Data for: Growth econometrics for agnostics and true believers

Abstract of associated article: The issue of model uncertainty is central to the empirical study of economic growth. Many recent papers use Bayesian Model Averaging to address model uncertainty, but (Ciccone and Jarociński, 2010) have questioned the approach on theoretical and empirical grounds. They argue that a standard ‘agnostic’ approach is too sensitive to small changes in the dependent variable, such as those associated with different vintages of the Penn World Table (PWT). This paper revisits their theoretical arguments and empirical illustration, drawing on more recent vintages of the PWT, and introducing an approach that limits the degree of agnosticism.

相关论文摘要：经济增长实证研究中，模型不确定性问题始终处于核心地位。近年来诸多研究采用贝叶斯模型平均（Bayesian Model Averaging）方法应对模型不确定性，但西科恩与雅罗钦斯基（Ciccone and Jarociński, 2010）从理论与实证层面针对该方法提出了质疑。他们指出，标准的"不可知论"式建模方法对因变量的微小变动过于敏感，例如与不同修订版的彭博世界贸易表（Penn World Table, PWT）相关的变动。本文重新审视了二人的理论论证与实证示例，采用更新修订版的彭博世界贸易表数据，并提出了一种可限制不可知论程度的建模方法。