Nowcasting the Portuguese GDP with Monthly Data

TL;DR

This paper introduces a straightforward multivariate method for nowcasting Portuguese GDP using monthly data and the HP filter, achieving comparable or better accuracy than existing models.

Contribution

It presents a novel combination of bridge equations and HP filter-based forecasts for improved GDP nowcasting in Portugal.

Findings

The method performs as well as the Targeted Diffusion Index model.

It outperforms the univariate Theta method in out-of-sample mean errors.

The approach is simple yet effective for real-time economic monitoring.

Abstract

In this article, we present a method to forecast the Portuguese gross domestic product (GDP) in each current quarter (nowcasting). It combines bridge equations of the real GDP on readily available monthly data like the Economic Sentiment Indicator (ESI), industrial production index, cement sales or exports and imports, with forecasts for the jagged missing values computed with the well-known Hodrick and Prescott (HP) filter. As shown, this simple multivariate approach can perform as well as a Targeted Diffusion Index (TDI) model and slightly better than the univariate Theta method in terms of out-of-sample mean errors.