The influence of privatization on financial performance of Vietnamese privatized state-owned enterprises

  • Received August 25, 2019;
    Accepted September 26, 2019;
    Published October 9, 2019
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.16(3).2019.30
  • Article Info
    Volume 16 2019, Issue #3, pp. 341-352
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This research evaluates the differences in financial performance of enterprises before and after privatization aiming to find out the influence of privatization on the enterprises’ performance. The study is based on the audited financial statements of 105 Vietnamese privatized enterprises privatized in the period from 2005 to 2016. Applying the Wilcoxon signed-rank test, the obtained results prove that after privatization profitability and outputs of investigated firms are significantly higher than prior privatization. However, there is no significant change of leverage. Applying a regression model to evaluate the factors affecting financial performance of firms in the research model, it was found out that the proportion of state ownership, economic growth, operating period, enterprise`s size, and business risk have positive influence on the financial performance of research firms. However, the leverage of these firms has a negative impact on the financial performance. In accordance with the obtained results, this study suggests that the privatization process should be continued regardless of firm size or business type. The government should create fair competition environment, remove incentives and supports for State-Owned Enterprises (SOEs), manage changes in privatized firms, and enforce the legal system.

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    • Table 1. Definition of criteria for analysing financial performance
    • Table 2. Expected impact of financial criteria on financial performance
    • Table 3. Results of the Wilcoxon Signed Rank test for research firms’ financial performance
    • Table 4. Summary of variables of the model
    • Table 5. Test result for multicollinearity
    • Table 6. Result summary for the linear regression estimation of models ROA, ROS, ROE