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*p <.05 All models were estimated using 10 datasets containing imputed values for cases with missing data (total N = 4582 in each dataset).
All models were estimated using maximum likelihood estimation.
All models were estimated at country level.
All models were estimated as dichotomous Rasch models.
All models were estimated in the R environment (R Core Team 2016).
All models were estimated using PySAL, a Python library for spatial analysis developed by the GeoDa Center for Geospatial Analysis and Computation [37].
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The response variables of the models are not utilized in modelling, and the parameters of all models are estimated simultaneously.
All models are estimated using OLS.
All models are estimated per NST/R 1 commodity type (10 models).
All models are estimated with year dummy variables and firm fixed effects.
All models are estimated with calendar year dummy and industry fixed effects.
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