Nonlinearities and Robustness in Growth Regressions
Nonlinearities and Robustness in Growth Regressions
复制标题
增长回归中的非线性和稳健性
DOI：
10.2139/ssrn.813132
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发表时间：
2005
期刊：
影响因子：
--
通讯作者：
Jenny Minier
中科院分区：
文献类型：
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作者：
Jenny Minier
跨国回归是试图揭示经济增长的经验决定因素的一种行之有效的方法。然而，在一篇有影响力的论文中，Levine和Renelt（1992）证明了这些研究的结果对条件变量的选择非常敏感。使用Leamer（1983）的极端界限检验的变体，他们表明几乎没有解释变量与增长密切相关。在本文中，我表明，这一极端悲观的结论部分是由于在传统的增长规格的线性特设假设。具体而言，在替代（非线性）规格，鲁棒变量的数量大幅增加。
Cross-country regressions are a well-established means of attempting to uncover the empirical determinants of economic growth. However, in an influential paper, Levine and Renelt (1992) demonstrate that the results of these studies are very sensitive to the choice of conditioning variables. Using a variant of Leamer's (1983) extreme bounds test, they show that almost no explanatory variables are robustly correlated with growth. In this paper, I show that this extremely pessimistic conclusion is partly due to the ad hoc assumption of linearity in the traditional growth specification. Specifically, under alternative (nonlinear) specifications, the number of robust variables increases substantially.