Economy

Rental Vacancy Rate

Goal: Monitor rental vacancy rate as an economic indicator of Edmonton Census Metropolitan Area's housing and rental market.Explore the data
% Annually
Final
% Annually
Dec 2017 Target
Goal Period ended December 2017

        Measure Description

        Rental Vacancy Rate measures the percent of all apartment and row house units that are vacant and available for rent. This indicator shows annual apartment vacancy rates (as a percentage rate, weighted average) in the Edmonton Census Metropolitan Area.

        This measure is an indicator and not a measure of the City's performance as the City has limited control over the rental market.

        Measure Importance

        A high vacancy rate is an indicator of imbalance between supply and demand for vacant apartment units which is a reflection of the state of the economy. A booming economy correlates to a low vacancy rate due to high demand while a high vacancy rate correlates to a a glut of supply which could be due to a slowdown in the economy or over construction of rental units.

        Historical Data

        This dataset is private.

        Explanation of Performance

        The rental vacancy rate in the Edmonton Census Metropolitan Area increased from 1.7% in October 2014 to 4.2% in October 2015.

        Did You Know?

        Low vacancy rates mean that households will have greater difficulty finding a place to rent, and can lead to an increase in rental prices as demand for rental apartments outweighs the available pool of rental units.

        Useful Links

        For more information on Edmonton’s rental market, see Canada Mortgage and Housing Corporation’s (CMHC) Rental Market Report - Edmonton CMA publication: https://www03.cmhc-schl.gc.ca/catalog/home.cfm?lang=en&fr=1402693264495 .

      Data Governance

      describes the quality of the data itself. Governance issues generally indicate that the data source is considered incomplete or unreliable.

      Model Health

      describes the quality of the predictive model. If the model health is poor, the trend prediction should not be trusted.

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      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