Report NEP-BIG-2020-01-06
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.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-BIG
The following items were announced in this report:
- Gert Bijnens & Shyngys Karimov & Jozef Konings, 2019. "Wage Indexation and Jobs. A Machine Learning Approach," Working Papers of Department of Economics, Leuven 643831, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
- Brynjolfsson, Erik & Collis, Avinash & Eggers, Felix, 2019. "Using Massive Online Choice Experiments to Measure Changes in Well-being," OSF Preprints akqhn, Center for Open Science.
- KONDO Satoshi & MIYAKAWA Daisuke & SHIRAKI Kengo & SUGA Miki & USUKI Teppei, 2019. "Using Machine Learning to Detect and Forecast Accounting Fraud," Discussion papers 19103, Research Institute of Economy, Trade and Industry (RIETI).
- Sidra Mehtab & Jaydip Sen, 2019. "A Robust Predictive Model for Stock Price Prediction Using Deep Learning and Natural Language Processing," Papers 1912.07700, arXiv.org.
- Firuz Kamalov, 2019. "Forecasting significant stock price changes using neural networks," Papers 1912.08791, arXiv.org.
- Soraya SEDKAOUI & Rafika Benaichouba, 2019. "How data analytics drive sharing economy business models?," Proceedings of International Academic Conferences 9911754, International Institute of Social and Economic Sciences.
- K, Ashin Nishan M & ASHIQ, MUHAMMED V, 2019. "Role of Energy use in the Prediction of CO2 Emissions and Growth in India: An Application of Artificial Neural Networks (ANN)," SocArXiv gkpbu, Center for Open Science.
- Jawwad Noor, 2019. "Intuitive Beliefs," Cowles Foundation Discussion Papers 2216, Cowles Foundation for Research in Economics, Yale University.
- Grodecka, Anna & Hull, Isaiah, 2019. "The Impact of Local Taxes and Public Services on Property Values," Working Paper Series 374, Sveriges Riksbank (Central Bank of Sweden).
- MIYAKAWA Daisuke, 2019. "Shocks to Supply Chain Networks and Firm Dynamics: An Application of Double Machine Learning," Discussion papers 19100, Research Institute of Economy, Trade and Industry (RIETI).
- Alexandru, Daia, 2019. "I Ntroducing A New T Echnical I Ndicator Based On Octav O Nicescu I Nformational E Nergy And Compare It With B Ollinger Bands For S&P 500 M Ovement P Redictions," OSF Preprints m478b, Center for Open Science.
- Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP54/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Watts, Duncan J & Beck, Emorie D & Bienenstock, Elisa Jayne & Bowers, Jake & Frank, Aaron & Grubesic, Anthony & Hofman, Jake M. & Rohrer, Julia Marie & Salganik, Matthew, 2018. "Explanation, prediction, and causality: Three sides of the same coin?," OSF Preprints u6vz5, Center for Open Science.
- Ian Burn & Patrick Button & Luis Felipe Munguia Corella & David Neumark, 2019. "Older Workers Need Not Apply? Ageist Language in Job Ads and Age Discrimination in Hiring," NBER Working Papers 26552, National Bureau of Economic Research, Inc.
- Li, Huafang, 2019. "Book Review: Donald Kettl, Little Bites of Big Data for Public Policy," OSF Preprints 8hy4b, Center for Open Science.
- Alexandru, Daia, 2019. "Experimented Kinetic Energy As Features For Natural Language Classification," OSF Preprints drwc6, Center for Open Science.
- Ho, Tung Manh, 2019. "AI-readiness for circular economy_Prospects and challenges," OSF Preprints s4jpz, Center for Open Science.
- Lily Shen & Stephen L. Ross, 2019. "Information Value of Property Description: A Machine Learning Approach," Working papers 2019-20, University of Connecticut, Department of Economics, revised Sep 2020.
- Michael Jansson & Demian Pouzo, 2019. "Towards a general large sample theory for regularized estimators," CeMMAP working papers CWP63/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Christopher R. Knittel & Samuel Stolper, 2019. "Using Machine Learning to Target Treatment: The Case of Household Energy Use," NBER Working Papers 26531, National Bureau of Economic Research, Inc.
- Kevin Kuo, 2019. "Generative Synthesis of Insurance Datasets," Papers 1912.02423, arXiv.org, revised Aug 2020.
- Jie Fang & Shutao Xia & Jianwu Lin & Zhikang Xia & Xiang Liu & Yong Jiang, 2019. "Alpha Discovery Neural Network based on Prior Knowledge," Papers 1912.11761, arXiv.org, revised Nov 2020.
- Jelena Bradic & Victor Chernozhukov & Whitney K. Newey & Yinchu Zhu, 2019. "Minimax Semiparametric Learning With Approximate Sparsity," Papers 1912.12213, arXiv.org, revised Aug 2022.
- Yosuke Uno & Ko Adachi, 2019. ""Don't know" Tells: Calculating Non-Response Bias in Firms' Inflation Expectations Using Machine Learning Techniques," Bank of Japan Working Paper Series 19-E-17, Bank of Japan.