Sectoral technological progress, migration barriers, and structural change in China

We construct a multi-sector Eaton-Kortum model, embodying migration barriers. * We infer technological progress and migration barriers across Chinese provinces. * The migration barriers are asymmetric across provinces. * Rich provinces gain less from inter-provincial trade than poor provinces. We introduce a novel accounting method to infer sectoral technology and migration barriers among Chinese provinces, using data on structural change and migration from 1990 to 2010. The method is based on a multi-sector Eaton-Kortum model, embodying labor mobility friction across provinces. We find that t... Mehr ...

Verfasser: Zheng Jiang
Dokumenttyp: Artikel
Reihe/Periodikum: Journal of comparative economics
Verlag/Hrsg.: Amsterdam, Elsevier
Sprache: Englisch
ISSN: 0147-5967
Weitere Identifikatoren: doi: 10.1016/j.jce.2015.01.001
Permalink: https://search.fid-benelux.de/Record/olc-benelux-1965001068
URL: NULL
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Datenquelle: Online Contents Benelux; Originalkatalog
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Link(s) : http://dx.doi.org/10.1016/j.jce.2015.01.001
http://dx.doi.org/10.1016/j.jce.2015.01.001

We construct a multi-sector Eaton-Kortum model, embodying migration barriers. * We infer technological progress and migration barriers across Chinese provinces. * The migration barriers are asymmetric across provinces. * Rich provinces gain less from inter-provincial trade than poor provinces. We introduce a novel accounting method to infer sectoral technology and migration barriers among Chinese provinces, using data on structural change and migration from 1990 to 2010. The method is based on a multi-sector Eaton-Kortum model, embodying labor mobility friction across provinces. We find that the implied migration barriers are high and asymmetric. This asymmetry of migration barriers contributes to the expansion of provincial manufacturing labor share among all the provinces. Moreover, in a country with structural change, rich provinces gain less from inter-provincial trade than poor provinces.