What drives the dynamics of top wealth inequality? To answer this question, I propose an accounting framework that decomposes the growth of the share of aggregate wealth owned by a top percentile ...into three terms: a within term, which is the average wealth growth of individuals initially in the top percentile relative to the economy; a between term, which accounts for individuals entering and exiting the top percentile due to changes in their relative wealth rankings; and a demography term, which accounts for individuals entering or exiting the top percentile due to death and population growth. I obtain closed‐form expressions for each term in a wide range of random growth models. Evidence from the Forbes 400 list suggests that the between term accounts for half of the recent rise in top wealth inequality.
Sorting out the effect of credit supply Chang, Briana; Gomez, Matthieu; Hong, Harrison
Journal of financial economics,
December 2023, 2023-12-00, Letnik:
150, Številka:
3
Journal Article
Recenzirano
We document that banks that cut lending more during the Great Recession were lending to riskier firms ex-ante. To understand the aggregate implications of this sorting pattern, we build an assignment ...model in which banks have heterogeneous costs to take on risky loans and firms have different credit risks. In the model, aggregate loan volume depends on the entire distribution of bank holding costs and firm credit risks. We then use our model to recover the change in the distribution of bank holding costs during the Great Recession and show that it explains two-thirds of the decline of aggregate loan volume during this period.
The cash-flow exposure of banks to interest rate risk, or income gap, is a significant determinant of the transmission of monetary policy to bank lending and real activity. When the Fed Funds rate ...rises, banks with a larger income gap generate stronger earnings and contract their lending by less than other banks. This finding is robust to controlling for factors known to affect the transmission of monetary policy to bank lending. It also holds on loan-level data, even when we control for firm-specific credit demand. When monetary policy tightens, firms borrowing from banks with a larger income gap reduce their investment by less than other firms.
Wealth Inequality in a Low Rate Environment Gomez, Matthieu; Gouin‐Bonenfant, Émilien
Econometrica,
January 2024, 2024-00-00, 20240101, Letnik:
92, Številka:
1
Journal Article
Recenzirano
Odprti dostop
We study the effect of interest rates on wealth inequality. While lower rates decrease the growth rate of rentiers, they also increase the growth rate of entrepreneurs by making it cheaper to raise ...capital. To understand which effect dominates, we derive a sufficient statistic for the effect of interest rates on the Pareto exponent of the wealth distribution: it depends on the lifetime equity and debt issuance rate of individuals in the right tail of the wealth distribution. We estimate this sufficient statistic using new data on the trajectory of top fortunes in the U.S. Overall, we find that the secular decline in interest rates (or more generally of required rates of returns) can account for about 40% of the rise in Pareto inequality; that is, the degree to which the super rich pulled ahead relative to the rich.
Chapter 1 uses recently available data on the top of the wealth distribution to study the relationship between asset prices and wealth inequality. I document three stylized facts: (1) the share of ...wealth invested in equity increases sharply in the right tail of the wealth distribution, (2) when stock market returns are high, wealth inequality increases and (3) higher wealth inequality predicts lower future stock returns. These facts correspond to the basic predictions of asset pricing models with heterogeneous agents. Quantitatively, however, standard models with heterogeneous agents cannot fully capture the joint dynamics of asset prices and the wealth distribution. Augmenting the model with additional sources of fluctuations in wealth inequality, namely in the form of time-varying investment opportunities for wealthy households, is crucial to match the observed fluctuations in wealth inequality and in asset prices. Chapter 2 takes a closer look at recent rise in top wealth inequality. I first derive an analytical formula that decomposes the growth of top wealth shares into three terms: the relative wealth growth of individuals in the top, a term due to idiosyncratic returns, and a term due to population renewal. I then map each term to the data using the annual ranking of Forbes Magazine’s list of the 400 wealthiest Americans. The decomposition reveals that the rise in top wealth shares in 1982-1994 is mostly driven by idiosyncratic returns, while the rise in top wealth shares in 1995–2015 is mostly driven by the relative growth of individuals at the top. Chapter 3, coauthored with Augustin Landier, David Sraer, and David Thesmar, investigates the heterogeneity of banks’ exposure to interest rate risk. In the cross-section of banks, income gap predicts the sensitivity of cash-flows and lending to interest rates. This analysis also allows us to link banks’ interest risk exposure to firm investment and employment.
There has been a dramatic rise in top wealth inequality in the United States since 1980. This paper stresses the role of composition effects in driving this phenomenon. I first show an analytical ...formula that expresses the growth of top wealth shares as the sum of three terms: the relative wealth growth of individuals at the top, a term due to idiosyncratic wealth shocks, and a term due to population renewal. I propose an accounting decomposition to estimate each term from a panel data of wealthy individuals. I then apply this decomposition to the annual ranking of Forbes Magazine's list of the 400 wealthiest Americans. This exercise reveals that the rise in the top 400 wealth share in 1982-1994 is mostly driven by an increase of the variance of idiosyncratic wealth shocks, while the rise in the top 400 wealth share in 1995-2015 is mostly driven by an increase of the wealth growth of individuals at the top.
We document that banks which cut lending more during the Great Recession were lending to riskier firms. To explain this evidence, we build a competitive matching model of bank-firm relationships in ...which risky firms borrow from banks with low holding costs. Based on default probabilities and equilibrium loan rates, we use our sorting model to recover the latent bank holding cost distribution. The measure of banks with low holding costs dropped during the Great Recession. This credit supply shift conservatively accounted for around 50% of the decline in corporate loans over this period. Our attribution cannot be captured by panel regression estimates from the bank lending channel literature.
We document that banks which cut lending more during the Great Recession were lending to riskier firms. To explain this evidence, we build a competitive matching model of bank-firm relationships in ...which risky firms borrow from banks with low holding costs. Based on default probabilities and equilibrium loan rates, we use our sorting model to recover the latent bank holding cost distribution. The measure of banks with low holding costs dropped during the Great Recession. This credit supply shift conservatively accounted for around 50% of the decline in corporate loans over this period. Our attribution cannot be captured by panel regression estimates from the bank lending channel literature.
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