl.handle.net/10481/73922
dc.description.abstractThe worsening of housing problems in many countries has become a topic of global interest. Researchers point to a variety of factors that influence individual housing tenure decisions. Our study is based on longitudinal English Housing Survey (EHS) data (2008–2009 to 2019–2020, with survey years matching financial years, i.e., running April–March) and identifies flows between different forms of housing tenure in the U.K. and analyses conditional dependencies of a range of EHS variables using a directed acyclic graph (DAG). More specifically, we take into account variables such as first-time buyers (FTB), mortgage payments, rent payments, share of mortgage/rent in household income, and receipt of housing benefit (HB), with some variables also reflecting a regional breakdown (captured separately for London and England excluding London) to illustrate the complex nature of regional differences in explaining changes in housing tenure. We address some of the problems and challenges of the housing market in the U.K. today, and, in particular, examine what influences private renters and those buying with a mortgage. A key conclusion from this study is that housing benefit does not necessarily ease the way for private renters into their own housing. The study is quantitative in nature and uses the English Housing Survey and Bayesian network (BN) analysis. Unlike traditional methods, such as multiple regression or panel regression, where the researcher somehow suggests the type of a relationship between certain variables, BN’s learning algorithm analyses different iterations between variables and finds the most appropriate relationships between them.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAtribución 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectHousing tenure in U.K.es_ES
dc.subjectPrivate renterses_ES
dc.subjectBuying with mortgagees_ES
dc.subjectBayesian network (BN) analysises_ES
dc.subjectDirectional acyclic graph (DAG)es_ES
dc.titlePrivate Renting vs. Mortgage Home Buying: Case of British Housing Market—A Bayesian Network and Directed Acyclic Graphs Approaches_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.3390/buildings12020189
dc.type.hasVersionVoRes_ES


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