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Report NEP-BIG-2023-03-27
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:
- Stephen Hansen & Peter John Lambert & Nicholas Bloom & Steven J. Davis & Raffaella Sadun & Bledi Taska, 2023, "Remote Work across Jobs, Companies, and Space," NBER Working Papers, National Bureau of Economic Research, Inc, number 31007, Mar.
- Nikhil Malik & Emaad Manzoor, 2023, "Does Machine Learning Amplify Pricing Errors in the Housing Market? -- The Economics of Machine Learning Feedback Loops," Papers, arXiv.org, number 2302.09438, Feb.
- Mahdieh Yazdani & Maziar Raissi, 2023, "Real Estate Property Valuation using Self-Supervised Vision Transformers," Papers, arXiv.org, number 2302.00117, Jan.
- Sharma, Rahul, 2021, "The Effects of Artificial Intelligence on the World as a Whole from an Economic Perspective," MPRA Paper, University Library of Munich, Germany, number 116596, Apr.
- Sonan Memon, 2022, "Inflation in Pakistan: High-Frequency Estimation and Forecasting," PIDE-Working Papers, Pakistan Institute of Development Economics, number 2022:12.
- Maudud Hassan Uzzal & Robert Ślepaczuk, 2023, "The performance of time series forecasting based on classical and machine learning methods for S&P 500 index," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-05.
- Lorena Torres Lahoz & Francisco Camara Pereira & Georges Sfeir & Ioanna Arkoudi & Mayara Moraes Monteiro & Carlos Lima Azevedo, 2023, "Attitudes and Latent Class Choice Models using Machine learning," Papers, arXiv.org, number 2302.09871, Feb.
- Shubhranshu Shekhar & Jetson Leder-Luis & Leman Akoglu, 2023, "Unsupervised Machine Learning for Explainable Health Care Fraud Detection," NBER Working Papers, National Bureau of Economic Research, Inc, number 30946, Feb.
- Hansen, Stephen & Lambert, Peter John & Bloom, Nicholas & Davis, Steven J. & Sadun, Raffaella & Taska, Bledi, 2023, "Remote Work across Jobs, Companies, and Space," IZA Discussion Papers, Institute of Labor Economics (IZA), number 15980, Feb.
- Albert,JoseRamonG. & Muñoz,MikaS. & Vizmanos,JanaFlorV. & Brucal,Arlan & Halili,RizaTeresita & Lumba,AngeloJose & Patanñe,GaileAnne, 2022, "Addressing Data Gaps with Innovative Data Sources," Discussion Papers, Philippine Institute for Development Studies, number DP 2022-55, DOI: https://doi.org/10.62986/dp2022.55.
- James Bell, 2023, "The global economic impact of AI technologies in the fight against financial crime," Papers, arXiv.org, number 2302.13823, Feb.
- Philippe Goulet Coulombe, 2021, "The Macroeconomy as a Random Forest," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 21-05, Jun.
- Pedro I. Hancevic & Hector H. Sandoval, 2023, "Solar Panel Adoption in SMEs in Emerging Countries," Working Papers, Red Nacional de Investigadores en Economía (RedNIE), number 222, Mar.
- Philippe Goulet Coulombe, 2022, "A Neural Phillips Curve and a Deep Output Gap," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 22-01, Jan.
- Philipp Adammer & Jan Pruser & Rainer Schussler, 2023, "Forecasting Macroeconomic Tail Risk in Real Time: Do Textual Data Add Value?," Papers, arXiv.org, number 2302.13999, Feb, revised May 2024.
- Laura Nurski, 2023, "Artificial intelligence adoption in the public sector- a case study," Bruegel Working Papers, Bruegel, number node_8829, Mar.
- Fazl Barez & Paul Bilokon & Arthur Gervais & Nikita Lisitsyn, 2023, "Exploring the Advantages of Transformers for High-Frequency Trading," Papers, arXiv.org, number 2302.13850, Feb.
- Dorinth van Dijk & Jasper de Winter, 2023, "Nowcasting GDP using tone-adjusted time varying news topics: Evidence from the financial press," Working Papers, DNB, number 766, Mar.
- Arun Kumar Polala & Bernhard Hientzsch, 2023, "Parametric Differential Machine Learning for Pricing and Calibration," Papers, arXiv.org, number 2302.06682, Feb, revised Feb 2023.
- Alper Deniz Karakas, 2023, "Reevaluating the Taylor Rule with Machine Learning," Papers, arXiv.org, number 2302.08323, Feb.
- Massimiliano Marcellino & Dalibor Stevanovic, 2022, "The demand and supply of information about inflation," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 22-06, Aug, revised Nov 2022.
- Daas, Piet & Hassink, Wolter & Klijs, Bart, 2023, "On the Validity of Using Webpage Texts to Identify the Target Population of a Survey: An Application to Detect Online Platforms," IZA Discussion Papers, Institute of Labor Economics (IZA), number 15941, Feb.
- Wee Ling Tan & Stephen Roberts & Stefan Zohren, 2023, "Spatio-Temporal Momentum: Jointly Learning Time-Series and Cross-Sectional Strategies," Papers, arXiv.org, number 2302.10175, Feb.
- Vasilis Syrgkanis & Ruohan Zhan, 2023, "Post Reinforcement Learning Inference," Papers, arXiv.org, number 2302.08854, Feb, revised Oct 2025.
- Ivan Guo & Nicolas Langren'e & Jiahao Wu, 2023, "Simultaneous upper and lower bounds of American-style option prices with hedging via neural networks," Papers, arXiv.org, number 2302.12439, Feb, revised Nov 2024.