Using household-level data to guide borrower-based macro-prudential policy

Many countries introduced borrower-based instruments to constrain credit to households exceeding a limit on their loan-to-value ratio, their (mortgage) debt-to-income ratio or their debt service-to-income ratio. We evaluate how well borrower-based instruments can target households that would become vulnerable after a shock. We apply the signals approach to derive “optimal” limits that minimize classification errors (either granting credit to financially vulnerable households or constraining credit to households that are not vulnerable). To illustrate, we simulate an adverse scenario using household-level data from Luxembourg. We find that combining several ratios could better target households that would become vulnerable after a shock.