MSc Real Estate Asset Management / Course details

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:
• Understanding different types of data. Presenting and summarising data using descriptive statistics.
• Gaining an excellent grasp of inferential statistics: probability, probability distributions, expected values, hypothesis testing, correlation and covariance.
• Learning to employ linear regression techniques, hypothesis testing of the regression output, conducting model diagnostics, and interpreting the results.
• 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.
• Running multivariate techniques using SPSS, interpreting, and presenting the results and statistical output. 

The first assessment is an online test 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.

The aims of the unit are to:
• Provide research-focused education on the analysis of real estate markets, to outstanding students from the UK and overseas;
• Provide a rigorous exposition of relevant analytical and quantitative tools;
• 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; 
• 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.

Students acquire their detailed knowledge and understanding of the course through a blended learning combination of asynchronous teaching and learning (T&L) material and on campus seminars, tutorials, and discussion and independent study. The asynchronous and interactive online T&L material is displayed in a webpage developed specifically for this unit. The range of teaching and learning methods includes videos, interactive material, quizzes, forums/padlets, and online workshops, used to introduce the topics every week in a structured manner. Online  workshops and video tutorials are used to instruct students in the use of statistical software and on campus seminars/tutorials are used to facilitate critical debate about key issues in real estate research.

Formative feedback will be provided through on campus Q&A, discussion and online interactive activities, workshops and tutorials. Verbal feedback will be available on coursework discussed during consultation hours and on campus assignment surgeries. Blackboard will be used as a repository for FAQs.

• Develop complete understanding of fundamental concepts in statistics, econometrics, and modelling relevant to real estate, housing, and planning.
• Demonstrate a full knowledge of the theory and practice of modern econometrics, particularly applied to real estate.
• Develop competence and understanding to be able to carry out good quality applied quantitative research with confidence and authority.
• Develop the critical insight to appraise econometric results obtained by other researchers.

• Systematically approach the construction of solution to a real-life problems, demonstrate the solution’s applicability and to show its theory connections.
• Produce a sustained, sophisticated, and logical argument, backed up by empirical statistical results.
• Design and apply appropriate research methodology to a wide range of real estate issues.

• Apply appropriate quantitative techniques to a real estate, housing, and planning contexts.
• Design and develop conclusions based on evidence including hypothesis testing and modelling outputs.

• Project manage complex tasks and deliver to strict deadlines.
• Make presentations and write reports that are well-researched, ethical, coherent, cogent and logically structured.

Online test (1 hour) 10%

Coursework (3000 words) 90%

Detailed feedback on summative assessments will be provided via Blackboard.

Gujarati, D. (2006) Essentials of econometrics, 3rd Ed, McGraw-Hill

Stewart, J. (1984) Understanding econometrics, 2nd Ed, Hutchinson