Inter-regional Insurance and Redistribution – A Non-parametric Application to Russia

Abstract

The paper examines inter-regional insurance and redistribution of Russia's fiscal system from 1995 to 2007. We use non-parametric methods for robustness and to tackle econometric problems of endogeneity and poolability. We will also use several specifications of variables. We find that the Russian inter-regional insurance system should be considered a stabilizing scheme against tax income and budget expenditure shocks, rather than against gross product or population income shocks, as typically assumed in literature considering data of other countries. Furthermore, we find evidence that the differences in the insurance estimates are mainly due to Federation-wide policy changes rather than a result of asymmetric treatment of regions.

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Notes

  1. 1.

    Here we will use terms inter-regional insurance and stabilization interchangeably. A variety of other names for the subject have been used in the literature as well; for example fiscal insurance, inter-regional risk sharing, intranational insurance and interstate insurance.

  2. 2.

    There is also plentiful theoretical literature on inter-regional insurance and redistribution. For readers interested in the theoretical literature on the theme, we recommend to see von Hagen (1998); Vigneault (2002); Persson and Tabellini (1996a, 1996b); Sala-i-Martin and Sachs (1991); Sanguinetti and Tommasi (2004); Lockwood (1999); Bayoumi and Masson (1998) and Fatás (1998).

  3. 3.

    The issue is shortly mentioned in Vigneault (2002) when referring to Von Hagen and Hepp (2000).

  4. 4.

    Vertical imbalance refers to the difference between regional mandates and funds available for their implementation. Horizontal imbalance refers to a situation where there are different revenue endowments or capabilities of revenue collection across sub-national governments.

  5. 5.

    These transfer flows include all transfers, such as the FFSR and mutual settlements.

  6. 6.

    We multiplied the annual share of industrial production and oil production of regional gross product with annual change in the real effective exchange rate and Ural's oil price, respectively. K-S use the real exchange rate but we think that the trade weighted real exchange rate is better suited as it grasps the effects on regional foreign trade better. The variables grasp foreign trade shocks to regions resulting from price differences and changes in exchange rates.

  7. 7.

    We exclude the Republic of Chechnya due to unreliable and partly unavailable data. The figures of eight autonomous districts are embedded into their administrative centre regions.

  8. 8.

    M-Z use four different accounting alternatives of increasing coverage for the stabilization flow measure: (a) Direct taxes, (b) a+social insurance, (c) b+transfers and (d) c+grants.

  9. 9.

    Net transfers are calculated by adding up transfers from Federal to regional level and deducting from these the money rendered from the regional to the Federal level.

  10. 10.

    In our longer data set there were 29 persistent donors (rendered payments exceed received transfers each year) and 14 persistent recipient regions.

  11. 11.

    To save space, we have not included the specific correlation matrices. These are available upon request.

  12. 12.

    For a nice introduction to non-parametric estimation, see DiNardo and Tobias (2001).

  13. 13.

    We use second order Gaussian for the continuous variables and Wang and van Ryzin (1981) kernel smoothing functions for the year dummies.

  14. 14.

    After controlling for income and expenditure differences we find that Far Eastern FD has received more transfers and rendered fewer TPs. This FD incorporates regions with a harsh climate, a lot of ethnic minorities as well as resource rich regions, which may give rise to non-economic motives in determining transfer flows. FD dummies were not used in the inter-regional insurance estimations, which already include all region effects and will be removed as variables enter the estimation as a deviation from average.

  15. 15.

    It would be an interesting research topic to examine if specific tax flows behind tax income changes could be singled out data-wise for the whole estimation time range. This would be interesting because if full stabilization concerns region's own tax base, it faces very bad fiscal incentives. Any failures in tax collection are fully neutralized while positive deviations are punished by seizing the increased income to Federal budget. Zhuravskaya (2000), in fact, has found evidence that the local administrations in Russia are facing almost complete crowding out, as an increase in own revenues is almost completely offset by a decrease in shared revenues with the regional administration. Furthermore, for example Alexeev and Kurlyandskaya (2003) and Desai et al. (2005) show that the system of fiscal relations where any excess regional tax income is taken away by the federal government creates incentives for the government of richer regions to collude with local large firms in order to divert their tax payments from federal budget. Unfortunately, with our current results we are not able to elaborate on this interesting issue and it is thus beyond the scope of this paper.

  16. 16.

    Major changes have occurred in the Russian intergovernmental fiscal sphere since Putin's inauguration. The VAT has been assigned completely to the Federal budget while the regional shares of income and profit taxes have been increased (Solanko and Tekoniemi, 2005). The most dramatic changes, however, have occurred in budget revenues from oil and gas, which currently flow almost completely to the Federal budget. Until 2002, 60% of taxes levied on mining operations went to regional budgets and the rest to the Federal budget, but in 2005 only 5% of taxes on oil production and 0% of natural gas production accrued to regional budgets (Kurlyandskaya, 2007). Furthermore, according to Kurlyandskaya (ibid.) the Federal transfers to regional budgets constitute approximately a half of the Federal oil and gas revenues suggesting that this ‘windfall’ money is indeed partly used for inter-regional equalization and stabilization.

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Acknowledgements

We would like to thank the Academy of Finland for research financing and Ilya Trounin, Mika Kortelainen, Mikael Linden, Pekka Ilmakunnas and two anonymous referees for valuable comments.

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Leppänen, S. Inter-regional Insurance and Redistribution – A Non-parametric Application to Russia. Comp Econ Stud 54, 633–660 (2012). https://doi.org/10.1057/ces.2012.16

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Keywords

  • inter-regional insurance
  • Russia
  • fiscal federalism
  • non-parametric analysis

JEL Classifications

  • P35
  • H77
  • C14