Jobs/Housing Balance

Reduce jobs/housing ratio to 1

This indicator measures the ratio of jobs to the amount of housing.Explore the data
ratio
Current
1ratio
Dec 2020 Target
Goal Period ended December 2020

            What is this indicator?

            This indicator measures the number of jobs per household in Santa Monica.

            Why is it important?

            The jobs/housing balance indicates the ratio of available housing to available jobs in the community. There is adequate housing to accommodate the labor market in the city when this ratio is close to 1.0.The jobs/housing balance is commonly associated with Vehicle Miles Traveled and is seen as a tool for alleviating traffic congestion and the associated environmental and social impacts.

            How are we doing?

            The ratio of jobs to housing tends to fluctuate most with the number of jobs. The housing stock is relatively static. The ratio of jobs to housing has been gradually increasing since 2002. It reached 1.54 in 2011 after a big dip during the recession in 2009-10 when the ratio was 1.44. As of 2014, the jobs to housing ratio is 1.57. Santa Monica has a jobs surplus. In order to meet the target ratio of 1.0 by 2020, the housing available in the city should match the labor force skills. Housing should be available in the price, size and location that reflect available jobs in the community.

            Though classed as an economic indicator, the jobs housing balance impacts lifestyle issues such as driving time, congestion and pollution. These in turn affect the quality of life in the area, as well as the attractiveness of the community to new residents and new businesses.

            Moving to a more disciplined approach of limiting development to allow for the provision of housing which matches the labor force skills in the region is an essential step towards a more sustainable future. It is important to craft policy solutions to accomplish this goal fairly, without disproportionately hurting sectors such as non-profits and area hospitals in favor or other already adequately represented commercial enterprises.

      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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