Given the significant share of housing and transportation costs in the household consumption basket, along with the expansion of public transportation as a key urban development policy, examining the relationship between their price indices is critically important. This study investigates the asymmetric and nonlinear effects of the transportation price index on urban housing sector inflation in Iran using the Nonlinear Autoregressive Distributed Lag (NARDL) model and quantile regression. The primary objective is to determine how positive and negative shocks to transportation prices asymmetrically affect housing inflation and to analyze these effects across different levels of the housing inflation distribution. The results from cointegration and NARDL tests on monthly data from 2004 to 2023 confirm a long-run asymmetric relationship. This indicates that the effect of positive transportation price shocks on housing inflation differs from that of negative shocks. Quantile regression sensitivity analysis reinforced these findings, showing that the impact of the transportation price index varies significantly across different quantiles of housing inflation. Additionally, the nonlinear model confirms a positive relationship between oil prices, the rental index, and housing prices in both the short and long run. These findings provide a foundation for designing more effective policies to control housing inflation and stabilize the market.