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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 (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:
- Diane Coyle & Wendy Li, 2021, "The Data Economy: Market Size and Global Trade," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers, Economic Statistics Centre of Excellence (ESCoE), number ESCoE DP-2021-09, Aug.
- 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, Economic Statistics Centre of Excellence (ESCoE), number ESCoE DP-2021-02, Mar.
- Diana Gabrielyan & Lenno Uusküla, 2022, "Inflation Expectations And Consumption With Machine Learning," University of Tartu - Faculty of Economics and Business Administration Working Paper Series, Faculty of Economics and Business Administration, University of Tartu (Estonia), number 142.
- 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, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, number 2022-11, Jun.
- Marian Moszoro & Mauricio Soto, 2022, "Road Quality and Mean Speed Score," IMF Working Papers, International Monetary Fund, number 2022/095, May.
- 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, Sobre México. Temas en economía, number 2022004, Jun.
- Ana Galvao & James Mitchell, 2021, "Communicating Data Uncertainty: Multi-Wave Experimental Evidence for U.K. GDP," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers, Economic Statistics Centre of Excellence (ESCoE), number ESCoE DP-2021-06, Jun.
- Mr. Sakai Ando & Mr. Taehoon Kim, 2022, "Systematizing Macroframework Forecasting: High-Dimensional Conditional Forecasting with Accounting Identities," IMF Working Papers, International Monetary Fund, number 2022/110, Jun.
- 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), Bank of Italy, Economic Research and International Relations Area, number 692, Jun.
- 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, The Field Experiments Website, number 00758.
- Yanzhao Zou & Dorien Herremans, 2022, "PreBit -- A multimodal model with Twitter FinBERT embeddings for extreme price movement prediction of Bitcoin," Papers, arXiv.org, number 2206.00648, May, revised Oct 2023.
- Mr. Philip Barrett, 2022, "Reported Social Unrest Index: March 2022 Update," IMF Working Papers, International Monetary Fund, number 2022/084, May.
- 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, Bank of Japan, number 22-E-05, Jun.
- Kevin Kamm & Michelle Muniz, 2022, "A novel approach to rating transition modelling via Machine Learning and SDEs on Lie groups," Papers, arXiv.org, number 2205.15699, May.
- 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, International Monetary Fund, number 2022/088, May.
- Callum Rhys Tilbury, 2022, "Reinforcement Learning for Economic Policy: A New Frontier?," Papers, arXiv.org, number 2206.08781, Jun, revised Feb 2023.
- Robert C. M. Beyer & Yingyao Hu & Jiaxiong Yao, 2022, "Measuring Quarterly Economic Growth from Outer Space," IMF Working Papers, International Monetary Fund, number 2022/109, Jun.
- 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, National Bureau of Economic Research, Inc, number 30170, Jun.
- Veli Andirin & Yusuf Neggers & Mehdi Shadmehr & Jesse M. Shapiro, 2022, "Surveillance of Repression: Theory and Implementation," NBER Working Papers, National Bureau of Economic Research, Inc, number 30167, Jun.
- Daniel Bjorkegren & Joshua E. Blumenstock & Samsun Knight, 2022, "(Machine) Learning What Policies Value," Papers, arXiv.org, number 2206.00727, Jun.
- 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, University of Michigan, Michigan Retirement Research Center, number wp423, Sep.
- Victor Quintas-Martinez, 2022, "Finite-Sample Guarantees for High-Dimensional DML," Papers, arXiv.org, number 2206.07386, Jun.
- Marcus Buckmann & Andreas Joseph, 2022, "An interpretable machine learning workflow with an application to economic forecasting," Bank of England working papers, Bank of England, number 984, Jun.
- Michael Kitchener & Nandini Anantharama & Simon D. Angus & Paul A. Raschky, 2022, "Predicting Political Ideology from Digital Footprints," Papers, arXiv.org, number 2206.00397, Jun.