M
Martin Hoesli
Researcher at University of Geneva
Publications - 269
Citations - 7779
Martin Hoesli is an academic researcher from University of Geneva. The author has contributed to research in topics: Real estate & Real estate investment trust. The author has an hindex of 47, co-authored 258 publications receiving 7192 citations. Previous affiliations of Martin Hoesli include École Normale Supérieure & University of Aberdeen.
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The capital structure of Swiss companies: an empirical analysis using dynamic panel data
TL;DR: In this paper, the determinants of the capital structure for a panel of Swiss companies listed in the Swiss stock exchange were analyzed for the period 1991-2000, and it was found that the size of companies and the importance of tangible assets are positively related to leverage, while growth and profitability are negatively associated with leverage.
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Do Housing Submarkets Really Matter
TL;DR: In this article, a large urban housing market is divided into sub-markets and the effects of alternative definitions of sub-market on the accuracy of predictions are explored, and the authors conclude that housing submarkets matter, and location plays the major role in explaining why they matter.
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Defining Housing Submarkets
TL;DR: In this paper, a statistical method for defining housing sub-markets was developed using household survey data for Sydney and Melbourne, Australia, and applied using principal component analysis (PCA) to extract a set of factors from the original variables for both local government area (LGA) data and a combined set of LGA and individual dwelling data.
Journal ArticleDOI
Do housing submarkets really matter
TL;DR: In this paper, a large urban housing market is divided into sub-markets and the effects of alternative definitions of sub-market on the accuracy of predictions are explored, and the authors conclude that housing submarkets matter, and location plays the major role in explaining why they matter.
Journal ArticleDOI
Spatial Dependence, Housing Submarkets, and House Price Prediction
TL;DR: In this article, the authors compared alternative methods of controlling for the spatial dependence of house prices in a mass appraisal context and concluded that the gains in accuracy from including submarket variables in an ordinary least squares specification are greater than any benefits from using geostatistical or lattice methods.