Estimation of heterogeneous agent models: A likelihood approach

Publikation: Working paperForskning

Standard

Estimation of heterogeneous agent models: A likelihood approach. / Parra-Alvarez, Juan Carlos; Posch, Olaf; Wang, Mu-Chun.

Aarhus : Institut for Økonomi, Aarhus Universitet, 2020.

Publikation: Working paperForskning

Harvard

Parra-Alvarez, JC, Posch, O & Wang, M-C 2020 'Estimation of heterogeneous agent models: A likelihood approach' Institut for Økonomi, Aarhus Universitet, Aarhus.

APA

Parra-Alvarez, J. C., Posch, O., & Wang, M-C. (2020). Estimation of heterogeneous agent models: A likelihood approach. Institut for Økonomi, Aarhus Universitet. CREATES Research Papers, Nr. 2020-05

CBE

Parra-Alvarez JC, Posch O, Wang M-C. 2020. Estimation of heterogeneous agent models: A likelihood approach. Aarhus: Institut for Økonomi, Aarhus Universitet.

MLA

Parra-Alvarez, Juan Carlos, Olaf Posch og Mu-Chun Wang Estimation of heterogeneous agent models: A likelihood approach. Aarhus: Institut for Økonomi, Aarhus Universitet. (CREATES Research Papers; Journal nr. 2020-05). 2020., 33 s.

Vancouver

Parra-Alvarez JC, Posch O, Wang M-C. Estimation of heterogeneous agent models: A likelihood approach. Aarhus: Institut for Økonomi, Aarhus Universitet. 2020 maj.

Author

Parra-Alvarez, Juan Carlos ; Posch, Olaf ; Wang, Mu-Chun. / Estimation of heterogeneous agent models: A likelihood approach. Aarhus : Institut for Økonomi, Aarhus Universitet, 2020. (CREATES Research Papers; Nr. 2020-05).

Bibtex

@techreport{55d3931dfe004f8683a7dee71db66644,
title = "Estimation of heterogeneous agent models: A likelihood approach",
abstract = "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.",
keywords = "Heterogeneous agent models, Continuous-time, Fokker-Planck equations, Kullback-Leibler divergence, Maximum likelihood",
author = "Parra-Alvarez, {Juan Carlos} and Olaf Posch and Mu-Chun Wang",
year = "2020",
month = may,
language = "English",
series = "CREATES Research Papers",
publisher = "Institut for {\O}konomi, Aarhus Universitet",
number = "2020-05",
type = "WorkingPaper",
institution = "Institut for {\O}konomi, Aarhus Universitet",

}

RIS

TY - UNPB

T1 - Estimation of heterogeneous agent models: A likelihood approach

AU - Parra-Alvarez, Juan Carlos

AU - Posch, Olaf

AU - Wang, Mu-Chun

PY - 2020/5

Y1 - 2020/5

N2 - 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.

AB - 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.

KW - Heterogeneous agent models

KW - Continuous-time

KW - Fokker-Planck equations

KW - Kullback-Leibler divergence

KW - Maximum likelihood

M3 - Working paper

T3 - CREATES Research Papers

BT - Estimation of heterogeneous agent models: A likelihood approach

PB - Institut for Økonomi, Aarhus Universitet

CY - Aarhus

ER -