Machine generated contents note: List of figures; List of tables; List of boxes; Preface; Acknowledgements; 1. Introduction; 2. Mathematical building blocks for real estate analysis; 3. Statistical tools for real estate analysis; 4. An overview of regression analysis; 5. Further issues in regression analysis; 6. Diagnostic testing; 7. Applications of regression analysis; 8. Time series models; 9. Forecasting evaluation; 10. Multi-equation structural models; 11. Vector autoregressive models; 12. Cointegration in real estate markets; 13. Real estate forecasting in practice; 14. The way forward for real estate modelling and forecasting; Index.

"As real estate forms a significant part of the asset portfolios of most investors and lenders, it is crucial that analysts and institutions employ sound techniques for modelling and forecasting the performance of real estate assets. Assuming only a basic understanding of econometrics, this book introduces and explains a broad range of quantitative techniques that are relevant for the analysis of real estate data. It includes numerous detailed examples, giving readers the confidence they need to estimate and interpret their own models. Throughout, the book emphasises how various statistical techniques may be used for forecasting and shows how forecasts can be evaluated. Written by a highly experienced teacher of econometrics and a senior real estate professional, both of whom are widely known for their research, Real Estate Modelling and Forecasting is the first book to provide a practical introduction to the econometric analysis of real estate for students and practitioners"--Provided by publisher.