The empirics of social capital and economic development: a critical perspective

This paper provides an introduction to the concept of social capital, and carries out a critical review of the empirical literature on social capital and economic development. The survey points out six main weaknesses affecting the empirics of social capital. Identified weaknesses are then used to analyze, in a critical perspective, some prominent empirical studies and new interesting researches published in last two years. The need emerges to acknowledge, also within the empirical research, the multidimensional, context-dependent and dynamic nature of social capital. The survey also underlines that, although it has gained a certain popularity in the empirical research, the use of “indirect” indicators may be misleading. Such measures do not represent social capital’s key components identified by the theoretical literature, and their use causes a considerable confusion about what social capital is, as distinct from its outcomes, and what the relationship between social capital and its outcomes may be. Research reliant upon an outcome of social capital as an indicator of it will necessarily find social capital to be related to that outcome. This paper suggests to focus the empirical research firstly on the “structural” aspects of the concept, therefore excluding by the measurement toolbox all indicators referring to social capital’s supposed outcomes

Cross-Country Growth Empirics and Model Uncertainty: An Overview

The aim of this paper is to provide an overview of empirical cross-country growth literature. The paper begins with describing the basic framework used in recent empirical cross-country growth research. Even though this literature was mainly inspired by endogenous growth theories, the neoclassical growth model is still the workhorse for cross-country growth empirics. The second part of the paper emphasises model uncertainty, which is indeed immense but generally neglected in the empirical cross-country growth literature. The most outstanding feature of the literature is that a large number of factors have been suggested as fundamental growth determinants. Together with the small sample property, this leads to an important problem: model uncertainty. The questions which factors are more fundamental in explaining growth dynamics and hence growth differences are still the subject of academic research. Recent attempts based on general-to-specific modeling or model averaging are promising but have their own limits. Finally, the paper highlights the implications of model uncertainty for policy evaluation