The specification of macro migration models and, hence, forecasts of migration potentials differ largely in the literature. Two main differences characterise macro migration models: first, whether migration flows or stocks are used as the dependent variable, and, second, whether the...

We propose an imperfect information model for the expectations of macroeconomic forecasters that explains differences in average disagreement levels across forecasters by means of cross sectional heterogeneity in the variance of private noise signals. We show that the forecaster-specific...

GDP forecasters face tough choices over which leading indicators to follow and which forecasting models to use. To help resolve these issues, we examine a range of monthly indicators to forecast quarterly GDP growth in a major emerging economy, Russia. Numerous useful indicators are identified...

Entwicklung eines quantitativen Modells zur Spread-Prognose von Credit Default Swaps am Beispiel von Banken (Sina Birk) - Analyse der Blockhain-Technologie und Einsatzmöglichkeiten in der Tullius Walden Bank AG (Lara Dominique Lydia Bolesch) - Analyse der Auswirkungen negativer Zinsen auf die...

Optimal forecasts are, under a squared error loss, conditional expectations of the unknown future values of interest. When stochastic demographic models are used in macroeconomic analyses, it becomes important to be able to handle updated forecasts. That is, when population development turns out...

There are over 3 billion searches globally on Google every day. This report examines whether Google search queries can be used to predict the present and the near future unemployment rate in Finland. Predicting the present and the near future is of interest, as the official records of the state...

The share of private consumption in gross domestic product is significant; therefore, private consumption has a great influence on economic growth, which makes it a major concept in economics. The purpose of the paper is to estimate and evaluate different forecasting models for private...

In this report we document the ETLAnow project. ETLAnow is a model for forecasting with big data. At the moment, it predicts the unemployment rate in the EU-28 countries using Google search data. This document is subject to updates as the ETLAnow project advances.

This report examines whether Google search queries can be used to predict the present and the near future house prices in Finland. Compared to a simple benchmark model, Google searches improve the prediction of the present house price index by 7.5 % measured by mean absolute error. In addition,...