VII. IPRI and Development
VII. IPRI and Development
The notion of development in its evolution has widened by incorporating dimensions and perspectives, weaving them into a multidimensional concept that nowadays includes economic, political, social, cultural, technological and ecological dimensions, for contemporaneous and future generations. Simultaneously, macro aggregates made way for micro details; the preponderance of averages demanded attention to deviations; quantitative indices were complemented with qualitative indicators; and objective evaluations gave up under subjective perceptions. Consequently, we have moved from those vertical plans to achieve ‘progress’ as a result, to open alternatives for expanding opportunities that allow individuals to achieve their goals in freedom.
This way, ethics is central to the analysis of the complexities of human social development, having received important theoretical contributions this century from Amartya Sen (1999) and Marta Nussbaum (2011). The body of work created by Sen and Nussbaum define development as the increase of human capabilities to achieve ‘development as freedom,’ providing a normative philosophical foundation for a theory of human rights, an essential requirement for a dignified life with social justice. According to them, ‘capability’ or ‘substantial freedom’ is the essential element of development. The central players in their model are human beings, how they assess their quality of life, and how they are able to make proactive efforts to improve their wellbeing. From this perspective, development does not refer to goods or services to which people have access, but rather to their ability to accomplish their goals in life. Therefore, the expansion of freedom is central to this approach (Levy-Carciente, S. et al. 2014)
With this in mind, and given the extensive literature that informs the important interactions between property rights and development, we analyzed in this edition different dimensions of development with the IPRI and its components, as follows:
VII.1. Economic Outcomes
Economic outcomes, obviously do not capture each factor of development. Many other factors are likely to influence it, however it is a first approach to it. Four economic elements are considered to evaluate the correlations with the IPRI and its components (for source details see Appendix IV):
The Gini coefficient is a statistical measure of the degree of variation represented in a set of values. When adjusting the GDP it captures income inequality (Source: World Bank).
Then we used the Pearson Correlation Coefficient, which is a measure of the linear dependence between two variables, to evaluate their correlations with the IPRI and its components. Most of the correlations found were significant and positively strong (see Table 9). We consider the following tranches or correlation ranges: None , Weak (0 - 0.3), Medium [0.3 - 0.5), Important [0.5 - 0.6), Good [0.6 - 0.8), Strong [0.8 – 1), Perfect .
GDP per capita correlations increased when it was adjusted by the Gini Coefficient, which is a measure of dispersion or inequality, giving to the GDP per capita a more adjusted measure in each country. This situation is valid for the IPRI and also for its components. The highest correlation was found for the IPRI and the adjusted GDP per capita (0.8392) followed by the IPR and the adjusted GDP per capita (0.8344) and the LP and the adjusted GDP per capita (0.8255).
Table 9: Pearson Correlation Coefficient
The relationship with domestic investments (Gross Capital Formation), showed for the LP a Pearson’s of 0.7672 followed by the IPRI (0.7636), the IPR (0.7073) and the PPR (0.6354) component.
Domestic production composition (Economic Complexity) exhibited also a high Pearson’s fit, IPR being the strongest with (0.7439), followed by the LP (0.7207), the IPRI (0.7204) and the PPR (0.5137) component.
Of all the items, the entrepreneurial environment was the one with the highest correlations in this order: LP (0.8861), IPRI (0.8781), IPR (0.8402) and PPR (0.6903). This finding points to entrepreneurship as a building block of innovation, investment, production and economic growth.
Figure 20 reports that, on average, countries in the top quintile of IPRI scores (i.e. top 20%) show a per capita income almost 13 times that of the countries in the bottom quintile. Even though it is an important disparity, it has improved in time as in 2016 that inequality was almost 21 times and in 2015 almost 24 times. Statistics are based on the averages of IPRI-2017 scores and corresponding data on average GDP per capita in USD constant terms (2010=100, source: World Bank data) for the last available year.
These results reinforce the significant and positive relationship between prosperity and a property rights system, measured at an individual level. The statistical dispersion of the GDP distribution in each country was considered in this analysis using the GINI coefficient, which improved the correlations.
Figures 19a an 19b display the best fit curve for the IPRI and its components with each economic variable and the coefficients of determination (R2). Figure 19a displays the relationship IPRI-economic outcomes showing countries with a population indicator. This reflects the huge proportion of population (represented by the radius of each circle) living in countries of middle level of IPRI and low to mid economic outcomes.
Figure 19a. IPRI Correlations with economic outcomes variables (with population information)
Figure 19b. IPRI Component Correlations with Economic Variables
Figure 20. Average Per Capita Income by IPRI Quintiles
Approaches such as human development, sustainable development, systemic competitiveness and the new institutional economics are valuable contributions to a development perspective that - following Heilbroner & Milberg – exposes the explicit indissoluble links between the economy and the underlying social order, relativizing its position, and recognizing that while development is possible, it is far from inevitable and may even be a reversible process.
Today, the reference paradigm is the one summarized as ‘development as freedom’, based on capabilities and opportunities, not on results. Under this new approach political, environmental and cultural dimensions, as well as subjective assessments are added to the traditional dimensions – such as technology and socioeconomics. Development as the increase of capabilities and opportunities becomes indissoluble from democracy and the republican condition of citizenship, valuing human rights, environmental sustainability, technological advance, emotions and cultures.
Through this perspective, the person moves from being a passive agent of decision-making and information reception to a genuine agent of change. These agents will be more active to the extent that they gain access to data and technology, and enjoy the guarantees for the free exercise of their freedoms in a given legal framework: A rule of law in which freedom has the unavoidable counterpart of responsibility.
To understand the relevance of liberties for development, the following elements were evaluated with the IPRI and its components:
IEF documents the positive relationship between economic freedom and a variety of positive social and economic goals. The ideals of economic freedom are strongly associated with healthier societies, cleaner environments, greater per capita wealth, human development, democracy and poverty elimination. (http://www.heritage.org/index/about). It is composed of 10 economic freedoms, within 4 categories:  Rule of Law (property rights, freedom from corruption);  Limited Government (fiscal freedom, government spending);  Regulatory Efficiency (business freedom, labor freedom, monetary freedom); and  Open Markets (trade freedom, investment freedom, and financial freedom). The IEF considers every component equally important in achieving the positive benefits of economic freedom. Each freedom is weighted equally in determining country scores
EFW measures the degree to which the policies and institutions of countries are supportive of economic freedom. In recent years, social scientists have focused on the identification and measurement of the impact of economic, political, legal, and cultural factors in the growth and development of economies. The EFW data set provides a comprehensive measure of the degree to which countries rely on voluntary exchange and market institutions to allocate resources. It has five dimensions:  Size of Government;  Legal System and Security of Property Rights;  Sound Money;  Freedom to Trade Internationally, and  Regulation. The EFW index covers 157 countries with data available for approximately 100 countries back to 1980. This data set enables scholars to analyze the impact of both cross-country differences in economic freedom and changes in that freedom across a time frame of more than three decades. (http://www.freetheworld.com/).
FW assesses the real-world rights and freedoms enjoyed by individuals, rather than governments or government performance per se. It is a result of a yearly survey that reports the degree of civil liberties and political rights in every nation and significant disputed territories around the world. It produces annual scores representing the levels of political rights and civil liberties in each state and territory, on a scale from 1 (most free) to 7 (least free). Depending on the ratings, the nations are then classified as "Free", "Partly Free", or "Not Free". (https://freedomhouse.org/report-types/freedom-world). It has two dimensions: Political Rights and Civil Liberties.
In its Political Rights Dimension countries and territories with a rating of 1 enjoy a wide range of political rights, including free and fair elections. Candidates who are elected actually rule, political parties are competitive, the opposition plays an important role and enjoys real power, lastly, the interests of minority groups are well represented in politics and government. On the opposite, countries and territories with a rating of 7 have few or no political rights because of severe government oppression, sometimes in combination with civil war. They may also lack an authoritative and functioning central government and suffer from extreme violence or rule by regional warlords.
In the Civil Liberties Dimension countries and territories with a rating of 1 enjoy a wide range of civil liberties, including freedoms of expression, assembly, association, education, and religion; they have an established and generally fair legal system that ensures the rule of law (including an independent judiciary), allow free economic activity, and tend to strive for equality of opportunity for everyone, including women and minority groups. At the other end, countries and territories with a rating of 7 have few or no civil liberties. They allow virtually no freedom of expression or association, do not protect the rights of detainees and prisoners, and often control or dominate most economic activity
The gap between political rights and civil liberties ratings is rarely more than two points. Politically oppressive states typically do not allow a well-developed civil society, for example, and it is difficult, if not impossible, to maintain political freedoms in the absence of civil liberties like press freedom and the rule of law.
HFI presents a broad measure of human freedom, understood as the absence of coercive constraint (based on the "negative" definition of freedom that prevents individuals from acting as they might wish), which includes economic freedom. It suggests that freedom plays an important role in human well-being, and offers opportunities for further research into the complex ways in which freedom influences, and can be influenced by, political regimes, economic development, and the whole range of indicators of human well-being. The index uses 76 distinct indicators gathered in two dimensions: personal (34) and economic (42) freedom, distributed in the following areas:  Rule of Law;  Security and Safety;  Movement;  Religion;  Association, Assembly, and Civil Society;  Expression;  Relationships;  Size of Government;  Legal System and Property Rights;  Access to Sound Money;  Freedom to Trade Internationally and  Regulation of Credit, Labor, and Business.
NRI measures the propensity for countries to exploit the opportunities offered by information and communications technology (ICT). The report is regarded as the most authoritative and comprehensive assessment of how ICT impacts the competitiveness and well-being of nations (http://reports.weforum.org/global-information-technology-report-2015). It is a composite index made up of four main categories (sub-indexes), 10 subcategories (pillars), and 53 individual indicators, as follows:  Environment (Political and regulatory environment (9 indicators) and Business and innovation environment (9 indicators));  Readiness (Infrastructure (4 indicators); Affordability (3 indicators) and Skills (4 indicators));  Usage (Individual usage (7 indicators); Business usage (6 indicators) and Government usage (3 indicators)) and  Impact (Economic impacts (4 indicators) and Social impacts (4 indicators)).
We found significant, positive and important to strong correlations between IPRI and its components with previous indices (Table 10). The strongest Pearson’s coefficient was with NRI, the closest fit with LP (0.881), followed by the IPRI itself (0.857), IPR (0.812) and PPR (0.678). The next closest score was the IEF, with good to strong correlations, then the HFI, EFW, FW-Civil Dimension and FW-Political Dimension. In all of these indices the highest correlations were with the LP component, followed by the IPRI itself, then IPR and finally the PPR component. PPR displays medium levels of correlations with HFI and FW. These results could be also seen in Figures 21a and 21b.
Political Freedom variables – Political Rights and Civil Liberties of the Freedom of the World Index by Freedom House are composed of numerical ratings running from 1-7, this way it could be considered a discrete item, therefore, it is not appropriate to evaluate correlations mathematically (Pearson’s correlation) as they generate tremendous dispersions and a correlation bias. However, this does not prevent conjectures based on their behavior related to the IPRI. In Figures 21a and 21b, the dot cloud generated by combining both measurements can be seen. In that sense, without having a mathematical measure of its correlation, a general positive linear relationship can be observed between political rights and civil liberties with property rights.
Table 10. Pearson Correlation Coefficients
Figure 21a. IPRI Correlation with Freedom measures (with population information)
Figure 21b. IPRI Component Correlations with Freedom Indices
VII.3. Human Capabilities
The pivotal element of the development equation is the people, and consequently their capabilities. For this dimension two elements were considered for evaluation:
Table 11. Pearson's Correlation Coefficients
Figure 22. IPRI Correlations with Human Capability Variables
The correlations found were significant and positive, they ranged from medium to good fits (See Table 11). The HDI showed higher correlations than the GIFE; and while the first is higher for LP (0.738) and followed by IPRI (0.679) and IPR (0.638), the GIFE is higher for IPR (0.610), as creative capabilities will be enhanced by the enjoyment of freedoms and for guarantees on intellectual property rights, followed by IPRI (0.605) and LP (0.59). The best fit curve for the indices and the coefficient of determinations is shown in Figure 22.
VII.4. Social Capital
Social capital has different definitions: it is understood as the network of relationships among people who live and work in a particular society, enabling that society to function effectively; or to undertake collective social action. Social capital is built upon trust, reciprocity, cooperation, assistance, support, interdependence, interaction, dialogue, involvement and participation (Jaffé, Levy-Carciente & Zanoni, 2007). Given the importance of having people as the axis around which the development concept and policies should rotate the Social Capital sub-index of the Prosperity Index by Legatum (http://www.li.com) and a group of variables from the International Institute of Social Studies (http://www.indsocdev.org) were used to assess the relationship between social capital and the IPRI:
We evaluated their correlation with the IPRI and its components (see Table 12 and Figure 23) and the strongest correlations were found between Civic Activism and the IPR (0.8098) followed by the IPRI (0.8013) and the LP (0.7995). The Social Capital component of the Prosperity Index by Legatum showed good correlations with the IPRI (0.747), LP (0.711), PPR (0.694) and the IPR (0.685). Interpersonal Safety & Trust, Inclusion of Minorities and Intergroup Cohesion displayed good correlations (0.6-0.8), especially with LP and IPRI.
Table 12. Pearson's Correlation Coefficients
Figure 23. IPRI Correlations with Social Capital
VII.5. Research and Innovation
In a 'knowledge society' structures and processes of material and symbolic reproduction are so immersed in knowledge operations that information processing, symbolic analysis and expert systems take precedence over other factors like capital and labor. Hence, innovation is a key block in a knowledge society. Using the World Bank data for research and innovation (http://wdi.worldbank.org/) we ran correlations of the IPRI and its component with three items:
The number of researchers engaged in R&D had the highest correlation, it was with the IPR component (0.796), followed by the IPRI (0.761) and LP (0.752). Then comes the correlation between R&D expenditure and the IPR (0.758), followed by the IPRI (0.685) and LP (0.635). The PPR showed medium correlations with R&D expenditure. The number of published scientific papers showed positive but weak to moderate correlations.
Table 13. Pearson's Correlation Coefficients
Figure 24. IPRI Correlations with R&D Variables
VII.6 Ecological Performance
The ecological environment is decisive for sustainable development. It is referenced in the recent Paris international climate change agreement dealing with greenhouse gases emissions mitigation, adaptation and finance starting in the year 2020. Given ecological performance relevance, we ran correlations of the IPRI with the Environmental Performance Index, developed by Yale University (EPI-Yale):
Table 14. Pearson's Correlation Coefficient
We found important positive correlations among the EPI and IPRI and its components being the strongest with LP (0.648) and the lowest with PPR (0.395). These results may indicate that to the extent that a society has stronger property rights the more capacity it has to apply appropriate policies protecting health and the environment through the conservation and protection of the ecosystem.
Figure 25. IPRI Correlations with Ecological Measurements
 Same result can be found at: http://marketmonetarist.com/2015/12/01/coase-was-right-the-one-graph-version/, following that well defined property rights are the best way to manage economic externalities.
 Jaffé, K.; S. Levy-Carciente; W. Zanoni. 2007. "The Economic Limits of Trust: The Case of Latin-American Urban Informal Commerce Sector" Journal of Developmental Entrepreneurship, Vol. 12, Sep(3):339-35.
 Heilbroner, R., & W. Milberg. 1998. La crisis de visión en el pensamiento económico moderno. Barcelona: Paidós
 These variables run in opposite direction of the IPRI. For this reason their direction was adjusted.
The coefficient of determination (R2) is a key output of the regression analysis. It is interpreted as the proportion of the variance in the dependent variable that is predictable from the independent variable. It ranges from 0 to 1.
 Sen, Amartya. 1999. Development as Freedom. Oxford: Oxford University Press.
 Nussbaum, Martha C. 2011. Creating Capabilities: The Human Development Approach. Cambridge: Harvard University Press
 Levy-Carciente, Sary et al. 2014. "From Progress to Happiness: Measurements for Latin America". Social Change Review, Summer 2014, Vol. 12(1): 73-112. DOI: 10.2478/scr-2014-0004
Correlation theory is aimed to show the possible relationship, association or dependence between two or more observed variables. Besides it allows for the analysis of the type of association (direct or indirect) and the level or degree of intensity between them.