Walter, R. J., Acolin, A., & Tillyer, M. S. (2024). Association between property investments and crime on commercial and residential streets: Implications for maximizing public safety benefits. SSM – Population Health, 25, 101537–101537. https://doi.org/10.1016/j.ssmph.2023.101537.
View Publication
Abstract
Physical property investments enhance public safety in communities while alleviating the need for criminal justice system responses. Policy makers and local government officials must allocate scare resources for community and economic development activities. Understanding where physical property investments have the greatest crime reducing benefits can inform decision making to maximize economic, safety, and health outcomes. This study uses Spatial Durbin models with street segment and census tract by year fixed effects to examine the impact of physical property investments on changes in property and violent crime over an 11-year period (2008-2018) in six large U.S. cities. The units of analysis are commercial and residential street segments. Street segments are classified into low, medium, and high crime terciles defined by initial crime levels (2008-2010). Difference of coefficients tests identify significant differences in building permit effects across crime terciles. The findings reveal there is a significant negative relationship between physical property investments and changes in property and violent crime on commercial and residential street segments in all cities. Investments have the greatest public safety benefit where initial crime levels are the highest. The decrease in violent crime is larger on commercial street segments, while the decrease in property crime is larger on residential street segments. Targeting the highest crime street segments (i.e., 90th percentile) for property improvements will maximize public safety benefits.
Keywords
Violent and property crime; Public safety; Physical property investments
CBE Researchers developed a report “Finding Common Ground: Best Practices for Policies Supporting Transit-Oriented Development,” with the Mobility Innovation Center and led by the Washington Center for Real Estate Research. Project Team: Mason Virant, Associate Director, Washington Center for Real Estate Research Christian Phillips, Urban Design and Planning PhD Program Steven C. Bourassa, PhD Director, Washington Center for Real Estate Research Arthur Acolin, Associate Professor, Runstad Department of Real Estate Visit the project page here.
Colburn, G., Hess, C., Allen, R., & Crowder, K. (2024). The dynamics of housing cost burden among renters in the United States. Journal of Urban Affairs, 1–20. https://doi.org/10.1080/07352166.2023.2288587.
View Publication
Abstract
Housing cost burden—defined as paying more than 30% of household income for housing—has become a central feature of the American stratification system with dire consequences for the health and well-being of adults and children living in burdened households. To date, existing research has largely focused on the overall prevalence and distribution of housing cost burden—that is, the percentage of households that are cost burdened at a given time and differences in exposure to housing cost burden based on race and income using cross-sectional sources of data. To more fully understand the dynamics of housing cost burden among renter households in the United States including the frequency and duration of spells, we use 50 years of longitudinal data from the Panel Study of Income Dynamics (PSID). The analysis reveals that, in contrast to the episodic nature of poverty, housing cost burden is deep, frequent, and persistent for a growing share of American households.
Keywords
Housing cost burden; rental housing; housing affordability; rent burden
Three CBE researchers were awarded Royalty Research Funds. This cycle, 93 proposals were submitted to the University of Washington Office of Research. 25 were selected for funding, a success rate of 27%. Vince Wang, Assistant Professor in the Runstad Department of Real Estate and Dylan Stevenson, Assistant Professor in Urban Design and Planning were awarded funding for their project entitled “Exploring Transformative Solutions to Build Housing Security and Climate Resilience: The Community Land Trust Model” Narjes Abbasabadi, Assistant Professor in…
Population Health Initiative gave 12 early-stage pilot grants to interdisciplinary teams. One team included Rebecca Walter, an associate professor in the Runstad Department of Real Estate. Project title: “Housing affordability and chronic stress in the US: Does affordability modify the effect of neighborhoods on health?” Project team: Amy J. Youngbloom, Department of Epidemiology Stephen J. Mooney, Department of Epidemiology Anjum Hajat, Department of Epidemiology Isaac Rhew, Department of Psychiatry & Behavioral Sciences Rebecca Walter, Runstad Department of Real Estate Project…
Xinyu Fu, Ruoniu Wang & Chaosu Li (2023). Can ChatGPT Evaluate Plans?, Journal of the American Planning Association, DOI: 10.1080/01944363.2023.2271893
View Publication
Abstract
Problem, research strategy, and findings
Large language models, such as ChatGPT, have recently risen to prominence in producing human-like conversation and assisting with various tasks, particularly for analyzing high-dimensional textual materials. Because planning researchers and practitioners often need to evaluate planning documents that are long and complex, a first-ever possible question has emerged: Can ChatGPT evaluate plans? In this study we addressed this question by leveraging ChatGPT to evaluate the quality of plans and compare the results with those conducted by human coders. Through the evaluation of 10 climate change plans, we discovered that ChatGPT’s evaluation results coincided reasonably well (with an average of 68%) with those from the traditional content analysis approach. We further scrutinized the differences by conducting a more in-depth analysis of the results from ChatGPT and manual evaluation to uncover what might have contributed to the variance in results. Our findings indicate that ChatGPT struggled to comprehend planning-specific jargon, yet it could reduce human errors by capturing details in complex planning documents. Finally, we provide insights into leveraging this cutting-edge technology in future planning research and practice.
Takeaway for practice
ChatGPT cannot be used to replace humans in plan quality evaluation yet. However, it is an effective tool to complement human coders to minimize human errors by identifying discrepancies and fact-checking machine-generated responses. ChatGPT generally cannot understand planning jargon, so planners wanting to use this tool should use extra caution when planning terminologies are present in their prompts. Creating effective prompts for ChatGPT is an iterative process that requires specific instructions.
Keywords
ChatGPT; large language model; natural language processing; plan evaluation; plan quality
Sun, F., Whittington, J., Ning, S., Proksch, G., Shen, Q., & Dermisi, S. (2023). Economic resilience during COVID-19: the case of food retail businesses in Seattle, Washington. Frontiers in Built Environment, 9. https://doi.org/10.3389/fbuil.2023.1212244
View Publication
Abstract
The first year of COVID-19 tested the economic resilience of cities, calling into question the viability of density and the essential nature of certain types of services. This study examines built environment and socio-economic factors associated with the closure of customer-facing food businesses across urban areas of Seattle, Washington. The study covers 16 neighborhoods (44 census block groups), with two field audits of businesses included in cross-sectional studies conducted during the peak periods of the pandemic in 2020. Variables describing businesses and their built environments were selected and classified using regression tree methods, with relationships to business continuity estimated in a binomial regression model, using business type and neighborhood socio-demographic characteristics as controlled covariates. Results show that the economic impact of the pandemic was not evenly distributed across the built environment. Compared to grocery stores, the odds of a restaurant staying open during May and June were 24%, only improving 10% by the end of 2020. Density played a role in business closure, though this role differed over time. In May and June, food retail businesses were 82% less likely to remain open if located within a quarter-mile radius of the office-rich areas of the city, where pre-pandemic job density was greater than 95 per acre. In November and December, food retail businesses were 66% less likely to remain open if located in areas of residential density greater than 23.6 persons per acre. In contrast, median household income and percentage of non-Asian persons of color were positively and significantly associated with business continuity. Altogether, these findings provide more detailed and accurate profiles of food retail businesses and a more complete impression of the spatial heterogeneity of urban economic resilience during the pandemic, with implications for future urban planning and real estate development in the post-pandemic era.
Steven Bourassa is an H. Jon and Judith M. Runstad Endowed Professor and Chair in the Runstad Department of Real Estate, and is Director of the Washington Center for Real Estate Research. Professor Bourassa was quoted in a Washington State Standard story entitled “Rents in Washington show signs of stabilizing,” as an expert in the field. Read the article here.
Gregg Colburn gave a talk to the Joint Center for Housing Studies, Initiative on Health and Homelessness, Government Performance Lab at Harvard University on November 3, 2023. The talk was recorded and is available on Youtube here.
Cai, M., Acolin, A., Moudon, A. V., & Shen, Q. (2023). Developing a multi-criteria prioritization tool to catalyze TOD on publicly owned land areas. Cities, 143, 104606-. https://doi.org/10.1016/j.cities.2023.104606
View Publication
Abstract
Public agencies can take a leading role in catalyzing TOD by making land available to developers (selling or leasing land, potentially below market prices). In particular, park-and-ride areas that are publicly owned can be leveraged to support TOD uses, such as affordable housing, office space, small businesses, and mixed-use buildings given their convenient access to transit systems and often large land areas. However, few previous studies have discussed the use of publicly owned park-and-rides, which are an important component of publicly owned land, as a catalyst for TOD. To fill the gap in the literature and effectively support TOD planning, this research developed a multi-criteria prioritization tool to identify the most promising locations for TOD and tested it at three park-and-ride sites owned by the Washington State Department of Transportation. The tool was developed through the Delphi process, which is an effective and inexpensive approach to evaluate relevant indicators by synthesizing the opinions of experts from various backgrounds. Five categories with a total of 14 TOD indicators, including transit supportive land-use zoning, job accessibility, land price, land-use mix, and household income, were selected as measures of TOD suitability. The importance of these indicators varied with three different TOD scenarios: (1) emphasis on affordable housing, (2) emphasis on market-rate housing, and (3) emphasis on mixed-use development. Using the calculated suitability scores, this tool can prioritize potential TOD sites for further review.
Keywords
TOD; Delphi method; Multi-criteria planning tool; Multi-sources geospatial data; Publicly owned land