6533b837fe1ef96bd12a337a

RESEARCH PRODUCT

GDP clustering: A reappraisal

Christopher F. ParmeterMichele Battisti

subject

Economics and EconometricsCross countryComputer sciencebusiness.industryDistribution (economics)Autoregressive modelModel based clusteringStatisticsEconometricsPer capitaSettore SECS-P/01 - Economia PoliticabusinessCluster analysisMixture densities output autoregressive isotropicFinancePanel data

description

Abstract This note explores clustering in cross country GDP per capita using recently developed model based clustering methods for panel data. Previous research characterizing the components of the overall distribution of output either use ad hoc methods, or methods which ignore/subvert the panel nature of the data. These new methods allow the characterization of the possible autoregressive relationship of output between time points. We show that traditional static clustering decade by decade gives mixed results regarding clustering over time, while the application of longitudinal mixtures presents three distinct clusters at all periods of time.

yearjournalcountryeditionlanguage
2012-12-01Economics Letters
https://doi.org/10.1016/j.econlet.2012.08.038