branding-doc-summary table { border-collapse: collapse; } branding-doc-summary th, branding-doc-summary td { border: 1px solid #000000; } branding-doc-summary li.doc-todo { list-style: none; } branding-doc-summary ul li { min-height: 20px; } branding-doc-summary ul li:has(input) { list-style: none; } Meeting assets for UBI Works’s Personal Meeting Room are ready! View meeting recap Meeting summary Quick recap Tianbo and UBI discussed the development of a land value tax (LVT) model, focusing on how to incorporate population growth and density effects, government spending mechanisms, and the connection between economic output and land values. They reviewed a paper by Tideman that showed land prices recovering after an initial shock from implementing LVT, with the recovery tied to above-baseline GDP growth. The conversation covered different policy mixes for LVT implementation, including revenue recycling, transfers to affected households, and the challenges of avoiding negative impacts on lower-income households. They also discussed the need to model the relationship between land values and economic output, with UBI sharing a blog series that explained different methodologies for estimating land value connections to GNI. The conversation ended with plans to schedule a follow-up discussion after Tianbo’s upcoming conference to delve deeper into the model’s technical aspects. Next steps Tianbo Implement in the model a connection between land value growth and aggregate output (e.g., GDP), including the feedback loop where economic growth increases land value appreciation, and test the impact on model results. Read the referenced blog series (parts 0, 1, and 2) and relevant literature to better understand the relationship between land value and economic output, and incorporate relevant insights into the model structure. Run simulations for a full shift from property taxes on structures to land value tax in BC, including impacts on output, investment, household earnings, and incidence, and prepare results for review next week. Calculate the minimum amount of tax revenue that should be reserved for transitional/compensatory policies (e.g., to ensure no household is worse off), as a baseline for policy mixes. UBI Reach out to Nick Tideman’s team to arrange a meeting with Tianbo to discuss modeling questions and issues related to the Tideman paper. Send Tianbo the list of priority policy mixes and relevant parameters for modeling (e.g., split rate property tax shift, uniform and targeted transfers, etc.). Collaboration Tianbo and UBI: Schedule and attend a follow-up meeting on Friday after Tianbo’s conference to discuss progress and next steps. Summary Bhutan Land Tax Project Discussion UBI discussed a new project with the Kingdom of Bhutan to help develop their land tax regime for a new special economic zone, which will start from scratch and potentially involve team travel to Bhutan. The discussion then shifted to analyzing a paper about population growth and density in relation to land taxes, where they determined that while the paper’s empirical findings were valuable, the specific model adjustments might not be necessary for their current work at the sub-national or national level. UBI also explained the concept of revenue recycling in land value capture, particularly how it relates to infrastructure investment and the collection of direct land value capitalization. Land Value Tax Modeling Approaches Tianbo and UBI discussed modeling approaches for implementing land value tax (LVT) with additional policy considerations. They agreed to focus initially on the collection mechanism and transfers, with plans to later explore comparative analysis of different spending approaches including infrastructure and household transfers. UBI emphasized the need to build a robust model that can test various policy mixes, including setting aside portions of revenue for transition costs or special externalities, with Tianbo agreeing to calculate minimum amounts needed for certain policy components. LVT Revenue Use Strategy Discussion UBI and Tianbo discussed upcoming deadlines for presenting early findings at conferences in June and July. They aligned on the next steps, focusing on examining how government can play a role in using land value tax (LVT) revenue to benefit people, similar to a carbon tax model with rebates to low-income households or lowering other taxes. They decided to compare the most likely uses of LVT revenue, excluding infrastructure due to unknowns. Land Value Tax Implementation Discussion UBI and Tianbo discussed the implementation of land value tax (LVT), focusing on two key priorities: reducing taxes and implementing both uniform and targeted transfers, such as per-household dividends or rebates. UBI explained that while LVT could be regressive in percentage terms, it could benefit lower-income households in absolute terms if accompanied by income tax reductions. They also touched on potential policy options, including tax holidays or deferments during the transition period and the possibility of exempting certain property types. UBI agreed to share additional details via email. UBI Impact on Lower-Income Households UBI explained that their modeling revealed negative impacts on lower-income households, particularly retirees with fixed incomes who own their homes free and clear and face new land value taxes without benefiting from other tax reductions. They found that the first to third income deciles were negatively affected because these households often have low or zero effective income tax rates. UBI noted that while high-income taxpayers with high effective tax rates would benefit significantly from the proposed changes, they determined that the approach would be politically unfeasible in Canada without additional transfers to protect lower-income households. Land Value Tax Implementation Scenarios UBI discussed the need to model different scenarios for implementing land value tax (LVT) to address various stakeholder priorities, including a maximalist approach and gradual transition options. They explored how to balance revenue neutrality with minimizing negative impacts on property owners, such as matching land appreciation rates to prevent loss in existing equity. Tianbo confirmed that the current model already separates land and property components, allowing for adjustments in tax rates for each. Land Value and Economic Growth UBI and Tianbo discussed the relationship between land appreciation and economic growth, with UBI explaining that land value is a function of economic output. They explored how implementing a land value tax could affect this relationship, potentially allowing for faster tax introduction as economic growth increases land values. Tianbo agreed to review the shared blog series to better understand the connection between GNI and land value, and to consider incorporating this relationship into the model to address the issue of land value decapitalization during tax reform. Land Price Trends Analysis Tianbo and UBI discussed land price trends in relation to a graph showing percent differences from baseline. UBI explained that the graph shows land prices declining initially due to the implementation of land value tax (LVT), but eventually growing faster than the baseline trend as the tax is fully implemented over 20 years. They analyzed how the land price curve becomes positive before the tax is fully implemented, with UBI suggesting this represents both the negative impact of the tax introduction and underlying growth in land values. Land Price Modeling Discussion Tianbo and UBI discussed concerns about land price modeling in an economic paper, particularly regarding whether land prices could permanently decrease or stabilize. UBI explained that the model uses GDP growth rates to calculate land price changes, which helped address Tianbo’s initial concerns. They agreed to meet again on Friday after Tianbo’s conference to further discuss the model and its implications, with Tianbo tasked to run simulations examining the impact of property tax rate changes in BC, including household earnings and economic output. View in Zoom AI can make mistakes. Review for accuracy. Please rate the accuracy of this summary. Thank you for choosing Zoom, The Zoom Team Zoom.com 55 Almaden Blvd San Jose, CA 95113 +1.888.799.9666 © 2026 Zoom Communications, Inc.