Printed from https://ideas.repec.org/n/nep-big/2021-10-18.html
Report NEP-BIG-2021-10-18
This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé (Tom Coupe) issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-BIG
The following items were announced in this report:
- Bernard Koch & Tim Sainburg & Pablo Geraldo & Song Jiang & Yizhou Sun & Jacob Gates Foster, 2021, "A Primer on Deep Learning for Causal Inference," Papers, arXiv.org, number 2110.04442, Oct, revised Nov 2023.
- Mahdieh Yazdani, 2021, "Machine Learning, Deep Learning, and Hedonic Methods for Real Estate Price Prediction," Papers, arXiv.org, number 2110.07151, Oct.
- Yufei Wu & Mahmoud Mahfouz & Daniele Magazzeni & Manuela Veloso, 2021, "Towards Robust Representation of Limit Orders Books for Deep Learning Models," Papers, arXiv.org, number 2110.05479, Oct, revised Dec 2022.
- Meerza, Syed Imran Ali & Meerza, Syed Irfan Ali & Ahamed, Afsana, 2021, "Food Insecurity Through Machine Learning Lens: Identifying Vulnerable Households," 2021 Annual Meeting, August 1-3, Austin, Texas, Agricultural and Applied Economics Association, number 314072, Aug, DOI: 10.22004/ag.econ.314072.
- Muhammad Apriandito Arya Saputra & Andry Alamsyah & Fajar Ibnu Fatihan, 2021, "Hotel Preference Rank based on Online Customer Review," Papers, arXiv.org, number 2110.06133, Oct.
- Harold D Chiang & Yukun Ma & Joel Rodrigue & Yuya Sasaki, 2021, "Dyadic double/debiased machine learning for analyzing determinants of free trade agreements," Papers, arXiv.org, number 2110.04365, Oct, revised Dec 2022.
- Danielsson, Jon & Macrae, Robert & Uthemann, Andreas, 2022, "Artificial intelligence and systemic risk," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 111601, Jul.
- Rebecca Christie, 2021, "Do robots dream of paying taxes?," Bruegel Policy Contributions, Bruegel, number 45076, Oct.
- Ayush Patnaik & Ajay Shah & Anshul Tayal & Susan Thomas, 2021, "But clouds got in my way: Bias and bias correction of VIIRS nighttime lights data in the presence of clouds," Working Papers, xKDR, number 7, Oct.
- Jiafeng Chen & Xiaohong Chen & Elie Tamer, 2021, "Efficient Estimation in NPIV Models: A Comparison of Various Neural Networks-Based Estimators," Papers, arXiv.org, number 2110.06763, Oct, revised Oct 2022.
- Romano, Stefania & Martinez-Heras, Jose & Raponi, Francesco Natalini & Guidi, Gregorio & Gottron, Thomas, 2021, "Discovering new plausibility checks for supervisory data," Statistics Paper Series, European Central Bank, number 41, Oct.
- David Bounie & Antoine Dubus & Patrick Waelbroeck, 2021, "Competition and Mergers with Strategic Data Intermediaries," CESifo Working Paper Series, CESifo, number 9339.
- M. Battisti & M. Del Gatto & A. F. Gravina & C. F. Parmeter, 2021, "Robots versus labor skills: a complementarity/substitutability analysis," Working Paper CRENoS, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia, number 202104.
- Goecke, Henry & Rusche, Christian, 2021, "Wer setzt die richtigen Weichen für die Künstliche Intelligenz? Eine Analyse der Wahlprogramme der Parteien im deutschen Bundestag," IW policy papers, Institut der deutschen Wirtschaft (IW) / German Economic Institute, number 20/2021.