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13 - Developments in Data for Economic Research
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- By Roberto Barcellan, Eurostat, Luxembourg, Peter Bøegh Nielsen, Statistics Denmark, Copenhagen, Denmark, Caterina Calsamiglia, CEMFI, Madrid, Spain, Colin Camerer, California Institute of Technology, Pasadena, CA, USA, Estelle Cantillon, Université Libre de Bruxelles, Brussels, Belgium, Bruno Crépon, CREST and JPAL, Paris, France, Bram De Rock, Université Libre de Bruxelles, ECARES, Brussels, Belgium, László Halpern, Hungarian Academy of Science, Budapest Hungary, Arie Kapteyn, University of Southern California, Los Angeles, CA, USA, Asim I. Khwaja, Harvard Kennedy School of Government, Cambridge, MA, Georg Kirchsteiger, Université Libre de Bruxelles, Vigdis Kvalheim, Norway Social Science Data Service, Bergen, Norway, Julia Lane, New York University, New York, USA, Markus Mobius, Microsoft Research, Cambridge, MA, USA, Luke Sibieta, Institute for Fiscal Studies, London, UK, Joseph Tracy, Federal Reserve Bank of New York, New York, USA, Frederic Udina, Idescat, Barcelona, Spain, Gugliemo Weber, University of Padua, Padua, Italy, Lisa Wright, Bureau Van Dijk, Manchester, UK
- Edited by Laszlo Matyas, Central European University, Budapest, Richard Blundell, University College London, Estelle Cantillon, Université Libre de Bruxelles, Barbara Chizzolini, Università Commerciale Luigi Bocconi, Milan, Marc Ivaldi, Wolfgang Leininger, Universität Dortmund, Ramon Marimon, European University Institute, Florence, Frode Steen
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- Book:
- Economics without Borders
- Published online:
- 24 March 2017
- Print publication:
- 27 April 2017, pp 568-611
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- Chapter
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Summary
Abstract
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.
Introduction
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.
Native and non-native processing of English wh- questions: Parsing strategies and plausibility constraints
- JOHN N. WILLIAMS, PETER MÖBIUS, CHOONKYONG KIM
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- Journal:
- Applied Psycholinguistics / Volume 22 / Issue 4 / December 2001
- Published online by Cambridge University Press:
- 11 July 2002, pp. 509-540
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The two experiments reported here investigated the processing of English wh- questions by native speakers of English and advanced Chinese, German, and Korean learners of English as a second language. Performance was evaluated in relation to parsing strategies and sensitivity to plausibility constraints. In an on-line plausibility judgment task, both native and non-native speakers behaved in similar ways. All groups postulated a gap at the first position consistent with the grammar, as predicted by the filler-driven strategy and as shown by garden path or filled-gap effects that were induced when the hypothesized gap location turned out to be incorrect. In addition, all subjects interpreted the plausibility of the filler-gap dependency, as shown by a reduction in the garden path effect when the initial analysis was implausible. However, the native speakers' reading profiles showed evidence of a more immediate effect of plausibility than those of the non-native speakers, suggesting that they initiated reanalysis earlier when the first analysis was implausible. Experiment 2 showed that the non-native speakers had difficulty canceling a plausible gap hypothesis even in an off-line (pencil and paper) task, whereas for the native speakers there was no evidence that the sentences caused difficulty in this situation. The results suggest that native and non-native speakers employ similar strategies in immediate on-line processing and hence are garden-pathed in similar ways, but they differ in their ability to recover from misanalysis.