Bibliographic record
Abstract
Abstract State governance in corporations controls the economy and employment to develop prosperity in China. Does privatization achieve both objectives? Privatization theory views that giving up state control benefits firms economically but is quite silent on the value of employment benefits. However, market mix theory (Sappington and Stiglitz, J Policy Anal Manag 6(4):567–582, 1987; Stiglitz, Whither Socialism? MIT Press, Cambridge, MA, and London, England, 1994) views that state control of firms to provide employment is valuable. It further implies that corporate performance and employment objectives can co-exist well together. We formalize Market Mix Theory to reveal its testable implications on dual objectives and performance. We test the notion that Chinese corporations pursue two objectives: maximizing economic value and employment, unlike the singular objective of value maximization in Western firms. As well, we test the benefit of partial privatization. First, we test the market mix theory by studying the relationship between state ownership and employment and financial performance as a combined objective. We show that mixed firms have the highest performance in wealth maximization and employment compared to private and state-controlled firms. Second, we examine Chinese SOEs’ Employment with a large sample of 2536 public firms using panel regressions. We find that state ownership and firm employment have a positive relationship. State ownership is positively related to employment stability. Moreover, performance has a negative relationship with state ownership–employment. This result supports our over-employment hypothesis, meaning that economic performance is sacrificed to provide employment. Lastly, we show executive pay for SOE managers is positively related to employment. The employment objective is real in determining state control in Chinese corporations without conflicting to maximize shareholder wealth. Rather, the mixed form of ownership is optimal and vitally contributes overall to the stability and prosperity of China. Our formalization of market mix theory better reflects the reality of motivation, performance and benefits of partial privatization as exemplified in Chinese state-owned enterprises.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".