Foreign Direct Investment and the Profit Rate: Empirical Evidence from the European Union

Abstract

This article aims to explain recent trends of foreign direct investment (FDI) in the developed world, and specifically in the case of the European Union (EU). It includes an empirical analysis of FDI in two distinct EU country groups and finds that the profit rate plays a significant role in determining FDI patterns. It is shown that relatively less developed Eastern EU members have a higher profit rate and thus have established themselves as an attractive FDI destination within the EU. Additional factors that influence FDI are market size, long-term FDI attractiveness, and trade protectionism. Finally, a sectoral analysis of FDI and trade shows that increased FDI in less developed Eastern EU members is mainly of an export-oriented type.

JEL Classification: F14, F15, F21, P16

Keywords

foreign direct investment profit rate European Union Marxist economics

1. Introduction

The assumption of an international equalization of the profit rates is an issue of controversy within the Marxist literature (Ricci 2018). Within a part of the Marxist literature (see among others Emmanuel 1972; Bettelheim 1972; Carchedi 2001), there is belief that on a world scale an international equalization of the rates of profit takes place. However, there seem to be both theoretical and empirical justifications that this is not actually the case. Indeed, the persistent existence of international profit rate differentials, because of the uneven development within the world economy, seems to be one of the main reasons behind international capital movements in the form of foreign direct investment (FDI).

According to the 2019 UNCTAD World Investment Report, FDI has grown slowly during the last decade, compared to the decades prior to the global economic crisis of 2008. The average annual growth rate of FDI during the 1990s was 21 percent, while from 2008 to 2018 it was only 1 percent. However, FDI demonstrates different dynamics between more and less developed economies. The inward stock of FDI in developed economies has gradually declined (as a share of the world total) since the early 2000s, while at the same time developing and transition economies have seen a stable rise in their share of inward FDI.

This article examines the different dynamics of FDI in two groups of countries within the European Union (EU). Specifically, the first group consists of more developed EU members, namely, Austria, Belgium, France, and Germany, while the second group consists of less developed Eastern EU members, namely, Czechia, Hungary, Poland, and Slovakia, which are known as the Visegrad countries.

Given that FDI is a tool of foreign capital in order to profit by producing on a global scale, a Marxist analysis of the profit rate may help explain recent FDI trends in the developed world, and specifically in the case of the EU. The article’s research question is which are the main motives that drive capital to invest, in the form of FDI, in relatively less developed countries within the developed world, such as the former transition Eastern economies within the EU.

To address this question, we present the basic logic behind Marx’s theory of the profit rate and its effect on FDI, in section 2. Additional motives that may act supplementarily to the profit rate motive are also discussed. In section 3, a macroeconomic empirical analysis is used to investigate if the profit rate can explain basic FDI trends in the case of the examined country groups. Additionally, a sectoral analysis of FDI and trade is performed for the examined Eastern EU members in order to detect additional motives behind FDI in this group. Conclusions and further research suggestions are discussed in the final section.

2. Theoretical Framework

2.1. Profit rate and capital exports

According to Marx (1991) and the classical Marxist literature (Hilferding 1981; Lenin 1999; Bukharin 1929), in its search for a higher rate of profit, capital is exported from advanced capitalist countries to less developed areas of the world, where “the profit rate is generally higher on account of the lower degree of development” (Marx 1991: 345). The higher profit rate being due to either a lower organic composition of capital or an increased rate of surplus value (super-exploitation of the local labor force).

However, capital exports from developed toward less developed countries do not lead to the formation of international production prices, that is, to an international equalization of the profit rates, something that would contrast with Lenin’s “law” of uneven development within the world economy (Lenin 1999: 96).

As Mandel (1976: 84) points out, “it is clear that the obstacles which. . . hinder the equalization of the rate of profit on a national scale, acquire an even greater weight on the international level. . . the greater relative immobility of capital and the prevalent immobility of labor-power” being among the factors that “have rendered possible the differences in the level of profit.” As Mandel (1976: 352) also argues, “the hypothesis of international equalization of the rates of profit. . . is completely contradicted by the law of uneven. . . development,” since such a hypothesis “presupposes perfect international mobility of capital—in effect, the equalization of all economic, social and political conditions propitious to the development of modern capitalism on a world scale.”

The classical Marxist tradition in the beginning of the twentieth century related the export of capital mainly to capital movements from advanced countries toward less developed areas, in accord with colonial or other long-term connections. The main reasons behind these capital movements are the lower costs for labor, raw materials, and land, compared with developed countries. A precondition for investment in less developed countries is the presence of basic industrial infrastructure (Lenin 1999: 71).

However, during most of the post–World War II period, capital is mainly exported to developed countries (Busch 1992: 203; Cantwell 2000: 14). This “paradoxical” phenomenon of cross-investments between developed countries is the main reason behind new research concerning the motives of international capital movements after 1945 (Hymer 1960: 11 ff).

In the post–World War II period, when capital (FDI) is exported to less developed areas, it is sent mainly where lower wages are combined with sufficient levels of productivity, because of local rapid industrial development and a disciplined and hardworking domestic workforce, which are typical characteristics found in countries often mentioned as developing, emerging, or newly industrialized economies (Bina and Yaghmaian 1990: 90). Especially after the 1990s, there seems to be a pattern in which foreign capital moves toward countries that have entered a process of dynamic industrial development (UNCTADstat 2020).

2.2. The Marxian profit rate and the net fixed capital return

Marx’s analysis (Marx 1991) of economic crises focuses on the fall of the profit rate. This fall may stem from either a rising organic composition of capital, which is referred to as the “The Law of the Tendential Fall in the Rate of Profit” (chapter 13 in volume 3 of Capital), or a decrease in the rate of surplus value caused by rising real wages, which is referred to as “Capital Over-Accumulation” (chapter 15 in volume 3 of Capital). The way in which these two main components of the profit rate function can help explain the international movements of capital, in order to either avoid the tendency toward crisis in its home country or simply seek a higher profit rate abroad.

Marxian analysis is based on the concepts of rate of surplus value (the ratio of unpaid labor to necessary labor, in value terms), technical composition of capital (the quantity, in material terms, of means of production per unit of living labor), and value (organic) composition of capital (the ratio of constant to variable capital, in value terms).

The Marxian profit rate (r) can be expressed through the following equation:

r = \frac{s}{C + v} = \frac{s / v}{C / v + 1}

(1)

where s = surplus value, C = constant capital, v = variable capital, s/v = rate of surplus value, and C/v = value (organic) composition of capital.

Given that the technical composition of capital increases with accumulation (investment) and technological development, Marx (1991: 317) argues that, ceteris paribus, the profit rate may fall if the value (organic) composition of capital increases, due to a more rapid increase in the technical composition of capital compared with the labor productivity it creates. This process was referred by Marx as the “Law of the Tendential Fall in the Rate of Profit.”

Furthermore, the profit rate, ceteris paribus, may fall because of a decrease in the rate of surplus value, which may take place because of very low unemployment rates, strong labor unions, and subsequent increases in real wages, which are not compensated by similar increases in productivity. This process was referred by Marx (1991: 360) as a crisis of “Capital Over-Accumulation.”

As equation (1) is expressed in value terms, we can instead use the net fixed capital return (R), which is an appropriate measurable indicator of the Marxian profit rate in money terms (see Duménil and Lévy 1993; Laibman 2010; Economakis, Anastasiadis, and Markaki 2010).

Net fixed capital return (R) is given by the following equation:

R = \frac{Y - L}{K}

(2)

where Y = net product, L = compensation of labor, and K = net fixed capital stock.

The numerator of equation (2) represents the distributional relationship between profits and wages, while the denominator expresses the level of technological development. We can transform equation (2) into the following three equations:

R = \frac{Y - L}{K}

(2)

R = \frac{1 - L / Y}{K / Y}

(2a)

R = \frac{P / Y}{K / Y}

(2b)

and

R = \frac{1 - \frac{L / N}{Y / N}}{\frac{K / N}{Y / N}}

(2c)

where P = profits (= Y – L), and N = total employment (employed labor and self-employed).

Equations (2a)–(2c) are modified versions of the Marxian equation (1). K/Y is the amount of net fixed capital stock required to produce a unit of net product and resembles the Marxian value (organic) composition of capital, L/Y is the labor share in net product, while 1 − $\frac{L}{Y}$ is the share of profits in net product (= P/Y) and is an indication of the rate of surplus value. Y/N can be seen as labor productivity, L/N is the average labor compensation (average wage), while K/N is the net fixed capital stock per employee (capital intensity), which resembles the technical composition of capital, in Marxian terms.

Equation (2c) shows that, ceteris paribus, the profit rate will fall (rise) if the average wage (L/N) increases faster (slower) than productivity (Y/N), or if capital intensity (K/N) rises faster (slower) than productivity (Y/N). However, there is the possibility of a change in both the numerator and denominator of equation (2c) over time, in which case the final movement of the profit rate cannot be predefined, and thus a concrete analysis of the changes in all the above variables is needed in order to determine the profit rate’s overall trend.

We expect, ceteris paribus, FDI to be attracted by countries in which the combination of the above variables acts in a way that tends to increase the profit rate.

2.2.1. Assumptions and research limitations

In this article, we use the net fixed capital return (equation (2)) in order to approximate the Marxian profit rate (equation (1)).

For the estimation of the net fixed capital return, we accept the Marxian thesis (Marx 1990) that, from the standpoint of the capitalist production process, “productive labor” is the labor paid from variable capital. Correspondingly, “production” from the standpoint of the capitalist production process is any process in which labor-power is exchanged for capital.¹

Nonetheless, the data used in order to calculate the net fixed capital return do not refer exclusively to the capitalist sector. They refer to the total economy; that is, they also include the public sector and the self-employed. This is a restriction of our analysis.²

L is the sum of total compensation of employees and of the self-employed. Since data regarding the compensation of the self-employed are not available, we assume that the average compensation of the self-employed is equal to the average wage. We then calculate the total compensation of the self-employed by multiplying the average wage by the number of self-employed. This is a similar approach to the one described by Gollin (2002: 468), according to which the average employee compensation is imputed for those workers who are self-employed. Specifically, total labor compensation (L) using this adjustment is: [(employee compensation / number of employees) * total workforce]. Thus, Y – L does not refer exclusively to profits, but rather to a notion of surplus, in general, for the whole economy.³ In the same sense, K is the net fixed capital stock for the whole economy. This means that, in our case, the net fixed capital return is underestimated, since K also refers to capital in the public sector.⁴

Equation (2) gives an indication of an economy’s capacity to generate surplus for a given net fixed capital stock. However, equation (2) also captures all essential aspects of the (Marxian) profit rate.

2.3. Additional motives of FDI

There are certain additional motives that can affect FDI, depending on the individual motives behind FDI. These motives, however, usually act only supplementarily to the basic profit rate motive. FDI in the sphere of production can be broadly categorized into the following three main types, depending on its relationship with foreign trade.

Market-seeking FDI aims at the production of goods for the domestic market, by substituting the exports of goods with the export of capital. FDI of this type usually follows an initial marketing strategy based on exports. One of the basic motives for foreign capital in order to invest in a specific location is the domestic market size (Lim 2001: 11; Dunning and Lundan 2008: 69).

Another additional motive behind market-seeking FDI, historically, is related to the need of foreign capital to circumvent protectionism of any kind, that is, measures of protectionist policy such as tariffs (Bukharin 1929: 98; Dunning and Lundan 2008: 70–71), and barriers to international trade such as currency devaluation (Busch 1992: 204), which restrict the extra profits obtained by more productive foreign capitals. Thus, foreign capitals that do not wish to see these extra profits diminish may choose to invest in protected domestic markets and produce locally (Groumpos and Economakis 2019: 33).

Ceteris paribus, market-seeking FDI is expected to have a positive impact on the host country’s trade balance, because of a decrease in imports.

Export-oriented FDI aims at the production of goods for the global market. FDI of this type may concern the production of final goods in a specific foreign country or may be associated with a decentralization of production, through the relocation of parts of the production process to various foreign countries. The basic motive for this type of FDI is the increase in the profit rate through the reduction of production costs (Lim 2001: 11; Dunning and Lundan 2008: 72). The most common way foreign capital chooses to reduce production costs is by investing in countries with low wages (and sufficient levels of productivity). This type of FDI is historically often also related to investments by foreign capital of advanced countries in the developing world, in order to gain access to cheap raw materials, in accord with colonial or other long-term connections (Cantwell 2000: 14).

Additionally, protectionism of any kind may also affect export-oriented FDI. A depreciated national currency may have a positive impact on export-oriented FDI as it, ceteris paribus, cheapens exported goods (Groumpos and Economakis 2019: 35). Tariffs on the other hand may have a negative impact on export-oriented FDI (Lim 2001: 13). The main reason is that export-oriented FDI may require substantial flows of intermediate inputs from and to the host country (Giannitsis 1983: 353), which means that tariffs would make final goods more expensive. Therefore, tariffs may have a mixed impact on FDI, depending on the specific type of investment (Groumpos and Economakis 2019: 42).

Ceteris paribus, export-oriented FDI is expected to have a positive impact on the host country’s trade balance, because of an increase in exports.

FDI in noninternationally tradable goods and services aims at the production of goods and services for the domestic market, as in the case of market-seeking FDI. This type of FDI, however, does not aim to substitute the exports of goods with the export of capital. FDI in noninternationally tradable goods and services basically includes investments in the energy, water, construction, transportation, logistics and communication services, and all other domestic service sectors. Thus, FDI in noninternationally tradable goods and services also does not usually promote exports from the host country. The additional motives for this type of FDI are similar to the ones concerning market-seeking FDI—the main difference being, however, that FDI of this type is not related to the host country’s foreign trade protection policy (Kolstad and Villanger 2008: 519; Riedl 2010: 742). The basic motives of this type of FDI are the profit rate and the size of the domestic market.

FDI in noninternationally tradable goods and services does not intend to substitute imports or create exports.

Other conditions that can affect FDI are the host country’s level of political and macroeconomic stability, quality of formal institutions, protection of property rights, and “friendliness” to foreign investment (Dunning and Lundan 2008: 680). The above conditions are mainly related to a low level of—or successfully suppressed—class struggle and a very low chance of nationalization of private corporations, which create conditions for unimpeded capital reproduction and capitalist domination within the host country. All the above can be encapsulated by the host country’s prior ability to attract foreign capital, that is, the host country’s long-term FDI attractiveness (Kudina and Pitelis 2014).

2.3.1. Relationship between FDI and foreign trade

The two types of FDI that relate to the host country’s foreign trade are market-seeking and export-oriented FDI. Table 1 presents the expected impact of these types of FDI on the exports and imports of the sector in which FDI takes place. By observing the changes in the share of sectoral FDI and sectoral exports and imports, we attempt to estimate the main type of FDI in each country of group 2 in section 3.6.

Table 1.

Expected Impact of Market-Seeking and Export-Oriented FDI on Foreign Trade.

	Change in Inward FDI Stock of Sector
	+		−
Type of FDI	Export oriented	Market seeking	Market seeking	Export oriented
Expected change in sector exports	+	+/−	+/−	−
Type of FDI	Export oriented	Market seeking	Market seeking	Export oriented
Expected change in sector imports	+	−	+	−

Note: + = increase; − = reduction; +/− = no specific impact.

2.4. The economic asymmetries of EU integration

The declared goal of the project of European economic integration, which began in 1957, was to remove custom duties in order to foster trade between country members. Since the late 1960s, trade between the then countries of the European Economic Community grew significantly.⁵ In 1993, the “Maastricht Treaty on European Union” was signed, establishing the “single market” and its “four freedoms” of movement of goods, services, people, and money, which brought the total abolition of tariffs and control over capital and labor movements between EU members. In 1999, the Eurozone was formed in order to further deepen European economic integration and, at the same time, create a new international currency that would compete with the dollar (Carchedi 2001: 141). One of the most significant EU enlargements, both economically and politically, took place in 2004, when eight former Eastern Bloc countries joined the EU,⁶ and thus integrated deeper into Western economic relations.

While the free movement of goods, capital, and labor within the EU was expected to achieve a convergence of wages and profits, the lack of actual labor mobility remains a crucial factor that perpetuates the existence of different wages and profit rates between EU members (verifying Mandel’s analysis). These differences continue during the last three decades, although Eastern European members resemble Western members more and more in their productive structure (Rubinić and Tajnikar 2021). Rubinić and Tajnikar (2019a, 2019b, 2022) argue that consistent wage differentials between EU members are a source of imperialist exploitation within the EU through intra-EU trade. Concerning capital exports, according to Smith (2016: 198) and Suwandi (2019: 20), imperialist exploitation results from “global labor arbitrage” based on international wage differentials, for a given labor productivity, in which foreign capital captures extra profits from less-developed countries through the substitution of higher-paid labor with low-paid labor. This is the case examined in the present article.

2.4.1. Motives of FDI in the EU

In the case of the EU, most of the additional motives of FDI have become either absent or modified. Protectionism of any kind is either absent, for FDI between EU members (intra-EU FDI), or has the same impact on FDI regardless of the EU host country, for FDI originating from non-EU members (extra-EU FDI).

Market-seeking FDI realized in the EU, either stemming from intra-EU FDI, or extra-EU FDI, is made primarily in order to serve the enlarged common EU market. This means that what counts is the common EU market size, and not the market size of individual EU members. Specifically, five of the eight countries examined in this study (Austria, Belgium, France, Germany, and Slovakia) are members of both the EU and the Eurozone. The other three countries (Czechia, Hungary, and Poland) are members of the EU and have experienced overall real currency appreciations (FRED 2020) while preparing to adopt the Euro (European Commission 2020). This means that the creation of the EU and the Eurozone has essentially eliminated the motives related to protectionism of any kind (tariffs and currency devaluation) for FDI between EU-Eurozone members (which are specific to market-seeking FDI), given that most FDI in the countries examined is intra-EU FDI, while most of their foreign trade is intra-EU trade (OECD 2020; Eurostat).⁷

Although the creation of the EU has eliminated a basic additional motive behind market-seeking FDI between EU members, it is possible that the EU may have a positive impact on export-oriented FDI between EU members, because of the elimination of additional transaction costs (tariffs).

Finally, FDI in noninternationally tradable goods and services does not seem to be affected in a significant way by the creation of the EU and the Eurozone, as FDI of this type does not concern internationally tradable goods and services.

3. Empirical Analysis

3.1. Grouping criteria

The analysis focuses on two distinct EU country groups. The first consists of more developed EU members, namely, Austria, Belgium, France, and Germany (group 1), while the second consists of less developed Eastern EU members, namely, Czechia, Hungary, Poland, and Slovakia (group 2). The grouping is made according to the GDP per capita, average wage, and capital intensity of each country, which are proxies for the level of capitalist development (Scarpetta et al. 2000).

According to table 2, group 1 includes EU members that demonstrate a substantially higher real GDP per capita, average wage, and capital intensity compared to EU members in group 2, that is, group 1 can be characterized as a group of EU members that are at a higher level of development compared with EU members in group 2. Furthermore, all countries in group 1 are Western European countries that are part of the EU economic core. On the other hand, all countries in group 2 are former Eastern European countries that reentered the world capitalist system as transition economies after decades of central planning, following the dissolution of the Eastern Bloc in the 1990s.

Table 2.

Grouping Macroeconomic Criteria.

Period average: 1991–2018		Real GDP per Capita^a	Average Wage^b	Capital Intensity^c
Group 1	Austria	40,796	42.584	261.195
	Belgium	37,716	50.821	218.576
	France	34,716	42.687	223.756
	Germany	37,257	38.253	195.103
Period average: 1995–2018
Group 2	Czechia	15,237	13.196	82.136
	Hungary	11,059	11.442	48.457
	Poland	9,834	11.182	41.609
	Slovakia	12,700	13.334	45.361

Constant 2015 prices, USD per capita; source: UNCTAD.

Constant 2015 prices, Euros per worker; source: AMECO, our calculations.

Concerning group 2, former Eastern European transition economies are unique compared to many developing economies in that significant investments in worker’s skills have been previously made (Dunning and Lundan 2008: 317). Moreover, as demonstrated by empirical indicators (ECI⁸), these countries rank very high even among developed economies regarding their productive capabilities, especially those related to medium- and high-tech products.

3.2. Data and model specification

The analysis uses time series annual data from 1991 to 2018 for group 1, and from 1995 to 2018 for group 2. The data for the calculation of the profit rate are from the AMECO (2020) database. Data for the calculation of aggregate FDI and GDP for each group are from the UNCTAD (2020) datacenter. Data used for the calculation of the profit rate, as well as GDP data, are at constant 2015 prices, in order to estimate the true growth of the time series that affect the profit rate, that is, to adjust for the effects of inflation. FDI data refer to inward FDI stock as a percentage of the world total.

We apply a dynamic autoregressive distributed lag (ARDL) approach (equation 3), which means that the models include lagged values of both the dependent and independent variables (regressors), as in time series analysis the impact of regressors on the dependent variable is rarely instantaneous (Gujarati and Porter 2009: 618). We use a general to specific ARDL approach in order to determine the most parsimonious model, which achieves normality of the residuals, and at the same time is consistent with the theoretical framework (Hendry and Richard 1983: 140).

The following general dynamic ARDL econometric model for each group is estimated:

\begin{matrix} F D I_{t} = α_{0} + β_{0} R_{t} + β_{1} R_{t - 1} + \dots + β_{k} R_{t - k} + γ_{0} G D P_{t} + γ_{1} G D P_{t - 1} + \dots + γ_{m} G D P_{t - m} \\ + φ_{1} F D I_{t - 1} + φ_{2} F D I_{t - 2} + \dots + φ_{p} F D I_{t - p} + E U R O + T A R I F F S + u_{t} \end{matrix}

(3)

This ARDL model is used to examine the impact of the profit rate, market size, and long-term FDI attractiveness on inward FDI for each group. The dependent variable is each group’s aggregate inward FDI stock as a percentage of the world total (FDI = FDI_group/FDI_world). Measuring FDI as a percentage of the world total provides a meaningful estimate of each group’s FDI attractiveness relative to the rest of the world. The first independent variable is each group’s profit rate (R). The second independent variable is each group’s aggregate market size (GDP) as a percentage of the world market size (GDP = GDP_group/GDP_world). Again, percentages are used here in order to estimate each group’s market size weight relative to the world market. We also use lagged values of the dependent variable (lagged FDI) as a regressor, to account for each group’s long-term FDI attractiveness. For group 2 we also examine the role of tariffs as all the countries of this group used trade protection until 2004 (TARIFFS dummy variable). The role of tariffs for group 1 could not be examined as the countries of this group abolished tariffs approximately at the beginning of the examined period (1993). However, for group 1 we manage to examine the role of the Eurozone as all the countries of this group formed the Eurozone simultaneously in 1999 (EURO dummy variable). The role of the Eurozone could not be examined for group 2 as most of these countries (except Slovakia) have not yet entered the Eurozone.

FDI is expected to be positively related to each group’s profit rate (R) and market size (GDP). Long-term FDI attractiveness (lagged FDI) is also expected to have a positive impact on FDI. Finally, the Eurozone (EURO), which is applicable in group 1, and trade protection (TARIFFS), which is applicable in group 2, are expected to have a mixed impact on FDI. Table 3 presents the variables and their expected impacts.

Table 3.

Variables and Expected Impacts.

Dependent Variable	Independent Variables		Lagged Dependent Variable	Dummy Variable (Group 1)	Dummy Variable (Group 2)
	R	GDP	FDI	EURO	TARIFFS
FDI	+	+	+^a	+/−	+/−

Note: FDI = foreign direct investment; R = profit rate. The plus sign means that a positive change in the independent variable has a positive impact on the dependent variable.

The plus sign in this case means that X_t₋₁ has a positive impact on X_t.

3.3. Preliminary observations

Figures 1 and 2 present the examined variables for country groups 1 and 2, that is, the inward stock of FDI as a percentage of the world total, GDP as a percentage of the world total, and the profit rate. The figures also illustrate the two dummy variables that represent the creation of the Eurozone for group 1 (EURO), and the accession to the EU for group 2 (TARIFFS).

Figure 1.

Variables for country group 1 (1991–2018).

Figure 2.

Variables for country group 2 (1995–2018).

According to figures 1 and 2, group 2 has a substantially higher profit rate, almost double on average, compared with group 1. Furthermore, the profit rate of group 2 demonstrates an impressive rise, while the profit rate of group 1 suffers an overall decline, during the examined period. This first observation verifies that, as anticipated by Marx, countries that are relatively less developed usually have a higher profit rate.

Two main subperiods are distinguished. The first subperiod involves the years prior to the global economic crisis of 2008, while the second covers the years from 2008 to 2018.

In particular, the profit rate of group 1 demonstrates a fluctuating upward trend until the global crisis of 2008, after which it suffers a deep drop and stabilizes at a level below its overall pre-crisis performance. On the contrary, the profit rate of group 2 demonstrates a sharp upward trend until the 2008 global crisis, after which it stops its increase but, however, stabilizes at a high level, in fact higher than its overall pre-crisis performance.

FDI also has different patterns in the two country groups. In group 1, FDI has a fluctuating overall downward trend. Its last upward movement is before the global economic crisis of 2008, after which FDI follows an almost steady downfall. On the other hand, FDI in group 2 has a less fluctuating overall upward trend. It follows a relatively steady upward trend until the 2008 global economic crisis, after which FDI declines while maintaining, however, its overall upward trend.

Finally, the relative market sizes of the two groups (as a percentage of the world market size) also have different trends. The first group’s relative market size declines almost throughout the entire examined period. On the contrary, the second group’s relative market size increases impressively before the 2008 global economic crisis and declines in the period that follows, while maintaining its overall upward trend.

3.4. Econometric analysis

The ARDL bound testing method is applied following Pesaran and Shin (1998) and Pesaran, Shin, and Smith (2001) in order to check for cointegration between the variables in the case of each group. Then, depending on the presence, or not of cointegration, we estimate either both a long-run and error correction (short-run) model, or only a short-run ARDL model for each group.

3.4.1. Tests for stationarity

We first examine the stationary properties of the variables. We use the Phillips-Perron (PP) unit root test as it is more robust when smaller samples are examined (Akeyede, Habiba, and Atanda 2016:153). The stationarity tests reveal that all the variables for both groups are I(1),⁹ which means that we can implement the ARDL bound testing method for cointegration.¹⁰

3.4.2. Tests for cointegration

The results of the F-bound tests for the two country groups are given in table 4. Both ARDL-bound tests are free of autocorrelation and heteroskedasticity.

Table 4.

Cointegration Tests.

Results of Bounds Test			ARDL	F Statistics		Result
Country group 1
Dependent variable	Dynamic regressors	Fixed regressors	(1, 0, 0)	20.339		Cointegration
Group 1 FDI	Group 1 GDPGroup 1 R	EURO,C	(1, 0, 0)	20.339		Cointegration
Bound critical values (for actual sample size T = 27)				α = 0.01		α = 0.05
				I(0)	I(1)	I(0)	I(1)
				6.18	7.87	4.27	5.47
Country group 2
Dependent variable	Dynamic regressors	Fixed regressors	(1, 0, 1)	2.784		No cointegration
Group 2 FDI	Group 2 GDPGroup 2 R	TARIFFS, C	(1, 0, 1)	2.784		No cointegration
Bound critical values (for actual sample size T = 23)				α = 0.01		α = 0.05
				I(0)	I(1)	I(0)	I(1)
				6.18	7.87	4.27	5.47

Note: ARDL = autoregressive distributed lag; FDI = foreign direct investment; R = profit rate. Bound critical values are obtained from Narayan (2005). The ARDL model was selected according to the Schwarz information criterion.

Table 4 indicates that there is a cointegration (long-run) relationship between the examined variables of group 1 and that there is no cointegration (no long-run) relationship between the variables of group 2.

According to Gujarati and Porter (2009: 769), the absence of cointegration between the variables of an econometric model suggests that a long-run relationship has not yet formed between the variables of the model. Concerning our model, the absence of cointegration indicates that the relationships between the examined variables of group 2 have not yet been established in a long-term perspective. This implies that the dissolution of the Eastern Bloc in the 1990s is very recent in terms of the economic potential it could create and consolidate between FDI and the independent (i.e., explanatory) variables.

3.4.3. Econometric estimations for group 1

For group 1, since there is cointegration, a long-run ARDL model is estimated, from which we extract the residuals and use them in order to also estimate an error correction (short-run) ARDL model. Models are selected according to the Schwarz information criterion (SIC). Both estimated models for group 1 are free of autocorrelation and heteroskedasticity.

According to the estimated long-run model (table 5) for group 1, all statistically significant coefficients have the expected effect on FDI. The standardized¹¹ coefficients show that the factor that seems to have the strongest impact on FDI, in the long run, is lagged FDI. This indicates that one of the factors behind FDI in group 1 is long-term FDI attractiveness. Two other factors that play an important role are the creation of the Eurozone (EURO) and market size (GDP). Finally, the profit rate (R) also seems to play a role, in the long run, although to a smaller degree.

Table 5.

Estimated ARDL Long-Run Coefficients for Group 1.

Dependent Variable: FDI
Regressor	Estimated Coefficient	Standardized Coefficient
FDI(−1)	0.378*** (0.084)	0.377
GDP	0.604*** (0.152)	0.332
R	1.013*** (0.282)	0.144
EURO	−0.027*** (0.006)	−0.333
Constant	−0.060 (0.021)	NA
Adjusted R²		0.97
DW statistic		2.12

Note: ARDL = autoregressive distributed lag; DW = Durbin Watson; FDI = foreign direct investment; NA = not applicable; R = profit rate. Standard errors are in parentheses.

***

p < 0.01.

According to the estimated short-run model (table 6), all statistically significant coefficients have the expected effect on FDI. The standardized coefficients show that the factor with the strongest impact on FDI, in the short run, is market size (GDP). The profit rate (R) also seems to play a (minor) role, in the short run.

Table 6.

Estimated ARDL Short-Run (ECM) Coefficients for Group 1.

Dependent variable: ΔFDI
Regressor	Estimated Coefficient	Standardized Coefficient
ΔFDI(−1)	0.249 (0.180)	0.249
ΔGDP	0.913*** (0.274)	0.508
ΔR	0.761* (0.367)	0.304
EURO	−0.003 (0.004)	−0.115
ECT(−1)	−1.073*** (0.347)	−0.542
Constant	0.002 (0.003)	NA
Adjusted R²		0.49
DW statistic		1.55

Note: ARDL = autoregressive distributed lag; DW = Durbin Watson; ECM = error correction model; FDI = foreign direct investment; NA = not applicable; R = profit rate. Standard errors are in parentheses.

p < 0.1; ***p < 0.01.

The negative sign of the EURO dummy variable in the long-run model indicates that the creation of the Eurozone has a negative impact on FDI, which implies that a part of FDI in group 1 was of a market-seeking type—in order to circumvent currency devaluations (FRED 2020), given that most inward FDI is intra-EU FDI—and continues to be, albeit diminishing. The existence of market-seeking FDI, during the examined period, is further supported by the significant positive coefficient of the market size (GDP). The positive coefficient of GDP also implies that a part of FDI could also be directed to noninternationally tradable goods and services.

3.4.4. Econometric estimations for group 2

For group 2, where there is no cointegration (no long-run) relationship, an ARDL short-run model is estimated. The estimated model for group 2 is free of autocorrelation and heteroskedasticity.

According to the estimated short-run model (table 7) for group 2, all statistically significant coefficients have the expected effect on FDI. The standardized coefficients show that the factor with the strongest impact on FDI is the profit rate (R), which is a motive for all types of FDI. The positive impact of both trade protection (TARIFFS) and the market size (GDP) shows that a part of FDI in group 2 is of a market-seeking type. However, market-seeking FDI seems to have played a role mostly during the first years of transition (Meyer 1995: 316). According to Kalotay and Hunya (2000: 41) and Jirasavetakul and Rahman (2018: 6), a close relationship between privatization and FDI in Central and Eastern Europe has developed since the beginning of the transition process. Therefore, the positive impact of GDP on FDI in our model indicates that another part of FDI was directed probably to noninternationally tradable goods and services (mainly previously state-owned enterprises), following the extensive privatization regime which generally took place in former Eastern European countries while adopting the market economy, during their transition period in the 1990s.

Table 7.

Estimated ARDL Short-Run Coefficients for Group 2.

Dependent Variable: ΔFDI
Regressor	Estimated Coefficient	Standardized Coefficient
ΔFDI(−1)	−0.154 (0.169)	−0.154
ΔGDP	0.926** (0.389)	0.390
ΔR	0.012 (0.050)	0.038
ΔR(−1)	−0.022 (0.052)	−0.069
ΔR(−2)	0.196*** (0.050)	0.599
TARIFFS	0.002*** (0.000)	0.493
Constant	0.001** (0.000)	NA
Adjusted R²		0.61
DW statistic		1.70

Note: ARDL = autoregressive distributed lag; DW = Durbin Watson; FDI = foreign direct investment; NA = not applicable; R = profit rate. Standard errors are in parentheses.

p < 0.05; ***p < 0.01.

3.5. Investigating the profit rate

The profit rate seems to play a significant role in determining inward FDI in the examined country groups, and especially in group 2.

It is shown that group 1 has a relatively low profit rate between 1991 and 2018, a period during which inward FDI demonstrates an overall fall. On the other hand, group 2 has a relatively high profit rate between 1995 and 2018, a period during which inward FDI demonstrates an overall increase. Furthermore, the declining trend of FDI in group 1 seems to follow the overall fall in the profit rate, while the increasing trend of FDI in group 2 seems to follow the overall rise in the profit rate, over the examined period.

There remains the question of why the profit rate has different levels and, additionally, demonstrates overall diverging trends in the two country groups.

Figure 3 presents the between-group ratio (group 1 / group 2) of the variables that affect the profit rate (R).

Figure 3.

Ratios of profit rate–related variables between group 1 and group 2 (1995–2018).

The higher level of R in group 2 can be reduced to the relation of the two main components of R, that is, L/Y and K/Y. As shown in figure 3, L/Y is lower (P/Y is higher) in group 2 compared to group 1. In addition, K/Y is also substantially lower in group 2. Furthermore, both main components of the profit rate act in a way that tends to increase the profit rate in group 2 relatively to group 1.

In order to further investigate the causes behind the overall diverging trends in the profit rate, we examine the changes of the variables that affect it.

According to table 8, in the period prior to the 2008 global crisis, R rises in both groups; however, the rise is much greater in group 2 (+43.8 percent compared to +13.9 percent in group 1). During the post-2008 crisis period (2008–2018), R drops in both groups, however, the drop in R for group 2 is much smaller (−2.6 percent compared to −15.4 percent in group 1). Finally, during the entire examined period, the profit rate has an overall downward trend in group 1 (−7.2 percent from 1991 to 2018) and an overall upward trend in group 2 (+37.1 percent from 1995 to 2018).

Table 8.

Profit Rate and Related Variables (Percentage Changes).

Period	R	L/Y	K/Y	P/Y	L/N	K/N	Y/N	Y	N
Group 1
1991–2007	13.9	−7.0	2.2	16.4	12.7	23.9	21.3	31.1	8.1
2008–2018	−15.4	7.8	0.4	−15.1	11.1	3.5	3.0	10.8	7.5
1991–2018	−7.2	1.4	4.2	−3.4	25.5	28.9	23.7	45.3	17.5
Group 2
1995–2007	43.8	−11.7	−15.7	21.2	45.2	38.7	64.5	68.3	2.3
2008–2018	−2.6	−0.2	3.0	0.3	23.2	27.1	23.4	30.9	6.0
1995–2018	37.1	−11.0	−12.6	19.9	82.9	79.7	105.5	128.7	11.3

Source: AMECO, our calculations.

Note: All values are percentages.

Regarding group 1, there are two causes for the overall drop in the profit rate. One cause is the overall rise in K/Y (+4.2 percent), and the other cause is the overall rise of L/Y (+1.4 percent). More specifically, K/Y rises, as capital intensity increases faster (+28.9 percent) than productivity (+23.7 percent), while L/Y rises, as productivity increases slower (+23.7 percent) than the average wage (+25.5 percent). In other words, there seem to be certain developments that are related, mainly, with the Marxian “Law of the Tendential Fall in the Rate of Profit” and also, to a lesser extent, with a process of “Capital Over-Accumulation” in the group of more developed EU members, during the examined period.

Regarding group 2, there are two causes for the overall rise in the profit rate. One cause is the overall fall in K/Y (−12.6 percent), and the other cause is the overall fall of L/Y (−11.0 percent). More specifically, K/Y falls, as capital intensity increases slower (+79.7 percent) than productivity (+105.5 percent), while L/Y falls, as productivity increases faster (+105.5 percent) than the average wage (+82.9 percent). In other words, it seems that Marx’s prediction that in less developed countries “the profit rate is generally higher on account of the lower degree of development” is verified in the case of less developed Eastern EU members, where it is shown that the profit rate stands higher owing to both a lower amount of net fixed capital stock required to produce a unit of net product and a lower labor share in net product.

The above show that considerably lower wages in group 2, for a given labor productivity, lead to a lower L/Y compared to group 1. Furthermore, although wages in group 2 tend to rise (relative to wages in group 1) over the examined period, the even faster rise of productivity in group 2 overcompensates for the rise of wages, ultimately leading to the decline of L/Y—rise of P/Y. Therefore, capital exported from more developed (high wage) countries to group 2 captures extra profits through the substitution of higher-paid labor with low-paid labor. This is a form of imperialist exploitation through capital exports (FDI), which results from “labor arbitrage” based on wage differentials, for a given labor productivity.

Furthermore, the increase of both capital intensity (K/N) and productivity (Y/N) indicates that a form of industrial transformation has taken place in the countries of group 2; that is, they have experienced structural changes and improved their technological base. A sign of this transformation is that while during the first years of transition most of the examined Eastern European countries took part mainly in the production of low-tech finished or intermediate products for Western multinational companies, since the early 2000s they began producing more “complex components,” such as engines for multinational car companies, for the EU market, while maintaining a skilled and cheap labor force (Berend 2009: 153 ff).

The great rise of productivity (Υ/Ν) in group 2 is formed by an impressive increase in the value of the net product (Y), in constant prices, for a very moderate increase in total employment (N). This may stem from the fact that during the examined period, a shift in investment took place toward more sophisticated industrial sectors, such as engineering, communications technology, and the chemical industry, which boosted labor productivity. This industrial transformation is partly a consequence of the presence of multinational companies, which have transferred technology, knowledge, and better management methods (Berend 2009: 160 ff). Furthermore, following the dissolution of the Eastern Bloc in the early 1990s, privatizations, which were widely seen as a mechanism for industrial, economic, and political reform, served as a tool for restructuring managerial incentives and labor relations, which gradually resulted in the intensification of the labor process and increases in labor productivity (Vickerstaff, Thirkell, and Scase 1998: 208 ff).

Additionally, the more than double rise in the value of net product in group 2 is accompanied by changes in supply (and demand) composition toward products of a higher technological level and, consequently, of a higher income elasticity of demand, which means the generation of “dynamics associated with the Engel curve” (on this connection, see Gualerzi 2016: 44), based on production restructuring (see also Economakis, Markaki, and Anastasiadis 2015: 426). Production transformation in the countries of group 2 is indicated by their increased position in ECI ranking¹² over the examined period. Czechia’s ranking increased from 16th to 7th, Hungary’s increased from 26th to 14th, Slovakia’s increased from 20th to 15th, and Poland’s increased from 29th to 23rd.

3.6. Sectoral analysis: Investigating the types of FDI in group 2

In this section, we perform a sectoral analysis of FDI and trade in each country of group 2 in order to estimate the main type of FDI. The estimation is based on the expected impact of FDI on the host country’s foreign trade, depending on the additional motive of FDI, according to table 1.

Initially, we determine the most attractive sectors for FDI and the trends of FDI in these sectors, by examining available OECD FDI sectoral data, during the period 2003–19. It is assumed that more attractive sectors usually hold a higher share of the total inward FDI stock. Furthermore, we determine the most exporting and importing sectors and the trends of the exports and imports in these sectors, by examining UNCTAD trade sectoral data, over the period 1995–2018.

FDI sectoral data refer to each sector’s average share of inward FDI stock as a percentage of total inward FDI stock in the industrial sector. Trade sectoral data refer to each sector’s average share of exports (imports) as a percentage of total exports (imports).

3.6.1. Sectoral data limitations

Concerning sectoral data, a first limitation is that they are available from 2003 to 2019 and thus do not cover the exact same period as aggregate FDI data. However, as FDI data refer to the stock of inward FDI, one can reasonably assume that the sectors with a significant stock of inward FDI during the period 2003–19 are the sectors that were receiving significant amounts of FDI also during the immediate previous period (1995–2002). Another limitation is that OECD has two separate time series on sectoral FDI that were compiled using different recording methods (BMD3 for 2003–12 and BMD4 for 2013–19). Therefore, the trends in sectoral FDI are presented in a more general form (general increase or decrease) and not as a percentage change.

3.6.2. Sectoral data examination

Tables 9 to 12 present the estimated main type of FDI, and the technological level in the top FDI recipient industrial sectors in group 2.

Table 9.

Technological Level and Types of FDI in Czechia (2003–19).

FDI Recipient Sector	FDI Share	Change in FDI Share	Change in Exports	Change in Imports	Technological Level	Type of FDI
Automotive industry	1/4	+	+175%	+61%	Medium/high	Export-oriented
Electrical and mechanical equipment	1/4	+	+36%	+33%	Medium/high	Export-oriented
Chemical products	1/8	Stable	−33%	−7%	Medium/high	Export-oriented
Metal products	1/8	−	−15%	Very few imports	Medium/low	Export-oriented
Industrial equipment	1/10	+	+66%	−18%	Medium/high	Export-oriented, Market-seeking
Food products	1/10	−	Very few exports	Very few imports	Low	unspecified

Note: FDI, foreign direct investment.

Source: Own calculations using OECD Stat Extracts.

Table 10.

Technological Level and Types of FDI in Hungary (2003–19).

FDI Recipient Sector	FDI Share	Change in FDI Share	Change in Exports	Change in Imports	Technological Level	Type of FDI
Automotive industry	1/4	+	+201%	+71%	Medium/high	Export-oriented
Chemical products	1/5	+	+4%	−14%	High	Market-seeking, export-oriented
Telcom equipment	1/5	+	+77%	−2%	Medium/high	Export-oriented, market-seeking
Electronic products	1/7	+	Very few exports	Very few imports	High	Unspecified
Mechanical products	1/10	+	+1437%	+153%	Medium/high	Export-oriented
Food products	1/10	−	Very few exports	Very few imports	Low	Unspecified

Note: FDI, foreign direct investment.

Source: Own calculations using OECD Stat Extracts.

Table 11.

Technological Level and Types of FDI in Poland (2003–19).

FDI Recipient Sector	FDI Share	Change in FDI Share	Change in Exports	Change in Imports	Technological Level	Type of FDI
Food products	1/5	−	+18%	−13%	Low	Export-oriented
Chemical products	1/6	+/−	+17%	−14%	Medium/high	Export-oriented, market-seeking
Automotive industry	1/6	+	+131%	+79%	Medium/high	Export-oriented
Metal products	1/8	+	+0.2%	Very few imports	Medium/low	Market-seeking
Wood, publishing, and printing	1/10	−	−14%	Very few imports	Low	Export-oriented, market-seeking
Electrical and mechanical equipment	1/20	+	+71%	+29%	Medium/high	Export-oriented

Note: FDI, foreign direct investment.

Source: Own calculations using OECD Stat Extracts.

Table 12.

Technological Level and Types of FDI in Slovakia (2003–18).

FDI recipient sector	FDI share	Change in FDI share	Change in Exports	Change in Imports	Technological Level	Type of FDI
Metal products	1/5	+	−72%	Very few imports	Medium/low	Market-seeking
Automotive industry	1/5	+	+583%	+185%	Medium/high	Export-oriented
Chemical products	1/10	+	−66%	−43%	Medium/high	Market-seeking
Petroleum products	1/10	−	−29%	−36%	Medium/low	Export-oriented
Mechanical equipment	1/12	−	+84%	+78%	Medium/high	Market-seeking
Wood, publishing, and printing	1/20	−	Very few exports	Very few imports	Low	unspecified
Food products	1/20	−	Very few exports	Very few imports	Low	unspecified

Note: FDI, foreign direct investment.

Source: Own calculations using OECD Stat Extracts.

The main finding is that FDI in the countries of group 2 seems to be primarily of an export-oriented type, as high levels of FDI in certain sectors, especially in the automotive industry, go hand in hand with increased exports. Specifically, the automotive industry is among the top recipient industries of FDI, holding approximately one-fifth of all inward FDI stock during the examined period. At the same time, the automotive industry is the largest and most dynamic exporting sector in almost all Eastern EU members examined.

Furthermore, tables 9 to 12 show that the examined Eastern EU members have relatively advanced industrial sectors, which usually produce medium- to high-tech products, showing that they resemble Western EU members in their productive structure.

Given that the greatest part of exports from the countries of group 2 is directed toward the rest of the EU, it seems that a main reason behind increased FDI to these countries is their relatively higher profit rate when producing medium- to high-tech products within the EU, for the EU market.

4. Summary and Conclusions

The objective of this study was to examine how the profit rate may help explain the heterogeneity of inward FDI in two distinct groups of members of the EU, over the examined periods. The first country group (group 1) consisted of more developed EU members (Austria, Belgium, France, Germany), while the second (group 2) consisted of less developed Eastern EU members (Czechia, Hungary, Poland, Slovakia). Additional motives behind FDI such as market size, protectionism of any kind, and long-term FDI attractiveness were also examined.

A main finding was that the profit rate seems to play a significant role in determining overall inward FDI trends in both country groups. It is shown that group 2 has a relatively higher profit rate between 1995 and 2018, a period during which inward FDI demonstrates an overall increase. On the other hand, group 1 has a relatively lower profit rate between 1991 and 2018, a period during which inward FDI demonstrates an overall fall.

The higher profit rate in group 2, as well as its overall upward trend, is shown to be caused by the lower amount of net fixed capital stock required to produce a unit of net product, and the lower labor share in net product, compared to group 1—which indicates that foreign capital invested in group 2 takes advantage of both low wages and rising labor productivity.

It is shown that the lower profit rate, as well as the overall downward trend of the profit rate, for group 1 is the result of both the overall rising net fixed capital stock required to produce a unit of net product (Marxian “Law of the Tendential Fall in the Rate of Profit”) and the overall increasing labor share in net product (“Capital Over-Accumulation”).

For group 1, additional factors behind FDI are market size and long-term FDI attractiveness. Finally, the creation of the Eurozone seems to have a negative impact on FDI, which implies that a part of FDI in group 1 is of a mostly market-seeking type.

For group 2, additional factors that seem to have attracted FDI are tariffs and market size. The fact that the market size also seems to play a role indicates that a part of FDI is probably directed to noninternationally tradable goods and services—mainly previously state-owned enterprises—as a close relationship between privatization and FDI in Central and Eastern Europe has developed since the beginning of the transition process. Finally, a sectoral analysis of FDI and trade shows that increased FDI in group 2 seems to be primarily of an export-oriented type, especially in the automotive industry.

Further research could include an extension of the number of more developed and less developed EU members examined, either in groups, or individually, in order to investigate if the profit rate continues to play a significant role in determining general FDI trends.

Footnotes

Acknowledgements

We thank the reviewers Ivan Rubinić, Juan Pablo Mateo, and the editorial coordinator Davide Gualerzi for their constructive comments, which helped us improve the quality of our work. We also would like to thank Dr. Theofanis Papageorgiou for his useful advice on the econometric analysis in the preliminary stages of this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Dimitris Groumpos

1

Accepting that “productive labor” is the labor paid from variable capital, we disagree with the distinction between “Marxian general profit rate” and “net profit rate,” since the calculation of the latter presupposes the consideration of trade as a “nonproductive” sector (see, among other works, Shaikh and Tonak 1996). As known, the notion of “productive” and “nonproductive” labor is a point of controversy within the Marxist literature—a controversy that stems from conceptual contradictions in Marx’s writings (for a review of Marx’s ambiguities on the issue, see, among other works, : 69 ff.)

2

According to : 42), the “profit rate” is “a variable whose empirical calculation admits various controversies.” Furthermore, the profit rate is a variable whose empirical calculation is subjected to various restrictions because of data availability issues.

3

In the level of abstraction of our analysis the distinction, made by , between entrepreneurial profit and interest is not considered.

4

It must be noted that according to a study by Cambridge Econometrics (see ), AMECO’s capital depreciation rates are considered high, and thus tend to overestimate the profit rate in all countries. As long as we are interested in the trend of variables between countries, and given that this overestimation applies to all countries equally, the validity of our results is not affected. The same could be assumed that applies for the underestimation of R due to K of the public sector.

5

The History of the European Union:

6

Ibid.

7

Between 2003 and 2018, over 63 percent of FDI directed to group 1 accounted for intra-EU FDI, while the respective percentage of intra-EU FDI directed to group 2 was over 70 percent (). At the same time, intra-EU trade accounted for over 60 percent of total trade for group 1, while the respective percentage of intra-EU trade for group 2 was over 70 percent (Eurostat).

8

ECI: Economic Complexity Index from The Observatory of Economic Complexity (2020), accessed at:

9

Stationary after taking first differences. Unit root and residual normality tests are not presented due to the lack of space. They are available, however, upon request.

10

The ARDL bound test for cointegration cannot be applied if some of the variables have an order of integration that is greater than I(1).

11

By standardizing regressors we can compare their impacts directly (: 158).

12

Economic Complexity Index accessed at: .

Author Biographies

Dimitris Groumpos studied at the Department of Electrical Engineering at the University of Patras (Dipl.Elec.Eng., 2006) and received a Master’s in Business Administration from the University of Patras (MBA 2013), where he is currently a PhD candidate at the Department of Business Administration. His research interests include international political economy, foreign direct investment, and international trade.

George Economakis studied at the Economics Department of the University of Athens (BA Economics, 1984) and Panteion University (MSc in Regional Development, 1988, and PhD in Political Economy, 1998). He is Professor of political economy in the Department of Business Administration at the University of Patras. His research interests include labor theory of value, theory of modes of production and social classes, theories of economic crises and imperialism, economic development, and international competitiveness.

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