Capital Income Risk and the Dynamics of the Wealth Distribution

Khieu, Hoang; Wälde, Klaus

doi:10.2139/ssrn.3261699

Cited by 2 publications

(1 citation statement)

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“…Given its dependence on one continuous random variable and one discrete random variable, the stationary joint density function, g (a, e), can be split into g (a, e h ) and g (a, e l ). Following Khieu and Wälde (2019), we refer to these individual probability functions as subdensities. For each e ∈ E, it follows that g (a, e) ≡ g (a | e) p (e), implying that g (a, e) da = p (e) ,…”

Section: Equilibriummentioning

confidence: 99%

Estimation of Heterogeneous Agent Models: A Likelihood Approach

2022

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We study the statistical properties of heterogeneous agent models. Using a Bewley-Hugget-Aiyagari model we compute the density function of wealth and income and use it for likelihood inference. We study the finite sample properties of the maximum likelihood estimator (MLE) using Monte Carlo experiments on artificial cross-sections of wealth and income. We propose to use the Kullback-Leibler divergence to investigate identification problems that may affect inference. Our results suggest that the unrestricted MLE leads to considerable biases of some parameters. Calibrating weakly identified parameters allows to pin down the other unidentified parameter without compromising the estimation of the remaining parameters. We illustrate our approach by estimating the model for the U.S. economy using wealth and income data from the Survey of Consumer Finances.

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Section: Equilibriummentioning

confidence: 99%