Causality relationship between foreign direct investments and economic improvement for developing economies: Russia case study

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1. Introduction Foreign direct investment (FDI) can play a significant role in economic development, particularly for developing economies. In the case of Russia, FDI has been seen as an important source of capital inflows and a means to improve the country’s economic conditions. According to some economists, FDI contributes to the increase in the productive capacity of the economy and can also serve as a vector for the dissemination of technologies or knowledge [1, 2]. There is a causal relationship between foreign direct investment and economic improvement in Russia. FDI can bring in new technology, increase competition, create employment opportunities, and increase productivity in the host country. Russia has been successful in attracting FDI in recent years, and this has contributed to the growth of various sectors of the economy, such as oil and gas, metals, and telecommunications. This brings up to date the debate on the effect of FDI on the economic growth of developing countries [3]. However, the relationship between FDI and economic development in Russia is not without challenges. One of the main challenges is the country’s dependence on natural resources, particularly oil and gas. While FDI in the natural resource sector has contributed to the country’s economic growth, it has also made the economy vulnerable to fluctuations in commodity prices. Some authors argue that FDI, i.e., investments carried out abroad by transnational or multinational companies with a view to acquire assets and manage production and marketing activities in host countries, positively affect economic growth [4]. Still others demonstrate that FDI only stimulates economic growth subject to the fulfillment of certain conditions, namely human capital, trade openness and good institutional governance [3, 5]. The objective of this article is therefore on the one hand to evaluate the relationship between FDI and economic growth in Russia, and on the other hand to highlight proposals from which the policies of economic improvement can rely on. The rest of the article is presented as follows: related works, material and methods, results and conclusion. 2. Related works For years, extensive study has been conducted to determine the relationship between FDI entry into host nations and economic progress. The causal relationship between GDP growth and FDI, in theory, can go either way. One the one hand, FDI inflows can boost growth for the host countries through the expansion of the capital stock, the creation of new jobs, and the transfer of technology [6]. On the other hand, expanding economies draw new investment possibilities, including FDI inflows, to the host nation [7]. Despite the fact that more studies support the positive, a smaller number of studies indicated that domestic investment competition has a detrimental impact on economic growth. Co-integration and panel Granger causality analyses in panel data was used to examine the connection between foreign direct investment and economic growth in 65 countries [8]. The findings reveal a discrepancy in the cointegration of the panel study’s relationship. The findings also point to a one-way causal relationship between FDI and GDP, which may be useful in prioritizing the allocation of resources across sectors to encourage FDI. The paper [9] explores the causal relationship between foreign direct investment and exports using annual data for 19 emerging economies in Asia from 1980 to 2015. China, Republic of Korea, Indonesia, Singapore, and Turkey have causality from export to FDI at 1% significant level, according to the first part of Granger Causality results. At a 5% level of significance, Nepal, Sri Lanka, the Philippines, Thailand, and Oman have a causal relationship between export and FDI. At a 10% level of significance, it is plausible to conclude that Bangladesh and India have a causal relationship between export and foreign direct investment, even though the likelihood value is extremely close to the 5% significance threshold. Sri Lanka, Indonesia, and Turkey have a causality from FDI to export at a 1% significant level, while India, Nepal, and Thailand have a causality from FDI to export at a 5% significance level, according to the second portion of the Granger causality association tests. Eventually, at a 10% level of significance, Hong Kong, Bangladesh, Singapore, Bahrain, Oman, and Saudi Arabia were determined to have a causal association between FDI and export. In a nutshell, the export-led growth hypothesis holds true for Asian countries’ growing economies. Granger causality test based on the vector error correction model was used to investigate the causal relationship between the two variables throughout the time span 1980-2014 [10]. The empirical findings offer compelling evidence for FDI’s causal role in Cambodia’s economic growth (GDP). The study does not, however, support a direct causal relationship between GDP and FDI. The growth impact of FDI is thus properly supported in Cambodia, it can be inferred. The study [11] looks at the connection between trade, FDI, and economic growth in Greece from 1960 to 2002. There may be an equilibrium relationship over the long term, according to the cointegration study. The Granger causality test results demonstrated that there is a causal relationship between the variables under investigation. Under the opendoor policy, economic growth, trade, and Investment seem to be mutually reinforcing. The authors of [12] determine whether there is a causal link between foreign direct investments and economic growth for developing countries. The 30 developing nations with the highest GDP growth rates in 2016 are taken into account in this context. Additionally, Dumitrescu Hurlin panel causality analysis is used to examine annual data for these nations for the years 1991 through 2015. It has been determined that foreign direct investments and economic growth are related causally. In other words, it is acknowledged that FDI plays a significant role in driving economic expansion. This instance demonstrates how a country’s economy might grow by luring foreign investors to make direct investments there. In the paper [13] the relationship between foreign direct investment (FDI) and the expansion of 117 nations throughout seven regions are investigated. The Granger causality approach and panel VAR/block exogeneity test were used to conduct predictive analysis among the panel series on a more recent panel dataset covering the years 2010-2020. In order to explore the interaction effects of the variables, which have not yet gained widespread acceptance in the field being examined, wavelet coherence techniques were also modified. The empirical findings show that FDI and economic growth both globally and in the Asian area are causally related in both directions. Contrarily, in the American region, the causality is unidirectional. For the majority of developed and emerging economies in the regional analysis, the results imply no causality. The causal association between foreign direct investments and economic development in Togo from 1991 to 2009 was studied in [14]. They tested and established the causal link between FDI and Togo’s economic growth using the Granger-causality. The study discovered a one-way link between FDI and GDP using time series data. It is possible to conclude that FDI causes GDP. The relationship between foreign direct investment (FDI) and economic growth in the nations of the Organization of Eastern Caribbean States (OECS) is experimentally examined in [15]. The research estimates a dynamic panel growth model using the generalized method of moments employing panel data consisting of annual data covering the period 1988-2013 from 34 countries, including the six OECS economies. The empirical findings indicate that while FDI has a beneficial impact on growth, on its own, it has very little of an effect. Its considerable impact is therefore primarily indirect. Moreover, infrastructure improvement and FDI interact favorably to boost economic growth, whereas FDI discourages local investment. According to the analysis of previous literature, no study on Russia has yet been done on the causal relationship between foreign direct investment and economic improvement for developing economies. 3. Materials and methods 3.1. Data Description The analysis makes use of Russian economic annual data from 1990 through 2020 from The World Development Indicator (WDI) provided by the World Bank. The level of GDP, inflows of foreign direct investment, population growth, inflation, government consumption, financial development, and investment are included in the considered statistics (see tables 1, 2). Table 1 Definition of variables Variables Definition GDPG The growth rate of the GDP FDI Inflow of Foreign Direct Investment in percentage of GDP GGFCE General Government Final Consumption Expenditures INF The Consumer Price Index POPG The growth rate of the population DCPS Domestique Credit to Private Sector Table 2 Descriptive and summary statistics Variables Mean Standard Deviation Minimum Maximum GDPG 0.736661 6.251199 -14.53107 10.00007 FDI 23.21095 1.494542 20.35158 25.69407 GGFCE 18.06510 1.715673 13.85744 21.067110 INF 109.4699 302.7925 2.878297 1481.166 POPG -0.079966 0.228914 -0.460024 0.286681 DCPS 28.98768 19.67446 3.077914 59.96833 Themostcommonlyusedindicatorsforgaugingeconomicsuccessofanation are its GDP and GDP per capita, which can be measured in terms of level or growth. Many metrics, including commonly used income statistics like GDP or GDP per capita, can be used to assess the economic success of a nation or region (measured either in level or growth terms). These metrics do have certain drawbacks, most notably the fact that they tend to overestimate national wealth and do not take into consideration overall welfare. Despite these problems, we employ per capita real GDP growth as the yardstick for measuring economic activity. 3.2. Methodology We conducted an empirical research using cointegration and causal analysis to determine the relationship between foreign direct investments and economic growth in Russia. This method enables us to assess the impact of foreign direct investment on economic development over the long term as well as the short term. In a single equation framework, auto regressive differentiated lag (ARDL) models are frequently used to investigate dynamic relationships with time series data. The differentiated lags element of the model allows the dependent variable’s present value to depend on both its own historical realizations, or the autoregressive part, and the present and past values of other explanatory variables. Variables might be either stationary, non-stationary, or both. The ARDL model can be used to distinguish between long-term and short-term impacts, as well as to test for cointegration or, more broadly, the presence of a long-term relationship, in its portrayal of Error Correction (EC) term between the relevant variables. There will be answers to frequently asked questions and a step-by-step guide for doing the boundaries test to determine whether a long-term relationship exists [16]. This test is implemented as a post-estimate command that displays recently determined critical values for finite samples and approximative p-values. To achieve our goals, we used a time series autoregressive distributed lag model (ARDL) as proposed by Pesaran, Shin, and Smith in their papers to estimate economic growth using a linear function that controls the interest variable, which is foreign direct investment. 3.2.1. Unit root tests It is necessary to identify the order of integration of variables in any econometrics research. Verifying that the variables in the regression are either integrated of order zero I(0) or, at most, integrated of order one I(1) is essential for estimating an ARDL model. Each cross sectional series unit root test has an Augmented Dickey Fuller (ADF) regression as its default baseline:

About the authors

Kouame A. Brou

Peoples’ Friendship University of Russia (RUDN University)

Email: broureino@gmail.com
ORCID iD: 0000-0003-1996-577X

PhD student of Department Information Technology

6, Miklukho-Maklaya St., Moscow, 117198, Russian Federation

Ivan V. Smirnov

Peoples’ Friendship University of Russia (RUDN University); Federal Research Center “Computer Science and Control” of RAS

Author for correspondence.
Email: ivs@isa.ru
ORCID iD: 0000-0003-4490-2017

Candidate of Physical and Mathematical Sciences, Assistant Professor of Department Information technology of Peoples’ Friendship University of Russia (RUDN University); Head of department of Federal Research Center “Computer Science and Control” Russian Academy of Sciences

6, Miklukho-Maklaya St., Moscow, 117198, Russian Federation; 44-2, Vavilova St., Moscow, 119333, Russian Federation

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