RESEARCH PAPERS ARE PRELIMINARY MATERIALS CIRCULATED TO STIMULATE DISCUSSION AND CRITICAL COMMENT. THE VIEWS EXPRESSED ARE THOSE OF THE INDIVIDUAL AUTHORS. WHILE RESEARCH PAPERS BENEFIT FROM ACTIVE UHERO DISCUSSION, THEY HAVE NOT UNDERGONE FORMAL ACADEMIC PEER REVIEW.
Restrictions on housing supply have contributed to a rapid increase in home prices and rents in many large cities. Incumbent homeowners may benefit financially from rising prices, while renters are harmed. Incumbent residents may also resist new local housing due to local congestion externalities. Supply restrictions are often implemented by city councils at the behest of their constituents. We analyze city council bills from Toronto, Canada spanning 2009 to 2020. A machine learning approach identifies bills related to housing supply. We link housing bills, councillor voting behaviour and local demographic information. We find that representing more homeowners causes a councillor to oppose more housing bills. Councillors are significantly more likely to oppose large housing developments if the project is within the boundaries of the ward they represent.
