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Published online by Cambridge University Press:  02 May 2019

Jarko Fidrmuc*
Zeppelin University, Mendel University Brno, Vilnius University
Moritz Degler
Oxford Economics Ltd., Zeppelin University Friedrichshafen
Address correspondence to: Jarko Fidrmuc, Department of Economics, Zeppelin University, Am Seemooser Horn 20, 88045 Friedrichshafen, Germany. e-mails:; Phone: +49 7541 6009-1241. Fax: +49 7541 6009-1499.


We present an analysis of interregional consumption risk sharing in Russia between 1999 and 2009 using novel estimation methods. In addition to standard fixed-effects panel estimations, we use system and difference GMM estimators to reflect time dynamic properties and possible endogeneity between output and consumption. Furthermore, we apply spatial models that control for spatial dependence across regions. The results show that regional consumption deviations from the national average are highly persistent in time and space. Nevertheless, the regional consumption risk sharing in Russia is relatively high with 70%–90% of idiosyncratic risk being smoothed. Finally, fiscal policy and the degree of financial development appear to contribute to the consumption smoothing.

© Cambridge University Press 2019

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We benefited from comments and suggestions made by Lidwina Gundacker, Martin Siddiqui, Benedikt Fritz, James Watson, Riikka Nuutilainen, Juha Junttila, Igor Bagaev, Betina Bökemeier Richard Frensch, Matthias Firgo, Gunther Maier, Mexin Guo, Makram El-Shagi, and other participants of the Meeting of the German Association for East European Studies in Berlin, October 2016, and 3rd HenU/INFER Workshop on Applied Macroeconomics in Kaifeng, March 2017. Jarko Fidrmuc appreciates also the hospitality of Leibniz Institute for East and Southeast European Studies (IOS) in Regensburg, which allowed him to work on this project. This research was funded by the European Social Fund No. 09.3.3-LMT-K-712-01-0123. The standard disclaimer applies.


Ahrend, R. (2012) Understanding Russian regions’ economic performance during periods of decline and growth - An extreme bound analysis approach. Economic Systems 36(3), 426443.CrossRefGoogle Scholar
Arbia, G. (2014) A Primer for Spatial Econometrics. With Applications in R. London: Palgrave Macmillan.Google Scholar
Arellano, M. and Bond, S. (1991) Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies 58(2), 277297.CrossRefGoogle Scholar
Arellano, M. and Bover, O. (1995) Another look at the instrumental variable estimation of errorcomponents models. Journal of Econometrics 68(1), 2951.CrossRefGoogle Scholar
Artis, M. J. and Hoffmann, M. (2006) The Home Bias and Capital Income Flows Between Countries and Regions. Discussion paper no. 5691, CEPR, London.CrossRefGoogle Scholar
Artis, M. J. and Hoffmann, M. (2008) Financial globalization, international business cycles and consumption risk sharing. Scandinavian Journal of Economics 110(3), 447471.CrossRefGoogle Scholar
Asdrubali, P., Sorensen, B. E. and Yosha, O. (1996) Channels of interstate risk sharing: United States 1963-1990. Quarterly Journal of Economics 111(4), 10811110.CrossRefGoogle Scholar
Backus, D. K., Kehoe, P. J. and Kydland, F. E. (1992) International real business cycles. Journal of Political Economy 100(4), 745775.CrossRefGoogle Scholar
Bai, Y. and Zhang, J. (2012) Financial integration and international risk sharing. Journal of International Economics 86(1), 1732.CrossRefGoogle Scholar
Becker, S. O. and Hoffmann, M. (2006) Intra- and international risk-sharing in the short run and the long run. European Economic Review 50(3), 777806.CrossRefGoogle Scholar
Belotti, F., Hughes, G. and Mortari, A. P. (2016) Spatial Panel Data Models Using Stata. Research paper no. 373, CEIS Tor Vergata, Rome.CrossRefGoogle Scholar
Berglof, E. and Lehmann, A. (2009) Sustaining Russia’s growth: The role of financial reform. Journal of Comparative Economics 37(2), 198206.CrossRefGoogle Scholar
Berkowitz, D. and DeJong, D. N. (2011) Growth in post-Soviet Russia: A tale of two transitions. Journal of Economic Behavior and Organization 79(1), 133143.CrossRefGoogle Scholar
Blundell, R. and Bond, S. (1998) Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics 87(1), 115143.CrossRefGoogle Scholar
Boyreau-Debray, G. and Wei, S. J. (2005) Pitfalls of a State-Dominated Financial System: The Case of China. Working paper no. 11214, NBER, Cambridge, MA.CrossRefGoogle Scholar
Crucini, M. J. (1999) On international and national dimensions of risk sharing. Review of Economics and Statistics 81(1), 7384.CrossRefGoogle Scholar
Demyanyk, Y., Ostergaard, C. and Sørensen, B. E. (2008) Risk Sharing and Portfolio Allocation in EMU. Economic papers no. 334, European Commission, Brussels.CrossRefGoogle Scholar
Desbonnet, A. and Kankanamge, S. (2017) Public debt and aggregate risk. Macroeconomic Dynamics 21(8), 19962032.CrossRefGoogle Scholar
Dreger, C., Fidrmuc, J., Kholodilin, K. A. and Ulbricht, D. (2016) Between the hammer and the anvil: The impact of economic sanctions and oil prices on Russia’s ruble. Journal of Comparative Economics 44(2), 295308.CrossRefGoogle Scholar
Du, J., He, Q. and Rui, O. M. (2011) Channels of interprovincial risk sharing in China. Journal of Comparative Economics 39(3), 383405.CrossRefGoogle Scholar
Elder, J. (2018) Oil price volatility: Industrial production and special aggregates. Macroeconomic Dynamics 22(3), 640653.CrossRefGoogle Scholar
Eller, M., Fidrmuc, J. and Fungáčová, Z. (2016) Fiscal policy and regional output volatility: Evidence from Russia. Regional Studies 50(11), 18491862.CrossRefGoogle Scholar
Fafchamps, M. and Gubert, F. (2007) The formation of risk sharing networks. Journal of Development Economics 83(2), 326350.CrossRefGoogle Scholar
Faia, E. (2018) A note on credit risk transfer and the macroeconomy. Macroeconomic Dynamics 22(4), 10961111.CrossRefGoogle Scholar
Fidrmuc, J. and Degler, M. (2018) Temporal and Spatial Dependence of Inter-regional Risk Sharing: Evidence from Russia. Leibnitz Institute for East and Southeast European Studies, Regensburg, Working paper no. 373.Google Scholar
Fidrmuc, J., Fungáčová, Z. and Weill, L. (2015) Does bank liquidity creation contribute to economic growth? Evidence from Russia. Open Economies Review 26(3), 479496.CrossRefGoogle Scholar
Fidrmuc, J., Kapounek, S. and Kuèerová, Z. (2017) Lending conditions in EU: The role of credit demand and supply. Economic Modelling 67(C), 285293.Google Scholar
Friedman, M. (1957) A Theory of the Consumption Function. Princeton: Princeton University Press.CrossRefGoogle Scholar
Guo, M. and Puyun, J. H. (2017) Intra-regional vs inter-regional risk sharing among EU and Non-EU countries. Paper presented at 3rd HenU/INFER Workshop on Applied Macroeconomics in Kaifeng.Google Scholar
Han, C. and Phillips, P. C. B. (2010) GMM estimation for dynamic panels with fixed effects and strong instruments at unity. Econometric Theory 26(1), 119151.CrossRefGoogle Scholar
Ho, C.-Y., Ho, W.-Y. A. and Li, D. (2015) Intranational risk sharing and its determinants. Journal of International Money and Finance 51(C), 89113.CrossRefGoogle Scholar
Jeanty, P.W. (2010a) Spmlreg: Stata Module to Estimate the Spatial Lag, the Spatial Error, the Spatial Durbin, and the General Spatial Models. Statistical Software Components no S457135, Boston College Department of Economics.Google Scholar
Jeanty, P. W. (2010b) Spwmatrix: Stata Module to Generate, Import, and Export Spatial Weights. Statistical Software Components no S457111, Boston College Department of Economics.Google Scholar
Kalemli-Ozcan, S., Luttini, E. and Sørensen, B. E. (2014) Debt crises and risk-sharing: The role of markets versus sovereigns. Scandinavian Journal of Economics 116(1), 253276.CrossRefGoogle Scholar
Kalemli-Ozcan, S., Sorensen, B. E. and Yosha, O. (2004) Asymmetric Shocks and Risk Sharing in a Monetary Union: Updated Evidence and Policy Implications for Europe. Discussion paper no. 4463, CEPR, London.Google Scholar
Kancs, D’A., Di Comite, F., and Diukanova, O. (2016) RHOMOLO odel manual: A dynamic spatial general equilibrium model for EU regions and sectors. Technical report 96776, Joint Research Centre, European Commission, Brussels.Google Scholar
Kapounek, S. (2017) The impact of institutional quality on bank lending activity: Evidence from Bayesian model averaging. Czech Journal of Economics and Finance 67(5), 372395.Google Scholar
Kolomak, E. A. (2011) Spatial externalities as a source of economic growth. Regional Research of Russia 1(2), 114119.CrossRefGoogle Scholar
Kose, M. A., Prasad, E. S. and Terrones, M. E. (2009) Does financial globalization promote risk sharing? Journal of Development Economics 89(2), 258270.CrossRefGoogle Scholar
Kukenova, M. and Monteiro, J.-A. (2009) Spatial Dynamic Panel Model and System GMM: A Monte Carlo Investigation. Munich Personal RePEc Archive, MPRA paper no. 13405, Munich.CrossRefGoogle Scholar
Letendre, M. and Wagner, J. (2018) Agency costs, risk shocks, and international cycles. Macroeconomic Dynamics 22(5), 11341172.CrossRefGoogle Scholar
Lewis, K. K. (1999) Trying to explain home bias in equities and consumption. Journal of Economic Literature 37(2), 571608.CrossRefGoogle Scholar
Lipiñska, A. and von Thadden, L. (in press) On the effectiveness of fiscal devaluations in a monetary union. Macroeconomic Dynamics. 153. doi:10.1017/S136510051800010XGoogle Scholar
Malik, S. (2015) Financial-integration thresholds for consumption risk-sharing. International Review of Economics and Finance 38(C), 7393.CrossRefGoogle Scholar
Mark, N. C. (1985) Some evidence on the international inequality of real interest rates. Journal of International Money and Finance 4(2), 189208.CrossRefGoogle Scholar
Mélitz, J. (2004) Risk-sharing and EMU. Journal of Common Market Studies 42(4), 815840.CrossRefGoogle Scholar
Notten, G. and de Crombrugghe, D. (2012) Consumption smoothing in Russia. Economics of Transition 20(3), 481519CrossRefGoogle Scholar
Obstfeld, M. and Rogoff, K. (2001) The six major puzzles in international macroeconomics: Is there a common cause? In: Bernanke, B. and Rogoff, K. (eds.), NBER Macroeconomics Annual 2000, Vol. 15, pp. 339412. Cambridge: MIT press.Google Scholar
Ord, K. (1975) Estimation methods for models of spatial interaction. Journal of the American Statistical Association 70(349), 120126.CrossRefGoogle Scholar
Roodman, D. (2009) How to do xtabond2: An introduction to difference and system GMM in Stata. Stata Journal 9(1), 86136.CrossRefGoogle Scholar
Skoufias, E. (2003) Consumption smoothing in Russia: Evidence from the RLMS. Economics of Transition 11(1), 6791.CrossRefGoogle Scholar
Sørensen, B. E., Wu, Y.-T., Yosha, O. and Zhu, Y. (2007) Home bias and international risk sharing: Twin puzzles separated at birth. Journal of International Money and Finance 26(4), 587605.CrossRefGoogle Scholar
Sørensen, B. E. and Yosha, O. (1998) International risk sharing and European monetary unification. Journal of International Economics 45(2), 211238.CrossRefGoogle Scholar
Stockman, A. C. and Tesar, L. L. (1995) Tastes and technology in a two-country model of the business cycle: Explaining international comovements. American Economic Review 85(1), 168185.Google Scholar
Tesar, L. L. and Werner, I. M. (1995) Home bias and high turnover. Journal of International Money and Finance 14(4), 467492.CrossRefGoogle Scholar
Xu, X. (2008) Consumption risk-sharing in China. Economica 75(298), 326341.CrossRefGoogle Scholar
Yu, J., de Jong, R. and Lee, L. F. (2008) Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both N and T are large. Journal of Econometrics 146(1), 118134.CrossRefGoogle Scholar
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