The dynamic factor network model with an application to international trade

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Standard

The dynamic factor network model with an application to international trade. / Bräuning, Falk; Koopman, Siem Jan.

In: Journal of Econometrics, Vol. 216, No. 2, 2020, p. 494-515.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Harvard

APA

CBE

MLA

Vancouver

Author

Bräuning, Falk ; Koopman, Siem Jan. / The dynamic factor network model with an application to international trade. In: Journal of Econometrics. 2020 ; Vol. 216, No. 2. pp. 494-515.

Bibtex

@article{b2bb9e4742d04c9b952cb4612f360b60,
title = "The dynamic factor network model with an application to international trade",
abstract = "We introduce a dynamic network model with probabilistic link functions that depend on stochastically time-varying parameters. We adopt a blockmodel framework and allow the high-dimensional vector of link probabilities to be a function of a low-dimensional set of dynamic factors. The resulting dynamic factor network model has a basic and transparent structure. However, parameter estimation, signal extraction of stochastic loadings and dynamic factors, and the econometric analysis generally are intricate tasks for which simulation-based methods are needed. We provide feasible and practical solutions to these challenging tasks, based on a computationally efficient importance sampling procedure to evaluate the likelihood function. An extensive Monte Carlo study demonstrates the performance of our method in finite samples, both under correct and incorrect model specifications. In an empirical study, we use the novel framework to analyze global patterns of banana exports and imports. We identify groups of heavy and light traders in this highly active commodity market and their time-varying trade probabilities.",
keywords = "Blockmodels, Dynamic factor models, International trade, Network analysis",
author = "Falk Br{\"a}uning and Koopman, {Siem Jan}",
year = "2020",
doi = "10.1016/j.jeconom.2019.10.007",
language = "English",
volume = "216",
pages = "494--515",
journal = "Journal of Econometrics",
issn = "0304-4076",
publisher = "Elsevier BV",
number = "2",

}

RIS

TY - JOUR

T1 - The dynamic factor network model with an application to international trade

AU - Bräuning, Falk

AU - Koopman, Siem Jan

PY - 2020

Y1 - 2020

N2 - We introduce a dynamic network model with probabilistic link functions that depend on stochastically time-varying parameters. We adopt a blockmodel framework and allow the high-dimensional vector of link probabilities to be a function of a low-dimensional set of dynamic factors. The resulting dynamic factor network model has a basic and transparent structure. However, parameter estimation, signal extraction of stochastic loadings and dynamic factors, and the econometric analysis generally are intricate tasks for which simulation-based methods are needed. We provide feasible and practical solutions to these challenging tasks, based on a computationally efficient importance sampling procedure to evaluate the likelihood function. An extensive Monte Carlo study demonstrates the performance of our method in finite samples, both under correct and incorrect model specifications. In an empirical study, we use the novel framework to analyze global patterns of banana exports and imports. We identify groups of heavy and light traders in this highly active commodity market and their time-varying trade probabilities.

AB - We introduce a dynamic network model with probabilistic link functions that depend on stochastically time-varying parameters. We adopt a blockmodel framework and allow the high-dimensional vector of link probabilities to be a function of a low-dimensional set of dynamic factors. The resulting dynamic factor network model has a basic and transparent structure. However, parameter estimation, signal extraction of stochastic loadings and dynamic factors, and the econometric analysis generally are intricate tasks for which simulation-based methods are needed. We provide feasible and practical solutions to these challenging tasks, based on a computationally efficient importance sampling procedure to evaluate the likelihood function. An extensive Monte Carlo study demonstrates the performance of our method in finite samples, both under correct and incorrect model specifications. In an empirical study, we use the novel framework to analyze global patterns of banana exports and imports. We identify groups of heavy and light traders in this highly active commodity market and their time-varying trade probabilities.

KW - Blockmodels

KW - Dynamic factor models

KW - International trade

KW - Network analysis

UR - http://www.scopus.com/inward/record.url?scp=85076213289&partnerID=8YFLogxK

U2 - 10.1016/j.jeconom.2019.10.007

DO - 10.1016/j.jeconom.2019.10.007

M3 - Journal article

AN - SCOPUS:85076213289

VL - 216

SP - 494

EP - 515

JO - Journal of Econometrics

JF - Journal of Econometrics

SN - 0304-4076

IS - 2

ER -