IS428 2016-17 Term1 Assign1 Yang Chengzhen

Abstract

This project aims to analyze the private residential market in year 2015. The 2 main focus will be price distribution and supply shares analysis based on data provided by Urban Redevelopment Authority. The results may facilitate property policy makers to have a better overview of the market thus alter the policy to coordinate property supply and demand. At the same time the buyers can take it as reference for choosing the properties.

Problem and Motivation

Singapore is a country with limited land supply while the demand for private residential properties has been fairly high.Thus managing supply and controlling price has becoming critical. The government has adopted Singapore Property Market Cooling Measures since 2009 to ease the property market. At year 2015, how was the price and supply changing? Is it time to loosen up / ease the policy? How should the measures to be adjusted to better measure and control the market? For buyers, is it a good period step into the market? We may find the answer through the analysis of property price and supply. Main variables involved are Unit price, region, Monthly number of transactions , private Property Price Index, and quarterly unit supply

Approaches

Data Selection: The 4 main data set I chose from the REALIS database are:

1. Quarterly private property price index in 2015
2. Private Residential Property Transactions in 2015
3. Quarterly Supply for Private Residential Properties
4. Quarterly availability & vacancy rate by property type

Pre-processing:

1. Used Excel to add 'quarter' column in 4 quarterly supply files.
2. Used Tableau to join data source and filter null values.

Overall Analysis: Price and Supply

Giving the data size being small and with 1 dimension and 1 measurements,I used bar chart to plot the private property price index over quarters in 2015. Finding 1 :According to the Private Property Price Index, the price of private properties has shown a decreasing trend over 2015.

To analyse the supply, we not only need to look at the change in number of projects but also number of units. The bar charts gives an overview of supply trends in 2015. Finding 2: The market supply has also been decreasing over quarters, this is indicated by both number of projects decrease and number of total units decrease.

Regional Analysis

To see the relationship between market demand (number of transactions) and price by region, I use the 2 variables as X,Y axis and used the average value as reference line. Thus the space has been split into 4 sections with 'demand-price' patterns 'high-high','high-low','low-low' and 'low-high'. Then we plot the value by regions. Finding 3: Central region has 'high-high' demand and price, while most of the regions fall under ' low-low' sections.  This indicates the inbalanced demand and price pattern among regions.

To see the trend of average price over time by region, I used line chart to plot the average unit price and color scheme to represent different regions. The rationale of using different color here is there are some major overlaps among the lines, thus having different color makes it easier to differentiate regions. Finding 4:Regionally,  The average price for East Region has been fairly stable.  Whereas for the rest ,the prices follow 'Increase - Decrease - Increase' trend over the quarters.

Property Type Analysis

To see the relationship between supply and price change over time by property type, I plotted average unit price and vacancy rate on 2 line charts sharing the Y axis: quarter. This approach makes it easier to compare the trend of supply and price.
Finding 5:The average price of apartment has been changed drastically as compared to the rest property types.
Finding 6:From Quarter 3, the vacancy rate for all property types has been increased.
Finding 7: While the price of condominium being relatively high, the vacancy rate is also high as compared to the rest

Policy Recommendations

Policy Recommendations:

• Customize Cooling Measures for different regions: increase the stamp duty for properties in central region (demand & price pattern showing 'high-high') and  decrease the stamp duty for north region (demand & price pattern showing 'low-low') .

• Encourage buying of detached house and terrace house giving the decreasing price but increasing vacancy

• Limit  development of apartments giving the drastically price increase and high vacancy rate

Tools Utilized

• Excel 2013 for data processing
• Tableau 10.0 for generating graphs
• Piktochart for generating infographics

Inforgraphics