Leaning Against Housing Booms Fueled by Credit

This study aims to empirically identify the state of the US housing market and establish a countercyclical state-dependent macroprudential policy rule. I do so by estimating a Markov switching model of housing prices, in which mortgage debt affects house prices nonlinearly and drives state transition probabilities. Second, I propose a state-contingent policy rule fed with the probability of being in each state, which I apply to setting a housing countercyclical capital buffer, a mortgage interest deduction, and a dividend payout restriction. Finally, I show that such hypothetical tools contain early warning information in a forecasting exercise to predict the charge-off rates of real estate residential loans and a financial stress index. The significance of this study is that it informs policymakers about the state of the housing market mechanically, while also providing a general rule to implement a state-contingent and timely macroprudential policy.