We present novel evidence on the effects of advanced technologies on employment, skill demand, and firm performance. The main finding is that advanced technologies led to increases in employment and no change in skill composition. Our main research design focuses on a technology subsidy program...

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,...

This paper examines the relationship between globalization and innovation. To do so, it draws from data that match the full population of workers and private-sector firms in Finland tracking them from 1995 to 2009. To correct for endogeneity the paper considers variation in trade exposure from...

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...

This paper explores offshoring of firms’ research and development functions. Our analysis employs a previously untapped and unique Eurostat International Sourcing Survey. The results are easy to summarize. First, the magnitude of R&D offshoring is small. Second, a large majority of R&D is...

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 uses an international input-output dataset to present an analysis of Finland’s position in global value chains. The results show that intermediate products account for a larger share – some three-quarters – of Finnish exports than they do in most other countries. The share of...