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On the issue of money supply endogeneity in the Russian economy

Vol. 25, Iss. 10, OCTOBER 2019

Received: 23 September 2019

Received in revised form: 7 October 2019

Accepted: 21 October 2019

Available online: 30 October 2019

Subject Heading: FINANCIAL CAPITAL

JEL Classification: E51

Pages: 2266–2280

https://doi.org/10.24891/fc.25.10.2266

Malkina M.Yu. National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation
mmuri@yandex.ru

https://orcid.org/0000-0002-3152-3934

Moiseev I.A. National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation
igorm32014@gmail.com

ORCID id: not available

Subject This article deals with the issues of the endogenous origin of money supply in the modern Russian economy.
Objectives The article aims to substantiate and validate (or disprove) the hypothesis about the endogenous nature of money supply in the Russian economy.
Methods For the study, we used a correlation and regression analysis, the least squares method, Cochrane–Orcutt autoregressive transformation, Granger causality test, and the Engle–Granger approach.
Results The article summarizes theoretical and empirical studies of foreign and Russian authors on the problem of the endogeneity of the money supply. Based on the quarterly data of the Russian economy for 2010–2018, it is revealed that the MIACR rate (Moscow Interbank Actual Credit Rate) and nominal GDP are the cause by Granger for M2, and MIACR rate is the cause by Granger for GDP. The article presents an autoregressive model of money supply dependence on these variables. The model meets all quality criteria. Regression ratios are interpreted as M2 money supply elasticity figures with respect to the factors under study.
Conclusions The conducted research confirms the hypothesis about the endogenous nature of money supply in the Russian economy in the period under review.

Keywords: post-Keynesian economics, monetary policy, correlation and regression analysis, least squares method, autoregressive transformation

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