Report NEP-BIG-2018-10-08

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:

• Jochen Hausler & Marcel Lang & Jessica Ruscheinsky, 2018. "News-based sentiment analysis in real estate: A supervised machine learning approach with support vector networks," ERES eres2018_153, European Real Estate Society (ERES).
• Philipp Maximilien Mueller, 2018. "Automation of the technical due diligence with artificial intelligence in the real estate industry," ERES eres2018_313, European Real Estate Society (ERES).
• Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018. "Nowcasting New Zealand GDP using machine learning algorithms," CAMA Working Papers 2018-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Gallego, J & Rivero, G & Martínez, J.D., 2018. "Preventing rather than Punishing: An Early Warning Model of Malfeasance in Public Procurement," Documentos de Trabajo 16724, Universidad del Rosario.
• Austin Nichols, 2018. "Implementing machine learning methods in Stata," London Stata Conference 2018 08, Stata Users Group.
• Fuli Feng & Xiangnan He & Xiang Wang & Cheng Luo & Yiqun Liu & Tat-Seng Chua, 2018. "Temporal Relational Ranking for Stock Prediction," Papers 1809.09441, arXiv.org, revised Jan 2019.
• Achim Ahrens & Christian B Hansen & Mark E Schaffer, 2018. "LASSOPACK and PDSLASSO: Prediction, model selection and causal inference with regularized regression," London Stata Conference 2018 12, Stata Users Group.
• Ryan Ferguson & Andrew Green, 2018. "Deeply Learning Derivatives," Papers 1809.02233, arXiv.org, revised Oct 2018.
• Ancil Crayton, 2018. "Central Bank Communication and the Yield Curve: A Semi-Automatic Approach using Non-Negative Matrix Factorization," Papers 1809.08718, arXiv.org.
• Mario Bodenbender & Björn-Martin Kurzrock, 2018. "Towards the broad application of machine learning for document classification and data migration in real estate," ERES eres2018_165, European Real Estate Society (ERES).
• Jahn, Malte, 2018. "Artificial neural network regression models: Predicting GDP growth," HWWI Research Papers 185, Hamburg Institute of International Economics (HWWI).
• Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2018. "Deep Neural Networks for Estimation and Inference," Papers 1809.09953, arXiv.org, revised Sep 2019.
• Paul Greenhalgh & Kevin Muldoon-Smith & Adejimi Adebayo & Josephine Ellis, 2018. "Experimental spatial modelling of commercial property stock using GIS," ERES eres2018_61, European Real Estate Society (ERES).
• Giovanni Cerulli, 2018. "Data-driven sensitivity analysis for matching estimators," London Stata Conference 2018 02, Stata Users Group.
• Junfeng Jiang & Jiahao Li, 2018. "Constructing Financial Sentimental Factors in Chinese Market Using Natural Language Processing," Papers 1809.08390, arXiv.org.
• Fernando A Morales & Cristian C Chica & Carlos A Osorio & Daniel Cabarcas J, 2018. "A big data based method for pass rates optimization in mathematics university lower division courses," Papers 1809.09724, arXiv.org, revised Oct 2020.
• Bantle, Melissa & Muijs, Matthias, 2018. "A new price test in geographic market definition – an application to german retail gasoline market," Working Paper 180/2018, Helmut Schmidt University, Hamburg.
• Trapp, Andrew C. & Teytelboym, Alexander & Martinello, Alessandro & Andersson, Tommy & Ahani, Narges, 2018. "Placement Optimization in Refugee Resettlement," Working Papers 2018:23, Lund University, Department of Economics, revised 20 Mar 2020.