  We employ an ARDL bounds testing approach to cointegration and Unrestricted
Error Correction Models (UECMs) to estimate the relationship between income and
CO2 emissions per capita in 21 Latin American Countries (LACs) over 1960-2017.
Using time series we estimate six different specifications of the model to take
into account the independent effect on CO2 emissions per capita of different
factors considered as drivers of different dynamics of CO2 emissions along the
development path. This approach allows to address two concerns. First, the
estimation of the model controlling for different variables serves to assess if
the EKC hypothesis is supported by evidence in any of the LACs considered and
to evaluate if this evidence is robust to different model specifications.
Second, the inclusion of control variables accounting for the effect on CO2
emissions is directed at increasing our understanding of CO2 emissions drivers
in different countries. The EKC hypothesis effectively describes the long term
income-emissions relationship only in a minority of LACs and, in many cases,
the effect on CO2 emissions of different factors depends on the individual
country experience and on the type and quantity of environmental policies
adopted. Overall, these results call for increased environmental action in the
region.
