Leadership and Economic Growth: a Text Analytics Approach


In recent years, a growing number of economists have come to recognize the importance of political leadership in promoting economic performance. However, without an agreed upon measure of leadership, formally demonstrating and testing this relationship remains elusive. This paper proposes identifying economic leadership by measuring the consistency with which leaders talk about economic issues. We employ a text analytics approach–Topic Modeling–to studying leaders’ discourses, and measure the relationship between these discourses and economic growth. Specifically, using the Latent Dirichlet Allocation (LDA) algorithm, we identified the topical content of U.S governors’ state of the state speeches from 2001 to 2013, constructed a consistency measure over these topics, and studied the relationship between the consistency of these topical content and the states’ real GDP growth. We find that the consistency with which governors address economic issues is strongly associated with economic growth. (JEL C40, H70, O40)