Continuity Under a Different Name: The Outcome of Privatisation in Serbia

ABSTRACT

Normally, privatisation is seen as beneficial. This paper considers the case of Serbia – a latecomer in the matter – where privatisation was partly a result of exogenous pressures and where the process has been deemed a failure. In Serbia, a sizeable number of privatised firms were bought by bureaucrats and politicians and all firms were subjected to a period of supervision. We argue that the design of this process allowed rent-seekers to conserve their privileges through asset-stripping, which explains the failure. In order to do so, we perform an empirical analysis of the determinants of liquidation, merger and bankruptcy of privatised firms from 2002 to 2015. We construct a novel data set from primary sources, free of the ‘survivorship bias’ and containing proxies for various types of owners, indirect signs of asset-stripping strategy and a broad range of controls. Our results indicate that firms owned by politicians faced significantly higher risks of bankruptcy, especially after the end of supervision.

KEYWORDS:

• Privatisation
• asset-stripping
• logistic regression
• survival analysis

Acknowledgements

The authors would like to thank Michael Guetta, Harald Hagemann, Ben Powell, Klaus Prettner, Athanasios Saitis and Edward Stringham Martyna Marczak for their support, help and comments, which helped us to improve our paper. The authors would like to thank Jadranka Spehar and Ljiljana Tomic from Privatisation Agency for allowing us to examine the missing contracts and an anonymous officer from Serbian Business Registers Agency as well as Djuro Djuric for helping us with missing data and additional clarifications about regulatory frameworks. Vadim Kufenko gratefully acknowledges the support provided by the Faculty of Business, Economics, and Social Sciences at the University of Hohenheim within the research area ‘Inequality and Economic Policy Analysis (INEPA)’. The authors would also like to thank the anonymous referees for their comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Vladan Ivanovic http://orcid.org/0000-0001-9205-8645

Vadim Kufenko http://orcid.org/0000-0003-4927-8815

Boris Begovic http://orcid.org/0000-0001-7343-190X

Nenad Stanisic http://orcid.org/0000-0002-7070-4826

Notes on contributors

Vladan Ivanović is an assistant Professor at the University of Kragujevac, School of Economics. He earned a PhD in Economics at the University of Kragujevac in 2014 and is at present a PhD candidate at the University of Hohenheim. He currently holds a Position of Vice-Dean at the University of Kragujevac, School of Economics. His main research interests are: transition economics, institutional economics, political economy, economic history.

Vadim Kufenko received his Doctor of Economic Sciences (Dr. oec.) degree in 2017 at the University of Hohenheim and is currently a postdoctoral research associate and a research area coordinator at the Institute of Economics, Faculty of Business, Economics, and Social Sciences at the University of Hohenheim. His main research interests include econometric analysis of time series and panel data, inequality, political economy and economic history with a focus on institutions and demographics.

Boris Begović is a professor of economics at the School of Law, University of Belgrade. His main research interest are: political economy, institutional economics, theory of economic growth, industrial organization, economics of competition policy and economic regulation, and economic analysis of law. His latest book was 'Economic Analysis of Criminal Deterrence' and now he is working on 'Theory and Institutions of economic regulation'.

Nenad Stanišić is an associate professor at the University of Kragujevac, School of Economics. He gained his PhD in Economics at the University of Belgrade in 2010. His main research interests are international economic integration and international economics.

Vincent Geloso is postdoctoral fellow at Texas Tech University and obtained his PhD from the London School of Economics. His research interests lie at the intersection between North American economic history, population economics and public economics.

Notes

1. According to the privatisation indicators of the European Bank for Reconstruction and Development (EBRD), Serbia is moving very slowly through the process. Since the transition within the former Yugoslavia began in 1989, the indicators of privatisation have recorded very moderate improvement. Although the scores are getting better, progress is slow and they reflect only the quantitative aspect of privatisation, in particular, how many of assets were privatised. The indicators do not reflect information about the fates of the privatised enterprises. This could be why some of the studies found negative public attitudes toward privatisation (Denisova et al. 2012).

2. The Privatisation Agency was funded by international organisations. It outsourced advisory work to private firms and offered high salaries to entice competent workers and prevent corruption (Cvetkovic et al. 2007, p. 228).

3. In addition, our strategy avoids ‘survivorship bias’. This measurement error arises when one includes in the dataset only those firms which have survived through privatisation.

4. As Megginson and Netter (2001) pointed out when they found that the identity of the new owners and managers was important in determining post-privatisation performance.

5. As Nellis (1999, p. 29) observed, institutionally weak economies that approached privatisation more cautiously have little to show for it.

6. 97% of all privatisation decisions were revised (Bolcic 2003).

7. Here we would like to note that there exist theories of endogenous time preferences that depend on wealth. Even though some authors reject such a relationship (see Ogaki and Atkeson 1997, for consumption decisions), it may still be the case that wealth, among many other factors, determines the individual discount factor. Distinguishing between the rich and the poor agents may be relevant for voucher privatisation; however, in our case, the sample consists of auctions and tenders. Our identification strategy is based on background information on the buyers: we isolate extremely influential tycoons, who already run multiple businesses, and persons with a political background. We elaborate on this category of owners in the data section.

8. The APR is the primary source of data regarding the survival of firms. In the case of bankruptcies, we had to complement this with data from the ALSU in order to fill some missing gaps. This source serves also as a control tool in order to check whether the data match those of APR.

9. We considered only legal disputes. While the list of other kinds of disputes is much broader, including complaints involving syndicates or minority shareholders, legal conflicts were easier to document exhaustively through media sources up to the end of 2015.

10. Article 31 of the Regulation on the sale of capital and property in auctions (Official Gazette of the Republic of Serbia 2001b), conferred an exclusive right to instalment buying on nationals.

11. We have identified the following reasons for contract changes: change of owner (contract of assignment, change of the stakes among the owners in the case of consortium or the change of members of consortium), payment of the full price before the contractually determined term, corrections of price or other elements (which were incorrectly or incompletely stipulated in the original contract), delay in instalments, change in dominant business activity (or addition of new activities to the dominant one), change of the legal form of the subject of the privatisation (from stock company to the limited liability form), or changes in originally negotiated investment dynamics.

12. For this purpose, we have used road distances.

13. One has to note that not all covariates may necessarily imply causality and there is room for discussion, which we elaborate in the next section.

14. For bootstrapping the errors, we use the bias correction as in Efron and Tibshirani (1994, pp. 14–15) and run 200 rounds. The settings for the seed of the pseudo-random number generator ensure comparability between the baseline and expanded specifications. Nevertheless, we report the latter estimates in the Appendix: due to potential sensitivity of the values of standard errors to bootstrapping parameters, they should be interpreted with caution. These bootstrapped standard errors merely serve as a check of whether the variables and the effects of interest remain significant with the bootstrapped standard errors.

15. Mergers are disregarded since after mergers the firms most likely continue to exist, but in a different form. This would contradict the underlying assumption of the survival analysis. On the contrary, liquidation and bankruptcies are related to failure and closure of the firms and therefore the firm as such ceases to exist.

16. One has to distinguish between the analysis of failure or failure rates for all firms privatised and the analysis of the performance of only the firms, which have survived. In the latter case one may be confronted with the ‘survivorship bias’, the phenomenon of a measurement error, mentioned in the critique of Kikeri and Nellis (2004). Our empirical strategy covers the broadest sample of firms, including the ones which failed to survive, i.e. which were in the meantime closed or were under bankruptcy procedure.

17. EBRD Transition Reports and Indicators, accessed on 30 October 2017: http://www.ebrd.com/what-we-do/economic-research-and-data/data/forecasts-macro-data-transition-indicators.html