ICPM

The course aims at providing fundamental knowledge as well as analytical skills in the areas of statistics and economics.  Students will enhance their capability of data analysis and interpretation upon results in different realms of research.

Mathematics, Calculator

The course introduces fundamental knowledge of statistics and economics. 

On top of the knowledge, analytical tools will be introduced, aiming to develop a student's capability in terms of: 
1）To understand fundamental theories and terminologies of statistics and economics.
2）To use professional knowledge, techniques, skills and tools necessary for problem solving. 
3）To be able to operate analytical software as a means of research skills.
To be able to interpret outputs generated by different software for further explanation for research questions.

1）Introduction on linear regression analysis and data type
Exercise: input data and data transformation                                          
2）Regression and statistical analysis 
Exercise: descriptive analysis and basic SPSS cord for regression
3）Multiple linear regression-specification and estimation
4）Logit model-specification and estimation 
Exercise: regression and residual analysis
5）Time series analysis 
Exercise: problem solving: linear regression
6）Correlation analysis and introduction on empirical regressions
Exercise: SPSS for correlation calculation
7）Macro determinants of cities’ housing prices (time series analysis)
Exercise: time series analysis of Beijing's housing price
8）Households’ housing consumption: research design and analysis (OLS regression)
Exercise: empirical analysis based on household survey data
9）Spatial analysis of housing prices based on hedonic technique (OLS regression)
Exercise: hedonic modeling in Beijing's new housing market
10）Households’ tenure choice based on discrete choice model (binary choice)
Exercise: modeling households’ tenure choices in Beijing
11）Residential location choice based on discrete choice model (multiple choice)
Exercise: modeling residential location choices in Beijing

The teaching and learning methods include the use of lectures to illustrate the theoretical foundations, supported by computer exercise tutorials, which will demonstrate the practical application of such theory. 

A series of lab exercises are provided to help students forming a comprehensive understanding of real estate economic analysis.  With the following exercises, students are encouraged to apply analytical, techniques and tools with software (SPSS) to solve practical problems.

Exercise 1: input data and data transformation                                          
Exercise 2: descriptive analysis and basic SPSS cord for regression
Exercise 3: regression and residual analysis
Exercise 4: problem solving: linear regression
Exercise 5: SPSS for correlation calculation
Exercise 6: time series analysis of Beijing's housing price
Exercise 7: empirical analysis based on household survey data
Exercise 8: hedonic modeling in Beijing's new housing market
Exercise 9: modeling households’ tenure choices in Beijing
Exercise 10: modeling residential location choices in Beijing

48 module hours

1）Correlation and Regression: Applications for Industrial Organizational Psychology and Management, Philp Bobko, 2nd Edition, Sage Publications
2）Econometric Analysis, by William H. Greene, Prentice – Hall International, Inc. 
3）Introduce to Linear Regression, by Douglas C. Montgomery, Elizabeth A. Peck and G. Geoffrey Vining, Wiley Series in Probability and Statistics
4）IBM SPSS for Intermediate Statistics: Use and Interpretation (4th Edition), by George Morgan, Nancy Leech, Gene Gloeckner and Karen Barrett, New York: Routledge, 2011. (the electronic version is available in the University library)

• Analytical Theories Techniques and Tools