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Big Data
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This RePEc Biblio topic is edited by Domenico Giannone. It was first published on 2017-12-03 17:10:31 and last updated on 2018-07-03 04:36:56.
Most relevant research
- 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, vol. 82(4), pages 540-554, November.
- Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers.
- Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
- 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, vol. 97, pages 1167-1179, December.
- 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 13-003, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 26 Nov 2012.
- Alberto Cavallo & Roberto Rigobon, 2016.
"The Billion Prices Project: Using Online Prices for Measurement and Research,"
Journal of Economic Perspectives,
American Economic Association, vol. 30(2), pages 151-178, Spring.
- Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," NBER Working Papers 22111, National Bureau of Economic Research, Inc.
- Liran Einav & Jonathan Levin, 2013.
"The Data Revolution and Economic Analysis,"
NBER Chapters,in: Innovation Policy and the Economy, Volume 14, pages 1-24
National Bureau of Economic Research, Inc.
- Liran Einav & Jonathan Levin, 2014. "The Data Revolution and Economic Analysis," Innovation Policy and the Economy, University of Chicago Press, vol. 14(1), pages 1-24.
- Liran Einav & Jonathan D. Levin, 2013. "The Data Revolution and Economic Analysis," NBER Working Papers 19035, National Bureau of Economic Research, Inc.
- Liran Einav & Johnathan Levin, 2013. "The Data Revolution and Economic Analysis," Discussion Papers 12-017, Stanford Institute for Economic Policy Research.
- Bok, Brandyn & Caratelli, Daniele & Giannone, Domenico & Sbordone, Argia M. & Tambalotti, Andrea, 2017.
"Macroeconomic nowcasting and forecasting with big data,"
Staff Reports
830, Federal Reserve Bank of New York.
- Bok, Brandyn & Caratelli, Daniele & Giannone, Domenico & Sbordone, Argia & Tambalotti, Andrea, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," CEPR Discussion Papers 12589, C.E.P.R. Discussion Papers.
- Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2017. "Human Decisions and Machine Predictions," NBER Working Papers 23180, National Bureau of Economic Research, Inc.
- Serena Ng, 2017. "Opportunities and Challenges: Lessons from Analyzing Terabytes of Scanner Data," NBER Working Papers 23673, National Bureau of Economic Research, Inc.
- Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
- Alexandre Belloni & Victor Chernozhukov, 2011. "High Dimensional Sparse Econometric Models: An Introduction," Papers 1106.5242, arXiv.org, revised Sep 2011.
- RePEc:ecl:stabus:3350 is not listed on IDEAS
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014.
"High-Dimensional Methods and Inference on Structural and Treatment Effects,"
Journal of Economic Perspectives,
American Economic Association, vol. 28(2), pages 29-50, Spring.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers CWP59/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E, 2017.
"Economic Predictions with Big Data: The Illusion Of Sparsity,"
CEPR Discussion Papers
12256, C.E.P.R. Discussion Papers.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2018. "Economic predictions with big data: the illusion of sparsity," Staff Reports 847, Federal Reserve Bank of New York.
- Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016.
"Bayesian Compressed Vector Autoregressions,"
Working Papers
2016_09, Business School - Economics, University of Glasgow.
- Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103R, Brandeis University, Department of Economics and International Businesss School, revised Apr 2016.
- Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Businesss School.
- Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2017. "Bayesian Compressed Vector Autoregressions," Working Paper series 17-32, Rimini Centre for Economic Analysis.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2017.
"Dissecting Characteristics Nonparametrically,"
CESifo Working Paper Series
6391, CESifo Group Munich.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2017. "Dissecting Characteristics Nonparametrically," NBER Working Papers 23227, National Bureau of Economic Research, Inc.
- Serhiy Kozak & Stefan Nagel & Shrihari Santosh, 2017.
"Shrinking the Cross Section,"
NBER Working Papers
24070, National Bureau of Economic Research, Inc.
- Kozak, Serhiy & Nagel, Stefan & Santosh, Shrihari, 2017. "Shrinking the Cross Section," CEPR Discussion Papers 12463, C.E.P.R. Discussion Papers.