Director of the Housing and Demographic Analysis Division of the US Department of Housing and Urban Development Office of Policy Development and Research

Shawn J. Bucholtz is director of the Housing and Demographic Analysis Division of the US Department of Housing and Urban Development (HUD) Office of Policy Development and Research (PD&R). He oversees HUD’s housing market surveys program, including the American Housing Survey and Rental Housing Finance Survey. He has a BS in public resource management from Michigan State University, an MS in agricultural and resource economics from the University of Maryland, and a PhD in computational social science from George Mason University.

For the Record: Shawn J. Bucholtz
Title: Statistical Official and Director of the Housing and Demographic Analysis Division
Agency/Office/Unit Name: Office of Policy Development and Research
Department: Department of Housing and Urban Development
Staff Size: Three federal employees, 50+ federal staff at the US Census Bureau, and numerous contractors
Annual Budget: $41 million

With the January 2019 enactment of the Foundations of Evidence-Based Policymaking Act (to be referred to as the evidence act here), every federal department and agency is required to have a statistics official who, among other responsibilities, represent the department/agency to the Interagency Council on Statistical Policy (ICSP), headed by the chief statistician of the US. Just as the ASA has been profiling ICSP federal statistical agency heads for many years, we now welcome new ICSP members to the federal statistical community.

Tell us more about your office.

My office’s mission is to provide the public with timely data about the housing market, focusing on housing conditions and production. To carry out that mission, my office oversees HUD’s housing market surveys programs, including the American Housing Survey, the Rental Housing Finance Survey, and the Survey of Construction.

The bulk of the $41 million annual funding for HUD’s housing market surveys program is provided to the US Census Bureau, which is responsible for data collection and most survey operations. My HUD team works with the Census Bureau to ensure we produce timely and accurate housing market data used by other federal agencies, local and state governments, housing trade associations, housing and community advocacy organizations, and academic and nonacademic researchers.

You’ve been named the statistical official. Will this be an entirely new position at your agency, or will you continue to serve in your current role along with being the statistical official?

For the time being, I will serve as the statistical official and continue my duties as the director of housing and demographic analysis.

How does the evidence act change the profile and work of your office? What are your top priorities in your expanded role in the department?

The bulk of the evidence act responsibilities and deliverables fall with the chief data officer (CDO). To meet the goals of the evidence act, HUD will create and staff an Office of the Chief Data Officer. As the statistical official, my top priority will be to support the CDO in that effort.

Beyond that, my staff and I have a tremendous amount of expertise in the production of data products for the public, so we will devote time to helping the CDO implement the open data provisions of the evidence act, including the creation of a HUD data catalog.

What do you see as the biggest challenge(s) for you as you take on this new role?

I believe my biggest challenge will be setting priorities. The “to do” list created by the evidence act is long and includes both inward-facing responsibilities (e.g., data governance) and outward-facing responsibilities (e.g., open data, evidence building).

As the statistical official, I will have a role in carrying out those responsibilities, working with our CDO and evaluation officer. As a team, we will have to determine which of the evidence act responsibilities need immediate attention and which responsibilities are more suited to long-term projects.

Fortunately, HUD is not starting from scratch! We have a strong track record of soliciting input from our stakeholders to help us prioritize how we conduct evidence-building activities and provide data to the public.

Tell us more about you and your professional path to becoming the statistical official.

I got my start as an undergraduate doing data entry for a survey about dairy farms. Since then, most of my professional career has revolved around the production and use of data.

I spent the first six years of my federal career at the US Department of Agriculture’s (USDA) Economic Research Service, where I worked on land use and environmental issues. After that, I spent three more years at USDA’s Farm Service Agency, where I helped implement agricultural conservation programs. I left the USDA to serve in my current role at HUD.

Along the way, I earned an MS in agricultural and resource economics from the University of Maryland and a PhD in computational social science from George Mason University.

What kind of support from the ICSP and broader statistical community do you look for?

I am thrilled that the evidence act expanded the ICSP membership to include HUD and other “nonstatistical” agencies. I see at least two ways in which the ICSP and broader statistical community can support the nonstatistical agencies as we implement the evidence act. First, I don’t think it is any secret that most of the very best examples of evidence-based policymaking have their roots in data-matching projects in which federal data from a nonstatistical agency was combined with other federal or nonfederal data to measure program performance or long-term outcomes. I hope the ICSP can help nonstatistical and statistical agencies work together to promote and undertake data-matching projects.

Second, to realize the open data provisions of the evidence act, the nonstatistical agencies will need a lot of technical assistance from the statistical agencies, and ICSP can help foster those relationships. In particular, the nonstatistical agencies will need help creating public-facing data products that are machine-readable and include robust privacy protections.