Abstract
Causality has gained substantial attention from both academics and the industry. However, it is not easy to reveal the real effect of an explanatory variable. The estimated effect is usually impacted by other explanatory variables. In this paper, we investigate the problem of extra explanatory variables and find that the problem can seriously affect the accuracy of the linear model. We further propose a method called matching (Flinn, 2006) to eliminate the impact of extra explanatory variables. Experimental results on the American wage data set suggest that the matching method can be used in reality.
A Method to Find Real Effects in Econometrics
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References
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