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Housing

COMMERCIAL RENTAL INDEX (BASE QUARTER 1998-Q4 = 100), QUARTERLY

Data from Jan 2011 to Jun 2024Updated about 2 months ago

URA (Urban Redevelopment Authority)

The rental indices for commercial properties (i.e. office and retail space) are compiled from tenancy agreement data from the Inland Revenue Authority of Singapore (IRAS).

To compute the rental indices, rental transactions are grouped by property type, locality etc. The median rental in each group is used to compute a sub-index. The rental index of a particular property type is the weighted average of all the sub-indices of that property type in the various groups. The indices are computed based on a Moving Average weight method, whereby the value of properties transacted in the past 12 quarters are used as weights.

Index by Quarter

Data explorer

COMMERCIALRENTALINDEXBASEQUARTER1998Q4100QUARTERLY.csv (108 rows, 2.3 KB)

Quarter
Quarter (Q)
Property type
Text
Index
Numeric
(Null)0.0%
(Null)0.0%
office50.0%
retail50.0%
(Null)0.0%
2011-Q1office168
2011-Q1retail115.7
2011-Q2office170.6
2011-Q2retail117.2
2011-Q3office172.2
2011-Q3retail117.9
2011-Q4office172.8
2011-Q4retail118.9
2012-Q1office172
2012-Q1retail118.6

Column legend

Title
Column name
Data type
Unit of measure
Description
QuarterquarterQuarter (Q)--
Property typeproperty_typeText--
IndexindexNumeric--

Sample OpenAPI query

This code can be used to test a sample API query. It retrieves the data catalogue of this dataset. For a complete guide on query parameters and syntax, please refer to the API documentation. Try it out on your browser to see the response schema.

import requests
          
datasetId = "d_862c74b13138382b9f0c50c68d436b95"
url = "https://data.gov.sg/api/action/datastore_search?resource_id="  + datasetId 
        
response = requests.get(url)
print(response.json())

About this dataset

Contact

chee_tuck_chuen@ura.gov.sg

Created on

07 Dec 2020

Licence

Free forever for personal or commercial use, under the Open Data Licence.

Agency

URA (Urban Redevelopment Authority)

Dataset usage

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API calls