S. V. Arzhenovskiy, T. G. Sinyavskaya, V. M. Nikoghosyan. Assessment of the Climate Impact on the Economic Variables of Monetary Policy: Regional Approach

UDК 331.104.22

doi: 10.15507/2413-1407.122.031.202301.070-086

Abstract

Introduction. The relevance of quantitative analysis of the impact of climate variables on macroeconomic indicators of monetary policy according to Russian data in the regional aspect is due to the absence of such research. The purpose of the article is to perform a quantitative assessment of the climate change impact on key macroeconomic variables of monetary policy on panel data by Russian regions.

Materials and Methods. Russian regions were the subject of the study. For calculations, the authors have formed the information base for 79 regions of the Russian Federation from 2000 to 2020 according to Rosstat. The applied methodology is based on the author’s approach, combining the use of factor analysis by region at fixed year and econometric modeling using integral factors obtained at the previous stage on the panel data by region. Econometric analysis was performed using a generalized method of moments and a two-stage systematic generalized method of moments.

Results. The significant impact of climate change on key macroeconomic variables controlled in the development and implementation of monetary policy measures – gross regional product and consumer price index – has been identified empirically. The research was based on econometric modeling.

Discussion and Conclusion. Objective climate change taking place in the Russian regions may adversely affect the economic situation, which requires intensification of implementation and development of measures aimed at improving the environmental situation: reduction of CO2 emissions, development and use of forest-saving technologies, etc. It is proposed to consider the climate situation in the implementation of monetary policy. The results of the research will be useful both in the development and implementation of regional policy, and for specialists, civil servants who plan to improve the territorial structure of the economic space of Russia in the long term.

Keywords: climate change, gross regional product, consumer price index, monetary policy, factor analysis, systemic generalized method of moments, panel data, Russian regions

Conflict of interests. The authors declare that there is no conflict of interest. The paper expresses solely the views of the authors, which may not coincide with the official position of the Bank of Russia. The Bank of Russia is not responsible for the content of this work.

For citation: Arzhenovskiy S.V., Sinyavskaya T.G., Nikoghosyan V.M. Assessment of the Climate Impact on the Economic Variables of Monetary Policy: Regional Approach. Russian Journal of Regional Studies. 2023;31(1):70–86. doi: https://doi.org/10.15507/2413-1407.122.031.202301.070-086

REFERENCES

1. Pretis F. Exogeneity in Climate Econometrics. Energy Economics. 2021;96. doi: https://doi.org/10.1016/j.eneco.2021.105122

2. Kolstad C.D., Moore F.C. Estimating the Economic Impacts of Climate Change Using Weather Observations. Review of Environmental Economics and Policy. 2020;14(1). doi: https://doi.org/10.1093/reep/rez024

3. Castle J.L., Hendry D.F. Climate Econometrics: An Overview. Foundations and Trends in Econometrics. 2020;10(3-4):145–322. doi: https://doi.org/10.1561/0800000037

4. Golub A., Lugovoy O., Potashnikov V. Quantifying Barriers to Decarbonization of the Russian Economy: Real Options Analysis of Investment Risks in Low-Carbon Technologies. Climate Policy. 2019;19(6):716–724. doi: https://doi.org/10.1080/14693062.2019.1570064

5. Zamolodchikov D.G., Grabovskii V.I., Korovin G.N., et al. Carbon Budget of Managed Forests in the Russian Federation in 1990–2050: Post-Evaluation and Forecasting. Russian Meteorology and Hydrology. 2013;38(10):701–714. doi: https://doi.org/10.3103/S1068373913100087

6. Mukherjee K., Ouattara B. Climate and Monetary Policy: Do Temperature Shocks Lead to Inflationary Pressures. Climatic Change. 2021;167(3). doi: https://doi.org/10.1007/s10584-021-03149-2

7. Beirne J., Dafermos Y., Kriwoluzky A., Renzhi N., Volz U., Wittich J. The Effects of Natural Disasters on Price Stability in the Euro Area. Berlin: German Institute for Economic Research; 2021. Available at: https://www.diw.de/documents/publikationen/73/diw_01.c.829788.de/dp1981.pdf (accessed 25.08.2022).

8. Faccia D., Parker M., Stracca L. Feeling the Heat: Extreme Temperatures and Price Stability. Working paper no. 2626. Frankfurt am Main: European central bank; 2021. Available at: https://www.ecb.europa.eu/pub/pdf/scpwps/ecb.wp2626~e86e2be2b4.en.pdf (accessed 25.08.2022).

9. Acevedo S., Mrkaic M., Novta N., Pugacheva E., Topalova P. The Effects of Weather Shocks on Economic Activity: What are the Channels of Impact? Journal of Macroeconomics. 2020;65. doi: https://doi.org/10.1016/j.jmacro.2020.103207

10. Bandt O., Jacolin L., Lemaire T. Climate Change in Developing Countries: Global Warming Effects, Transmission Channels and Adaptation Policies. Banque de France Working Paper No. 822. 2021. Available at: https://publications.banque-france.fr/sites/default/files/medias/documents/wp822_0.pdf (accessed 25.08.2022).

11. Kahn M.E., Mohaddes K., Ng R.N.C., Pesaran M.H., Raissi M., Jui-Chung Yang. Long-Term Macroeconomic Effects of Climate Change: A Cross-Country Analysis. NBER Working Paper No. 26167. 2019. doi: https://doi.org/10.3386/w26167

12. Kalkuhl M., Wenz L. The Impact of Climate Conditions on Economic Production. Evidence from a Global Panel of Regions. Journal of Environmental Economics and Management. 2020;103. doi: https://doi.org/10.1016/j.jeem.2020.102360

13. Oganesyan V.V., Sterin A.M., Vorobyova L.N. Potential Damage from Severe and Adverse Weather Events in the Russian Federation: Regional Features. Hydrometeorological Research and Forecasts. 2021;(1):143–156. (In Russ., abstract in Eng.) doi: https://doi.org/10.37162/2618-9631-2021-1-143-156

14. Arzhenovskiy I.V., Dakhin A.V. Cognitive Regionology: The Experience of Modeling Regional Socio-Economic Processes. Regionology. Russian Journal of Regional Studies. 2020;28(3):470–489. (In Russ., abstract in Eng.) doi: https://doi.org/10.15507/2413-1407.112.028.202003.470-489

15. Yakovleva E.N., Yashalova N.N., Vasil’tsov V.S. Climate Security of the Russian Federation: Statistics, Facts, Analysis. Voprosy statistiki. 2020;(2):74–84. (In Russ., abstract in Eng.) doi: https://doi.org/10.34023/2313-6383-2020-27-2-74-84

16. Yakovleva E.N., Yashalova N.N., Ruban D.A., Vasil’tsov V.S. Methodological Approaches to Valuation of Natural-Climatic Risks for the Purposes of Country’s Sustainable Development. Proceedings of the Russian State Hydrometeorological University. 2018;(52):120–137. Available at: https://www.rshu.ru/university/notes/archive/issue52/UZ-52el-120-137.pdf (accessed 25.08.2022). (In Russ., abstract in Eng.)

17. Windmeijer F. A Finite Sample Correction for the Variance of Linear Efficient Two-step GMM Estimators. Journal of Econometrics. 2005;126(1):25–51. doi: https://doi.org/10.1016/j.jeconom.2004.02.005

18. Roodman D. A Note on the Theme of Too Many Instruments. Oxford Bulletin of Economics and Statisitcs. 2009;71(1):135–158. doi: https://doi.org/10.1111/j.1468-0084.2008.00542.x

Submitted 19.09.2022; revised 05.10.2022; accepted 17.10.2022.

Аbout the authors:

Sergey V. Arzhenovskiy, Dr. Sci. (Economics), Professor, Head Economist, Rostov Regional Division of the Southern Main Branch of the Central Bank of the Russian Federation (22a Sokolov ave., Rostov-on-Don 344006, Russian Federation); Department of Statistics, Econometrics and Risk Assessment, Rostov State University of Economics (69 Bolshaya Sadovaya St., Rostov-on-Don 344002, Russian Federation), ORCID: https://orcid.org/0000-0001-8692-7883, Researcher ID: L-2758-2016, Scopus ID: 56685608200, sarzhenov@gmail.com

Tatiana G. Sinyavskaya, Cand. Sci. (Economics), Associate Professor, Department of Statistics, Econometrics and Risk Assessment, Rostov State University of Economics (69 Bolshaya Sadovaya St., Rostov-on-Don 344002, Russian Federation), ORCID: https://orcid.org/0000-0002-4120-9180, Scopus ID: 57210161952, sin-ta@yandex.ru

Vardan M. Nikogosyan, Cand. Sci. (Economics), Associate Professor, Department of Statistics, Econometrics and Risk Assessment, Rostov State University of Economics (69 Bolshaya Sadovaya St., Rostov-on-Don 344002, Russian Federation), ORCID: https://orcid.org/0000-0002-2963-5654, don15@mail.ru

Contribution of the authors:

S. V. Arzhenovskiy ‒ putting forward a scientific problem; formulation of the scientific hypothesis of the study; definition of research methodology; interpretation of the obtained results.

T. G. Sinyavskaya ‒ estimation of models; critical analysis of materials; interpretation of the obtained results.

V. M. Nikoghosyan ‒ collection and systematization of statistical data; estimation of models.

The authors have read and approved the final version of the manuscript.

 

Лицензия Creative Commons
All the materials of the "REGIONOLOGY" journal are available under Creative Commons «Attribution» 4.0