Anneli Kaasa

Effects of Different Dimensions of Social Capital on Innovation: Evidence from Europe at the Regional Level

This paper investigates how different dimensions of social capital influence innovation output. The novelty of the paper lies in the fact that for measuring social capital, instead of one overall index, six factors are constructed of 20 indicators using principal components analysis. Then, human capital and R&D are also included in the analysis as factors of innovation. Unlike many previous studies, this one uses the structural equation modelling approach instead of regression analysis in order to take into account the relationships between the factors of innovation. Regional-level data from Eurostat Regio and the European Social Survey are analysed. Compared to preceding studies, a larger number of observations is used. The findings provide strong support for the argument that social capital indeed influences innovative activity and furthermore, that different dimensions of social capital have dissimilar effects on innovation.

How does culture contribute to innovation? Evidence from European countries

Culture is deemed to be a crucial basis for innovation in various respects. The aim of this paper is to explore the relationships between different cultural dimensions introduced by G. Hofstede (2001, Cultures consequences: Comparing values, behaviors, insititutions, and organizations across nations, 2nd ed., Thousand Oaks, CA: Sage) and the capability of initiating innovation measured by the number of patent applications using the sample of European countries at the regional level. As a novel approach, instead of using Hofstedes original index scores, the measures for the cultural dimensions are based on the European Social Survey. We have learned that to be successful in patenting, a region should have power distance, uncertainty avoidance, family-related collectivism (as opposed to friend-related and organisation-related collectivism), and lower than average masculinity. In addition, the negative relationships between these cultural dimensions and patenting are stronger when there is a higher patenting intensity. However, culture alone does not serve as a guarantee for a high level of patenting intensity.

Individual-Level Determinants of Social Capital in Europe: Differences between Country Groups

This paper investigates the effect of various individual-level determinants on social capital in Europe, in order to find out whether there are differences between the transition and non-transition countries. The novelty lies in more comprehensive sets of both determinants and dimensions of social capital covered. Data from World Values Survey for 31 European countries (including 16 transition countries) are analysed. Based on the estimation results of the measurement and structural model for all countries separately, the countries are clustered into three groups to complement the comparison of transition and non-transition countries. Differently from the previous results, the findings of this study provide support for the argument that the sources of social capital are remarkably different in transition and non-transition countries. Moreover, the results indicate that within both of these country groups subgroups have to be distinguished.

European Social Survey as a source of new cultural dimensions estimates for regions

This article draws attention to the European Social Survey (ESS) database that widens the horizon of cross-cultural studies. The ESS has the potential to overcome several weaknesses of earlier data sets used for cross-cultural analysis – it provides unique opportunities for the analysis of differences between regions within nation states, and the data are representative of entire populations. We aim to develop a measurement tool of cultural dimensions based on the ESS that enables a deeper comparison of European regions besides country-level analysis. For creating ESS-based indicators, the initial indicators were selected based on Hofstede (2001), using the double classification method. Latent variables of cultural dimensions were computed using confirmative factor analysis. The results enable us to evaluate cross-cultural differences between regions inside the nation state as well as to figure out culturally close regions across nation state borders. The results of our analysis confirm that countries may be much more heterogeneous in terms of cultural variation than several cultural studies presume. Cultural heterogeneity varies across countries, and there are some quite homogeneous countries in the meaning of cultural dimensions, but most countries face cultural differences between its regions that have to be taken into account. It is also very important that the deeper the subdivision, the larger the differences. In some cases, border regions are remarkably less similar to the rest of the regions of the country than to the neighbouring regions of another country with a common border. In the case of countries with high cultural homogeneity, the use of nation-level cultural indicators may be justified, but in the case of highly heterogeneous countries a regional approach could be suggested instead.

Factors Influencing Income Inequality In Transition Economies

A sharp rise of income inequality in the transition countries has caused a wide-ranging discussion about the factors affecting inequality. The present paper investigates a number of factors that influence income inequality in the transition countries. The main contribution of the study lies in its different approach to analysing these factors. While previous studies have either mainly focussed on single factors of inequality or have used regression analysis involving but a few factors, the author of the present paper uses principal component analysis in order to analyse as many different indicators as possible and at the same time avoid the problem of possible multicollinearity. As a result, four components are formed from the initial indicators. The impact of these components on income inequality and the component scores are then analysed.

Factors of Income Inequality and Their Influence Mechanisms: A Theoretical Overview

When analysing the factors of income inequality, first as many factors as possible have to be included in order to obtain valid results. The present article systematises the factors of income inequality discussed in the pertinent literature into five groups and summarises the hypotheses about the signs of the influences of the discussed factors on income inequality. But additionally the influences between the factors themselves that form indirect effects on income inequality have to be included. In this article, these influences are discussed and arranged in a system to give an idea about the possible indirect effects on income inequality of all the factors discussed in the article.

Religion and social capital: evidence from European countries

This exploratory study investigates how various aspects related to religion are related to different dimensions of social capital, based on the latest data from the European Values Study. The study intends to include as many religion-related variables as possible and to cover all main dimensions of social capital. In addition to regression analysis, cluster analysis is used for further exploration of religious composition and its consequences for social capital. The broadest conclusions are that religion is highly related to social capital, but the cognitive dimensions of social capital seem to have a closer relationship with social capital than the structural dimensions. Also, many relationships may be overlooked if not enough different religion-related aspects and social capital dimensions are analysed.

Culture, religion and social capital: evidence from European regions

Purpose – The purpose of this paper is to investigate the possible relationship of religion and culture with the social capital in a particular region. Design/methodology/approach – The data of 85 regions from 26 European countries are analysed. Regression analysis is used for analysing cultural dimensions, religion-related aspects and the communist past as possible factors of social capital components. In addition, graphic analysis is used for the generalisation of the results. Findings – The results from both the regression and graphic analyses indicate that cultural dimensions capture the possible reasons for different levels of social capital better than religion-related aspects or the division according to the communist background. Research limitations/implications – Conclusions can be drawn only for the European regions analysed. Data were not available for regions in all European countries and including control variables was limited by the data availability. Practical implications – When intending to develop policies for increasing social capital, the culture of a particular region should be assessed in order to predict the success of the policies. Originality/value – The novelty of this study lies in including cultural dimensions based on Hofstede’s concept to the set of possible factors determining the level of social capital in a region.

Honesty and Trust: Integrating the Values of Individuals, Organizations, and the Society

Purpose — The purpose of this chapter is to assess empirically the levels of trust across the world and to explore possible differences in the levels of trust among different groups of respondents.Design/methodology/approach — We analyze the individual-level data from 81 countries around the world using latest available European Values Study (EVS) and World Values Survey (WVS) datasets (most data refer to the year 2008). Methodologically, we compose three trust indicators using confirmatory factor analysis and then compare the level of trust in different groups. After that we calculate country-level means of trust indicators and use these as inputs in cluster analysis.Findings — The results of our empirical analysis show that the level of trust among supervisors do not differ significantly from the overall level of trust in a society, supporting the hypothesis that honesty and trust tend to be contagious. Still, there are statistically significant differences in trust levels between almost all explored population groups which were composed on the basis of previous theoretical and empirical literature.Limitations — Our analysis covered only selected socio-economic determinants of trust. It would be reasonable to add some contextual or systemic factors at the level of nation (like GDP per capita, quality of formal institutions, society’s polarization, or others) into further analysis.Originality/value — Our analysis distinguishes between three different types of trust which are studied both at individual and national level. Also, differences between age groups and educational groups, men and women, religious and non-religious persons are examined. Finally, we compare the levels of trust of those supervising someone with the average trust levels in the society as a whole.

Human Capital and Social Capital as Interacting Factors of Economic Development

When studying empirically the differences in levels of income and development between nations and regions, it appears that these enormous and growing differences cannot be fully explained by traditional theories of economic growth, which consider physical capital as the main factor of development. The basic assumption made in classical and neoclassical economic theory states that society consists of a set of independent individuals, each of whom acts to achieve goals that are independently arrived at, implying that the best institution to govern economic exchanges is free market. However, market mechanism based on individually rational behaviour will often not guarantee collectively optimal outcomes because of externalities, whose solving requires cooperative behaviour and attitudes. Acknowledging such duality in economic theory has forced economists to look for new explanations to economic processes. Earlier, the concept of human capital – consisting of good education and health which should yield higher productivity — was added into endogenous growth models, and following empirical work has proved that human capital has strong explanatory power in growth regressions.