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Personnel Power: Governing State-Owned Enterprises

Published online by Cambridge University Press:  07 June 2021

Wendy Leutert
Affiliation:
Indiana University
Samantha A. Vortherms*
Affiliation:
Department of Political Science, 5229 Social Science Plaza B, University of California-Irvine, Irvine, CA 92697-5100
*
*Corresponding author: Samantha A. Vortherms, email: s.vortherms@uci.edu
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Abstract

State-owned enterprises (SOEs) retain a strong presence in many economies around the world. How do governments manage these firms given their dual economic and political nature? Many states use authority over executive appointments as a key means of governing SOEs. We analyze the nature of this “personnel power” by assessing patterns in SOE leaders’ political mobility in China, the country with the largest state-owned sector. Using logit and multinomial models on an original dataset of central SOE leaders’ attributes and company information from 2003 to 2017, we measure the effects of economic performance and political connectedness on leaders’ likelihood of staying in power. We find that leaders of well-performing firms and those with patronage ties to elites in charge of their evaluation are more likely to stay in office. These findings suggest that states can leverage personnel power in pursuit of economic and political stability when SOE management is highly politically integrated.

Information

Type
Research Article
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of V.K. Aggarwal.
Figure 0

Figure 1: Spectrum of SOE Executive Management Systems

Figure 1

Figure 2: Administrative Hierarchy and Organizational Structure of Core Central SOEs in ChinaSource: Leutert, 2020.

Figure 2

Table 1: Leadership Mobility Outcomes for China's Central SOE Leaders

Figure 3

Figure 3: Average ROA for Central SOE Largest Subsidiary over Time, with 95 Percent Confidence Intervals

Figure 4

Figure 4: Marginal Effects Power Continuation, Logit Models with 90 Percent and 95 Percent Confidence IntervalsAll models include controls for age, experience, and SOE industry. Models in Panel A include cumulative connections while models in Panel B include control of ROA. Full results available in appendix tables A4 and A5.

Figure 5

Figure 5: Marginal Effects of Key Independent Variables on Probability of Exit and Political Mobility, Three Level Models with 90 Percent and 95 Percent Confidence IntervalsStaying in the state-owned economy estimated as the baseline option. Marginal effects predicted from the multinomial logit model. Full results available in appendix table A6.

Figure 6

Table 2: Marginal Effects of Patron Connections at Three Levels on Power Continuation and Mobility Outcomes

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Leutert and Vortherms supplementary material

Leutert and Vortherms supplementary material

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