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Big Data

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This RePEc Biblio topic is edited by Domenico Giannone (pgi49). It was first published on 2017-12-03 17:10:31 and last updated on 2018-07-03 04:36:56.

Most relevant research

  1. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000, "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, volume 82, issue 4, pages 540-554, November.
  2. Stock J.H. & Watson M.W., 2002, "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, volume 97, pages 1167-1179, December.
  3. Francis X. Diebold, 2012, "A Personal Perspective on the Origin(s) and Development of “Big Data": The Phenomenon, the Term, and the Discipline, Second Version," PIER Working Paper Archive, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 13-003, Aug, revised 26 Nov 2012.
  4. Alberto Cavallo & Roberto Rigobon, 2016, "The Billion Prices Project: Using Online Prices for Measurement and Research," Journal of Economic Perspectives, American Economic Association, volume 30, issue 2, pages 151-178, Spring.
  5. Liran Einav & Jonathan Levin, 2013, "The Data Revolution and Economic Analysis," NBER Chapters, National Bureau of Economic Research, Inc, "Innovation Policy and the Economy, Volume 14".
  6. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2017, "Macroeconomic nowcasting and forecasting with big data," Staff Reports, Federal Reserve Bank of New York, number 830, Nov.
  7. Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2017, "Human Decisions and Machine Predictions," NBER Working Papers, National Bureau of Economic Research, Inc, number 23180, Feb.
  8. Serena Ng, 2017, "Opportunities and Challenges: Lessons from Analyzing Terabytes of Scanner Data," NBER Working Papers, National Bureau of Economic Research, Inc, number 23673, Aug.
  9. Hal R. Varian, 2014, "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, volume 28, issue 2, pages 3-28, Spring.
  10. Alexandre Belloni & Victor Chernozhukov, 2011, "High Dimensional Sparse Econometric Models: An Introduction," Papers, arXiv.org, number 1106.5242, Jun, revised Sep 2011.
  11. Athey, Susan & Imbens, Guido W., 2015, "Machine Learning for Estimating Heterogeneous Causal Effects," Research Papers, Stanford University, Graduate School of Business, number 3350, Apr.
  12. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014, "High-Dimensional Methods and Inference on Structural and Treatment Effects," Journal of Economic Perspectives, American Economic Association, volume 28, issue 2, pages 29-50, Spring.
  13. Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2017, "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers, Centre for Economic Policy Research, number 12256, Aug.
  14. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016, "Bayesian Compressed Vector Autoregressions," Working Papers, Business School - Economics, University of Glasgow, number 2016_09, Mar.
  15. Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2017, "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series, CESifo, number 6391.
  16. Serhiy Kozak & Stefan Nagel & Shrihari Santosh, 2017, "Shrinking the Cross Section," NBER Working Papers, National Bureau of Economic Research, Inc, number 24070, Nov.