A Narrative Approach to Creating Instruments with Unstructured and Voluminous Text: An Application to Policy Uncertainty

We quantify the effects of policy uncertainty on the economy using a proxy structural vector autoregression (SVAR). Our instrument in the proxy SVAR is a set of exogenous uncertainty events constructed using a text-based narrative approach. Usually the narrative approach involves manually reading texts, which is difficult in our application as our text—the parliamentary record—is unstructured and lengthy. To deal with such circumstances, we develop a procedure using a natural language technique, latent Dirichlet analysis. Our procedure extends the possible application of the narrative identification approach. We find the effects of policy uncertainty are significant, and are underestimated using alternative identification methods.