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Analysis of the heterogeneity factors and assessment of the structural levels of inflation in Russian regions
https://doi.org/10.32609/0042-8736-2021-9-51-68
Abstract
The article analyzes the factors of deviation of regional rates of price growth from the national average and estimates the structural levels of inflation in Russian regions, which can be achieved if the Bank of Russia maintains inflation at 4%. The assessment of the structural levels of regional inflation was carried out using groupings of regions according to the degree of labor mobility, transport accessibility, sectoral specifics of the economy, the share of social transfers in the population’s income, and the region’s affiliation with the federal district. The greatest significance was shown by such factors of heterogeneity of regional inflation as the volume of lending to individuals, the level of price rigidity, inflationary expectations and the nominal effective exchange rate of the ruble. In addition, for each Russian region, an assessment of labor mobility was given through the Okun coefficient. It is concluded that the Balassa—Samuelson effect in the long-term period is a significant factor in inflation heterogeneity only in regions with high labor mobility. The results of assessing the structural levels of regional inflation can be taken into account in the development of monetary policy and in the implementation of the information policy of the Bank of Russia.
Keywords
structural inflation rates,
Okun’s coefficient,
Balassa—Samuelson effect,
price rigidity,
monetary policy
JEL: Е31, Е37, Е52, Е58
About the Authors
O. N. Semiturkin
Siberian Main Branch of the Bank of Russia
Russian Federation
Russian Federation
Oleg N. Semiturkin
Novosibirsk
A. A. Shevelev
Siberian Main Branch of the Bank of Russia; Institute of Economics and Industrial Engineering, the Siberian Branch of the Russian Academy of Sciences
Russian Federation
Russian Federation
Andrey A. Shevelev
Novosibirsk
M. I. Kvaktun
Siberian Main Branch of the Bank of Russia
Russian Federation
Russian Federation
Maria I. Kvaktun
Novosibirsk
References
1. Bank of Russia (2014). Guidelines for the single state monetary policy in 2015 and for 2016 and 2017.
2. Bank of Russia (2020). Monetary policy report, No. 4.
3. Vakulenko E., Gurvich E. (2015). The relationship of GDP, unemployment rate and employment: In-depth analysis of Okun’s law for Russia. Voprosy Ekonomiki, No. 3, pp. 5—27. (In Russian). https://doi.org/10.32609/0042-8736-2015-3-5-27
4. Deryugina E., Karlova N., Ponomarenko A., Tsvetkova A. (2018). The role of regional and sectoral factors in Russian inflation developments. Bank of Russia Working Paper Series, No. 36, pp. 1—33. (In Russian).
5. Zhemkov M. I. (2019). Regional effects of inflation targeting in Russia: Factors of heterogeneity and structural inflation rates. Voprosy Ekonomiki, No. 9, pp. 70—89. (In Russian). https://doi.org/10.32609/00428736-2019-9-70-89
6. Perevyshin Y. N., Sinelnikov-Murylev S. G., Trunin P. V. (2017). Determinants of price differentiation across Russian regions. HSE Economic Journal, No. 3, pp. 361—384. (In Russian).
7. Sinelnikov-Murylev S. G., Perevyshin Y. N., Trunin P. V. (2020). Inflation differences in the Russian regions: An empirical analysis. Economy of Region, Vol. 16, No. 2, pp. 479—493. (In Russian). http://doi.org/10.17059/2020-2-11
8. Alberola E., Tyrvainen T. (1998). Is there scope for inflation differentials in EMU? An empirical evaluation of the Balassa-Samuelson model in EMU countries. Banco de Espana Working Paper, No. 9823.
9. Beck G., Hubrich K., Marcellino M. (2009). Regional inflation dynamics within and across euro area countries and a comparison with the United States. Economic Policy, Vol. 24, No. 57, pp. 141—184. https://doi.org/10.1111/j.1468-0327.2009.00214.x
10. Canzoneri M., Cumby R., Diba B., Eudey G. (2002). Productivity trends in Europe: Implications for real exchange rates, real interest rates, and inflation. Review of International Economics, Vol. 10, No. 3, pp. 497—516. https://doi.org/10.1111/1467-9396.00346
11. Cecchetti S. G., Mark N. C., Sonora R. J. (2002). Price level convergence among United States cities. International Economic Review, Vol. 43, No. 4, pp. 1081—1099. https://doi.org/10.1111/1468-2354.t01-1-00049
12. Duarte M., Wolman A.L. (2003). Fiscal policy and regional inflation in a currency union. FRB of Richmond Working Paper, No. 03-11. https://doi.org/10.2139/ssrn.2184493
13. Galí J. (2008). Monetary policy, inflation, and the business cycle. An introduction to the new Keynesian framework and its applications. Princeton University Press.
14. Hofmann B., Remsperger H. (2005). Inflation differentials among the Euro area countries: Potential causes and consequences. Journal of Asian Economics, Vol. 16, No. 3, pp. 403—419. https://doi.org/10.1016/j.asieco.2005.04.009
15. Honohan P., Lane P. (2003). Divergent inflation rates in EMU. Economic Policy, Vol. 18, No. 37, pp. 357—394. https://doi.org/10.1111/1468-0327.00110_1
16. Konopczak K. (2013). The Balassa—Samuelson effect and the channels of its absorption in the Central and Eastern European Countries. National Bank of Poland Working Paper, No. 163. https://doi.org/10.2139/ssrn.2361415
17. Lagoa S. (2017). Determinants of inflation differentials in the euro area. Is the New Keynesian Phillips Curve enough? Journal of Applied Economics, Vol. 20, No. 1, pp. 75—103. https://doi.org/10.1016/S1514-0326(17)30004-1
18. Marques H., Pino G., Horrillo J. (2014). Regional inflation dynamics using space—time models. Empirical Economics, Vol. 47, No. 3, pp. 1147—1172. https://doi.org/10.1007/s00181-013-0763-9
19. Mihaljek D., Klau M. (2004). The Balassa—Samuelson effect in Central Europe: A disaggregated analysis. Comparative Economic Studies, No. 46, pp. 63—94. https://doi.org/10.1057/palgrave.ces.8100041
20. Nagayasu J. (2016). Regional inflation, spatial locations and the Balassa—Samuelson effect: Evidence from Japan. Urban Studies, Vol. 54, No. 6, pp. 1482—1499. https://doi.org/10.1177/0042098016629915
21. Okun A. M. (1962). Potential GNP: Its measurement and significance. Proceedings of the Business and Economic Statistics Section of the American Statistical Association.
22. Parsley D., Wei S. (1996). Convergence to the law of one price without trade barriers or currency fluctuations. Quarterly Journal of Economics, Vol. 111, No. 4, pp. 1211—1236. https://doi.org/10.3386/w5654
23. Pesaran М. Н., Shin Y., Smith R. Р. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, Vol. 94, No. 446, рр. 621—634. https://doi.org/10.1080/01621459.1999.10474156
24. Ridhwan M. M. (2016). Inflation differentials, determinants, and convergence: Evidence from Indonesia subnational data. Journal of Developing Areas, Vol. 50, No. 5, pp. 257—276. https://doi.org/10.1353/jda.2016.0030
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For citations:
Semiturkin O.N., Shevelev A.A., Kvaktun M.I. Analysis of the heterogeneity factors and assessment of the structural levels of inflation in Russian regions. Voprosy Ekonomiki. 2021;(9):51-68. (In Russ.) https://doi.org/10.32609/0042-8736-2021-9-51-68
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