<![CDATA[Abstract This study aims to analyze the effects of mortgage interest rates, GDP per capita, and population growth on housing affordability in Canada during 2006–2023. Housing affordability is measured using the Price-to-Income Ratio (PIR), which is classified into affordable and unaffordable categories. This study employs secondary panel data from 10 Canadian provinces obtained from the World Bank, Statistics Canada, the Canadian Real Estate Association (CREA), and TradingView. Binary logistic regression is used to examine the effects of the independent variables on housing affordability. The results show that the model is statistically significant both simultaneously and partially. Mortgage interest rates, GDP per capita, and population growth significantly affect housing affordability in Canada. The findings indicate that housing affordability is influenced by financing conditions, economic factors, and demographic dynamics. The model explains 52.0% of the variation in housing affordability and achieves a classification accuracy of 84.4%. Abstrak Penelitian ini bertujuan menganalisis pengaruh suku bunga KPR, PDB per kapita, dan pertumbuhan penduduk terhadap keterjangkauan perumahan di Kanada periode 2006–2023. Keterjangkauan perumahan diukur menggunakan Price-to-Income Ratio (PIR) yang diklasifikasikan menjadi kategori affordable dan unaffordable. Penelitian ini menggunakan data sekunder berbentuk panel pada 10 provinsi di Kanada yang diperoleh dari World Bank, Statistics Canada, Canadian Real Estate Association (CREA), dan TradingView. Metode analisis yang digunakan adalah regresi logistik biner. Hasil penelitian menunjukkan bahwa model signifikan secara simultan maupun parsial. Suku bunga KPR, PDB per kapita, dan pertumbuhan penduduk terbukti berpengaruh signifikan terhadap keterjangkauan perumahan di Kanada. Temuan penelitian menunjukkan bahwa keterjangkauan perumahan dipengaruhi oleh faktor pembiayaan, kondisi ekonomi, dan dinamika demografi. Model mampu menjelaskan 52,0% variasi keterjangkauan perumahan dengan tingkat akurasi klasifikasi sebesar 84,4%.]]>
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