Course Title: Economic Studies for Real Estate

Part A: Course Overview

Course Title: Economic Studies for Real Estate

Credit Points: 12

Course Code	Campus	Career	School	Learning Mode	Teaching Period(s)
ECON1131	City Campus	Postgraduate	325H Property, Constr & Proj Mgt	Face-to-Face

Course Coordinator: Ric Lombardo

Course Coordinator Phone: +61 3 9925-3905

Course Coordinator Email:r_lombardo@rmit.edu.au

Course Coordinator Location: 8.8.72

Course Coordinator Availability: TBA

Pre-requisite Courses and Assumed Knowledge and Capabilities

None

Course Description

ECON 1131 comprises two components: 1) property data analysis and 2) urban economics and real estate markets. The first component introduces students to elementary quantitative methods of interest to real-estate practitioners. It will also provide a useful lead into the second component of the course that revolves around theoretical model building and empirical research in the discipline area of urban economics and real estate markets. In other words, an understanding of the techniques considered in the first component will provide students with an insight into how they may be usefully applied when undertaking economic studies for real estate.

Objectives/Learning Outcomes/Capability Development

At the completion of this course, students should:

• be familiar with the competing ways in which property related data might be collected and presented.
• appreciate the principles governing sound survey design.
• be able to calculate various statistical measures designed to describe the nature of a property related data set.
• be able to write non-technical reports based on the calculation of descriptive statistical measures.
• be able to make inferences about the attributes of populations that are of relevance to property data analysts.
• be able to estimate the relationships that might plausibly exist between property related variables.
• be able to measure the strength of linear association that might plausibly exist between property related variables.
• be able to compute as well as interpret elasticity measures.
• be able to use probability concepts to facilitate business decision-making in a world of risk.
• be able to use basic time series forecasting techniques to predict the future course of property related variables
• be conversant with the basic models of microeconomics and macroeconomics (the supply/demand model of perfect competition, the aggregate demand and supply model of the macro-economy and the four sector    Keynesian income expenditure determination model).
• understand – within a Ricardian model framework - the influence that commuting costs as well as growth at the city edge exert on land prices and house rentals.
• understand how residential density is related to distance from the CBD
• understand how hedonic pricing may be used to impute prices to various attributes of housing units.
• be conversant with models that purport to explain how profit maximising space producers decide on the optimal mix of attributes – other than density – comprising a housing unit.
• appreciate how to model the relationship between employment density and distance from the CBD.
• be conversant with models that purport to explain why firms – in the past – tended to locate close to the CBD as well as more current models that purport to explain the more recent trends of decentralisation and suburbanisation of firms.
• understand what conditions must be satisfied for different sized manufacturing and office centres to co-exist stably
• be conversant with the location decisions of firms as well as quantitative techniques that may be used to predict the likelihood that shoppers will frequent a given retail centre.
• understand how one might use quantitative techniques to simulate the impact that a shopping centre expansion might have on retail patronage at the centre concerned as well as competing centres.
• be able to use a simple model for determining the optimal or ideal density for an existing location and/or redeveloped land.
• appreciate – through the use of various conceptual models and tools of analysis - how the demand for real estate at the local level is influenced by factors determining growth at the regional and metropolitan level.
• be acquainted with the basic economic models used in the study of urban development and real estate markets.
• be acquainted with empirical work that has been conducted to test theories about the operation of urban development and real estate markets.
• have a broad understanding of the forces affecting cities and urban development that is crucial to making sensible decisions in a built environment.

Overview of Learning Activities

Self directed learning plays an important role in this course. Whilst lectures provide a guide to study and assistance with exercises it is expected that considerable work will be undertaken outside of class. The intention here is to foster in students, the ability to be creative and autonomous in their quest for knowledge and discovery.

Lectures provide an overview of the core knowledge required and a guide to reading and application work. Lecturer determined exercises provide an opportunity for the discussion of problems and practical applications.

To facilitate the self directed learning task, students are to make use of course material formally made available by the lecturer for this course along with the prescribed reading.

The assessment in this course provides an opportunity for students to demonstrate their knowledge of all the core concepts, theories, and techniques covered in the course and the ability to apply them to solve simple, basic problems relevant to real estate economics.

Overview of Learning Resources

Hand Calculator and Computer:

A calculator with statistical functions might be useful. If the HP-10B has been bought this will suffice.

It is assumed that students have access to a computer - either at home or at university - which enables them to run statistical applications at the very least on Excel.

Overview of Assessment

Students may elect one of two alternative assessment options described below.

Option 1: One take home exam (worth 50%) held over the 8th academic week and one research project due for submission at the end of the 14th academic week (worth 50%)

Option 2: One take home exam (worth 50%) held over the 8th academic week and another take-home exam (worth 50%) held over the 14th academic week.

Exam 1 will cover material relating to property data analysis and Exam 2 will relate to urban economics and real estate markets. The topic chosen for the research project whilst nominated by the student must apply at least one of the quantitative techniques to an issue related to urban economics and real estate markets. Approval to formally proceed with the research project must be obtained from the course co-ordinator

Students with disabilities may request different forms of assessment if required.