We start from the assertion that a useful monetary policy design should be founded on more realistic assumptions about what policymakers can know at the time when policy decisions have to be made. Since the Taylor rule - if used as an operational device - implies a forward looking behaviour, we...

"Big data" is becoming an increasingly important aspect of our daily lives as the digital sources of information and intelligence that it encompasses become more structured and more publicly available. These sources may enable the generation of new datasets providing high-frequency and timely...

Data revisions to national accounts pose a serious challenge to policy decision making. Well-behaved revisions should be unbiased, small and unpredictable. This paper shows that revisions to German national accounts are biased, large and predictable. Moreover, using filtering techniques designed...

Data on Google searches help predict the unemployment rate in the U.S. But the predictive power of Google searches is limited to short-term predictions, the value of Google data for forecasting purposes is episodic, and the improvements in forecasting accuracy are only modest. The results,...

In this paper a Bayesian vector autoregressive model for nowcasting the seasonally non-adjusted unemployment rate in EU-countries is developed. On top of the official statistical releases, the model utilizes Google search data and the effect of Google data on the forecasting performance of the...

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,...

The internet has become the primary source of information for most of the population in modern economies, and as such, it provides an enormous amount of readily available data. Among these are the data on the internet search queries, which have been shown to improve forecasting models for...