Report NEP-BIG-2022-07-25

This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé issued this report. It is usually issued weekly.

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Other reports in NEP-BIG

The following items were announced in this report:

• Diane Coyle & Wendy Li, 2021. "The Data Economy: Market Size and Global Trade," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2021-09, Economic Statistics Centre of Excellence (ESCoE).
• Stef Garasto & Jyldyz Djumalieva & Karlis Kanders & Rachel Wilcock & Cath Sleeman, 2021. "Developing experimental estimates of regional skill demand," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2021-02, Economic Statistics Centre of Excellence (ESCoE).
• Diana Gabrielyan & Lenno Uusküla, 2022. "Inflation Expectations And Consumption With Machine Learning," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 142, Faculty of Economics and Business Administration, University of Tartu (Estonia).
• Kaiser, Caspar & Oparina, Ekaterina & Gentile, Niccolò & Tkatchenko, Alexandre & Clark, Andrew E. & De Neve, Jan-Emmanuel & D’Ambrosio, Conchita, 2022. "Human Wellbeing and Machine Learning," INET Oxford Working Papers 2022-11, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
• Marian Moszoro & Mauricio Soto, 2022. "Road Quality and Mean Speed Score," IMF Working Papers 2022/095, International Monetary Fund.
• Thibaut Plassot & Isidro Soloaga & Pedro J. Torres L., 2022. "A Random Forest approach of the Evolution of Inequality of Opportunity in Mexico," Working Paper Series Sobre México 2022004, Sobre México. Temas en economía.
• Ana Galvao & James Mitchell, 2021. "Communicating Data Uncertainty: Multi-Wave Experimental Evidence for U.K. GDP," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2021-06, Economic Statistics Centre of Excellence (ESCoE).
• Mr. Sakai Ando & Mr. Taehoon Kim, 2022. "Systematizing Macroframework Forecasting: High-Dimensional Conditional Forecasting with Accounting Identities," IMF Working Papers 2022/110, International Monetary Fund.
• Valerio Astuti & Marta Crispino & Marco Langiulli & Juri Marcucci, 2022. "Textual analysis of a Twitter corpus during the COVID-19 pandemics," Questioni di Economia e Finanza (Occasional Papers) 692, Bank of Italy, Economic Research and International Relations Area.
• Majid Ahmadi & Nathan Durst & Jeff Lachman & Mason List & Noah List & John List & Atom Vayalinkal, 2022. "Nothing Propinks Like Propinquity: Using Machine Learning to Estimate the Effects of Spatial Proximity in the Major League Baseball Draft," Artefactual Field Experiments 00758, The Field Experiments Website.
• Yanzhao Zou & Dorien Herremans, 2022. "PreBit -- A multimodal model with Twitter FinBERT embeddings for extreme price movement prediction of Bitcoin," Papers 2206.00648, arXiv.org, revised Oct 2023.
• Mr. Philip Barrett, 2022. "Reported Social Unrest Index: March 2022 Update," IMF Working Papers 2022/084, International Monetary Fund.
• Sei Sugino & Yuji Maruo, 2022. "Economic Implications of the Use of Personal Information: Potential Impact of the Digital Platform Companies on Payment Services," Bank of Japan Review Series 22-E-05, Bank of Japan.
• Kevin Kamm & Michelle Muniz, 2022. "A novel approach to rating transition modelling via Machine Learning and SDEs on Lie groups," Papers 2205.15699, arXiv.org.
• Karim Barhoumi & Seung Mo Choi & Tara Iyer & Jiakun Li & Franck Ouattara & Mr. Andrew J Tiffin & Jiaxiong Yao, 2022. "Overcoming Data Sparsity: A Machine Learning Approach to Track the Real-Time Impact of COVID-19 in Sub-Saharan Africa," IMF Working Papers 2022/088, International Monetary Fund.
• Callum Rhys Tilbury, 2022. "Reinforcement Learning for Economic Policy: A New Frontier?," Papers 2206.08781, arXiv.org, revised Feb 2023.
• Robert C. M. Beyer & Yingyao Hu & Jiaxiong Yao, 2022. "Measuring Quarterly Economic Growth from Outer Space," IMF Working Papers 2022/109, International Monetary Fund.
• Sara B. Heller & Benjamin Jakubowski & Zubin Jelveh & Max Kapustin, 2022. "Machine Learning Can Predict Shooting Victimization Well Enough to Help Prevent It," NBER Working Papers 30170, National Bureau of Economic Research, Inc.
• Veli Andirin & Yusuf Neggers & Mehdi Shadmehr & Jesse M. Shapiro, 2022. "Surveillance of Repression: Theory and Implementation," NBER Working Papers 30167, National Bureau of Economic Research, Inc.
• Daniel Bjorkegren & Joshua E. Blumenstock & Samsun Knight, 2022. "(Machine) Learning What Policies Value," Papers 2206.00727, arXiv.org.
• Joelle Abramowitz, 2021. "What We Talk about When We Talk about Self-employment: Examining Self-employment and the Transition to Retirement among Older Adults in the United States," Working Papers wp423, University of Michigan, Michigan Retirement Research Center.
• Victor Quintas-Martinez, 2022. "Finite-Sample Guarantees for High-Dimensional DML," Papers 2206.07386, arXiv.org.
• Buckmann, Marcus & Joseph, Andreas, 2022. "An interpretable machine learning workflow with an application to economic forecasting," Bank of England working papers 984, Bank of England.
• Michael Kitchener & Nandini Anantharama & Simon D. Angus & Paul A. Raschky, 2022. "Predicting Political Ideology from Digital Footprints," Papers 2206.00397, arXiv.org.