This analysis investigates the predictive power of the most important leading indicators for the German economy, which are provided by the ifo Institute and IHS Markit. We conduct an out-of-sample, real-time forecast experiment for growth of gross domestic product and growth of gross value added...

Comprehensive and international comparable leading indicators across countries and continents are rare. In this paper, we use a free and instantaneous available source of leading indicators, the ifo World Economic Survey (WES), to forecast growth of Gross Domestic Product (GDP) in 44 countries...

The ifo Institute is Germany’s largest business survey provider, with the ifo Business Climate Germany as one of the most important leading indicators for gross domestic product. However, the ifo Business Survey is not solely limited to the Business Climate and also delivers a multitude of...

In this paper, we study the predictive power of electricity consumption data for regional economic activity. Using unique weekly and monthly electricity consumption data for the second-largest German state, the Free State of Bavaria, we conduct a pseudo out-of-sample forecasting experiment for...

We have studied the relationship between Receiver Operating Characteristics (ROC) and Precision-Recall Curve (PRC) both analytically and using a real-life empirical example of yield spread as a predictor of recessions. We show that false alarm rate in ROC and inverted precision in PRC are...

We investigate the potential for statistical forecasting of aggregate oil and gas investment on the Norwegian Continental Shelf (NCS). A unique and detailed dataset containing data from 109 different fields on the NCS between 1970 and 2015 was employed. A set of 1080 autoregressive distributed...

We examine forecast accuracy and efficiency of the Social Security Administration's projections for cost rate, trust fund balance, trust fund ratio made during 1980-2020 with horizons up to 95 years. We find that the reported deterioration in the accuracy of the forecasts during 2010’s has...

Over the last decade, the topic of regional economic forecasting has become increasingly prevalent in academic literature. The most striking problem in this context is data availability at a regional level. However, considerable methodological improvements have been made to address this problem....

Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on U.S. GDP,...

This paper applies component-wise boosting to the topic of regional economic forecasting. Component-wise boosting is a pre-selection algorithm of indicators for forecasting. By using unique quarterly real gross domestic product data for two German states (the Free State of Saxony and...