There has been a steep increase in empirical research in economics in the past 20-30 years. This chapter brings together several actors and stakeholders in these developments to discuss their drivers and implications. All types of data are considered: official data, data collected by researchers, lab experiments, randomized control trials, and proprietary data from private and public sources. When relevant, emphasis is placed on developments specific to Europe. The basic message of the chapter is that there is no single type of data that is superior to all others. We need to promote diversity of data sources for economic research and ensure that researchers are equipped to take advantage of them. All stakeholders -researchers, research institutions, funders, statistical agencies, central banks, journals, data firms, and policy-makers -have a role to play in this. IntroductionThe past 20-30 years have witnessed a steady rise in empirical research in economics. In fact, a majority of articles published by leading journals these days are empirical, in stark contrast with the situation 40 or 50 years ago (Hamermesh, 2013). This change in the distribution of methodologies used in economic research was made possible by improved computing power but, more importantly, thanks to an increase in the quantity, quality and variety of data used in economics. This chapter brings together several actors and stakeholders in these changes to discuss their drivers and implications.1 All types of data are considered. When relevant, emphasis is placed on developments specific to Europe. Sections 13.2 and 13.3 deal with official microdata. Section 13.2 focuses on the level of access to microdata in Europe and its determinants. Section 13.3 focuses on cross-country data harmonization. Section 13.4 then switches gears entirely and discusses the benefits and costs of large-scale data collection efforts led by researchers, instead of statistical offices. Section 13.5 discusses data produced by researchers, either in the context of lab experiments or in the context of randomized control trials. Both types of data have led to major advances; for the first one in our understanding of human behaviour and the robustness of economic institutions; for the second in our understanding of the impact of policies and the mechanisms underlying them. The chapter closes by discussing new forms of collaborations that researchers are developing with private-and public-sector organizations, with the benefit of access to data of very high quality, as well as the opportunity to contribute to product and policy designs, and what it implies for how research is organized, evaluated and funded.The basic message of the chapter is that there is no single type of data that is superior to all others. Each type of data is unique and has advantages over the others for a given research question. In many cases, they even complement one another. We need to promote this diversity and ensure researchers are equipped to take advantage of them. All stakeholders -res...