This paper offers two innovations for empirical growth research. First, the paper discusses principal components augmented regressions to take into account all available information in well-behaved regressions. Second, the paper proposes a frequentist model averaging framework as an alternative...

The aim of this paper is to provide an overview of empirical cross-country growth literature. The paper begins with describing the basic framework used in recent empirical crosscountry growth research. Even though this literature was mainly inspired by endogenous growth theories, the...

Today, the generation and use of huge volumes of data are redefining our “intelligence” capacity and our social and economic landscapes, spurring new industries, processes and products, and creating significant competitive advantages. In this sense, data-driven innovation (DDI) has become a...

"This report focuses on digital data and analytics and their effects on innovation, growth and well-being. It aims to improve the evidence bases on the role of data-driven innovation (DDI) in boosting productivity growth and contributing to well-being. It also offers policy guidance for...

This paper uses the adaptive LASSO estimator to determine the variables important for economic growth. The adaptive LASSO estimator is a computationally very simple procedure that performs at the same time both consistent parameter estimation and model selection. The methodology is applied to...

This paper derives forecasts for euro area real GDP growth based on a bottom up approach from the production side. That is, GDP is forecast via the forecasts of value added across the different branches of activity, which is quite new in the literature. Linear regression models in the form of...