In the US, the linkages between the housing market, the credit market and the real sector have been striking in the past decades. To explain these linkages, I develop a small-scale DSGE model in which agents update non-rational beliefs about future house price growth, in accord with recent survey data evidence. Conditional on subjective house price beliefs, expectations are model-consistent. In the model with non-rational expectations, both standard productivity shocks and shocks in the credit sector generate endogenously persistent booms in house prices. Long-lasting excess volatility in house prices, in turn, affects the financial sector (because housing assets serve as collateral for household and entrepreneurial debt), and propagates to the real sector. This amplification and propagation mechanism improves the ability of the model to explain empirical puzzles in the US housing market and to explain the macro-financial linkages during 1985-2019. The learning model can also replicate the predictability of forecast errors evidenced in survey data.