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The Data Revolution and Economic Analysis

Citations

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. big data and economic research
    by René Böheim in Econ Tidbits on 2013-05-14 10:38:00
  2. The fuss about big data
    by Economic Logician in Economic Logic on 2013-09-25 19:01:00

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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Cited by:

  1. Christian Baker & Jeremy Bejarano & Richard W. Evans & Kenneth L. Judd & Kerk L. Phillips, 2014. "A Big Data Approach to Optimal Sales Taxation," BYU Macroeconomics and Computational Laboratory Working Paper Series 2014-03, Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory.
  2. Qaisar Ali & Hakimah Yaacob & Shazia Parveen & Zaki Zaini, 2021. "Big data and predictive analytics to optimise social and environmental performance of Islamic banks," Environment Systems and Decisions, Springer, vol. 41(4), pages 616-632, December.
  3. Batel Ziv & Yisrael Parmet, 2022. "Improving nonconformity responsibility decisions: a semi-automated model based on CRISP-DM," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(2), pages 657-667, April.
  4. Thomas F. Crossley & Jochem Bresser & Liam Delaney & Joachim Winter, 2017. "Can Survey Participation Alter Household Saving Behaviour?," Economic Journal, Royal Economic Society, vol. 127(606), pages 2332-2357, November.
  5. Anna Gerbrandy, 2019. "Rethinking Competition Law within the European Economic Constitution," Journal of Common Market Studies, Wiley Blackwell, vol. 57(1), pages 127-142, January.
  6. Nathan, Max & Rosso, Anna, 2022. "Innovative events: product launches, innovation and firm performance," Research Policy, Elsevier, vol. 51(1).
  7. Whitaker, Stephan D., 2018. "Big Data versus a survey," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 285-296.
  8. Max Nathan & Anna Rosso, 2017. "Innovative events," Development Working Papers 429, Centro Studi Luca d'Agliano, University of Milano, revised 08 Apr 2019.
  9. Patel, Pankaj C. & Devaraj, Srikant & Quigley, Narda R. & Oghazi, Pejvak, 2020. "The influence of sunlight on taxi driver productivity," Journal of Business Research, Elsevier, vol. 115(C), pages 456-468.
  10. Matteo Iacopini & Carlo R.M.A. Santagiustina, 2021. "Filtering the intensity of public concern from social media count data with jumps," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1283-1302, October.
  11. Simson L. Garfinkel, 2018. "Privacy and Security Concerns When Social Scientists Work with Administrative and Operational Data," The ANNALS of the American Academy of Political and Social Science, , vol. 675(1), pages 83-101, January.
  12. Nathan, Max & Rosso, Anna, 2015. "Mapping digital businesses with big data: Some early findings from the UK," Research Policy, Elsevier, vol. 44(9), pages 1714-1733.
  13. Götz, Thomas B. & Knetsch, Thomas A., 2019. "Google data in bridge equation models for German GDP," International Journal of Forecasting, Elsevier, vol. 35(1), pages 45-66.
  14. Figlio, D. & Karbownik, K. & Salvanes, K.G., 2016. "Education Research and Administrative Data," Handbook of the Economics of Education,, Elsevier.
  15. Avi Goldfarb & Shane M. Greenstein & Catherine E. Tucker, 2015. "Introduction to "Economic Analysis of the Digital Economy"," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 1-17, National Bureau of Economic Research, Inc.
  16. Nathan, Max & Rosso, Anna, 2014. "Mapping information economy businesses with big data: findings from the UK," LSE Research Online Documents on Economics 60615, London School of Economics and Political Science, LSE Library.
  17. Jens Prüfer & Christoph Schottmüller, 2021. "Competing with Big Data," Journal of Industrial Economics, Wiley Blackwell, vol. 69(4), pages 967-1008, December.
  18. Martin Browning & Thomas F. Crossley & Joachim Winter, 2014. "The Measurement of Household Consumption Expenditures," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 475-501, August.
  19. Nathan, Max & Rosso, Anna, 2014. "Mapping information economy businesses with big data: findings from the UK," LSE Research Online Documents on Economics 60615, London School of Economics and Political Science, LSE Library.
  20. Katsuyuki Tanaka & Takuji Kinkyo & Shigeyuki Hamori, 2018. "Financial Hazard Map: Financial Vulnerability Predicted by a Random Forests Classification Model," Sustainability, MDPI, vol. 10(5), pages 1-18, May.
  21. Laurent Bergé, 2018. "Efficient estimation of maximum likelihood models with multiple fixed-effects: the R package FENmlm," DEM Discussion Paper Series 18-13, Department of Economics at the University of Luxembourg.
  22. Cwynar Andrzej & Cwynar Wiktor & Pater Robert & Kaźmierkiewicz Piotr, 2017. "Information needs of financial market professionals in the big data and social media era. The empirical evidence from Poland," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 13(4), pages 1-13, December.
  23. Justin Longo & Alan Rodney Dobell, 2018. "The Limits of Policy Analytics: Early Examples and the Emerging Boundary of Possibilities," Politics and Governance, Cogitatio Press, vol. 6(4), pages 5-17.
  24. Jin-Hyuk Kim & Tin Cheuk Leung, 2013. "Quantifying the Impacts of Digital Rights Management and E-Book Pricing on the E-Book Reader Market," Working Papers 13-03, NET Institute.
  25. Dengler, Sebastian & Prüfer, Jens, 2021. "Consumers' privacy choices in the era of big data," Games and Economic Behavior, Elsevier, vol. 130(C), pages 499-520.
  26. 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.
  27. Serena Ng, 2017. "Opportunities and Challenges: Lessons from Analyzing Terabytes of Scanner Data," NBER Working Papers 23673, National Bureau of Economic Research, Inc.
  28. Shaoming Cheng & Sukumar Ganapati & Giri Narasimhan & Farzana Beente Yusuf, 2022. "A machine learning‐based analysis of 311 requests in the Miami‐Dade County," Growth and Change, Wiley Blackwell, vol. 53(4), pages 1627-1645, December.
  29. Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
  30. Agnese Carella & Federica Ciocchetta & Valentina Michelangeli & Federico Maria Signoretti, 2020. "What can we learn about mortgage supply from online data?," Questioni di Economia e Finanza (Occasional Papers) 583, Bank of Italy, Economic Research and International Relations Area.
  31. Juan Tenorio & Wilder Perez, 2024. "Monthly GDP nowcasting with Machine Learning and Unstructured Data," Papers 2402.04165, arXiv.org.
  32. de Pedraza, Pablo & Vollbracht, Ian, 2020. "The Semicircular Flow of the Data Economy and the Data Sharing Laffer curve," GLO Discussion Paper Series 515, Global Labor Organization (GLO).
  33. Ana Suárez Álvarez & María R. Vicente, 2023. "Going “beyond the GDP” in the digital economy: exploring the relationship between internet use and well-being in Spain," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
  34. DeVaro, Jed & Kim, Jin-Hyuk & Wagman, Liad & Wolff, Ran, 2018. "Motivation and performance of user-contributors: Evidence from a CQA forum," Information Economics and Policy, Elsevier, vol. 42(C), pages 56-65.
  35. Jesse Tack & Keith H. Coble & Robert Johansson & Ardian Harri & Barry J. Barnett, 2019. "The Potential Implications of “Big Ag Data” for USDA Forecasts," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 41(4), pages 668-683, December.
  36. Kaiser, Ulrich & Kuhn, Johan M., 2020. "The value of publicly available, textual and non-textual information for startup performance prediction," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
  37. David Figlio & Krzysztof Karbownik & Kjell Salvanes, 2017. "The Promise of Administrative Data in Education Research," Education Finance and Policy, MIT Press, vol. 12(2), pages 129-136, Spring.
  38. Lane, Julia I. & Owen-Smith, Jason & Rosen, Rebecca F. & Weinberg, Bruce A., 2015. "New linked data on research investments: Scientific workforce, productivity, and public value," Research Policy, Elsevier, vol. 44(9), pages 1659-1671.
  39. D. Kalaivani & P. Sumathi, 2019. "Factor based prediction model for customer behavior analysis," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(4), pages 519-524, August.
  40. Levent Bulut, 2015. "Google Trends and Forecasting Performance of Exchange Rate Models," IPEK Working Papers 1505, Ipek University, Department of Economics.
  41. Pablo Pedraza & Ian Vollbracht, 2023. "General theory of data, artificial intelligence and governance," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
  42. Blazquez, Desamparados & Domenech, Josep, 2018. "Big Data sources and methods for social and economic analyses," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 99-113.
  43. Thomas Rouyard & Yukichi Mano & Bocar Mamadou Daff & Serigne Diouf & Khadidiatou Fall Dia & Laetitia Duval & Josselin Thuilliez & Ryota Nakamura, 2022. "Operational and Structural Factors Influencing Enrolment in Community-Based Health Insurance Schemes: An Observational Study Using 12 Waves of Nationwide Panel Data from Senegal," Post-Print halshs-03641124, HAL.
  44. Aur'elien Ouattara & Matthieu Bult'e & Wan-Ju Lin & Philipp Scholl & Benedikt Veit & Christos Ziakas & Florian Felice & Julien Virlogeux & George Dikos, 2021. "Scalable Econometrics on Big Data -- The Logistic Regression on Spark," Papers 2106.10341, arXiv.org.
  45. Resce, Giuliano & Vaquero-Piñeiro, Cristina, 2022. "Predicting agri-food quality across space: A Machine Learning model for the acknowledgment of Geographical Indications," Food Policy, Elsevier, vol. 112(C).
  46. John Hudson, 2017. "Identifying economics’ place amongst academic disciplines: a science or a social science?," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 735-750, November.
  47. HaeOk Choi & KwangHo Lee, 2020. "Micro-Operating Mechanism Approach for Regulatory Sandbox Policy Focused on Fintech," Sustainability, MDPI, vol. 12(19), pages 1-11, October.
  48. Wagner Piazza Gaglianone & João Victor Issler, 2014. "Microfounded Forecasting," Working Papers Series 372, Central Bank of Brazil, Research Department.
  49. Delogu, Marco & Lagravinese, Raffaele & Paolini, Dimitri & Resce, Giuliano, 2024. "Predicting dropout from higher education: Evidence from Italy," Economic Modelling, Elsevier, vol. 130(C).
  50. Haskamp, Ulrich, 2017. "Improving the forecasts of European regional banks' profitability with machine learning algorithms," Ruhr Economic Papers 705, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  51. Nenad Živić & Igor Andjelković & Tolga Özden & Milovan Dekić & Edward Castronova, 2017. "Results of a massive experiment on virtual currency endowments and money demand," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-14, October.
  52. Tuhkuri, Joonas, 2016. "ETLAnow: A Model for Forecasting with Big Data – Forecasting Unemployment with Google Searches in Europe," ETLA Reports 54, The Research Institute of the Finnish Economy.
  53. Schultze, Steven R. & Mujica, Frances C. & Kleinheksel, A.J., 2019. "Demographic and spatial trends in diabetes-related virtual nursing examinations," Social Science & Medicine, Elsevier, vol. 222(C), pages 225-230.
  54. Daniel Hopp, 2021. "Economic Nowcasting with Long Short-Term Memory Artificial Neural Networks (LSTM)," Papers 2106.08901, arXiv.org.
  55. Marieke Bos & Emily Breza & Andres Liberman, 2018. "The Labor Market Effects of Credit Market Information," The Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2005-2037.
  56. Zhou, Jinyan & Du, Ping & Zhao, Wen & Feng, Siche, 2022. "Skill requirements and remunerations in the private teacher labor market: Estimations with online advertisements in China," International Journal of Educational Development, Elsevier, vol. 92(C).
  57. Abu Taher, Sheikh & Uddin, Md. Kama, 2018. "Use of big data in financial sector of Bangladesh – A review," 22nd ITS Biennial Conference, Seoul 2018. Beyond the boundaries: Challenges for business, policy and society 190348, International Telecommunications Society (ITS).
  58. Resce, Giuliano & Maynard, Diana, 2018. "What matters most to people around the world? Retrieving Better Life Index priorities on Twitter," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 61-75.
  59. Ka Chung Ng & Ping Fan Ke & Mike K. P. So & Kar Yan Tam, 2023. "Augmenting fake content detection in online platforms: A domain adaptive transfer learning via adversarial training approach," Production and Operations Management, Production and Operations Management Society, vol. 32(7), pages 2101-2122, July.
  60. Samppa Suoniemi & Lars Meyer-Waarden & Andreas Munzel & Alex Ricardo Zablah & Detmar Straub, 2020. "Big data and firm performance: The roles of market-directed capabilities and business strategy," Post-Print hal-02957479, HAL.
  61. Abhishek Nagaraj & Fernando Stipanicic & Matteo Tranchero, 2024. "The Importance of Confidential Microdata for Economic Research," NBER Chapters, in: Data Privacy Protection and the Conduct of Applied Research: Methods, Approaches and their Consequences, National Bureau of Economic Research, Inc.
  62. Konstantin Klemmer & Tobias Brandt & Stephen Jarvis, 2018. "Isolating the effect of cycling on local business environments in London," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-31, December.
  63. Marcel Fafchamps & Julien Labonne, 2017. "Do Politicians’ Relatives Get Better Jobs? Evidence from Municipal Elections," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 33(2), pages 268-300.
  64. Zhongqi Deng & Yu Zhang & Ao Yu, 2020. "The New Economy in China: An Intercity Comparison," SAGE Open, , vol. 10(4), pages 21582440209, December.
  65. Cristiano Codagnone & Fabienne Abadie & Federico Biagi, 2016. "The Future of Work in the ‘Sharing Economy’. Market Efficiency and Equitable Opportunities or Unfair Precarisation?," JRC Research Reports JRC101280, Joint Research Centre.
  66. Vincze, János, 2017. "Információ és tudás. A big data egyes hatásai a közgazdaságtanra [Information and knowledge: some effects of big data on economics]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(11), pages 1148-1159.
  67. Huidong Sun & Mustafa Raza Rabbani & Muhammad Safdar Sial & Siming Yu & José António Filipe & Jacob Cherian, 2020. "Identifying Big Data’s Opportunities, Challenges, and Implications in Finance," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
  68. Alessandra Garbero & Giuliano Resce & Bia Carneiro, 2021. "Spatial dynamics across food systems transformation in IFAD investments: a machine learning approach," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(5), pages 1125-1143, October.
  69. Gabriel Suarez & Juan Raful & Maria A. Luque & Carlos F. Valencia & Alejandro Correa-Bahnsen, 2021. "Enhancing User' s Income Estimation with Super-App Alternative Data," Papers 2104.05831, arXiv.org, revised Aug 2021.
  70. Jian Gao & Tao Zhou, 2017. "Quantifying China's Regional Economic Complexity," Papers 1703.01292, arXiv.org, revised Nov 2017.
  71. Antulov-Fantulin, Nino & Lagravinese, Raffaele & Resce, Giuliano, 2021. "Predicting bankruptcy of local government: A machine learning approach," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 681-699.
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