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Advisory committees are part and parcel of policy making for nearly 50 federal agencies ranging from the vast Department of Defense to the tiny Administrative Council of the United States. Advisory committee input is used at many levels ranging from the development of high-level strategic initiatives, as vehicles for research community input, to program prioritization efforts, as instruments of program evaluation, all the way down to the provision of input on very narrowly defined decisions, such as the peer review of individual research proposals. Regulatory agencies, particularly those with responsibility for human health and the environment, rely heavily on advisory committees for the production of scientific assessments that inform the setting of standards (Jasanoff 2009).
In practice, there are many reasons that advisory committees are used by the federal bureaucracy. Fleisher provides a conceptual framework which situates federal advisory committees in the broader policy context whereby government agencies use input from the advisory committees to mediate the pressures they feel from other government policy makers, such as Congress or the Executive Office, and advocacy groups as they run their policy formulation, implementation, and policy revision processes (Fleisher 2015). Moffitt provides an excellent and sweeping overview, arguing that advisory committees are used to manage agency reputation, avoid ‘embarrassing situations,’ to compensate for deficiencies in agency knowledge, and to redress agency weakness that derives from instability or tumult inside the agency (Moffitt 2010).
In the United States the process whereby advice is sought from advisory committees is strictly regulated by the Federal Advisory Committee Act (FACA) of 1972 (Bybee 1994; Ginsberg 2009), with oversight of these committees provided by the General Services Administration's (GSA) Committee Management Secretariat. The GSA characterizes advisory committees according to the following uses: (i) national policy issues, (ii) non-scientific programs, (iii) scientific technical programs, (iv) grant recommendations, (v) regulatory negotiations, (vi) special emphasis areas, and (vii) other. The Federal Advisory Committee Act Amendments of 1997 (P.L. 105-153) amended FACA to govern agency use of reports provided by the National Academy of Sciences and the National Academy of Public Administration.
Advisory committees are numerous and engage a large number of people in providing advice to government. In 2016 there were approximately 1,000 active FACA committees used by about 50 federal agencies, costing $339.6 million (General Services Administration 2016).
The scientific advances that underpin economic growth and human health would not be possible without research investments. Yet demonstrating the impact of research programs is a challenge, especially in areas that span disciplines, industrial sectors, and encompass both public and private sector activity. All areas of research are under pressure to demonstrate benefits from federal funding of research. This exciting and innovative study demonstrates new methods and tools to trace the impact of federal research funding on the structure of research, and the subsequent economic activities of funded researchers. The case study is food safety research, which is critical to avoiding outbreaks of disease. The authors make use of an extraordinary new data infrastructure and apply new techniques in text analysis. Focusing on the impact of US federal food safety research, this book develops vital data-intensive methodologies that have a real world application to many other scientific fields.
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.
The 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. 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 themechanisms underlying them.