The new model class of mixtures of generalised nonlinear models (GNMs) is introduced. The model is specified, identifiability issues discussed, their 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 dierences lead to distinct components. Countries belonging to the same component exhibit convergence to a homogeneous steady state. The components dier in the initial technological endowment and the contribution of the economic variables to the economic growth.
|Journal||Econometrics and Statistics|
|Publication status||Submitted - Mar 2021|