Predicting economic indicators using Political Texts

Abstract

The paper proposes a new text-based indicator aimed at assessing the impact over time of political debate on economy. Textual data from the plenary verbatim reports of the Italian Parliament are pre-processed and relevant themes, whose temporal evolution allows predicting fluctuations in fundamental macro-economic variables, are estimated via a Correlated Topic Model. Specifically, a Political Debate Index is derived based on a time-varying weighting function of the estimated topic proportions. The capability, in terms of out-of-sample forecasts accuracy, of the proposed approach in improving the predictability of selected economic indicators is evaluated considering different predictors. The reached results seem to support the evidence that qualitative information conveyed by the daily political debate does have an impact on the economic dynamic over time and can be usefully used to improve the economic predictions performance.

Keywords: text analysis, forecasting, macroeconomic indicators

DOI: 10.54941/ahfe1002559