The environmental Kuznets curve for carbon dioxide emissions: A seemingly unrelated cointegrating polynomial regressions approach
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Date
2016
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Abstract
We present estimation and inference techniques for systems of seemingly unrelated cointegrating
polynomial regressions. In particular, we present two fully modified-type estimators and
Wald-type hypothesis tests based upon them. We develop tests for poolability of subsets of
coefficients over subsets of equations. For the case that these restrictions are not rejected, we
provide the correspondingly pooled estimators. This group-wise pooling turns out to be very
useful in our application where we analyze the environmental Kuznets curve for CO2 emissions
for seven early industrialized countries. Group-wise pooled estimation leads to almost the same
results as unrestricted estimation whilst reducing the number of estimated parameters by about
one third. Fully pooled, panel-data type estimation performs poorly in comparison.
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Keywords
cointegrating polynomial regression, seemingly unrelated regression, poolability, fully modified estimation, environmental Kuznets curve