State Ownership and Labor Redundancy : Estimates Based on Enterprise-Level Data from Vietnam
Privatizing, or restructuring state-owned enterprises, may lead to massive layoffs, but the number of redundant workers is usually unknown beforehand. The authors estimate labor redundancy by comparing employment levels across enterprises with...
| Main Authors: | , |
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| Format: | Policy Research Working Paper |
| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2014
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/2001/05/1121280/state-ownership-labor-redundancy-estimates-based-enterprise-level-data-vietnam http://hdl.handle.net/10986/19659 |
| Summary: | Privatizing, or restructuring
state-owned enterprises, may lead to massive layoffs, but
the number of redundant workers is usually unknown
beforehand. The authors estimate labor redundancy by
comparing employment levels across enterprises with
different degrees of state ownership. In their model, state
enterprises are a hybrid between labor-managed enterprises,
and profit-maximizing enterprises, with the profit motive
becoming less prominent as the state of capital increases.
This model leads to an employment equation, that is
estimated using an enterprise database from Vietnam. In this
database, constructed especially for this paper, roughly a
third of the enterprises are fully state-owned, a third are
fully private, and a third are joint ventures between the
state, and the private sector. The employment equations
control for sector activity, region, and the
enterprise's age, among other variables. The results
suggest that if the state share of capital were brought down
to zero, roughly half of the workers in the corresponding
enterprises would be redundant. This is more than ten times
the estimate by the current enterprise directors. The
results also show a wide dispersion of redundancy across
sectors of activity. There is only a weak correlation
between estimated labor redundancy, and twelve ad hoc
indicators of profitability, productivity, and labor cost.
But the correlation between most ad hoc indicators also is
weak, suggesting that these indicators are not reliable
tools for identifying the most overstaffed enterprises. |
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