Document Type

Working Paper

Date

1-2021

Keywords

Foreign Direct Investment, Productivity Dynamics, Non-Hicks-Neutral Effect, China's Manufacturing Sector, Nonparametric Model

Language

English

Acknowledgements

We thank seminar participants at the 5th InsTED Workshop at Syracuse University and Comparative Analysis of Enterprise Data (CEAD) at University of Michigan for helpful comments and suggestions. All errors are our own. The corresponding author is Hoang Pham. Email: hoang.pham@oregonstate.edu. Address: Bexell 422A, 2251 SW Campus Way, Corvallis, OR 97331, United States. Cellphone: +1 970 449 2335.

Disciplines

Economic Policy | Economics | Public Affairs, Public Policy and Public Administration

Description/Abstract

This paper studies two novel productivity characteristics of foreign acquisition on high-tech manufacturing firms: the dynamic and the non-Hicks-neutral effects. A dynamic productivity effect of foreign ownership arises when adoption of foreign technology and management practices takes time to fully realize. Furthermore, these dynamic adjustments may be capital or labor augmenting as adoption of advanced production technologies tends to have non-neutral productivity implications in developed countries. We propose and implement an econometric framework to estimate both effects using firm-level data from China's manufacturing sector. Our framework extends the nonparametric productivity framework developed by Gandhi, Navarro and Rivers (2020), in which identification is achieved using a firm's first-order conditions and timing assumptions. We find strong evidence of dynamic and non-neutral effects from foreign ownership, with significant differences across investment sources. Investment from OECD sources is found to provide a long-term productivity boost for all but the largest recipients, while that from Hong Kong, Macau and Taiwan does not raise performance. These findings have implications for China's declining labor share and for the rising domestic value-added content of its high-tech exports.

ISSN

1525-3066

Additional Information

Working paper no. 236

Source

Local input

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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