Housing and the Financial Crisis

‘Drivers of the Great Housing Boom-Bust: Credit Conditions, Beliefs, or Both?,’ Ludvigson, V. and J. Cox, 2019.

Two potential driving forces of house price áuctuations are commonly cited: credit conditions and beliefs. We posit some simple empirical calculations using direct measures of credit conditions and beliefs to consider their potentially distinct roles in house price áuctuations at the aggregate level. Changes in credit conditions are positively related to the fraction of riskier non-conforming debt in total mortgage lending, while measures of beliefs are unrelated to this ratio. Credit conditions explain quantitatively large magnitudes of the variation in quarterly house price growth and also predict future house price growth. Beliefs bear some relation to contemporaneous house price growth but have little predictive power. A structural VAR analysis implies that shocks to credit conditions have quantitatively important dynamic causal e§ects on house price changes.

‘Liquidity Constraints in the U.S. Housing Market,’ Midrigan, V. (with D. Gorea), 2018.

We study the severity of liquidity constraints in the U.S. housing market using a life-cycle model with uninsurable idiosyncratic risks in which houses are illiquid, but agents have the option to extract home equity by refinancing their long-term mortgages. The model implies that three quarters of homeowners are liquidity constrained and willing to pay an average of 5 cents to extract an additional dollar of liquidity from their home. Most homeowners value liquidity for precautionary reasons, anticipating the possibility of income declines and the need to make mortgage payments in future periods. Mortgage assistance policies structured as credit lines to homeowners who experience a shortfall in income greatly reduce the severity of liquidity constraints.

‘Household Leverage and the Recession,’ Midrigan, V. (with T. Philippon and C. Jones), 2017.

During the Great Recession, employment declined more in regions where household debt declined more. We study a model where liquidity constraints amplify the response of consumption and employment to changes in debt. We estimate the model using Bayesian likelihood methods on state-level and aggregate data. Credit shocks account well for the differential rise and fall of employment across individual states. Credit shocks explain a smaller fraction of the initial drop in aggregate employment but the tightening of household credit greatly contributes to the slow recovery in the aftermath of recession.