Quotation Omerovic, Sanela, Friedl, Herwig, Grün, Bettina. 2021. Modelling Multiple Regimes in Economic Growth by Mixtures of Generalised Nonlinear Models. Econometrics and Statistics.


RIS


BibTeX

Abstract

The new model class of mixtures of generalised nonlinear models (GNMs) is introduced. The model is specified, identifiability issues discussed, the fitting in a maximum likelihood framework using the expectation-maximisation (EM) algorithm outlined and an appropriate computational implementation introduced. The new model class is applied to capture cross-country heterogeneity when considering the augmented Solow model including human capital accumulation as underlying model structure. The inherent heterogeneity is attributed to multiple regimes being present within the selected country data set. The results highlight that country-specific differences lead to distinct components. Countries belonging to the same component exhibit convergence to a homogeneous steady state. The components differ in the initial technological endowment and the contribution of the economic variables to economic growth.

Tags

Press 'enter' for creating the tag

Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Econometrics and Statistics
Language English
Title Modelling Multiple Regimes in Economic Growth by Mixtures of Generalised Nonlinear Models
Year 2021
Reviewed? Y
URL https://www.sciencedirect.com/science/article/pii/S2452306221000307?via%3Dihub
DOI https://doi.org/10.1016/j.ecosta.2021.02.008
Open Access N

Associations

People
Grün, Bettina (Details)
External
Friedl, Herwig (Technische Universität Graz, Austria)
Omerovic, Sanela (FMA, Austria)
Organization
Institute for Statistics and Mathematics IN (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
1105 Computer software (Details)
1113 Mathematical statistics (Details)
5701 Applied statistics (Details)
Google Scholar: Search