Human Freedom and Economic Prosperity: Evidence from Eastern Europe

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Miguel Á. Padriñán via Pixabay // CC

The main mechanism that relates human freedom to economic growth is channeled through institutional and economic factors, such as government effectiveness, investments, and trade. Therefore, institutions are an important determinant of economic prosperity in countries worldwide.

Institutions shape human behavior, set the “rules of the game” in society, and reflect the prevailing norms and values. Both economic science and history have proved that economies and societies flourish in a market-supportive environment where institutions adhere to personal choice, self-ownership, and the rule of law.

In this paper, we focus on exploring the fractional effects of institutional changes on economic growth (measured as GDP per capita) and on productivity (measured as GDP per person employed).

We developed ordinary least squares (OLS) panel regression models for selected economies of Eastern Europe, or around 20 cross-section units (countries) in the period between 2008 and 2016.

The cross-country regression models demonstrate that institutions presented with human freedom and human capital have the highest influence and are statistically significant determinants of economic growth and productivity in the selected economies of Eastern Europe.

Introduction

Eastern Europe has overcome the period of Soviet repression and is now oriented towards the Western values of freedom and democracy. However, 30 years after the fall of the Berlin Wall, authoritarianism in Europe is becoming increasingly popular among politicians, policy makers and the general public.

The process of globalization and the presence of transnational companies, the 2008 financial crisis followed by the European debt crisis and the rise of the populist parties and leaders in Europe, has thus created challenges to the rule of law and democracy, being truly global in nature.

Unfortunately, Eastern European countries are not an exception. 

The latest Human Freedom Index, which is co-published by the Cato Institute, the Fraser Institute, and the Liberales Institute at the Friedrich Naumann Foundation for Freedom (Vásquez and Porčnik 2018) concludes that human freedom in Eastern Europe has been decreasing over time. 

The Human Freedom Index defines freedom as the absence of coercive constraints, and incorporates personal, civil, and economic freedom.

The average human freedom score in Eastern Europe in 2008 was 7.71, while in 2016 it was 7.67. We make an assumption that a decrease in the average human freedom score reflects a rise in authoritarian inclination and an erosion of liberal values.

If the average human freedom score in Eastern Europe is proven to be statistically significant, then difficult times for Eastern Europe is on the horizon.

The key question that we aim to answer with our research is: Does respecting and protection of human freedom create economic benefits for the countries? The main hypothesis we are testing is that improving human freedom does not impose economic costs on the country, but on the contrary, it creates an economically stimulating environment with regards to economic growth.

More precisely, we are interested in the following questions:

1) Can a relationship between economic prosperity and human freedom be documented empirically?; and

2) Does human freedom contribute positively to economic prosperity, or is there a trade-off between these two?

We employ the Human Freedom Index (Vásquez and Porčnik 2018) as a broad measure of the institutional environment. The index presents human freedom understood in a negative context, as the absence of coercive constraint.

The areas covered by the index are: rule of law; security and safety; movement; religion; association, assembly, and civil society; expression and information; identity and relationships; size of government; legal system and property rights; access to sound money; freedom to trade internationally; and regulation of credit, labor, and business.

Using a sample of 22 countries between the years 2008-2016, we have constructed several ordinary least squares (OLS) regression models to study how changes in the level of human freedom effect economic growth. Our analysis will improve the understanding of the concept of human freedom and how it relates to economic and societal prosperity.

The rest of the paper is organized as follows: Section 2 reviews the empirical literature on human freedom, human rights, democracy and economic prosperity. The data sources and the description are presented in Section 3. The findings of the empirical study and discussion of the results are presented in Section 4. In the last section, the main conclusions from the research are given.

Literature Review

Institutions and their impact on economic prosperity are closely examined by the New Institutional Economics (hereinafter: NIE). Institutions can be defined as humanly devised constraints that structure human behavior (North 1994, 360).

More specifically, institutions can be seen as legal, administrative or customary arrangements, whose purpose is to enhance repetitive human interactions that cannot be predicted (Pejovich 2008).

According to NIE, effective institutions reduce transaction costs (North 1991), reduce market inefficiencies (Acemoglu, Johnson, and Robinson 2005) and support good governance (Pejovich 2008; Kaufmann, Kraay, and Mastruzzi 2009).

In the economics literature, institutions are acknowledged as important determinants of economic growth (Rodrik, Subramanian, and Trebbi 2004; Moral-Benito 2012). Effective institutions and good governance have positive implications on economic growth (Marslev and Sano 2016).

In our previous paper (Kocevska and Makrevska Disoska 2017), we examined the impact of institutions and free trade on economic growth in selected transitional economies from Central and Eastern Europe and the Western Balkans. The findings indicated that countries should put a greater focus on the institution’s quality, which is likely to result in enhanced growth prospects.

Acemoglu, Johnson and Robinson (2005) argued that different institutions create different outcomes in economic performance. These authors define two types of institutions: economic and political institutions.

Economic institutions shape the incentives and constraints of economic actors, while political institutions allocate de jure and de facto political power. Glaeser at al. (2004), show that countries evidence economic growth if political institutions are stable and predictable, and there are investments in human and physical capital.

With the introduction of political institutions to the research agenda of the NIE, a variety of research projects emerged to investigate their economic impact. Here we would like to highlight two separate flows: human rights and democratization as an explanatory variable of economic prosperity.

Regarding human rights, one group of economists and political scientists take up the stance that protecting human rights collides with economic growth. This group of scholars argues that granting too many political or civil rights to individuals could even make the economy worse off (Koob, Jørgensen, and Sano 2017).

Seymour and Pincus (2008) warn about the possibility of delegitimization of social choices that deny minority rights to generate growth of the majority in a society.

Nevertheless, most economists emphasize the positive role of human rights on economic prosperity. The fundamental argument in favor of this thesis is that societies, where human rights are respected, generate certainty and predictability for economic actors.

Secure and predictable environments are supportive of economic growth and welfare, investments, and productivity. Koob, Jørgensen, and Sano (2017) consider human rights as freedom and participation rights defined in Empowerment Rights Index from CIRI human rights data (hereinafter: CIRI index) (Cingranelli and Richards 2008). Their research confirms the instrumental role of human rights in economic growth.

Blume and Voigt (2007) examine the effect of four different categories of human rights on economic growth and welfare. Specifically, they are interested in the impact of fundamental human rights, property rights, civil rights and social rights on investment and productivity.

Their factor analysis shows that none of these categories of human rights has a significant negative impact on welfare and growth. By using pooled ordinary least squares regression models, the authors have found that fundamental human rights and property rights encourage investment, while social or emancipatory rights have a distinct impact on total factor productivity.

Accumulation of physical capital (investments) and total factor productivity, according the authors, are possible channels of influence of human rights on economic growth.

Blanton and Blanton (2007a; 2007b) examine the implications of protection of human rights on trade and foreign direct investments. By using pooled regressions, these authors have found that better protection of human rights proves to be stimulating for trade and attracting foreign investments in the countries.

Some authors have examined the opposite relation, i.e., how economic growth impacts human rights. McKay and Vizard (2005) argue that although it is expected that economic development has an impact on human rights, the strength and direction of the relationship are unclear.

Another important aspect of political institutions, essential for the economy, is the democratization of societies. Theoretically speaking, the relationship between democracy and economic prosperity is unclear.

Some authors argue that democracy and economic growth are clashing concepts (Lindblom 1977; Schumpeter 1942; Wood 2007), while on the other hand, there are scholars who support the thesis that democratic environment supports growth. The argument in favor of democratization follows the same logic as human rights.

Thus, Sen (1999) discusses that civil and political freedom is beneficial for societies because they promote economic security and predictability. Disrespecting human rights can lead to an unfortunate economic climate by lowering investments, productivity and growth in the country.

A substantial literature in political science and economics examines the relationship between democratization and economic prosperity.

One of the first organized attempts to explore in detail this relationship comes from Barro (1996), who finds that the effect of democracy on economic growth is minor and negative. After this breakthrough, many authors followed his research agenda.

Although different data and model specifications have been used, their work strengthens the evidence in favor of the hypothesis that democracy is supportive to economic growth (Rodrik and Wacziarg 2005; Persson and Tabellini 2008; Bates, Fayad and Hoeffler 2012).

Acemoglu (2008) argues that in the long run, democratic institutions perform better than non-democratic institutions. Democratic redistribution can often be a drag for economic growth, but sometimes it may take the form of education or public goods, and thus become supportive for economic growth (Benabou 1996; Lizzeri and Persico 2004).

Papaioannou and Siourounis (2008) have constructed a new measure of permanent democratizations. They find that on average, democratizations are associated with a 1% increase in annual per capita growth, but in the medium and long run, it stabilizes at a higher level.

Moreover, Acemoglu et al. (2014) report that democracy has a robust and sizable effect on economic growth by using a panel of countries in the period between 1960 and 2010. The authors estimate a 20 percent rise of the country’s GDP in the long run, following a shift from non-democracy to democracy.

Their results show that there is no differential effect of democracy on economic growth according to the level of economic development.

Data and Methodology

This section of the paper serves to test whether human freedom has a statistically significant impact on economic prosperity. For this purpose, we have constructed a model based on the work of Blume and Voight (2007), and Koob, Jørgensen, and Sano (2017).

Usage of OLS panel regressions in explaining the institutional environment and political rights as a determinant of economic growth is characteristic of the work of Blume and Voight (2007).

A selection of variables is made in accordance with the work of Koob, Jørgensen, and Sano (2017), who use institutional factors, economic factors (variables) and alternative aspects of quality of human capital to estimate the GDP per capita growth.

These authors are more interested in evaluating long-term effects on economic growth by using an autoregressive model with distributed lags (ADL).

However, the length of the time series data for our sample is very limited. To overcome this obstacle, all our models are panel regressions using the OLS method.

We investigate how human freedom affects economic growth in the countries of Eastern Europe. In our research, we focus on a geographically compact region.

In addition, what is common for these countries is that they share a similar historical institutional background. Eastern Europe overcame a period of repressive communist regimes and oriented itself towards the Western values of freedom and democracy at the end of the twentieth century.

For this reason, we created two sets of regression models with separate dependent variables. In the first case, the dependent variable is the economic growth measured by “initial” log GDP per capita. The data is retrieved from the World Development Indicators.

In the second set of models, the dependent variable is GDP per person employed (constant 2011 PPP $) as a standard measure for labor productivity. GDP per person employed is calculated as the gross domestic product (GDP) divided by the total employment in the economy. Purchasing power parity (PPP) GDP is GDP converted to 2011 constant international dollars using PPP rates. The data covers the period from 2008 through 2016.

The novelty of our work is that we use the Human Freedom Index (Vásquez and Porčnik 2018) (hereinafter: HFI) as an institutional variable used to forecast economic growth instead of the CIRI index. HFI has already been utilized in the literature as a variable used to explain the institutional environment (Coka, Freier, and Mollerstrom 2017; Lawson 2019; Berggren, and Gutmann 2019).

We decided to use HFI instead of the CIRI index because two different sources in CIRI are based on expert assessments rather than surveys, which can make the CIRI data biased (Koob, Jørgensen, and Sano 2017).

HFI presents a broad measure of human freedom, and it uses 79 distinct indicators of personal and economic freedom in the areas of Rule of Law; Security and Safety; Movement; Religion; Association, Assembly, and Civil Society; Expression and Information; Identity and Relationships; Size of Government; Legal System and Property Rights; Access to Sound Money; Freedom to Trade Internationally and Regulation of Credit, Labor, and Business.

On a scale of 0 to 10, where 10 represents more freedom, the average human freedom rating for 162 countries in the period 2008-2016 for the observed counties was 7.67.

Human development factors are included in the analysis with two variables: human capital retrieved from the Penn World Tables version 9.1 and life expectancy from the World Bank’s World Development Indicators.

The easy access to information, education and mobility of the population can lead to a more educated and healthier population that will contribute to economic growth. Enhancing the economic, social and cultural rights can influence the human development factors.

The literature broadly suggests a positive relationship between human capital and economic growth (Barro 1991; Levine and Renelt 1992; Mankiw et al. 1992).

However, unlike Koob, Jørgensen, and Sano (2017), we exclude the institutional variables that refer to the effective institutions and good governance mostly because these variables are part of the Human Freedom Index. The correlation matrix presented us a significantly high correlation among these variables.

For the economic factors, we used the following variables: net investment in non-financial assets (as % of GDP), trade as a % of GDP and unemployment (as a percentage of the total labor force, ILO estimate).

Net investment in non-financial assets includes fixed assets, inventories, valuables, and no produced assets. Net investment in non-financial assets also includes consumption of fixed capital. The data is retrieved from the World Development Indicators database.

Trade is the sum of exports and imports of goods and services measured as a share of gross domestic product. The data is retrieved from the World Development Indicators. A number of existing empirical literature supports a positive link between trade openness and growth (Dollar 1992; Dollar and Kraay 2002; Sachs and Warner 1995).

However, the direction of the relationship between them is ambiguous, as some studies find no robust evidence (Rodriguez 2007).

Regarding the unemployment variable, we use the logic behind Okun’s Law. Output depends on the amount of labor used in the production process, so there is a positive relationship between output and employment.

The unemployment rate is calculated as a % of the total labor force in the country according to the unified methodology from the International Labor Organization. The data is retrieved from the World Development Indicators.

Total employment equals the labor force minus the unemployed, so there is a negative relationship between output and unemployment (conditional on the labor force).

Basic descriptive statistics about the variables used in the regression models, including mean, median, maximum and minimum values, standard deviation and number of observations, are provided in the following table (Table 1).

Table 1. Descriptive statistics of variables

1Source: Authors’ calculations. Note: Descriptive statistics refer to individual samples.

Results and Discussion

In the following tables, we present the results for both sets of regressions. In the first seven regressions (Table 2), the dependent variable is a log of the GDP per capita. In the second seven regressions, the dependent variable is the GDP per employee (Table 3). The independent variables are the same in both sets of regressions.

As it can be observed, regressions present similarities and slight differences. Still, the most important thing is that most of the independent variables have a statistically significant influence on the GDP per capita growth and increase of productivity. We will outline and comment on the results separately for each set of regressions.

Table 2. Dependent variable: log (GDP)

2Note: Numbers in parentheses are corresponding standard deviations. ***: p<0.01; **: p < 0.05; *: p < 0.1.

In regressions with the log of GDP per capita being a dependent variable (Table 2), the variables human freedom, human capital, investment in non-financial assets, and life expectancy are statistically significant determinants for the increase of the GDP growth in the selected countries.

The results show that our “focus” variables – human freedom and human capital – have a positive and significant influence on GDP growth. In all seven regressions, the values of the coefficients are rather high. An increase in the protection of the human freedoms by 1 unit (on a 0 to 100 scale) results in a rise in economic growth by 3–8%.

Rise in the index of human capital by 1 unit (on a 0 to 100 scale) results in an increase of the economic growth by approximately 4%. In other words, upholding the right to human freedoms will demonstrate a significant positive effect on economic growth.

From the selected economic variables, only the investment is statistically significant with a positive sign. The coefficients indicate that a 1% increase in investments leads to a higher level of GDP per capita by around 10%.

The coefficient of the unemployment variable is negative, which is expected, but unfortunately, it is not statistically significant. The sign of the variable trade is negative, meaning that an increase of trade leads to lower GDP per capita.

However, the empirical literature suggests that trade impacts growth negatively for countries that specialize in low-quality products (Huchet, Le Mouël, and Vijil 2011). This suggests that increasing the dependency of the observed economies to trade without ensuring the improvement of the quality of their exports may have negative consequences in terms of economic growth.

Nevertheless, the model shows that this explanation cannot be taken into consideration since the variable is not statistically significant. In general, the results from the first group of regressions indicate that GDP growth in these countries is likely determined by non-economic variables or by institutional variables.

Table 3. Dependent variable: log (PRO)

3Note: Numbers in parentheses are corresponding standard deviations. ***: p<0.01; **: p < 0.05; *: p < 0.1.

The results from the other set of regressions in Table 3 are similar. All six variables appear to be statistically significant for the increase in productivity in the observed group of countries. The positive signs of the coefficients of human freedom, human capital, and life expectancy remain with high coefficients.

In these sets of regressions, the influence of the human capital is greater than human freedom, which is expected having in mind that the main driver of productivity is the human capital. Life expectancy also has a positive and significant influence over the labor productivity.

The economic variables, investments, unemployment rate, and trade, have a statistically significant influence over the productivity growth. The values of the coefficient for investment are considerable and indicate that a 1% increase in investments could lead to around an 8% increase in productivity.

Regarding the trade variable, in these sets of regressions, the coefficient is negative and statistically significant over productivity. We confirm the previously stated argument about the negative relationship, although the coefficient is rather low.

The unemployment variable is positive and statistically significant, which is also expected to have in mind that the dependent variable in this set of regressions is productivity.

Productivity growth makes the downward wage constraint binding, thus leading to higher long-run unemployment. Since productivity is measured as GDP per employee, when the number of employees decreases (higher unemployment rate) the value of the productivity rises.

The model shows that the increase in unemployment by 1% leads to the twofold increase in productivity.

Conclusions

This paper contributes to the existing literature by innovating and expanding on the human freedom approach towards economic progress. It explores the determinants of economic prosperity in Eastern Europe, which is a region including countries with a common historical and institutional background. The liberal democracy is currently under threat, especially in the established democracies in Europe.

Eastern Europe is presently full of populist leaders who attack human rights and the rule of law while choosing nationalism over liberalism.  For example, the Visegrad countries are governed by populist parties, such as Viktor Orbán’s Fidesz in Hungary and Jarosław Kaczyński’s Law and Justice in Poland, which are also characterized by authoritarianism, attacks on the judicial independence and the free press, and nationalism.

Our OLS regression models offer an insight into the relationship between economic prosperity and human freedom in Eastern Europe. We find that better and freer institutions have a positive impact on economic growth and productivity in the selected countries.

Both human freedom and human capital are statistically significant determinants that have the most substantial influence on economic prosperity. These findings suggest that Eastern Europe should embrace liberalism and uphold human freedom to enhance growth prospects.

We encourage reform in this region oriented towards the values of liberalism and non-coercion, and respect for human rights and civil liberties.


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The paper was published in The Visio Journal No. 4. Cite the paper: Elena Makrevska Disoska and Katerina Shapkova Kocevska, “Human Freedom and Economic Prosperity: Evidence from Eastern Europe,” The Visio Journal no. 4 (December 2019): 37-48.


The article was originally published at: http://visio-institut.org/human-freedom-and-economic-prosperity/


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