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Workshop on Empirical Research with Large Datasets

Workshop on Empirical Research with Large Datasets
19 Dec. 2022 to 20 Dec. 2022
19 Dec. 14:00-18:30 | 20 Dec. 09:30-12:30
Porto Business School
Av. Fabril do Norte 425
Porto

Banco de Portugal is pleased to invite you to participate in the Workshop on Empirical Research with Large Datasets, promoted by the Banco de Portugal Microdata Research Laboratory (BPLIM), to be held on December, 19 and 20, at Porto Business School, Porto.

The event will be on-site, with limited seats. The event will also be streamed live, with no limit to participants online. Register here to watch the event online.

For more information, please contact us bplim@bportugal.pt.

Program

19 December 2022

14:00-14:15

Welcome

14:15-15:00

“Reproducibility and collaboration when your data is really large or confidential”
Lars Vilhuber, Cornell University and American Economic Association

15:00-15:45

“Big Data Analytics: A guide to economists making the transition to Big Data”
Ulrich Matter, University of St.Gallen

15:45-16:15

Coffee Break

16:15-17:00

“Large surveys and other continuous data streams in statistics production”
Frauke Kreuter, LMU Munich and University of Maryland

17:00-17:45

“Thoughts on Working with Corporate Data”
John Horton, MIT Sloan School of Management and NBER

17:45-18:30

Roundtable: “The challenges of working with large empirical datasets in RDCs”
Lars Vilhuber, Cornell University and American Economic Association
Paulo Guimarães, BPLIM - Banco de Portugal
Pedro Campos, Instituto Nacional Estatística (INE)
Stefan Bender, Deutsche Bundesbank

20 December 2022

09:30-10:00

Breakfast

10:00-10:45

“How to work efficiently with large datasets”
Mauricio Caceres, Brown University

10:45-11:30

“Open source tools for really large data”
Miguel Portela and Nelson Areal, Universidade do Minho

11:30-12:15

“Why is my computer so slow? How distributed computing can help you with data intensive workloads”
Jannic Cutura, European Central Bank

12:15-12:30

Closing Remarks

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