2019/39 | LEM Working Paper Series | ||||||||||||||||
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Exporting and productivity as part of the growth process: Causal evidence from a data-driven structural VAR |
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Tommaso Ciarli, Alex Coad and Alessio Moneta |
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Keywords | |||||||||||||||||
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Productivity; Exporting; Learning-by-exporting; Causality; Structural VAR; Independent Component Analysis.
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JEL Classifications | |||||||||||||||||
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L21, D24, F14, C22
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Abstract | |||||||||||||||||
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This paper introduces a little known category of estimators - Linear Non-Gaussian
vector autoregression models that are acyclic or cyclic - imported
from the machine learning literature, to revisit a well-known debate. Does
exporting increase firm productivity? Or is it only more productive firms that
remain in the export market? We focus on a relatively well-studied country
(Chile) and on already-exporting firms (i.e. the intensive margin of exporting).
We explicitly look at the co-evolution of productivity and growth, and
attempt to ascertain both contemporaneous and lagged causal relationships.
Our findings suggest that exporting does not have any causal influence on
the other variables. Instead, export seems to be determined by other dimensions
of firm growth. With respect to learning by exporting (LBE), we find
no evidence that export growth causes productivity growth within the period
and very little evidence that exporting growth has a causal effect on subsequent TFP growth.
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