On the Effectiveness of Loan-to-Value Regulation in a Multiconstraint Framework

Abstract

Models in the infinite horizon macro-housing literature often assume that borrowers are constrained exclusively by the loan-to-value (LTV) ratio. Motivated by the Swedish micro-data, I explore an alternative arrangement where borrowers are constrained by the feasibility of repayment, but choose a house of maximum permissible size conditional on the LTV restriction. While stricter LTV limits are often considered as a measure to tackle the rise in household indebtedness, I find that policy designed to lower the maximum permissible LTV ratio may actually leave the debt-to-GDP ratio unchanged and increase housing prices in equilibrium if borrowers are bound by two constraints at the same time. In a model with occasionally binding constraints, I show that also for the analysis of the short-run effects of different policies, the consideration of multiple constraints, possibly binding at the same time, is important. The effectiveness of LTV as a measure to tackle the rise in indebtedness has to be reassessed and is likely lower than previously shown.

Macroprudential Policy Analysis via an Agent Based Model of the Real Estate Sector

“…Empirical and theoretical papers provide insights on the effectiveness of these instruments in smoothing the real estate cycle (Greenwald, 2018) and in reducing household debt and increase resilience (Cassidy and Hallissey, 2016). Moreover, Grodecka, 2019 studies the interactions between LTV and LSTI limits, showing that multiple binding constraints can augment the effectiveness of LTV in tackling the rise in indebtedness.…”