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Going by the Numbers: What’s Important Close communication between the sponsor and the data geeks Know what’s possible & what’s reliable Find the appropriate scale for the sponsor’s objectives Use filters: focus on the big picture & drill down when it adds value Don’t filter bad news Know your audience and work on communicating effectively Tie to policy & program responses

Close communication between the sponsor and the data geeks The sponsor needs to be engaged in shaping the details of the study…have a small advisory group and a go-to person for getting questions answered One answer leads to more questions…know when to stop The data geeks need to know how to frame options and when to go beyond the questions asked

Know what’s possible & reliable Mine the secondary data CHAS tabulations American Housing Survey Published tables Microdata Mine administrative data & other ‘big data’ sources Collect primary data carefully and selectively Data is expensive to collect Target your biggest ‘unknowns’ Qualitative data can help gain useful insights & build direction

Data Sources Data from published ACS tables and Public Use Microdata Sample files to provide maximum detail and precision ACS 5-year, 3-year and 1-year files 5-year CHAS tabulation for housing supply and gap analysis Sales data, property tax data, building permits, inspections Primary data collection □ Quantitative: Household & housing surveys □ Qualitative: Focus groups, meetings & forums 03/31/2015 Virginia Center for Housing Research at Virginia Tech 6

Find the appropriate analytical scale for the sponsor’s objectives Geographic scale Region Counties, cities and towns Smaller geographies (census tracts, block groups, …) Policy scale Development scale Site Subdivision

Key Measures Cost Burden □ Households are defined as cost burdened if gross housing cost is 30% or more of total household income □ Gross housing cost includes utilities □ Cost Burden shown for <30% (not cost burdened), 30-49%, and 50% (severe cost burden) 03/31/20158 Virginia Center for Housing Research at Virginia Tech

The Affordability Deficit ($Gap) The amount of additional income needed to eliminate a housing cost burden Gross housing cost minus 30% of household income If gross housing cost greater than 30% of household income, deficit (negative value) occurs Measure is calculated in dollars 03/31/2015 Virginia Center for Housing Research at Virginia Tech 9

The region’s annual affordable housing deficit is $862 million (2012$), an average of $6,422 per cost-burdened household. 03/31/ Virginia Center for Housing Research at Virginia Tech

Use filters: focus on the big picture & drill down when it adds value The big picture emerges from the questions asked and what the data tells you Meta-narrative Questions What’s positive/good and what’s negative/bad? Compared to whom or what (other places or previous times)? Look at the ‘usual suspects’ as to why we vary Age, income (HUD AMI Categories), household type/composition Race, ethnicity Location Who is Keyser Söze?

Affordable housing is a problem for nearly 30% of households everywhere 03/31/2015 About 30% or more of households in every area are cost- burdened and more than 10% have severe cost burdens 12 Virginia Center for Housing Research at Virginia Tech

03/31/ Virginia Center for Housing Research at Virginia Tech Number of Cost Burdened Households by Census Tract Data Source: U.S Census 2013 American Community Survey

Lack of affordable housing hits all AMI categories, but is most severe for lower income households. Households with low incomes (below 80% of AMI) bear 80% of the region’s affordable housing deficit. 03/31/ Virginia Center for Housing Research at Virginia Tech

Half of cost burdened households are owners 03/31/ Virginia Center for Housing Research at Virginia Tech

Cost burdened households in the region are most likely to be people living alone 03/31/ Virginia Center for Housing Research at Virginia Tech One-person households are a large segment of cost burdened households

Seniors make up a large portion of cost- burdened, single-person households. 03/31/ Virginia Center for Housing Research at Virginia Tech

Housing Demand Projections: Senior housing grows substantially; middle-age market contracts 11/21/ Virginia Center for Housing Research at Virginia Tech

Don’t filter bad news Break big rocks into smaller ones How do you solve a multi-million dollar problem?

Know your audience and work HARD on communicating Measures and indexes Graphs and maps Meta narratives

Tie to policy & program responses Examples of past successes Examples of what can be done Identify next steps Monitor progress

Who do you call? Mel Jones! Virginia Center for Housing Research Phone: (540)