Exporting and productivity as part of the growth process: Causal evidence from a data-driven structural VAR - Tommaso Ciarli; Alexander Coad; Alessio Moneta (Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM), 2019)
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.
Keywords: L21; D24; F14; C22; 330; Productivity; Exporting; Learning-by-exporting; Causality; Structural VAR; Independent Component Analysis