A Multiplier Approach to Understanding the Macro Implications of Household Finance

Working Paper: NBER ID: w13555

Authors: Yili Chien; Harold Cole; Hanno Lustig

Abstract: Our paper examines the impact of heterogeneous trading technologies for households on asset prices and the distribution of wealth. We distinguish between passive traders who hold fixed portfolios of stocks and bonds, and active traders who adjust their portfolios to changes in expected returns. To solve the model, we derive an optimal consumption sharing rule that does not depend on the trading technology, and we derive an aggregation result for state prices. This allows us to solve for equilibrium prices and allocations without having to search for market-clearing prices in each asset market separately. We show that the fraction of total wealth held by active traders, not the fraction held by all participants, is critical for asset prices, because only these traders respond to variation in state prices and hence absorb the residual aggregate risk created by non-participants. We calibrate the heterogeneity in trading technologies to match the equity premium and the risk-free rate. The calibrated model reproduces the skewness and kurtosis of the wealth distribution in the data. In contrast to existing models with heterogeneous agents, our model matches the high volatility of returns and the low volatility of the risk-free rate.

Keywords: Household Finance; Asset Pricing; Wealth Distribution

JEL Codes: G12


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
fraction of wealth held by active traders (G19)asset prices (G19)
active traders respond to variations in state prices (F16)absorb residual aggregate risk (G52)
passive traders do not adjust portfolios (G11)residual aggregate risk (D80)
interaction between active and passive traders (F16)countercyclical variation in risk premia (E32)
active traders increase consumption in low state price scenarios (D11)affect market dynamics (D49)
trading technology heterogeneity (F12)economic outcomes (F61)
trading technology heterogeneity (F12)wealth distribution (D31)
active traders influence asset prices (G19)wealth distribution (D31)

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