Identifying “Tipping Points” in Consumer Liabilities Using High Frequency Data
*Names in bold indicate Presenter
In this paper we define a new notion of a household "tipping point" using principles of economics and a novel high-frequency consumer-level dataset. We attempt to create a metric which identifies when a household reaches the point where their debt holdings become a drag on their activity rather than an engine for growth. We begin by posing a question: how does economics help in the identification of such a tipping-point? The answer is a tipping point occurs when an individual can no longer satisfy their individual budget constraint. This is the point where an individual must turn to bankruptcy or a foreclosure to satisfy their budget constraint. The ratio of the total debt payment to after-tax income has proven to be an informative measure to specify this tipping. However, we show that this metric should be conditioned on such things as available wealth, the liquidity of the assets, ability to raise additional debt, and the structure of this debt. The depth of our data allows us to assess how this ratio behaves based on age groups and income quartiles. We also assessed the ability of the debt payment to income ratio to predict bankruptcy and foreclosure events. A preliminary examination of this measure based on the dynamics of the monthly debt payment to income ratio suggests that this metric has some predictive content when compared to alternative metrics based on the dynamics of the FICO score.