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1 June 2019

“Ye Shall Know Them by Their Fruits”: Prosperity and Institutional Religion in Europe and the Americas †

Swiss-Latin American Center (CLS-HSG), University of St. Gallen, CH-9000 St. Gallen, Switzerland
“Ye Shall Know Them by Their Fruits”: The Holy Bible, King James Version (Cambridge Edition, 1769). Scripture quotations from The Authorized (King James) Version. Rights in the Authorized Version in the United Kingdom are vested in the Crown. Reproduced by permission of the Crown’s patentee, Cambridge University Press.
This article belongs to the Special Issue Poverty and Wealth in Biblical and Global Contexts

Abstract

Low competitiveness is a common denominator of historically Roman Catholic countries. In contrast, historically Protestant countries generally perform better in education, social progress, and competitiveness. Jesus Christ described the true and false prophets coming on his behalf, as follows: “Ye shall know them by their fruits”. Inspired by this parable, this paper explores the relations between religious systems (‘prophets’) and social prosperity (‘fruits’). It asks how Protestantism influences prosperity as compared to Roman Catholicism in Europe and the Americas. Most empirical studies have hitherto disregarded the institutional influence of religion. Taking the work of Max Weber as their starting point, they have instead emphasised the cultural linkage between religious adherents and prosperity. This paper tests various correlational models and draws on a comprehensive conceptual framework to understand the institutional influence of religion on prosperity in Europe and the Americas. It argues that the uneven contributions of Roman Catholicism and Protestantism to prosperity are grounded in their different historical and institutional foundations and in the theologies that are pervasive in their countries of influence.

1. Introduction

Institutions play a crucial role in the prosperity of societies. Historical evidence shows that institutions are shaped by cultural variables and vice-versa (Acemoglu and Robinson 2012; Inglehart and Baker 2000; Alesina and Giuliano 2015). In the Americas, these institutional relations can be traced back to European colonisation (Engerman and Sokoloff 2002), and religion has underpinned the cultural values that shape institutions.
At least two dimensions of religion’s influence on prosperity are worth close attention: the institutional and the cultural (Manow 2002, p. 9). However, most empirical works studying religion as a key determiner of prosperity have merely paid scant attention to the institutional effects of religion. Instead, they have mainly concentrated on the cultural influence of religious affiliations (often using the proportion of adherents as a sole indicator of religion) (Acemoglu et al. 2001; La Porta et al. 1999; Hofstede 2001).
This traditional research paradigm, which focuses on the cultural influence of religion, stems from Max Weber’s groundbreaking The Protestant Ethic and the Spirit of Capitalism (Weber 1905). Weber argued that the Protestant Reformation initiated modern capitalism and that Protestant societies economically outpaced Catholic ones (Weber 1905, p. 133). His assertion, that religion exerts a cultural influence on prosperity through a particular work ethic, has been fiercely criticised over the last century. To this day, the ensuing debate has remained polarised. Numerous quantitative studies have linked religion and prosperity indicators, either supporting (mainly on the cross-country level) or refuting (mainly on the sub-national level) Weber’s basic claim (see, among others: Granato et al. 1996; Hayward and Kemmelmeier 2011; Delacroix and Nielsen 2001; Cantoni 2009; Di Matteo 2015).
Typically, cross-country empirical approaches have ignored decisive Church–State power relations. For instance, the historical agreements (concordats) between individual countries and the Roman Catholic Church–State have been neglected. Moreover, the sociological explanations in several empirical studies are often either Weberian or purely hypothetical, neither further developed nor related to other disciplines and historical sources. An obvious hiatus is evident in the sociology of religion. Critical approaches are lacking, in particular, that is, ones that take “issues of domination and inequality seriously” (Hjelm 2014, p. 857).
This restricted scope means that the interrelations between prosperity and religion tend to be trivialised or misunderstood when analysing religion as a development factor. For instance, Acemoglu and Robinson (2012) criticised Weber’s theory of Protestant ethics as one that “does not work”. Likewise, Hofstede (2001) stated that economic industrialisation brings people to believe in more “inclusive” religious systems, such as Protestantism, yet not vice versa. However, such an approach is ahistorical (see Table 1).
Table 1. Historical timeline of some key religio-political events in Christendom (Source: Author’s chart; based on the theoretical framework of this study). Among others, sources include Woodberry (2012), Miller (2012), Acemoglu et al. (2011), Snyder (2011), Bruce (2007), Berman (2003), Witte (2002), Heussi (1991), D’Aubigne (1862), and Eusebius of Caesarea (ca. 340 AD).
Protestantism not only broke the political (as well as the institutional and economic) hegemony of the Roman Catholic Church–State, but also arrested its growing influence in Europe. The modern state and secular institutions emerged from these processes (which later also influenced democracy, the American Constitution, and the French and Industrial Revolutions) (Snyder 2011; Woodberry 2012; Becker et al. 2016; Witte 2002) (see Table 1 and Section 7).
Recent research largely confirms the Reformation’s key role in Europe’s economic and political trajectory, although for very different reasons than those highlighted by Weber (Woodberry 2012; Becker et al. 2016, p. 22). Thus, the notion of a “better” Protestant work ethic might grossly oversimplify an intricate question: Why do Protestant societies have better prosperity indicators than Roman Catholics or Orthodox ones? This paper argues that a particular work ethic is, at best, no more than one of many contributing factors.
La Porta et al. (1998) found that hierarchical Christian religions (i.e., Orthodoxy or Roman Catholicism) unfavourably affect social development. In contrast, various factors account for the robust empirical associations between Protestantism and prosperity: the rise and spread of education and printing (Becker and Woessmann 2009; Androne 2014); the development of democratic institutions (Woodberry 2012); and, the weakening of hierarchical structures (La Porta et al. 1999; Volonté 2015). Therefore, the effects of Christianity on prosperity vary depending on the different institutional emphases that a dominant religious denomination places on a given society.
Insights from disciplines, such as political science (Manow and van Kersbergen 2009), international relations (Snyder 2011), or law (Witte 2002; Berman 2003), have been crucial to understanding the institutional influence of religion on prosperity patterns. Yet, these findings have often not been integrated into the array of explanations that are provided by empirical studies associating religion and prosperity. Therefore, it is necessary to build a comprehensive transdisciplinary theory based on the findings of different disciplines. In turn, this will enhance their explanatory power.
This paper seeks to establish such “synthesised coherence” by interconnecting “work that previously had been considered unrelated” (Golden-Biddle 2007, p. 33).
Christianity has been central to Western civilisation. Nevertheless, the diverse historical trajectories of the various Christian denominations first established and later determined different sets of societal norms and institutions. This study explores the institutional influence of Christianity on prosperity in present-day Europe and the Americas. It is part of extensive doctoral research on qualitative prosperity models and detailed case studies. Therefore, some sections contain “empirical expectations” for further research.
This paper has nine sections: Section 2 presents the research model. Section 3 defines prosperity as a concept linked to competitiveness in the countries studied and associated with biblical notions. Section 4 briefly diagnoses prosperity in Europe and the Americas and establishes that historically Protestant countries perform better than Roman Catholic ones. Section 5 studies the prosperity-religion nexus, reviews some leading empirical works, and shows the influential and often disregarded role of institutional religion on prosperity. Section 6 discusses institutions as prosperity triggers. Section 7 examines the historical influence of religion on different legal traditions in Europe and the Americas. Section 8 presents the materials and methods that were used. Section 9 discusses the empirical results, while Section 10 offers some concluding remarks.

2. Research Model

Figure 1 synthesises the logic underlying this study by interrelating the factors and variables of interest. This model, which structures this paper, is of course not exhaustive. Some variables or conditions are embedded within others, and vice versa (see Supplementary Materials).
Figure 1. Research model of this study (Source: Author’s figure). Note: Arrows and numbers indicate potential causal relations, based on which prosperity (A), religion (B), and institutions (D) are theoretically explored in Section 5, Section 6 and Section 7.
The variables and factors that are considered in this study are interdependent. This integration helps reconcile previous, mutually exclusive disciplinary approaches. It also highlights the need to explain the religion–prosperity nexus through the interlinkages between diverse factors, theories, and disciplines, rather than through mono-causal explanations of prosperity. The neo-classical economic approach hithero prevalent in the literature considered history, geography, ecology, and culture (including religion and social norms) as “residuals”, thus leaving little room for explicit modelling of these features (Michalopulos and Papaioannou 2017).
Each of these separate theories may contain “a grain of truth” in understanding prosperity imbalances across countries (Moran et al. 2007, p. 3). For example, geography and environment theories explain how seasonal lands may provide better conditions for developing a society and its economy (Diamond 1997; Sachs 2001). Institutional theory has explained how institutions model the prosperity of societies and perpetuate equality loops or concentrations of wealth (North 1990; Acemoglu and Robinson 2012). Cultural theory has focused on how cultural variables (that traditionally include religion) influence prosperity (Landes 1999; Hofstede 2001).
However, some relations are not studied here, since they are less relevant (e.g., environmental influences on culture, and vice-versa. This paper does not theorise the influence of environment and geography, language, and ethnicities on prosperity for reasons of scope, although some of these factors appear in the empirical results. It instead considers the sociology of religion and theological disciplines through an institutional and legal lens. Finally, it also draws on international relations, political science, law, and economics.

3. Outcome: Prosperity and the Global Competitiveness Index (GCI)

This paper defines prosperity in its broader sense, success in general, rather than in purely economic terms (i.e., GDP). Therefore, it links the concepts of “prosperity” and “competitiveness” (GCI), which both result from related identical conditions. The World Economic Forum has developed the Global Competitiveness Index (GCI) as a comprehensive proxy of prosperity tracking the performance of nearly 140 countries in terms of twelve categories: institutions, technological readiness, innovation, higher education and training, health and primary education, business sophistication, infrastructure, macroeconomic environment, labour market efficiency, market size, financial market development, and goods market efficiency. The World Economic Forum identified such categories as determinants of productivity through empirical and theoretical research, which in turn is the primary determinant of economic growth and prosperity (World Economic Forum 2014).
Thus, the World Economic Forum (2014) defines competitiveness as “the set of institutions, policies and factors that determine the level of productivity of a country. The level of productivity, in turn, sets the level of prosperity that can be reached by an economy.” (p. 4). Consequently, prosperity and competitiveness (GCI) are here often used indiscriminately.
The GCI is a highly comprehensive measure that places countries on an objective scale of prosperity. The fact that institutions, education, transparency, and other factors are already included within the GCI (or prosperity) presents a significant advantage for studies like this one. First, close theoretical and empirical relations exist among these variables. Accordingly, they all belong to the same kind of “prosperity phenomenon” (GCI). Consequently, their causality requires no further discussion, as they are not isolated but aggregated in the GCI. Second, such aggregated factors (GCI) allow for focusing on other (exogenous) determinants of the “competitiveness phenomenon”. Therefore, this paper focuses on the potential exogenous variables that are not included in the GCI (e.g., legal origin and state religion, as background proxies of the influence of religion on institutions).
“Prosperity” is often associated with obeying moral commandments throughout the Holy Scriptures (see Table 5). For instance, “Keep therefore the words of this covenant, and do them, that ye may prosper in all that ye do” (Deuteronomy 29: 9, King James Version). The opposite (the consequence of disobedience) relates to misfortunes: “if thou wilt not hearken unto the voice of the Lord thy God, to observe to do all his commandments and his statutes which I command thee this day; that all these curses shall come upon thee, and overtake thee” (Deuteronomy 28: 15).
Protestant countries have applied the moral principles of the Decalogue in their legal systems (Table 5). In contrast, Catholic countries have mostly based their legal systems on Roman and Canon law, which mostly derives from the Catholic Sacraments and Greek philosophy, rather than from the biblical commandments (Table 4).
The next section finds clear distribution patterns of prosperity in the countries that are studied here: high competitiveness, in countries with a Protestant tradition, and lower competitiveness in countries with a Roman Catholic or Orthodox background.
Empirical expectation: Countries applying the Sola Scriptura principle of the Protestant Reformation may be expected to exhibit higher prosperity rates than others. Such application should be reflected in Protestant-influenced legal origins (i.e., German, English, or Scandinavian).

4. Diagnosis: Prosperity in Europe and the Americas

A review of prosperity indicators in Europe and the Americas reveals that historically Protestant countries have done better than predominantly Roman Catholic ones (Inglehart and Baker 2000; Becker et al. 2016; La Porta et al. 1999).

4.1. Competitiveness (GCI) in Europe and the Americas

Switzerland achieves the highest competitiveness score worldwide. Next, the so-called “advanced economies” are in the top 90–100% (United States, Canada, Australia, New Zealand, Northern Europe). The 70–80% most competitive countries include Italy, Spain, Portugal, Austria, and Ireland. Latin America and the Caribbean countries rank among the 40–80% most competitive (World Economic Forum 2014) (see Supplementary Materials for details).

4.2. Social Progress in Europe and the Americas

Economic performance alone (GDP) does not fully explain social progress (variables correlate 0.78) (Porter et al. 2015). The Social Progress Index (SPI) is a comprehensive framework for measuring social progress independently of, and complementary to, GDP. The SPI is a robust and holistic framework for determining national social and environmental performance (Porter et al. 2015).
Norway, Sweden, and Switzerland score the highest SPI rates in the world (around 88 each). Mediterranean countries score around 80. All Latin American countries reach average distribution scores, which range from 79 (Uruguay) to 60 (Guyana) (Ibid).
Figure 2 shows the differences in SPI scores in the Americas. Following the historical trend, Canada and the United States have better prosperity conditions (i.e., SPI and GCI) than all Latin American countries. Uruguay exhibits the highest SPI value in Latin America.
Figure 2. Social Progress Index in the Americas in 2015; amended from Porter et al. (2015)1.
Except for some countries (e.g., Uruguay and Chile), the SPI and GCI confirm an old view: “…Latin America is, after all, the only part of the world which is both Christian and underdeveloped” (Levine 1981, p. 35). The next section addresses the prosperity-religion nexus as a feature that help to better explain the imbalanced SPI and GCI differences among countries.

5. Prosperity and Religion

The link between prosperity and religion is undeniable. For instance, in the United States—the second most competitive country worldwide according to the World Economic Forum (2014)—, religion accounts for almost one-third of the national GDP (USD 4.8 trillion annually; Grim and Grim 2016). Only the revenues of faith-based organisations in the US (USD 378 billion annually) represent more than the global annual revenues of Apple and Microsoft combined (Ibid.).
However, empirical research regarding prosperity determinants typically neglects the influence of religion (McCleary and Barro 2003, p. 760). As a determinant, religion suffers from similar mainstream disregard in other disciplines, such as law (Berman 2003; Witte 2002), international relations (Snyder 2011), or political science (Manow and van Kersbergen 2009).

Institutional Influence of Religion on Prosperity

The institutions and cultural values of historically Protestant countries considerably differ from Roman Catholic, Orthodox, or Islamic societies. The enduring effects of Protestantism on prosperity in Europe today, for instance, owe more to the institutional influence of religion in the longue durée than to the number of its adherents, which has significantly diminished over time (Inglehart and Baker 2000, p. 49). For instance, Protestantism’s association with prosperity is partly explained on its historical focus on education and human capital building (Becker and Woessmann 2009).
The interactions between institutions and culture have partly determined the prosperity of nations. Empirical evidence suggests that causality exists in both directions. Culture may change in different ways, depending on the type of institutions, while institutions may work differently, depending on the cultural context (Alesina and Giuliano 2015, p. 938).
Therefore, the entangled cultural and institutional influences of religion sometimes complicate empirical differentiation (Barro and McCleary 2005). However, religion cannot be reduced to the proportion of adherents, although most of the literature on religion as a prosperity determinant has been largely confined to this indicator.
Barro and McCleary (2005) developed an empirical approach to institutional religion in their classification of “State religion”. However, “State religion” is mostly also related to population adherence and it does not account, for instance, for the international agreements (i.e., concordats) between the Roman See and individual countries.
A key feature of other relevant studies (Becker and Woessmann 2009; Becker et al. 2016; Woodberry 2012; Gill 1998) has been to identify how Protestantism has destabilised the institutional hegemony of Roman Catholicism. This has proven more important than the effects of religious believers per se.
Becker et al. (2016) concluded that Protestantism encouraged a wide range of societal developments, based on their comparative examination and state-of-the-art systematic synthesis. Overall, most empirical studies on the consequences of the Reformation associate it with the positive development of governance and the economy. Subsequently, most empirical studies confirm the positive impact of Protestantism on prosperity based on different variables and on various spatial and temporal configurations (Becker et al. 2016).
Economic prosperity has been robustly linked with secularisation and declining levels of religiosity (Barro and McCleary 2003; Inglehart and Baker 2000). Secularisation precedes economic growth, which means that prosperity has not caused secularisation in the past (Ruck et al. 2018). Section 7.3.4 discusses Protestantism as an institutional precursor of secularism.
Thus, most empirical findings to date contradict the prevailing Roman Catholic ideology, which has insisted (however, without providing empirical evidence) on restoring what it praises as a “prosperous and peaceful medieval society” (Restrepo 1939; Ratzinger and Pera 2006). Medieval Christianity allowed for the Roman Church–State to create a theocratical order, in which papal power established a hierarchical society where spiritual power prevailed over temporal power. This Roman Catholic ideal means that the ecclesiastical hierarchy determines the legal principles and basic norms of collective life (Figueroa 2016, p. 155). This perspective calls for reviewing the distinct institutional ideologies of historical Protestantism and Roman Catholicism as the roots of their differences.

6. Institutions as Triggers of Prosperity

Institutions are “the rules of the game in a society” (North 1990, p. 3). They can be either formal (i.e., official and openly codified; e.g., constitutional laws) or informal (i.e., unwritten or socially shared rules) (Helmke and Levitsky 2004). Informal institutions are frequently more persistent than the formal ones (North 1997) and they pertain to how laws are enforced (Woodruff 2006).
The quality of institutions has been theoretically and empirically linked to prosperity (and thus also to transparency) outcomes (North 1990; La Porta et al. 1999; Acemoglu et al. 2001; Acemoglu and Johnson 2005; Acemoglu and Robinson 2012; Williamson 2000). Such studies have credibly associated empirical evidence and theory. Therefore, institutions are widely accepted as playing a determinant (causal) role in the prosperity of societies even if alternative interpretations exist (Woodruff 2006).
However, several problems arise when considering institutions inter alia as triggers of prosperity:
  • Scant agreement exists on how to empirically measure formal or informal institutions. Different studies measuring institutions with varied methods measure different things. Sometimes, even gauging the outcome in isolation from other factors is challenging (Woodruff 2006).
  • Endogeneity issues plague the causal approaches of institutions to prosperity, although, to a lesser extent, the effect of political institutions on transparency. However, previous treatments of endogeneity have not been convincing (Persson and Tabellini 2003; Woodruff 2006; Kunicová 2006).
  • It is not entirely clear which institutions are fundamental to prosperity-transparency processes (Woodruff 2006, p. 106).
  • Formal institutions have little effect on broad prosperity outcomes. However, informal institutions matter and they have a more significant effect (Glaeser et al. 2004; Woodruff 2006; Treisman 2000).
  • Although quite strong associations often exist, the causal arrow may point in both directions (from prosperity/transparency to institutional choice and from institutions to prosperity/transparency) (Rose-Ackerman 2006, p. xxv).
  • Informal institutions are the most difficult to measure (and change), since they are largely determined by history (Woodruff 2006, p. 121).
Thus, research on institutions and prosperity/transparency has not provided conclusive evidence of causality. The strongest evidence relates to the impact of underlying social structures (informal institutions), which is highly difficult to address, both in prospective and in policy terms (Lambsdorff 2006; Woodruff 2006; Rose-Ackerman 2006).
In practical terms, institutions and transparency/trust may all have coincided with prosperity, as empirical evidence exists for arguing causality in both directions (Fukuyama 1995; Uildriks 2009; Morris 2003; Armony 2004). Therefore, prosperity, transparency (corruption’s opposite), trust, and institutions are inseparable concepts. Ethical transparency/trust values promoting institutional stability and prosperity is one causal cyclical logic that might be expected (Fukuyama 1995).
History and culture have shaped current institutional structures (Acemoglu et al. 2001; Acemoglu and Robinson 2012; Rose-Ackerman 2006). At the same time, empirical evidence also shows that institutional structures shape cultural values (i.e., trust and civic norms) (Uildriks 2009, p. 7); (Alesina and Giuliano 2015). In any event, religion has played a crucial role in corroborating both cultural values and institutions (Arruñada 2009; Manow 2002; Paldam 2001; Treisman 2000; Inglehart and Baker 2000).
Acemoglu and Robinson (2012) have explained how inclusive institutions create inclusive markets, incentives, and opportunities for prosperity. Inclusive institutions create positive feedback loops, which prevent an elite’s efforts to undermine them. However, throughout its history, Latin America has experienced a negative institutional feedback loop, which has perpetuated corruption, mistrust, and elitist-extractive institutions (Acemoglu and Robinson 2012; Uildriks 2009).
If political institutions are key (Acemoglu and Robinson 2012), who creates them? Lawyers and policy makers have moral and religious backgrounds (i.e., historically, these are predominantly Protestant in North America and Roman Catholic in Latin America). However, the influence of such values, but, more importantly, the institutional influence of the Church on those elites, is neglected in such works.
On this evidence, it is therefore essential to recognise which revolutions created better institutions. We also need to ask which triggers changed an old regime into a new status quo. Thus, countries that had not fully adopted the principles of such revolutions preserved elements of the old regime. These notions are explored below.

8. Materials and Methods

The quantitative part of this study consists of correlational research. This involves testing some prominent prosperity theories that are based on investigating the relationships between diverse variables. Rather than seeking to prove causation, instead, this section empirically explores whether institutional religion or a population’s religious affiliation are related to competitiveness.
Several analyses were conducted to generate different explanatory models, and thereby to determine the most critical variables in the datasets. This quantitative part is correlational, not experimental (causal). Thus, the importance of individual variables is based on their explanatory power, not on causal relations.3
This section comprises three subsections. The first overviews the process of modelling competitiveness (GCI). The second contains the methodological protocols. The third presents the empirical results of the correlational analysis of GCI.

8.1. Data, Population, and Empirical Strategy

The countries that were studied here were selected based on data availability. Data come either from constructed or from secondary (i.e., existing) sources that are available in public databases. Further, data consist of censuses of currently available indicators for the following cross-country analyses (see Supplementary Materials).

8.2. Modelling Competitiveness (GCI) (Phases 1 and 2)

Several variables that are associated with theories of prosperity (see Supplementary Materials) were modelled as possible exogenous determinants of competitiveness in most countries worldwide.4 For example, the Environment Performance Index (EPI) is linked to geographical and environmental determinants, while religion (adherents) is related to cultural and Weberian theory. State religion and legal origins are proxies of the institutional influence of religion. The possible different contributions of those variables were tested to explain the variation in competitiveness (GCI).
The next generation of models focused on countries in Europe and the Americas, i.e., the two continents under study. Finally, the subsequent generation of models isolated the influence of variables, such as state religion and share of population adherents on different religious affiliations. Such isolation ought to benefit model fitness, as these variables are related (Barro and McCleary 2005) and might overfit the model.
Phase 1. Worldwide (107 countries): The database comprises data series available on competitiveness, corruption, social inequality, as well as other social, environmental, and economic indicators. It also includes indicators of denominational tradition and religious background for most of the surveyed countries.
Phases 2 and 3. Europe and the Americas (66 countries): Cases with straightforward data access for most variables in Europe and the Americas.5 Christianity has been the dominant religion for at least the past two centuries in Europe and the Americas, unlike in other regions. The majority of these continents’ populations currently adhere to Roman Catholic, Orthodox, or Protestant churches of various denominations (Johnson and Zurlo 2016).

Protocol

A twelve-step protocol was followed (summarised below):
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Step 1 aimed to include as many countries as possible in the database. However, the same data were not available for all the observed variables. Thus, some variables (e.g., GLOBE cultural index) (Center for Creative Leadership 2014) were excluded from analysis, as the corresponding data were only available for a sample of three dozen countries. Where less than 25% of values were still missing in the remaining dataset, they were imputed while using Multivariate Imputation by Chained Equations in R (mice).
Step 2 involved using automated functions to help select a high number of variables (see above) from different theoretical backgrounds (see Supplementary Materials). Although the results of an automated model search may be arbitrary, about 40 of these models were created while using different approaches to eliminate path-dependence and bias.
Step 3 sought to meet linear regression assumptions in all of the models. The assumptions were tested in a continuous process whenever a new model was created. Among other assumptions, checking the Variance Inflation Factor (VIF) and the correlation value tested for multicollinearity. VIF results refused multicollinearity and, along with low correlation values, suggest that these variables are orthogonal. Likewise, all the significant correlations among the predictor and criterion variables were controlled for.
Step 4 involved using cross-validation based on the prediction quality of shuffled groups of observations. Models and variables exhibiting the best prediction ability were selected. “Step” is an automatic method that is based on the R function step (), which is also used to perform variable selection. These methods are useful when the number of explanatory variables is large, and when fitting all of the possible models proves to be unfeasible (University of Columbia 2017).
Step 5 involved Beta standardisation, which is necessary for comparing the size of influence between variables. This indicates the significance of each variable in the context of others (and thus facilitates comparison). However, the goal is not to test significance in this step. Nor can Beta standardisation be computed for interaction variables (see the “Standardised” column in the Results).
In Step 4, Model 1 (see Results), two selected variables that might potentially outshine each other were analysed: religious denomination (proportion in population) and state religion. Consequently, separate models were run to isolate these variables in Step 6.
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Europe and the Americas exhibited higher data quality and availability. Consequently, there was no need to impute data as in the world models (Phase 1: Models 1, 2, and 3). Therefore, stable regional models with higher reliability (i.e., avoiding data imputation and thus reducing bias) were created (Phase 2: Models 4 and 5).
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Step 7. Data availability issues meant that some countries were excluded (e.g., most of the small island states in the Caribbean). Step 8 resembled steps 2, 3, and 4, while step 9 was similar to step 5.

9. Empirical Results (Correlational Analysis)

9.1. Phase 1: Competitiveness in the World

The analysis of competitiveness as a criterion variable associates different predictor variables usually corresponding to theories of prosperity. Model 1 (Table 7) was chosen from more than 30 models, as it exhibits the greatest cross-validation and satisfactorily explains GCI variability.
Table 7. Model 1. Competitiveness in the world (Author’s figure).

9.1.1. Model 1

G C I i = β 0 + β 1 EPI i + β 2 M u l a t t o i + β 3 A s i a n i + β 4 Protestant_St.Rel i + β 5 Catholic_pop i + β 6 Orthodox_pop i + β 7 Protestant_pop i + β 8 Muslim_pop i + β 9 German_LO i
Coefficients:
Positive Correlations
The most significant variable is the Environment Performance Index (EPI), which highly positively correlates with competitiveness GCI (0.72). If EPI were removed from the model, R squared would drop by 17%. However, the same model without EPI exhibits similar results to Model 1 (Table 7) for the remaining variables. Here, an increase of EPI by one point is associated with a GCI growth of 0.026 points. EPI occupies larger units (mean value 70) than GCI (mean value 4) (the scale is standardised, i.e., these values refer to the non-standardised ranges; see Supplementary Materials).
A second important variable that is positively related to competitiveness (GCI) is the German legal origin: “GERMAN (LO)”. On average, such countries have a higher GCI (by 0.229).
Third, if Protestantism were the state religion “PROTESTANT (S.R)” (e.g., United Kingdom (UK), Sweden, Denmark), then the overall effect on GCI would be positive. Establishing Protestantism as a state religion leads to a GCI increase of 0.223, which is far greater (almost double) than for a highly Protestant population. This confirms the higher importance of the institutional influence of religion as compared with the influence of the proportion of adherents (see Section 5, Section 6 and Section 7).6
Negative Correlations
All of the variables related to religion distribution in a population—Catholics (%), Orthodox (%), Protestants (%), and Muslims (%)—are negatively correlated with GCI, although these correlations are only marginally significant. Nonetheless, the Orthodox population causes the most substantial negative effect. If the share of the Orthodox population increased by 1%, then GCI would decrease by 0.0078 units. The same goes for changes in the Roman Catholic population, where a 1% increase would mean a GCI decrease by 0.0057. Similarly, if the share of the Protestant population increased by 1%, then GCI would decrease by 0.0054. Finally, if the share of the Muslim population increased by 1%, GCI would decrease by 0.0047. On the other hand, the Mulatto and Asian ethnical values both have a negative effect. A growth of 1% in the mulatto/Asian population means a 0.00117/0.00194 decrease in GCI, respectively.
Models Analysing Major Religious Population Groups or State Religions Separately
Model 1 (Table 7) has shown a differential influence of religion distribution in a population and of state religion on GCI. Models 2 (Table 8) and 3 (Table 9) were run to separate any potential differential influence. Separate analysis of the two variables eliminates the possibility of religious population distribution and state religion “overfitting” the model.
Table 8. Model 2. Competitiveness in the world including the percentage of religious adherents and excluding state religion variables (Author’s figure).
Table 9. Model 3. Competitiveness in the world including state religion and excluding the percentage of religion adherents (Author’s figure).

9.1.2. Model 2 (Population Percentages)

Model 2 (Table 8) shows the relation between the percentage of religious adherents and competitiveness, while excluding state religion variables.
G C I i = β 0 + β 1 EPI i + β 2 Caucasian i + β 3 M u l a t t o i + β 4 A s i a n i + β 5 D o g m a s i + β 6 S o c i a l i s t i   + β 7 German i + β 8 Catholic_pop i + β 9 Muslim_pop i + β 10 Orthodox_pop i
Coefficients:
This model (Table 8) confirms the findings of Model 1 (Table 7) in the same order:
1. EPI is the most significant variable.
2. Increasing Orthodox, Catholic, and Muslim populations negatively influence GCI. However, neither Protestant population nor other Christian adherents are significant in Model 2.
3. Model 2 confirms the direction and influence of most other variables in Model 1. However, in Model 2, Caucasian ethnic values positively influence GCI. Likewise, Dogmas and Socialist legal origin negatively impact GCI.

9.1.3. Model 3 (including State Religion)

Model 3 (Table 9) excludes the percentage of religion adherents variables. State religion variables alone explain most of the variability otherwise explained by religious population.
G C I i = β 0 + β 1 EPI i + β 2 Caucasian i + β 3 M u l a t t o i + β 4 A s i a n i + β 5 Catholic i + β 6 Protestant i + β 7 S o c i a l i s t i + β 8 German i
Coefficients:
The results of Model 3 (Table 9) ratify those of the previous models. The most significant positive influence on GCI comes from EPI, Protestant state religion, Caucasian ethnicity, and German legal origin. In contrast, Asian and Mulatto ethnicities, Roman Catholic state religion, and Socialist legal origin negatively affect GCI.

9.2. Phase 2: Modelling Competitiveness (Europe and the Americas)

The following models were explicitly produced for Europe and the Americas and they exclude the noise in the world database. Models 4 and 5 compare whether the same variables chosen in the previous “world” models are still significant in Europe and the Americas.

9.2.1. Model 4: Results of Cross-Validation

G C I i = β 0 + β 1 H o s t i l i t i e s i + β 2 German_lan i + β 3 Catholic_pop i + β 4 Orthodox_pop i + β 5 EPI i
Coefficients:
This result shows the high robustness of this model (Table 10), in that it explains almost 66% of GCI variability with four significant variables at a 99% confidence level:
Table 10. Model 4. Competitiveness in Europe and the Americas (cross-validation method) (Author’s figure).
1. EPI is the most important variable because it accounts for most of GCI variability. The increase in EPI by one percentage point is related to “GCI” growth of approximately 0.038 percentage points.
2. The second most important variable is Orthodox population, which exerts the most substantial negative effect in the model. If the Orthodox population increased by one percentage point, GCI would decrease by approximately 0.010 percentage points.
3. Similarly, the effect of the Roman Catholic population also negatively influences competitiveness. If the Roman Catholic population increased by one percentage point, then GCI would drop by approximately 0.005 percentage points. This finding, along with the previous one (2), are consistent with La Porta et al.’s (1999) conclusions regarding the negative influence of hierarchical religions on prosperity.
4. Finally, the proportion of the German-speaking population positively affects GCI. An increase of one percentage point in the German-speaking population would mean a GCI increase by approximately 0.008 percentage points.

9.2.2. Model 5: Results with Step

G C I i = β 0 + β 1 H o s t i l i t i e s i + β 2 GERMAN_LEGAL i + β 3 Catholic_pop i + β 4 Orthodox_pop i + β 5 EPI i
Coefficients:
“Step” is a fundamentally different method, yet it mostly exhibits the same results (Table 11) as cross-validation (Table 10). Step analysis further confirms the choice of the right variables (based on reality, not on random data effects). The only difference is that Step analysis chose GERMAN (legal origin) instead of German language (percentage of German-speaking population), with 99% confidence. The sections discussing the theoretical framework and conclusions further discuss these variables and findings.
Table 11. Model 5. Competitiveness in Europe and the Americas (Step method) (Author’s figure).
GERMAN (legal origin) is a binomial variable, meaning that, if a country has a German legal origin, its GCI is 0.759 higher. If it has no German legal origin, the variable does not affect GCI. Only these two extremes exist.
On the other hand, the variable Social hostilities due to religion also appears in Models 4 and 5. It exhibits the lowest value of standardised beta and also low values. More importantly, this variable appeared only at 90% confidence value (all other results had a 99% confidence value). Therefore, this variable is not sufficiently significant.
Finally, standard deviation confirmed the results of both cross-validation (Table 10) and Step (Table 11) and found the same, most robust coefficients. Consequently, only four variables in the models had statistical significance.

9.3. Conclusions for the Correlational Analysis on Competitiveness

9.3.1. Conclusions for Competitiveness in the World (All Models)

The consistent results of the five previous models are:
(1) A positive influence of EPI on GCI;
(2) A positive influence of a German legal origin (or German language) on GCI;
(3) A negative influence of an Orthodox population on GCI;
(4) A negative influence of a Roman Catholic population (or Roman Catholic State Religion) on GCI.
These results are valid for the world—Models 1 (Table 7), 2 (Table 8), and 3 (Table 9)—, as well as for Europe and the Americas—Models 4 (Table 10) and 5 (Table 11)—.
Partially conclusive findings:
Ethnic influence appeared with some degree of importance in the world models, but disappeared in Europe and the Americas.
Socialist legal origin negatively influenced GCI—Models 2 (Table 8), and 3 (Table 9)—.
The influence of the share of Protestants in the population is inconclusive. In Model 1 (Table 7), Protestants negatively affected GCI, after Orthodox and Roman Catholics, but disappeared in Model 2 (Table 8), which analyses religious population.
Neither Protestant population (1) nor Protestant State Religion (2) are significant variables for competitiveness in Europe and the Americas—Models 4 (Table 10) and 5 (Table 11)—. There are two hypothetical reasons for such findings. First, the high influence of Pentecostalism in the Protestant population today might neutralise the possible positive effect of historical Protestantism. Pentecostalism impacts little on human capital and institutions (Becker et al. 2016; McCleary 2013; Woodberry 2012) and has often fallen into established practices “of corporatism and clientage” (Martin 1999, p. 40; Schäfer 1997). Second, while Switzerland and the United States are the most competitive (GCI) countries, they do not have Protestantism as their state religion, despite being historically Protestant (Barro and McCleary 2005; Inglehart and Baker 2000).
Nonetheless, Protestant State Religion exhibited a positive significance on Model 3 that analysed State Religion separately (Table 9). This suggests that Protestant State Religion is more important for GCI than the proportion of Protestants in the population. The effect of Protestant State Religion on higher GCI might also be related to its influence in diminishing the institutional power of the Roman Church (Section 7). The latter conclusions both confirm Fanfani’s claim, as early as 1936 (as cited in Grier 1997), that the separation of State and Church is the critical prosperity trigger. Such a separation mainly occurred in Protestant countries for anti-clerical reasons. Fanfani argued that religion per se harms prosperity, unless it leads to the separation of ecclesiastical and political/economic powers (as historical Protestantism did).

9.3.2. Conclusions for Competitiveness in Europe and the Americas

In Europe and the Americas, the combination of variables that are found in Models 4 and 5 largely explains GCI variability in the following order of importance:
Environmental Performance Index (EPI)
EPI significantly correlates with competitiveness (GCI), as suggested by environmental and geographical theory on prosperity (Diamond 1997; Sachs 2001; Brown and Lall 2006). Of all the variables considered, this index has by far the highest positive influence on GCI and it explains most of the GCI diversity. Higher EPI strongly implies higher GCI.
Legal Origin
As predicted (see variables description), German legal origin and German language are strongly correlated with GCI. The influence of the Reformation on the German legal system has been widely discussed (Witte 2002; Berman 2003) (see Section 7). Similarly, several studies (Besch 1999; Greenslade 1963) have discussed the influence of the Reformation on the dissemination and standardisation of the German language.

10. General Conclusions

Institutional factors that are related to religion exert a stronger structural and long-term influence on prosperity (competitiveness) than the cultural influence of religion (adherents). Several pieces of evidence corroborate this conclusion: (1) the vast amount of relevant historical, theological, and theoretical information; (2) the empirical results of two key variables (State religion and Legal origin); and, (3) close analysis of specific cases.
Model 1 (Table 7) and Model 3 (Table 9) empirically confirmed that the influence of Protestant State religion is almost twice that of adherents. Close empirical analysis helps better understand the historical legacy, status quo, and dynamics of power, institutions, and prosperity in diverse countries.
For instance, seriously considering the role of the Roman Catholic Church as a state actor has profound implications. The importance of Roman Catholicism is based more on its institutional and political ideology, rather than on its belief system (although religious belief is also necessary for maintaining political ideology and the status quo).
The Reformation, in turn, brought forth a wide range of modern institutions. Among these, education and democracy are the most crucial for ensuring prosperity outcomes. Likewise, Protestantism has impacted the secularisation of the state in Protestant countries (and also in Roman Catholic ones, albeit to a lesser, more indirect extent). The application of Protestant (biblical) principles) (Table 5) to the law, instead of a relativistic ethical code, has enhanced trust and thus prosperity. Protestantism cultivates horizontal relations of power and secular-rational attitudes towards authority (Becker et al. 2016; Woodberry 2012; Manow and van Kersbergen 2009; Witte 2002; Inglehart and Baker 2000; Treisman 2000).
According to Witte (2002), one of the main triggers for the transformation of medieval legislation codes (i.e., medieval canon law)—and thus of institutions/prosperity in Protestant countries—was the direct incorporation of several principles from the Holy Scriptures via the Protestant Reformation.
The underlying rationale is that the Sola Scriptura principle of the Protestant Reformation influenced German, English, and Scandinavian legal systems (Witte 2002; Doe and Sandberg 2010; Manow and van Kersbergen 2009). Today, countries that share these legal origins are also the most prosperous. On the other hand, French legal origins, which emerged from the French Revolution, spread essential secularising elements in Europe, even if these were not always transferred (e.g., to Spanish and Portuguese colonies in Latin America). The socialist legal origin, which originated in the Bolshevik Revolution, incorporated atheist elements (Miller 2012; Berman 2003), but its countries are less prosperous. All of these modern legal origins replaced medieval canon law, although each borrowed some of its elements to a different extent. Natural and canon (Catholic) law are based rather on Greek philosophy than on the Scriptures (Selling 2018); (Gula 2002). Nevertheless, they are still valid today for the Roman Catholic Church–State, in particular (though not limited to), its countries of influence.
The Protestant Reformation required the rejection of the exaltation of powers of the papacy in medieval canon law. However, canon law could not be completed ousted everywhere. Certain aspects are still evident, albeit to a lesser degree, even in Protestant countries, such as the United States, via indirect influence. In Lutheran territories, for instance, canon law was tested against the Holy Scriptures, and only those aspects that passed scrutiny were preserved (Helmholz 1992).
However, for instance, the current Pentecostalisation of Protestantism might have weakened the former socio-political impact of historical Protestantism.
State institutions in Latin America have been closely linked with Roman Catholicism, in that they uphold feudal-medieval structures. The Protestant Reformation has not been allowed to directly influence institutions in Latin America as it did in North America or in northern Europe.
One of the crucial elements determining prosperity differences in countries of French legal origin is the level of anti-clericalism adopted in legislation. For instance, Uruguay adopted the French code and it boldly incorporated the secular-democratic and anticlerical principles that descend from the French Revolution in its constitution and other institutions (e.g., education). As a result, it exhibits the greatest social progress across Latin America, partly due to the persistence of such institutional arrangements.
The introduction of anti-clerical (and non-Socialist) principles is linked to higher institutional performance and prosperity levels, regardless of legal tradition (i.e., in all historically Protestant countries). The French Revolution and experiences made on its basis also reveal the same pattern (good results are only achieved if anti-clericalism exists). Countries with strong anti-clerical movements (e.g., France, Italy, Uruguay, or Chile) exhibit better social progress and competitiveness than countries with the same legal traditions and institutional systems yet strongly influenced by the Roman Church–State (i.e., most Latin American countries).
Further research on the institutional influence of religion could complement the present analysis through (quantitative) time series and (qualitative) cases studies (e.g., Venezuela and the US.). Other indicators of potential value for further qualitative and quantitative analyses might include the number of years since officialising relations with the Roman See per country, the number of dioceses, diocesan priests, persons per diocesan priests, the total number of priests, and the total number of persons per priest/per year/per country.

Supplementary Materials

The following datasets are available online at https://www.mdpi.com/2077-1444/10/6/362/s1: Quantitative models of prosperity analysis (regressions) for Europe and the Americas.

Funding

This research received no external funding.

Acknowledgments

I thank Mark Kyburz, Per Wikström, Benjamin Hoffmann, and the blind peer reviewers and editors of this journal for their helpful comments to previous versions of this paper. I also express my deepest gratitude to: Karl Bailey for his generosity in helping to build the first database; Pavel Chlup and Maria Kralova for their invaluable help in the quantitative models; Tina Freyburg, Carsten Trenkler, Roland Fuess, Yvette Sánchez, and Karen Elliott for their opportune comments helping sharpen the correlational models and conclusions. I am also highly indebted to Silvia Garcia, and Paul and Mirjam Wright for their invaluable support. All Scripture quotations from The Authorized (King James) Version. The Holy Bible, King James Version. Cambridge Edition: 1769. Rights in the Authorized Version in the United Kingdom are vested in the Crown. Reproduced by permission of the Crown’s patentee, Cambridge University Press.

Conflicts of Interest

The author declares no conflict of interest.

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1
The GCI displays a similar trend to the SPI. GCI is empirically modelled, as this index is comprehensive and does not directly include “environmental performance” (EPI). The SPI is not empirically modelled, as it contains information about environmental performance that would induce endogeneity in the models when including the EPI.
2
D. Martin Luthers Werke: Kritische Gesamtausgabe, 78 vols. (Weimar, 1883–1987).
3
Please refer to the Supplementary Materials for a detailed description of the variables and their interactions in the general research model. Also included in the Supplementary Materials is a summary of the theories, indicators, and sources utilised in the models.
4
In the following sections, italics are used to identify variables or parameters.
5
Due to data availability issues, some countries were excluded (e.g., most of the small island states in the Caribbean). However, most countries in Europe and the Americas provide rich data. See Supplementary Materials for detailed information on countries, sources, and main variables.
6
Exceptionally, while variables, like “Agnostic” and “Independent” indicating religion distribution in a population, positively affected GCI, they were not significant enough to be included in the model.

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