Money supply impact on investment and GDP: statistical analysis
Abstract
The question of how the changes in money supply influence investment and GDP have been studied intensively in recent history. However, not all aspects of this impact are sufficiently researched. In particular, the “new normality” (that has evolved recently) limits the use of well-known classical concepts and models in monetary policy, especially for emerging economies to which Ukraine belongs. Thus, the subject of this study was to assess the relationship between monetary aggregates, investment, and GDP by the world economic data analysis using mathematical statistics.
As the information base for the study, the World Bank official statistics were taken (including broad money, gross capital formation, and GDP). More than 71% of all investigated countries showed a significant correlation between M3 and gross investment. The issue of how the strength of this relationship depends on the level of socio-economic development was investigated. Classification of countries was carried out using the “nearest neighbors” method in a two-dimensional feature space, namely, per capita income and correlation tightness. The analysis showed that 79% of all countries fall into the class with a proven high correlation. Moreover, their level of wealth and development was irrelevant.
A cluster analysis of countries was fulfilled in the chosen feature space using the “mean shift” method. With the help of this method, all countries have been distributed into five clusters with different socio-economic conditions and an accuracy of 91%. Among them, there was a group of countries highly sensitive to change in monetization, up to extremely negative economic impacts.
The study helped to conclude that, regardless of economic development, GDP benefits from an increase in the money supply. Although this factor is considered necessary, it is nevertheless not sufficient for economic growth, especially in the time of the fourth industrial revolution, when the government has to play a more active and complex role in accelerating national technological development.
Keywords
Full Text:

References
Damiano, Sandri, Itai Agur, Damien Capelle, Giovanni Dell'Ariccia (2022). Monetary Finance: Do Not Touch, or Handle with Care? International Monetary Fund. Retrieved from https://www.imf.org/en/Publications/Departmental-Papers-Policy-Papers/Issues/2022/01/11/Monetary-Finance-Do-Not-Touch-or-Handle-with-Care-464862
Vishnevsky, V. (2022). Digital technologies and problems of industrial development. Economics of Ukraine, 1, pp. 47-66. DOI: https://doi.org/10.15407/economyukr.2022.01.047 [in Ukrainian].
Adam, K., & Weber, H. (2019). Optimal Trend Inflation. American Economic Review, 109 (2), pp. 702-737. DOI: http://dx.doi.org/10.1257/aer.20171066
Phillips, A.W. (1958). The Relation Between Unemployment and the Rate of Change of Money Wage Rates in the United Kingdom, 1861-1957. Economica. pp. 283-299.
Kaldor, N. (1971). Conflicts in National Economic Objectives. Economic Journal, 81 (321), pp. 1-16.
Inflation in the US accelerated to a record since 1982 (2021, December 10). Economic truth. [in Russian].
Zaiko, N. (2015). Quantitative Easing in the United States: Implications for Developing Countries. Regional problems of economic transformation, 6 (56), рр. 96-100 [in Russian].
Krugman, P. (2010). Why Is Deflation Bad? The New York Times. Retrieved from https://krugman.blogs.nytimes.com/2010/08/02/why-is-deflation-bad/
Stiglitz, J. (2008). Inflation Targeting: A Test of Reality. News №. 88. Retrieved from https://elitetrader.ru/index.php?newsid=11988 [in Russian].
Perevyshina, E.A. (2017). Influence of inflation on the pace of economic growth. Finance and credit, 9, pp. 18-30 [in Russian].
Kartaev, F. (2017). Is inflation targeting good for economic growth? Voprosy Ekonomiki, 2, pp. 62-74. DOI: https://doi.org/10.32609/0042-8736-2017-2-62-74 [in Russian].
Stiglitz, J. (2008, May 6)). The Failure of Inflation Targeting. Project Syndicate. Retrieved from https://www.project-syndicate.org/commentary/the-failure-of-inflation-targeting
Blinov, S. (2015). Real money and economic growth. Munich Personal RePEc Archive. Retrieved from https://mpra.ub.uni-muenchen.de/id/eprint/67256 [in Russian].
National Bank of Ukraine. Retrieved from https://bank.gov.ua.
Price index for construction works. Ministry of Finance of Ukraine. Retrieved from https://index.minfin.com.ua/economy/index/buildprice/
Pshinko, A., Myamlin, V., & Myamlin, S. (2012). Influence of the velocity of circulation of the money supply on the efficiency of the national economy. Science and progress of transport. Bulletin of the Dnepropetrovsk National University of Railway Transport, 42, pp. 300-311 [in Russian].
Fumio Hayashi (2001). The 1990s in Japan: A Lost Decade. The University of Tokyo. DOI: https://doi.org/10.1006/redy.2001.0149.
China's Potential Loss From NPLs Estima-ted At $1 Trillion (2016). RBC. Retrieved from https://www.rbc.ru/finances/06/05/2016/572c79239a7947861367effd
Kartaev, F. (2019). How inflation targeting influences economic growth. Ekons. Retrieved from https://econs.online/articles/opinions/kak-inflyatsionnoe-targetirovanie-vliyaet-na-rost/ [in Russian].
Kartaev, F. (2018). Assessment of the impact of monetary policy on economic growth for various groups of countries. Finance: theory and practice, 22 (1). pp. 50-63. DOI: https://doi.org/10.26794/2587-5671-2018-22-1-50-63 [in Russian].
Klochkova, O. (2017). Modeling the impact of inflation on economic growth for countries with different levels of economic freedom. Economic policy, 12 (5), pp. 22-41.
The World Bank. Retrieved from https://www.worldbank.org
Kelion, L. (2021, February 5). The world is running out of chips. What does the coronavirus have to do with it and what will happen to electronics now? BBC. Retrieved from https://www.bbc.com/russian/news-55950090 [in Russian].
Scikit-learn. Retrieved from https://scikit-learn.org/
Lypnytska, P. InvestM3World. GitHub. Retrieved from https://github.com/Polinden/InvestM3World
All of Statistics: A Concise Course in Statistical Inference. (2004). Springer. New York. P. 434.
Hastie, T. (2017). The Elements of Statistical Learning. Springer. New York. P. 745.
Comaniciu, D., Meer, P. (2002). Mean Shift: A Robust Approach Toward Feature Space Analysis. EEE Transactions on Pattern Analysis and Machine Intelligence, 24(5), pp. 603-619. DOI: http://dx.doi.org/10.1109/34.1000236
DOI: https://doi.org/10.15407/econindustry2022.01.089
Refbacks
- There are currently no refbacks.








