Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/228137
Authors: 
Ciarli, Tommaso
Coad, Alexander
Moneta, Alessio
Year of Publication: 
2019
Series/Report no.: 
LEM Working Paper Series No. 2019/39
Abstract: 
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.
Subjects: 
Productivity
Exporting
Learning-by-exporting
Causality
Structural VAR
Independent Component Analysis
JEL: 
L21
D24
F14
C22
Document Type: 
Working Paper

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