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Report NEP-BIG-2018-01-22
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:
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins, 2017, "Double/debiased machine learning for treatment and structural parameters," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies, number CWP28/17, Jun.
- Okay Gunes, 2017, "Hedonic Recommendations: An Econometric Application on Big Data," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers), HAL, number halshs-01673355, Dec.
- Raeid Saqur & Nicole Langballe, 2017, "PrivySense: $\underline{Pri}$ce $\underline{V}$olatilit$\underline{y}$ based $\underline{Sen}$timent$\underline{s}$ $\underline{E}$stimation from Financial News using Machine Learning," Papers, arXiv.org, number 1801.00091, Dec, revised Feb 2018.
- Martin Boyer & Philippe De Donder & Claude Fluet & Marie-Louise Leroux & Pierre-Carl Michaud, 2017, "Long-term Care Insurance: Knowledge Barriers, Risk Perception and Adverse Selection," Cahiers de recherche, Chaire de recherche Industrielle Alliance sur les enjeux économiques des changements démographiques, number 1701.
- Martha Bailey & Connor Cole & Morgan Henderson & Catherine Massey, 2017, "How Well Do Automated Linking Methods Perform? Lessons from U.S. Historical Data," NBER Working Papers, National Bureau of Economic Research, Inc, number 24019, Nov.
- Thomas R. Cook & Aaron Smalter Hall, 2017, "Macroeconomic Indicator Forecasting with Deep Neural Networks," Research Working Paper, Federal Reserve Bank of Kansas City, number RWP 17-11, Sep, DOI: 10.18651/RWP2017-11.
- Rickard Nyman & Sujit Kapadia & David Tuckett & David Gregory & Paul Ormerod & Robert Smith, 2018, "News and narratives in financial systems: exploiting big data for systemic risk assessment," Bank of England working papers, Bank of England, number 704, Jan.
- Galina Hale & Jose A. Lopez, 2018, "Monitoring Banking System Connectedness with Big Data," Working Paper Series, Federal Reserve Bank of San Francisco, number 2018-01, Apr, DOI: 10.24148/wp2018-01.
- Yun-Cheng Tsai & Jun-Hao Chen & Jun-Jie Wang, 2018, "Predict Forex Trend via Convolutional Neural Networks," Papers, arXiv.org, number 1801.03018, Jan.
- Jannis Kueck & Ye Luo & Martin Spindler & Zigan Wang, 2017, "Estimation and Inference of Treatment Effects with $L_2$-Boosting in High-Dimensional Settings," Papers, arXiv.org, number 1801.00364, Dec, revised Jul 2021.
- Christian Gouriéroux & Alain Monfort & Eric Renault, 2017, "Consistent Pseudo-Maximum Likelihood Estimators," Working Papers, Center for Research in Economics and Statistics, number 2017-10, Jan.
- Michael Jansson & Demian Pouzo, 2017, "Towards a General Large Sample Theory for Regularized Estimators," Papers, arXiv.org, number 1712.07248, Dec, revised Jul 2020.
- Jérôme Baray & Albert da Silva & Jean-Marc Leblanc, 2017, "L'analyse lexicale au service de la cliodynamique : traitement par intelligence artificielle de la base Google Ngram," Post-Print, HAL, number hal-01648487, Nov.