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Communicating Uncertainty in Official Economic Statistics: An Appraisal Fifty Years after Morgenstern

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Cited by:

  1. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
  2. Aljoscha Minnich & Hauke Roggenkamp & Andreas Lange, 2023. "Ambiguity Attitudes and Surprises: Experimental Evidence on Communicating New Information within a Large Population Sample," CESifo Working Paper Series 10783, CESifo.
  3. Feige, Edgar L., 2015. "Reflections on the meaning and measurement of Unobserved Economies: What do we really know about the “Shadow Economy”?," MPRA Paper 68466, University Library of Munich, Germany.
  4. Hobler, Stephan, 2022. "Multi-layered rational inattention and time-varying volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 138(C).
  5. Maria Elena Bontempi & Michele Frigeri & Roberto Golinelli & Matteo Squadrani, 2021. "EURQ: A New Web Search‐based Uncertainty Index," Economica, London School of Economics and Political Science, vol. 88(352), pages 969-1015, October.
  6. Ana Beatriz Galvão & James Mitchell, 2019. "Measuring Data Uncertainty: An Application using the Bank of England's "Fan Charts" for Historical GDP Growth," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-08, Economic Statistics Centre of Excellence (ESCoE).
  7. Dennis J. Fixler & Eva de Francisco & Danit Kanal, 2021. "The Revisions to GDP, GDI, and Their Major Components," Survey of Current Business, Bureau of Economic Analysis, vol. 101(1), pages 1-3, January.
  8. Zachary H. Seeskin, 2016. "Evaluating the Use of Commercial Data to Improve Survey Estimates of Property Taxes," CARRA Working Papers 2016-06, Center for Economic Studies, U.S. Census Bureau.
  9. Herzog, Bodo, 2019. "Optimal policy under uncertainty and rational inattention," Research in International Business and Finance, Elsevier, vol. 50(C), pages 444-449.
  10. Katharina Glass, 2018. "Predictability of Euro Area Revisions," Macroeconomics and Finance Series 201801, University of Hamburg, Department of Socioeconomics.
  11. Daniel H. Weinberg & John M. Abowd & Robert F. Belli & Noel Cressie & David C. Folch & Scott H. Holan & Margaret C. Levenstein & Kristen M. Olson & Jerome P. Reiter & Matthew D. Shapiro & Jolene Smyth, 2017. "Effects of a Government-Academic Partnership: Has the NSF-Census Bureau Research Network Helped Improve the U.S. Statistical System?," Working Papers 17-59r, Center for Economic Studies, U.S. Census Bureau.
  12. Battistin, Erich & De Nadai, Michele & Krishnan, Nandini, 2020. "The Insights and Illusions of Consumption Measurements," IZA Discussion Papers 13222, Institute of Labor Economics (IZA).
  13. van der Bles, Anne Marthe & van der Liden, Sander & Freeman, Alessandra L. J. & Mitchell, James & Galvao, Ana Beatriz & Spiegelhalter, David J., 2019. "Communicating uncertainty about facts, numbers, and science," EMF Research Papers 22, Economic Modelling and Forecasting Group.
  14. Ilaria Benedetti & Federico Crescenzi & Tiziana Laureti, 2020. "Measuring Uncertainty for Poverty Indicators at Regional Level: The Case of Mediterranean Countries," Sustainability, MDPI, vol. 12(19), pages 1-19, October.
  15. Ana Beatriz Galvão & James Mitchell, 2024. "Communicating Data Uncertainty: Multiwave Experimental Evidence for UK GDP," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(1), pages 81-114, February.
  16. Markandya, Anil & Arto, Iñaki & González-Eguino, Mikel & Román, Maria V., 2016. "Towards a green energy economy? Tracking the employment effects of low-carbon technologies in the European Union," Applied Energy, Elsevier, vol. 179(C), pages 1342-1350.
  17. Dionissi Aliprantis & Kristen Tauber, 2020. "Measuring Deaths from COVID-19," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2020(18), pages 1-7, July.
  18. Dionissi Aliprantis & Daniel R. Carroll & Eric Young, 2021. "The Racial Wealth Gap and Access to Opportunity Neighborhoods," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2021(18), pages 1-5, September.
  19. Dionissi Aliprantis & Kristen Tauber & Hal Martin, 2022. "What Determines the Success of Housing Mobility Programs?," Working Papers 2022-043, Human Capital and Economic Opportunity Working Group.
  20. Mazzi Gian Luigi & Mitchell James & Carausu Florabela, 2021. "Measuring and Communicating the Uncertainty in Official Economic Statistics," Journal of Official Statistics, Sciendo, vol. 37(2), pages 289-316, June.
  21. Malte Knüppel & Fabian Krüger, 2022. "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
  22. Loretta J. Mester, 2016. "Acknowledging Uncertainty, 10-07-2016; Shadow Open Market Committee Fall Meeting, New York, NY," Speech 77, Federal Reserve Bank of Cleveland.
  23. Dennis J. Fixler & Eva de Francisco & Danit Kanal, 2021. "The Revisions to GDP, GDI, and Their Major Components," Survey of Current Business, Bureau of Economic Analysis, January.
  24. Galvao, Ana Beatriz & Mitchell, James & Runge, Johnny, 2019. "Communicating Data Uncertainty: Experimental Evidence for U.K. GDP," EMF Research Papers 30, Economic Modelling and Forecasting Group.
  25. Peter A.G. van Bergeijk, 2017. "Making Data Measurement Errors Transparent: The Case of the IMF," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 18(3), pages 133-154, July.
  26. Ilaria Benedetti & Gianni Betti & Federico Crescenzi, 2020. "Measuring Child Poverty and Its Uncertainty: A Case Study of 33 European Countries," Sustainability, MDPI, vol. 12(19), pages 1-12, October.
  27. Meyer, Bruce D. & Mittag, Nikolas, 2021. "An empirical total survey error decomposition using data combination," Journal of Econometrics, Elsevier, vol. 224(2), pages 286-305.
  28. Knüppel, Malte & Krüger, Fabian, 2017. "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168294, Verein für Socialpolitik / German Economic Association.
  29. Dionissi Aliprantis & Hal Martin, 2020. "Neighborhood Sorting Obscures Neighborhood Effects in the Opportunity Atlas," Working Papers 20-37, Federal Reserve Bank of Cleveland.
  30. Peter A.G. van Bergeijk, 2019. "Deglobalization 2.0," Books, Edward Elgar Publishing, number 18560.
  31. Peter ven de Ven & Anne Harrison & Barbara Fraumeni & Diane Coyle, 2017. "The Future of the National Accounts: Statistics and the Democratic Conversation My thanks to Dave Giles, James Grant, Magnus Henrekson, Johannes Hirata, Alice Nakamura, Peter Sinclair and Geoff Tily f," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63, pages 223-237, December.
  32. M. E. Bontempi & R. Golinelli & M. Squadrani, 2016. "A New Index of Uncertainty Based on Internet Searches: A Friend or Foe of Other Indicators?," Working Papers wp1062, Dipartimento Scienze Economiche, Universita' di Bologna.
  33. Binswanger, Johannes & Oechslin, Manuel, 2020. "Better statistics, better economic policies?," European Economic Review, Elsevier, vol. 130(C).
  34. Umed Temurshoev, 2015. "Uncertainty treatment in input-output analysis," Working Papers 2015-004, Universidad Loyola Andalucía, Department of Economics.
  35. Battistin, Erich & De Nadai, Michele & Krishnan, Nandini, 2023. "The insights and illusions of consumption measurements," Journal of Development Economics, Elsevier, vol. 161(C).
  36. Ronald B. Davies & Joseph Francois, 2018. "Making the Worst of a Bad Situation: A Note on Irexit," The Economic and Social Review, Economic and Social Studies, vol. 49(4), pages 455-462.
  37. Manuel Oechslin & Elias Steiner, 2022. "Statistical capacity and corrupt bureaucracies," The Review of International Organizations, Springer, vol. 17(1), pages 143-174, January.
  38. Dichev, Ilia & Huang, Xinyi & Lee, Donald K.K & Zhao, Jianxin, 2023. "You have a point - but a point is not enough: The case for distributional forecasts of earnings," SocArXiv 4b2y8, Center for Open Science.
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