2 • The impact of telecommuting on homeownership and housing choices • Important implications for understanding the fastevolving housing markets and guidance for housing policy Study Methodology This study utilized pre-pandemic data from the 2009 and 2017 U.S. National Household Travel Surveys (NHTS) to analyse the historical relationship between telecommuting and housing preferences. A three-step Instrumental Variable (IV) approach was employed to investigate the causal impact of telecommuting on homeownership and housing choices. Pre-Covid-19 data were utilized to ensure accuracy and mitigate various temporary shock factors from the pandemic. The dataset was limited to households with a maximum of two workers aged between 16-65. Observations with missing telecommuting information were excluded from the dataset. The 2009 sample included 96,675 individual workers and 71,556 households, while the 2017 sample comprised 85,109 individual workers and 62,889 households. Binary dependent variables are assigned to individual/ household homeownership or housing type. Independent variables included telecommuting status, socioeconomic characteristics, and current residence status. Owning housing was denoted by 1, renting housing by 0; detached and duplex by 1, townhouse and apartment by 0. Telecommuting status of working from home at least once a week was denoted by 1, rarely or never telecommute by 0. Household-level age represents the average age of the two workers; household-level commute distance indicated the average commute distance of the two workers; household-level marital status denoted the relationship between the two workers; household-level occupation identified if the two workers were in the same industry (1) or different industries (1 each); household-level education indicated the highest education level. Age was categorized into three subgroups: young households (16-29 years old), middle-aged households (30-55 years old), and older households (56-65 years old). Urban areas were defined as areas with a population size > 50,000 people; urban clusters as areas with a population size between 2,50050,000 people; areas with a population< 2,500 were classified as rural areas. Regional fixed effects were controlled by a set of Core-Based Statistical Area (CBSA) dummy variables. Findings and Analysis Positive Correlation between Telecommuting and Homeownership At the individual level, telecommuting has a statistically significant and positive impact on homeownership, with telecommuters being more likely to be homeowners compared to non-telecommuters. Estimated marginal effects revealed that telecommuters in 2009 were 34.9% more likely to be homeowners, the percentage has increased to 41% in 2017. Similar trends were observed at the household level: both one-worker and two-worker households with telecommuters were more likely to be homeowners. For one-worker households, telecommuting households were 36.4% more likely to be homeowners in 2009 and 36.6% more likely in 2017. For two-worker households, telecommuting households were 54.7% more likely to be homeowners in 2009 and 41% more likely in 2017. When examining household life cycle stages across three age subgroups, it was found that among oneworker households, the presence of telecommuters had a statistically significant impact on the middleaged subgroup (30-55 years old). In this subgroup, households were 42.9% more likely to be homeowners in 2009 and 47.6% more likely in 2017. The impact of telecommuting status on younger and older households’ likelihood of homeownership was limited. However, both middle-aged and younger two-worker households were significantly influenced by telecommuters regarding homeownership. In 2009, middle-aged twoworker households with telecommuters were 67.6% more likely to be homeowners, decreasing to 40.1% in 2017. Young telecommuting two-worker households were 30.8% less likely to own a house in 2009 but 55.8% more likely in 2017. Older telecommuting households were 12.2% more likely to be homeowners in 2017. A spatial heterogeneity test indicated that the impact of telecommuting on homeownership was consistently observed in urbanized areas in both surveyed years. In 2009, telecommuters in urbanized areas were 26.8% more likely to become homeowners Influence of Telecommuting on Homwownership and Housing Choice: A Study Based on Pre-pandemic Data Public Policy BULLETIN
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