IS428 2016-17 Term1 Assign1 Rachel Tay

Abstract

It is undeniable that urban planning is essential in Singapore, given the limited amount of land available and the ever-growing population. Categorising the market into the five planning regions, it is evident that there is an oversupply of private residential units, and 2 planning areas that are relatively expensive given their planning region. In light of these trends, I proposed 3 policy recommenations. Firstly, ample demand has to be hyped to match the oversupply in the market, especially in the North. Secondly, the unit price per square metre in Yishun should be reviewed as it is priced relatively more expensive than the units in the same planning region. Lastly, the employment of expansionary measures should be considered to boost the sluggish demand.

Problem and Motivation

Due to the vast lack of land in Singapore, urban planning has always been a key discussion topic. The authorities have invested a lot of resources and effect into ensuring that there is sufficient land resource to support the every progress and development of the nation. With this in mind, I would like to explore the current status of the private residential properties market, in terms of its supply and price, and answer determine if there is an oversupply in the market and if the private housing unit prices in each region are affordable in relative terms.

Tools Utilised

1. Excel 2015 for data organisation purposes. 2. Tableau for data visualisation purposes. 3. REALIS and data.gov database for data.

Private Properties Supply

The bar chart generated above shows the total number of private residential units and its respective average vacancy rate across the 5 different regions. Seeing that the values represented in the chart are discrete measures, they were displayed as points for the vacancy rate and in bars for the available stock. Keeping in mind that a bar graph is a useful encoder for quantitative values, I chose to represent the available stock with a bar chart as it allows for easy comparison of their bar lengths and the relative magnitudes of the number of units across the planning regions. I chose to represent the vacancy rates with points as they can encode the values using location alone and should I use bar charts again, overlapping the bars would come across as confusing as their respective axes are different. On top of all these visual considerations, as I am using roughly the same axes and the same measures, I standardised the colours used for each measure for easy comparison and reading.