The Relationship between Foreign Competition and Innovation Activities Based on Quantile Regression

Abstract

This article uses quantile regression to shed light on the complex relationship between foreign competition and innovation activities. Quantile regression is more powerful than classical linear regression since quantile regression can produce estimates for all conditional quantiles of the distribution of the innovation activities variable, whereas classical linear regression only estimates the conditional mean effects. The empirical evidence shows that the effect of foreign competition on make innovation activities is different across the conditional quantiles of the distribution of innovation activities, something classical linear regression would leave unidentified. This finding suggests that estimating the quantile effect of innovation activities variable can well be more insightful than effect. Additionally, this article finds a U-shaped relationship between foreign competition and make innovation activities.