By Sami Alpanda and Sarah Zubairy
In this paper, we build a dynamic stochastic general-equilibrium model with housing and household debt, and compare the effectiveness of monetary policy, housing-related fiscal policy, and macroprudential regulations in reducing household indebtedness. The model features long-term fixed-rate borrowing and lending across two types of households, and differentiates between the flow and the stock of household debt. We use Bayesian methods to estimate parameters related to model dynamics, while level parameters are calibrated to match key ratios in the U.S. data. We find that monetary tightening is able to reduce the stock of real mortgage debt, but leads to an increase in the household debt-to-income ratio. Among the policy tools we consider, tightening in mortgage interest deduction and regulatory loan-to-value (LTV) are the most effective and least costly in reducing household debt, followed by increasing property taxes and monetary tightening. Although mortgage interest deduction is a broader tool than regulatory LTV, and therefore potentially more costly in terms of output loss, it is effective in reducing overall mortgage debt, since its direct reach also extends to home equity loans.
It is important to understand what drives household indebtedness, especially excessive indebtedness. While this paper is using the right method to look at this, I think it is asking the wrong questions. If there is excessive indebtedness, there must be some optimal level, and this optimal level is not zero. Thus, it is misplaced to focus on reducing debt, maybe one needs to increase it, at least for some segments of the population. I am also not sure that one should worry about the consequences on output with this model as it can directly measure well-being. When we use output, it is because we have no better proxy. The paper is still very much worth reading, keeping in mind the questions it should be addressing. Once refocused, this is going to be a great paper.