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Econometrics at scale: Spark up big data in economics

  • This paper provides an overview of how to use "big data" for economic research. We investigate the performance and ease of use of different Spark applications running on a distributed file system to enable the handling and analysis of data sets which were previously not usable due to their size. More specifically, we explain how to use Spark to (i) explore big data sets which exceed retail grade computers memory size and (ii) run typical econometric tasks including microeconometric, panel data and time series regression models which are prohibitively expensive to evaluate on stand-alone machines. By bridging the gap between the abstract concept of Spark and ready-to-use examples which can easily be altered to suite the researchers need, we provide economists and social scientists more generally with the theory and practice to handle the ever growing datasets available. The ease of reproducing the examples in this paper makes this guide a useful reference for researchers with a limited background in data handling and distributed computing.

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Verfasserangaben:Benjamin Bluhm, Jannic Cutura
URN:urn:nbn:de:hebis:30:3-518045
DOI:https://doi.org/10.2139/ssrn.3226976
Titel des übergeordneten Werkes (Englisch):SAFE working paper series ; No. 266
Schriftenreihe (Bandnummer):SAFE working paper (266)
Verlag:SAFE
Verlagsort:Frankfurt am Main
Dokumentart:Arbeitspapier
Sprache:Englisch
Jahr der Fertigstellung:2020
Jahr der Erstveröffentlichung:2020
Veröffentlichende Institution:Universitätsbibliothek Johann Christian Senckenberg
Datum der Freischaltung:10.02.2020
Freies Schlagwort / Tag:Apache Spark; Distributed Computing; Econometrics
Ausgabe / Heft:February 6, 2020
Seitenzahl:49
Bemerkung:
An earlier version of this paper circulated as "Time Series Econometrics at Scale: A Practical Guide to Parallel Computing in (Py)Spark".
HeBIS-PPN:460762621
Institute:Wirtschaftswissenschaften / Wirtschaftswissenschaften
Wissenschaftliche Zentren und koordinierte Programme / House of Finance (HoF)
Wissenschaftliche Zentren und koordinierte Programme / Center for Financial Studies (CFS)
Wissenschaftliche Zentren und koordinierte Programme / Sustainable Architecture for Finance in Europe (SAFE)
DDC-Klassifikation:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
JEL-Klassifikation:C Mathematical and Quantitative Methods / C5 Econometric Modeling / C53 Forecasting and Other Model Applications
Sammlungen:Universitätspublikationen
Lizenz (Deutsch):License LogoDeutsches Urheberrecht