Assistant Professor of Economics
University of Amsterdam
Macroeconomics with heterogeneous agents · Macro-Finance · Household finance · Computational Economics
We evaluate the hypothesis that rising inequality was a causal source of the US household debt boom since 1980. The mechanism builds on the observation that households care about their social status. To keep up with the ever richer Joneses, the middle class substitutes status-enhancing houses for status-neutral consumption. These houses are mortgage-financed, creating a debt boom across the income distribution. Using a stylized model we show analytically that aggregate debt increases as top incomes rise. In a quantitative general equilibrium model we show that Keeping up with the Joneses and rising income inequality generate 60% of the observed boom in mortgage debt and 50% of the house price boom. We compare this channel to two competing mechanisms. The Global Saving Glut hypothesis gives rise to a similar debt boom, but does not generate a house prices boom. Loosening collateral constraints does not generate booms in either debt or house prices. Finally, we provide novel empirical evidence on the relationship between top incomes and household debt. Mortgage debt rose substantially more in US states that experienced stronger growth in top incomes. There is no such relationship between top incomes and non-mortgage debt. These findings support to the importance of the comparisons channel.
Housing wealth effects—the reaction of consumption to changes in house prices—were at the heart of the Great Recession. Empirical and quantitative macroeconomic studies have found that housing wealth effects are stronger for more indebted households. One important policy implication is that lowering debt limits for borrowers will dampen the consumption slump in a house price bust. Such conclusions might be premature. We build a simple life-cycle model with housing with closed form solutions for housing wealth effects. We show that the strength of housing wealth effects crucially depends on the underlying household characteristics which also determine the debt levels. In this framework imposing one-size-fits-all debt limits does not necessarily mitigate housing wealth effects. To be effective, policies have to be tailored to borrowers’ characteristics. Aggregate housing wealth effects can be reduced in three ways: (i) if old homeowners reduce their housing wealth; (ii) if the home ownership rate decreases; (iii) if agents have smaller houses. We provide a simple empirical test of our model predictions. When explaining housing wealth effects, we find that the level of mortgages turns statistically insignificant once relevant household characteristics (age and a proxy for housing preferences) are added.
2020: AEA in San Diego (Poster) · AFA in San Diego (Poster) · University of Amsterdam · University of Bologna · virtual Western Finance Association
2019: Mannheim-Frankfurt Macro Workshop · Stockholm University · Nordic Macro Symposium in Smögen (Discussant) · Econometric Society European Meeting in Manchester · New Approaches for Understanding Business Cycles (CEPR, Mannheim, Poster) · European Winter Meeting of the Econometric Society in Rotterdam
2018: Financial Markets and Macroeconomic Performance (CEPR, Frankfurt, Poster) · CEPR European Summer Symposium in Financial Markets in Gerzensee (evening sessions) · Econometric Society European Meeting in Cologne · Winter Meeting of the Austrian Economic Association in Vienna
University of Amsterdam
Amsterdam School of Economics
1018 WB Amsterdam