Real Estate Modelling

PLAN71062 Real Estate Modelling 20 Semester 2 Postgraduate Taught Level 7 Sotirios Thanos Unit coordinator 1 FHEQ level (Framework for Higher Education Qualifications) ' Masters/Integrated Masters P4 ' European Credit Transfer & Accumulation System Rating : 10.0 This unit is designed to train the students in conducting applied quantitative research in real estate, housing, or planning contexts. In more detail, the unit introduces and fully covers the following topics: <div> <ul> <li> Understanding different types of data. Presenting and summarising data using descriptive statistics.</li> <li> Gaining an excellent grasp of inferential statistics: probability, probability distributions, expected values, hypothesis testing, correlation and covariance.</li> <li> Learning to employ linear regression techniques, hypothesis testing of the regression output, conducting model diagnostics, and interpreting the results.</li> <li> Gaining expertise in the econometric modelling of real estate time-series data. This include time series models, modelling univariate time series, unit root processes, multivariate time series, and forecasting.</li> <li> Running multivariate techniques using SPSS, interpreting, and presenting the results and statistical output.  </li> </ul>   </div>   This unit is designed to train the students in conducting applied quantitative research in real estate, housing, or planning contexts. In more detail, the unit introduces and fully covers the following topics: <ul> <li> Understanding different types of data. Presenting and summarising data using descriptive statistics.</li> <li> Gaining an excellent grasp of inferential statistics: probability, probability distributions, expected values, hypothesis testing, correlation and covariance.</li> <li> Learning to employ linear regression techniques, hypothesis testing of the regression output, conducting model diagnostics, and interpreting the results.</li> <li> Gaining expertise in the econometric modelling of real estate time-series data. This include time series models, modelling univariate time series, unit root processes, multivariate time series, and forecasting.</li> <li> Running multivariate techniques using SPSS, interpreting, and presenting the results and statistical output.  </li> </ul> <div> The first assessment is an online, to assess the understanding of key concepts in statistics and econometrics.In the second assessment, the students are required to analyse housing data by employing regression techniques, and to present, interpret, and explain the regression results in a 3,000 words paper.</div>   <ul> <li> Provide research-focused education on the analysis of real estate markets, to outstanding students from the UK and overseas;</li> <li> Provide a rigorous exposition of relevant analytical and quantitative tools;</li> <li> Give students a good grounding in statistics and modern econometric techniques. The students will fully understand the ways in which these techniques are applied to the empirical analysis of data in the real estate, housing, or planning fields;  </li> <li> Enable students to conduct excellent quantitative research during their PG dissertation, to progress to higher degrees, or to follow successful careers in the real estate sector, for both public and private organizations, in the UK and overseas.</li> </ul>   <ul><li>Develop complete understanding of fundamental concepts in statistics, econometrics, and modelling relevant to real estate, housing, and planning.</li><li>Demonstrate a full knowledge of the theory and practice of modern econometrics, particularly applied to real estate.</li><li>Develop competence and understanding to be able to carry out good quality applied quantitative research with confidence and authority.</li><li>Develop the critical insight to appraise econometric results obtained by other researchers.</li></ul>  <ul><li>Systematically approach the construction of solution to a real-life problems, demonstrate the solution’s applicability and to show its theory connections.</li><li>Produce a sustained, sophisticated, and logical argument, backed up by empirical statistical results.</li><li>Design and apply appropriate research methodology to a wide range of real estate issues.</li></ul> <ul><li>Apply appropriate quantitative techniques to a real estate, housing, and planning contexts.</li><li>Design and develop conclusions based on evidence including hypothesis testing and modelling outputs.</li></ul> <ul><li>Project manage complex tasks and deliver to strict deadlines.</li><li>Make presentations and write reports that are well-researched, ethical, coherent, cogent and logically structured.</li></ul> This module is delivered entirely by distance-learning. You will receive access to the online virtual learning environment which will contain the learning materials and the online tools required to interact with tutors and your fellow students.  <div> The learning materials have been specifically designed to provide an interactive and carefully structured introduction to each topic, guidance on further reading, opportunities for reinforcement activity (checking that you can apply your knowledge) and formative feedback (monitoring your progress and identifying ways to improve).The material is designed to allow you to study in a flexible manner (at your own pace) but there will be certain points during the block of study when summative (tutor-assessed) work will need to be submitted.The course materials should be considered as the starting point for your study of the subject and you should read as much professional literature (professional body publications, market reports and periodicals) and academic literature (textbooks and refereed journal articles) as you can.</div>   2 Written assignment (inc essay) 90% 9 Set exercise 10% Test in class (1 hour) 10%Coursework (3,000) 90% PLAN71062 RE DL Conditions (Programme 07880 &10027) MSc Real Estate Distance Learn MSc Real Estate Blended Learn PGDT Taught Component Optional N  Reading ListGujarati, D. (2006) Essentials of econometrics, 3rd Ed, McGraw-HillStewart, J. (1984) Understanding econometrics, 2nd Ed, Hutchinson Lectures 15 0 135