Explaining Self-Declared Social Tolerance for Human Diversity in Latin America and the Caribbean

Abstract

Social tolerance enables heterogeneous persons to find harmony in their differences. This has been shown to reduce the likelihood of inter- and intra-group conflicts, thereby creating an environment conducive for economic and social development. This paper examines socio-economic factors that influence individual differences in social tolerance in Latin America and the Caribbean. Being mindful of the fact that there are socio-cultural differences between Latin America and the Caribbean, five dimensions of social tolerance are investigated: tolerance for racial and religious dissimilarity, homosexuals, AIDS victims and immigrants. Using the 2005 World Values Survey data, we simultaneously estimate tolerance towards these groups using multivariate probit models. Education is found to positively and significantly enhance all five dimensions of social tolerance, suggesting that policies meant to enhance social tolerance should be directed towards improving educational systems. Overall, the analysis underscores heterogeneity of factors affecting self-declared tolerance of the selected social groups. Thus, analyses of social tolerance and ensuing policies should be developed specific to a particular dimension of tolerance.     

CONDITIONALLY HETEROSKEDASTIC FACTOR MODELS WITH SKEWNESS AND LEVERAGE EFFECTS

Conditional heteroskedasticity, skewness and leverage effects are well‐known features of financial returns. The literature on factor models has often made assumptions that preclude the three effects to occur simultaneously. In this paper I propose a conditionally heteroskedastic factor model that takes into account the presence of both the conditional skewness and leverage effects. This model is specified in terms of conditional moment restrictions and unconditional moment conditions are proposed allowing inference by the generalized method of moments (GMM). The model is also shown to be closed under temporal aggregation. An application to daily excess returns on sectorial indices from the UK stock market provides strong evidence for dynamic conditional skewness and leverage with a sharp efficiency gain resulting from accounting for both effects. The estimated volatilitypersistence from the proposed model is lower than that estimated from models that rule out such effects. I also find that the longer the returns' horizon, the fewer conditionally heteroskedastic factors may be required for suitable modeling and the less strong is the evidence for dynamic leverage. Some of these results are in line with the main findings of Harvey and Siddique ( 1999 ) and Jondeau and Rockinger ( 2003 ), namely that accounting for conditional skewness impacts the persistence in the conditional variance of the return process. Copyright © 2012 John Wiley & Sons, Ltd.     

Does Corporate Social Responsibility Influence Firm Performance? Empirical Evidence from Harare,Zimbabwe

The influence of the dimensions of corporate social responsibility on firm performance are tested in Harare, Zimbabwe using perceptual data from a sample of 155 firms over a period of three years. Structural equation modeling was used to test the research hypotheses. The study found that employee relations, customer relations, community relations and investor relations all had a positive effect on firm performance. Environmental relations, diversity relations and supplier relations all did not influence firm performance. The study has implications on theory, policy and practice, and future research.     

Comprehensive Community Initiative: Evaluation of a transformation system in Mhakwe community in Zimbabwe

This article explores community perceptions on implementation and impacts of the Mhakwe Comprehensive Community Initiative (CCI) in Mhakwe Ward, Zimbabwe. A mixed-methods research methodology was adopted. Qualitative data were collected from action research, focus group discussions and key informant interviews. Quantitative data were collected using a structured questionnaire from a random cluster sample, and were analysed using SPSS and Stata with binomial logistic regression to determine factors significantly affecting selected variables and the chi-square test for independence to determine association between variables. Thematic reviews were utilised to analyse qualitative data. Community perceptions on issues affecting multi-stakeholder collaborations, ownership, and control, internal and external enabling factors were explored. The article concludes that leadership development, strengthening family institutions, enhancing ownership and building capacity of local institutions to coordinate such initiatives are fundamental building blocks for CCIs. This article recommends CCIs as a practical framework for empowering marginalised communities.     

Federal lending and aggregate economic activity

Attention to federal activity in credit markets is typically focused on the government's role as a borrower. In contrast, scant attention is paid to its equally large and dominant role as a lender. This paper evaluates the aggregate impact of federal lending activity within the framework of a vector autoregressive representation of the US macroeconomy. The empirical regularities uncovered suggest that aggregate federal lending activity does not have a net positive impact on output.     

Bootstrapping realized multivariate volatility measures

We propose a bootstrap method for statistics that are a function of multivariate high frequency returns such as realized regression, covariance and correlation coefficients. We show that the finite sample performance of the bootstrap is superior to the existing first-order asymptotic theory. Nevertheless, and contrary to the existing results in the bootstrap literature for regression models subject to error heteroskedasticity, the Edgeworth expansion for the pairs bootstrap that we develop here shows that this method is not second-order accurate. We argue that this is due to the fact that the conditional mean parameters of realized regression models are heterogeneous under stochastic volatility.