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Report NEP-BIG-2020-11-30
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:
- Krystian Andruszek & Piotr Wójcik, 2020, "Predicting well-being based on features visible from space – the case of Warsaw," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2020-37.
- Jiafeng Chen & Daniel L. Chen & Greg Lewis, 2020, "Mostly Harmless Machine Learning: Learning Optimal Instruments in Linear IV Models," Papers, arXiv.org, number 2011.06158, Nov, revised Jun 2021.
- Sidra Mehtab & Jaydip Sen & Subhasis Dasgupta, 2020, "Robust Analysis of Stock Price Time Series Using CNN and LSTM-Based Deep Learning Models," Papers, arXiv.org, number 2011.08011, Nov, revised Jan 2021.
- Shao, Yongtong & Xiong, Tao & Li, Minghao & Hayes, Dermot & Zhang, Wendong & Xie, Wei, 2020, "China's Missing Pigs: Correcting China's Hog Inventory Data Using a Machine Learning Approach," ISU General Staff Papers, Iowa State University, Department of Economics, number 202001010800001619, Jan.
- Martin Johnsen & Oliver Brandt & Sergio Garrido & Francisco C. Pereira, 2020, "Population synthesis for urban resident modeling using deep generative models," Papers, arXiv.org, number 2011.06851, Nov.
- Jikhan Jeong, 2020, "Identifying Consumer Preferences from User- and Crowd-Generated Digital Footprints on Amazon.com by Leveraging Machine Learning and Natural Language Processing," 2020 Papers, Job Market Papers, number pje208, Nov.
- Adam Bouland & Wim van Dam & Hamed Joorati & Iordanis Kerenidis & Anupam Prakash, 2020, "Prospects and challenges of quantum finance," Papers, arXiv.org, number 2011.06492, Nov.
- Zhijun Chen & Chongwoo Choe & Jiajia Cong & Noriaki Matsushima, 2020, "Data-driven mergers and personalization," ISER Discussion Paper, Institute of Social and Economic Research, The University of Osaka, number 1108, Nov.
- Schubert, Torben & Jäger, Angela & Türkeli, Serdar & Visentin, Fabiana, 2020, "Addressing the productivity paradox with big data: A literature review and adaptation of the CDM econometric model," MERIT Working Papers, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT), number 2020-050, Nov.
- Gusarov, N. & Talebijmalabad, A. & Joly, I., 2020, "Exploration of model performances in the presence of heterogeneous preferences and random effects utilities awareness," Working Papers, Grenoble Applied Economics Laboratory (GAEL), number 2020-12.
- Item repec:spo:wpmain:info:hdl:2441/3mgbd73vkp9f9oje7utooe7vpg is not listed on IDEAS anymore
- Piotr Wójcik & Bartłomiej Wieczorek, 2020, "We have just explained real convergence factors using machine learning," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2020-38.
- Item repec:spo:wpmain:info:hdl:2441/7v8fvu0bf08jcoi4epn8cutjm8 is not listed on IDEAS anymore
- Lijuan Huo & Jin Seo Cho, 2020, "Sequentially Estimating Approximate Conditional Mean Using the Extreme Learning Machine," Working papers, Yonsei University, Yonsei Economics Research Institute, number 2020rwp-180, Oct.
- Shawn K. McGuire & Charles B. Delahunt, 2020, "Predicting United States Policy Outcomes with Random Forests," Working Papers Series, Institute for New Economic Thinking, number inetwp138, Oct, DOI: 10.36687/inetwp138.
- Juan J Dolado & Florentino Felgueroso & Juan F.Jimeno, 2020, "Past, Present and Future of the Spanish Labour Market: When the Pandemic meets the Megatrends," Studies on the Spanish Economy, FEDEA, number eee2020-37, Nov.
- Xingchen Wan & Jie Yang & Slavi Marinov & Jan-Peter Calliess & Stefan Zohren & Xiaowen Dong, 2020, "Sentiment Correlation in Financial News Networks and Associated Market Movements," Papers, arXiv.org, number 2011.06430, Nov, revised Feb 2021.