LIM, K.Y. ORCID: 0000-0003-1978-176X, 2019. Industrial transformation with heterogeneous labour and foreign experts. Macroeconomic Dynamics, 23 (8), pp. 3225-3266. ISSN 1365-1005
|
Text
PubSub10964_Lim.pdf - Post-print Download (626kB) | Preview |
Abstract
This paper develops an endogenous growth model with industrial transformation and a stylised foreign expert-based 'internalisation advantage' framework to determine the composition of heterogeneous foreign multinationals in a developing host economy. A key feature of the model is the introduction of a dichotomous relationship between domestic and foreign firms, where the latter perceives heterogeneity among the productivity of domestic workers. This results in the skills acquisition decision and foreign subsidiaries' operational mode choice to be determined along the same ability distribution of the host economy. This subsequently determines the shares of the di¤erent types of multinationals in a host economy. Parameterised for Malaysia, policy experiments are conducted. A balanced investment liberalisation measure for all foreign firms is found to outperform measure targeting only selected types, though there is a threshold doing-business cost value below which such a standalone FDI-promoting policy does not generate positive growth effect. This then calls for composite programme that maximises the policy complementarities between human capital and FDI-promoting policies.
Item Type: | Journal article | ||||
---|---|---|---|---|---|
Publication Title: | Macroeconomic Dynamics | ||||
Creators: | LIM, K.Y. | ||||
Publisher: | Cambridge University Press | ||||
Date: | December 2019 | ||||
Volume: | 23 | ||||
Number: | 8 | ||||
ISSN: | 1365-1005 | ||||
Identifiers: |
|
||||
Divisions: | Schools > Nottingham Business School | ||||
Record created by: | Linda Sullivan | ||||
Date Added: | 08 May 2018 10:57 | ||||
Last Modified: | 21 Apr 2020 13:22 | ||||
URI: | https://irep.ntu.ac.uk/id/eprint/33454 |
Actions (login required)
Edit View |
Views
Views per month over past year
Downloads
Downloads per month over past year