Report NEP-BIG-2023-01-09

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:

• Rameshwar Garg & Shriya Barpanda & Girish Rao Salanke N S & Ramya S, 2022, "Machine Learning Algorithms for Time Series Analysis and Forecasting," Papers, arXiv.org, number 2211.14387, Nov.
• Li, Ziqi, 2022, "Understanding Factors Influencing Willingness to Ridesharing Using Big Trip Data and Interpretable Machine Learning," OSF Preprints, Center for Open Science, number chy4p, Apr, DOI: 10.31219/osf.io/chy4p.
• Meisenbacher, Stephen & Norlander, Peter, 2022, "Creating Data from Unstructured Text with Context Rule Assisted Machine Learning (CRAML)," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1214.
• Item repec:dar:wpaper:135656 is not listed on IDEAS anymore

• Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann & Achim Ahrens, 2022, "ddml: Double/debiased machine learning in Stata," Swiss Stata Conference 2022, Stata Users Group, number 02, Nov.
• Kakuho Furukawa & Ryohei Hisano, 2022, "A Nowcasting Model of Exports Using Maritime Big Data," Bank of Japan Working Paper Series, Bank of Japan, number 22-E-19, Dec.
• Zhenkun Zhou & Zikun Song & Tao Ren, 2022, "Predicting China's CPI by Scanner Big Data," Papers, arXiv.org, number 2211.16641, Nov, revised Oct 2023.
• Tamay Besiroglu & Nicholas Emery-Xu & Neil Thompson, 2022, "Economic impacts of AI-augmented R&D," Papers, arXiv.org, number 2212.08198, Dec, revised Jan 2023.
• Zheng Cao & Raymond Guo & Wenyu Du & Jiayi Gao & Kirill V. Golubnichiy, 2022, "Optimizing Stock Option Forecasting with the Assembly of Machine Learning Models and Improved Trading Strategies," Papers, arXiv.org, number 2211.15912, Nov.
• Marc Wildi & Branka Hadji Misheva, 2022, "A Time Series Approach to Explainability for Neural Nets with Applications to Risk-Management and Fraud Detection," Papers, arXiv.org, number 2212.02906, Dec.
• Kim Ristolainen, 2022, "Narrative Triggers of Information Sensitivity," Discussion Papers, Aboa Centre for Economics, number 156, Dec.
• Massimiliano Fessina & Giambattista Albora & Andrea Tacchella & Andrea Zaccaria, 2022, "Which products activate a product? An explainable machine learning approach," Papers, arXiv.org, number 2212.03094, Dec.
• Tauchert, Christoph, 2022, "Adoption of AI-based Information Systems from an Organizational and User Perspective," Publications of Darmstadt Technical University, Institute for Business Studies (BWL), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 135700.
• Altman, Edward I. & Balzano, Marco & Giannozzi, Alessandro & Srhoj, Stjepan, 2022, "Revisiting SME default predictors: The Omega Score," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1207.
• Luigi Biagini & Simone Severini, 2022, "Can Machine Learning discover the determining factors in participation in insurance schemes? A comparative analysis," Papers, arXiv.org, number 2212.03092, Dec, revised Dec 2022.
• Sara Salamat & Nima Tavassoli & Behnam Sabeti & Reza Fahmi, 2022, "Text Representation Enrichment Utilizing Graph based Approaches: Stock Market Technical Analysis Case Study," Papers, arXiv.org, number 2211.16103, Nov.
• Edouard Ribes, 2022, "Using classification techniques to accelerate client discovery: a case study for wealth management services," Working Papers, HAL, number hal-03887759, Dec.
• Item repec:hal:wpaper:hal-03880381 is not listed on IDEAS anymore

• Edward I. Altman & Marco Balzano & Alessandro Giannozzi & Stjepan Srhoj, 2022, "Revisiting SME default predictors: The Omega Score," Working Papers, Faculty of Economics and Statistics, Universität Innsbruck, number 2022-19.
• Jan Ditzen & Francesco Ravazzolo, 2022, "Dominant Drivers of National Inflation," BEMPS - Bozen Economics & Management Paper Series, Faculty of Economics and Management at the Free University of Bozen, number BEMPS97, Dec.
• Luigi Biagini, 2022, "Applications of Machine Learning for the Ratemaking in Agricultural Insurances," Papers, arXiv.org, number 2212.03114, Dec, revised Dec 2022.
• Laura Bonacorsi & Vittoria Cerasi & Paola Galfrascoli & Matteo Manera, 2022, "ESG Factors and Firms' Credit Risk," Working Papers, University of Milano-Bicocca, Department of Economics, number 507, Dec, revised Dec 2022.
• Thi Thu Giang Nguyen & Robert Ślepaczuk, 2022, "The efficiency of various types of input layers of LSTM model in investment strategies on S&P500 index," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2022-29.
• Damian Kisiel & Denise Gorse, 2022, "Axial-LOB: High-Frequency Trading with Axial Attention," Papers, arXiv.org, number 2212.01807, Dec.
• Morteza Tahami Pour Zarandi & Mehdi Ghasemi Meymandi & Mohammad Hemami, 2022, "A comprehensive study of cotton price fluctuations using multiple Econometric and LSTM neural network models," Papers, arXiv.org, number 2212.01584, Dec, revised Dec 2022.
• Laura Bonacorsi & Vittoria Cerasi & Paola Galfrascoli & Matteo Manera, 2022, "ESG Factors and Firms’ Credit Risk," Working Papers, Fondazione Eni Enrico Mattei, number 2022.36, Nov.
• Ziwei Mei & Zhentao Shi & Peter C. B. Phillips, 2022, "The boosted HP filter is more general than you might think," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University, number 2348, Sep.
• Julia Cagé & Nicolas Hervé & Béatrice Mazoyer, 2022, "Social Media Influence Mainstream Media: Evidence from Two Billion Tweets," Working Papers, HAL, number hal-03877907, Jul.
• C. Biliotti & F. J. Bargagli-Stoffi & N. Fraccaroli & M. Puliga & M. Riccaboni, 2022, "Breaking Down the Lockdown: The Causal Effects of Stay-At-Home Mandates on Uncertainty and Sentiments During the COVID-19 Pandemic," Papers, arXiv.org, number 2212.01705, Dec, revised Jun 2023.
• Jie Zou & Jiashu Lou & Baohua Wang & Sixue Liu, 2022, "A Novel Deep Reinforcement Learning Based Automated Stock Trading System Using Cascaded LSTM Networks," Papers, arXiv.org, number 2212.02721, Dec, revised Jul 2023.
• Zhongchen Song & Tom Coupé, 2022, "Predicting Chinese consumption series with Baidu," Working Papers in Economics, University of Canterbury, Department of Economics and Finance, number 22/19, Dec.
• MASSUCCI Francesco & SERI Alessandro, 2022, "Exploratory study understanding the SDG alignment along research activities and technological innovation of Scoreboard companies," JRC Research Reports, Joint Research Centre, number JRC130479, Nov.
• Hyo Sang Kim & Eunjung Kang & Yuri Kim & Seongman Moon & Huisu Jang, 2022, "Exchange Rate Predictability Based on Market Sentiments," World Economy Brief, Korea Institute for International Economic Policy, number 22-42, Sep.
• Axenbeck, Janna & Berner, Anne & Kneib, Thomas, 2022, "What drives the relationship between digitalization and industrial energy demand? Exploring firm-level heterogeneity," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 22-059.
• Peter Fisker & Kenneth Mdadila, 2022, "Urban Poverty Mapping with Open Spatial Data: Evidence from Dar es Salaam," DERG working paper series, University of Copenhagen. Department of Economics. Development Economics Research Group (DERG), number 22-17, Dec.
• Dorothee Weiffen & Ghassan Baliki & Tilman Brück, 2022, "Violent conflict moderates food security impacts of agricultural asset transfers in Syria: A heterogeneity analysis using machine learning," HiCN Working Papers, Households in Conflict Network, number 381, Dec.
• Edouard Ribes, 2022, "Transforming personal finance thanks to artificial intelligence: myth or reality?," Working Papers, HAL, number hal-03862261, Nov.
• Joel Terschuur, 2022, "Educational Inequality of Opportunity and Mobility in Europe," Papers, arXiv.org, number 2212.02407, Dec, revised Mar 2023.
• Item repec:hal:wpaper:hal-03903047 is not listed on IDEAS anymore

• Kühl, Niklas & Goutier, Marc & Baier, Lucas & Wolff, Clemens & Martin, Dominik, 2022, "Human vs. supervised machine learning: Who learns patterns faster?," Publications of Darmstadt Technical University, Institute for Business Studies (BWL), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 135657.
• Dimitrios Kanelis & Pierre L. Siklos, 2022, "Emotion in Euro Area Monetary Policy Communication and Bond Yields: The Draghi Era," CQE Working Papers, Center for Quantitative Economics (CQE), University of Muenster, number 10322, Dec.
• Dimitrios Kanelis & Pierre L. Siklos, 2022, "Emotion in Euro Area Monetary Policy Communication and Bond Yields: The Draghi Era," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2022-75, Dec, revised Jun 2024.
• Dragos Gorduza & Xiaowen Dong & Stefan Zohren, 2022, "Understanding stock market instability via graph auto-encoders," Papers, arXiv.org, number 2212.04974, Dec.
• Rossouw, Stephanié & Greyling, Talita, 2022, "Collective emotions and macro-level shocks: COVID-19 vs the Ukrainian war," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1210.
• Emily Silcock & Luca D'Amico-Wong & Jinglin Yang & Melissa Dell, 2022, "Noise-Robust De-Duplication at Scale," NBER Working Papers, National Bureau of Economic Research, Inc, number 30726, Dec.
• Taiga Saito & Shivam Gupta, 2022, "Big data applications with theoretical models and social media in financial management," CARF F-Series, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo, number CARF-F-550, Dec.
• Salazar, Lina & Palacios, Ana Claudia & Selvaraj, Michael & Montenegro, Frank, 2021, "Using Satellite Images to Measure Crop Productivity: Long-Term Impact Assessment of a Randomized Technology Adoption Program in the Dominican Republic," IDB Publications (Working Papers), Inter-American Development Bank, number 11607, Sep, DOI: http://dx.doi.org/10.18235/0003604.
• Irene Aldridge & Payton Martin, 2022, "ESG In Corporate Filings: An AI Perspective," Papers, arXiv.org, number 2212.00018, Nov.
• Massimiliano Marcellino & Dalibor Stevanovic, 2022, "The demand and supply of information about inflation," CIRANO Working Papers, CIRANO, number 2022s-27, Dec.
• Proeger, Till & Meub, Lukas, 2022, "Fortgeschrittene Digitalisierung und Künstliche Intelligenz im Handwerk: Eine Webscraping-Analyse im Handwerkskammerbezirk Osnabrück-Emsland-Grafschaft Bentheim," ifh Forschungsberichte, Volkswirtschaftliches Institut für Mittelstand und Handwerk an der Universität Göttingen (ifh), number 5, DOI: 10.47952/gro-publ-116.
• Oeindrila Dube & Joshua E. Blumenstock & Michael Callen & Michael J. Callen, 2022, "Measuring Religion from Behavior: Climate Shocks and Religious Adherence in Afghanistan," CESifo Working Paper Series, CESifo, number 10114.
• Carmen Vázquez de Castro Álvarez-Buylla, 2022, "Tecnologías emergentes e IA: algunos ejemplos prácticos de aplicaciones y de los procesos de aprendizaje," Fedea Economy Notes, FEDEA, number 2022-33, Dec.
• Sholler, Dan & MacInnes, Ian, 2022, "The economic impact of AI on employment and income disparities," 31st European Regional ITS Conference, Gothenburg 2022: Reining in Digital Platforms? Challenging monopolies, promoting competition and developing regulatory regimes, International Telecommunications Society (ITS), number 265669.

Report NEP-BIG-2023-01-09

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: