1,720,984 research outputs found
Spatial Autocorrelation and Real Estate Studies: A Literature Review
Get PDFSpatial autocorrelation is a phenomenon where the values of variable located within certain geographic area show a similar pattern. It is a source of imperfection in house price modelling that employs the popular technique of hedonic regression. Despite its long established concept,it is only recently when spatial autocorrelation has started to gain the attention of real estate studies. However, the evidence has come mainly from the USA. This paper reviews the literature on spatial autocorrelation and real estate studies. It describes some basic aspects of spatial autocorrelation in respect of hedonic price modelling (HPM) for housing markets. The importance of considering spatial autocorrelation and ways of dealing with the phenomenon are outlined. The paper also discusses two main approaches of modelling spatial autocorrelation, namely the spatial weight matrix and the geo-statistical approaches. It stresses the preference of the former in previous real estate studies that involve economic analysis. The paper concludes by highlighting the importance of considering spatial autocorrelation when cross sectional data are used. Evidence from countries including Malaysia would enrich the literature of spatial autocorrelation consideration in real estate studies
Hedonic modelling of housing markets using geographical information system (GIS) and spatial statistics : a case study of Glasgow, Scotland
No full textThe research methodology comprises theoretical, empirical and evaluation stages. The theoretical stage provides evidence that substantiates the need for the study and outlines possible ways to address spatial elements in hedonic price modelling. The empirical stage illustrates the application of GIS and spatial statistics in the estimation of hedonic models for housing markets in Glasgow, Scotland, using 2,715 house prices for 2002 and 61 independent variables. GIS is used in this study to construct spatial variables including detailed accessibility measures, to help detect the hedonic problems of heteroscedasticity and spatial autocorrelation, and for visualisation. Spatial statistics are used to test formally and model explicitly the spatial autocorrelation. The evaluation stage assesses 46 hedonic models, using OLS and spatial hedonic, for a priori segmentations involving the spatial, structural and nested sub-markets. It also draws general conclusions about the importance of detailed accessibility measures and spatial statistics in sub-market modelling. This study finds that the nested sub-market modelling using a spatial hedonic approach is most effective, followed by the spatial and structural sub-markets. The OLS sub-market modelling generally reduces spatial autocorrelation but does not eliminate it. There is a greater incidence of spatial autocorrelation when the market size, with measured by geographical area or density of dwellings is larger. The spatial hedonic modelling improves the performance of the individual OLS models and the three segmentation approaches, although the relative performance of the latter remains unchanged. Nevertheless, will the spatial hedonic, the entire market model outperforms the OLS model of structural sub-markets. Flat-based OLS sub-market models benefit substantially from the spatial hedonic. The results also suggest that an individual accessibility measure is more significant than the zonal measure because it is able to capture the micro effect of location on price. Further, spatial statistics produce more accurate, robust and reliable estimates of implicit prices.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Penggunaan sistem maklumat geografi (GIS) dalam penilaian harta tanah berasaskan kaedah perbandingan
No full textVariations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Hedonic modelling of housing markets using Geographical Information System and spatial statistics : Glasgow, Scotland
Get PDFThis paper presents the results of a simultaneous consideration of detailed accessibility measures and spatial autocorrelation in house price hedonic modelling. It illustrates the application of GIS and spatial statistics in the estimation of hedonic models for the entire housing market in Glasgow, Scotland, using 2,715 house prices for 2002 and 61 independent variables. GIS is used in this study to construct spatial variables including detailed accessibility measures, to help detect spatial autocorrelation, and for map visualisation. Spatial statistics are used to test formally and model explicitly the spatial autocorrelation. The results suggest that an individual accessibility measure is more influential than a zonal accessibility measure because the former is able to capture the micro effect of location on house price. Furthermore, the application of spatial statistics can produce more accurate and reliable estimates of implicit prices
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