IDEAS home Printed from https://ideas.repec.org/r/fip/fedhwp/wp-00-26.html

Data revisions and the identification of monetary policy shocks

Citations

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


Cited by:

  1. Pierre L. Siklos & Diana N. Weymark, 2008. "Data Revisions, Gradualism, and US Inflation Pressure in Real Time," Vanderbilt University Department of Economics Working Papers 0816, Vanderbilt University Department of Economics.
  2. Kwamie Dunbar & Abu S. Amin, 2012. "Credit risk dynamics in response to changes in the federal funds target: The implication for firm short‐term debt," Review of Financial Economics, John Wiley & Sons, vol. 21(3), pages 141-152, September.
  3. Elena Afanasyeva & Jochen Güntner, 2014. "Lending Standards, Credit Booms and Monetary Policy," Economics working papers 2014-11, Department of Economics, Johannes Kepler University Linz, Austria.
  4. Brissimis, Sophocles N. & Magginas, Nicholas S., 2006. "Forward-looking information in VAR models and the price puzzle," Journal of Monetary Economics, Elsevier, vol. 53(6), pages 1225-1234, September.
  5. Amir-Ahmadi, Pooyan & Matthes, Christian & Wang, Mu-Chun, 2017. "Measurement errors and monetary policy: Then and now," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 66-78.
  6. Aguirre, Idoia & Vázquez, Jesús, 2018. "Inflation monitoring in real time: A comparative analysis of the Federal Reserve and the Bank of England," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 200-209.
  7. Fabrice Collard & Harris Dellas, 2010. "Monetary Misperceptions, Output, and Inflation Dynamics," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(2-3), pages 483-502, March.
  8. repec:ehu:dfaeii:8760 is not listed on IDEAS
  9. Magdalena Borys & Roman Horváth & Michal Franta, 2009. "The effects of monetary policy in the Czech Republic: an empirical study," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 36(4), pages 419-443, November.
  10. Nilss Olekalns & Kalvinder Shields, 2008. "Nowcasting, Business Cycle Dating and the Interpretation of New Information when Real Time Data are Available," Department of Economics - Working Papers Series 1040, The University of Melbourne.
  11. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
  12. Gazzani, Andrea & Venditti, Fabrizio & Veronese, Giovanni, 2024. "Oil price shocks in real time," Journal of Monetary Economics, Elsevier, vol. 144(C).
  13. Michael J. Dueker, 2002. "The monetary policy innovation paradox in VARs: a \\"discrete\\" explanation," Review, Federal Reserve Bank of St. Louis, vol. 84(Mar.), pages 43-50.
  14. Belongia, Michael T. & Ireland, Peter N., 2016. "The evolution of U.S. monetary policy: 2000–2007," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 78-93.
  15. Ulf Von Kalckreuth & Guntram B. Wolff, 2011. "Identifying Discretionary Fiscal Policy Reactions with Real-Time Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(6), pages 1271-1285, September.
  16. N. Kundan Kishor & Evan F. Koenig, 2009. "VAR Estimation and Forecasting When Data Are Subject to Revision," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 181-190, July.
  17. Yu, Xiangrong, 2013. "Measurement error and policy evaluation in the frequency domain," Journal of Macroeconomics, Elsevier, vol. 38(PB), pages 307-329.
  18. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
  19. Phan, Tuan, 2016. "Has Monetary Policy Become More Aggressive, But Less Effective Over Time?," MPRA Paper 107200, University Library of Munich, Germany.
  20. Raul Ibarra, 2016. "How important is the credit channel in the transmission of monetary policy in Mexico?," Applied Economics, Taylor & Francis Journals, vol. 48(36), pages 3462-3484, August.
  21. M. Berument & Selahattin Togay & Afsin Sahin, 2011. "Identifying the Liquidity Effects of Monetary Policy Shocks for a Small Open Economy: Turkey," Open Economies Review, Springer, vol. 22(4), pages 649-667, September.
  22. Gregory E. Givens, 2017. "Do Data Revisions Matter for DSGE Estimation?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(6), pages 1385-1407, September.
  23. Pierre Siklos, 2006. "What Can We Learn from Comprehensive Data Revisions for Forecasting Inflation: Some US Evidence," Working Papers eg0049, Wilfrid Laurier University, Department of Economics, revised 2006.
  24. William T. Gavin, 2003. "FOMC forecast: is all the information in the central tendency?," Review, Federal Reserve Bank of St. Louis, vol. 85(May), pages 27-46.
  25. Paredes, Joan & Pedregal, Diego J. & Pérez, Javier J., 2009. "A quarterly fiscal database for the euro area based on intra-annual fiscal information," Working Paper Series 1132, European Central Bank.
  26. Ahsan ul Haq Satti & Wasim Shahid Malik, 2017. "The Unreliability of Output-Gap Estimates in Real Time," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 56(3), pages 193-219.
  27. Kamalyan, Hayk, 2022. "Data revisions and the effects of monetary policy volatility," Economics Letters, Elsevier, vol. 215(C).
  28. Dean Croushore & Tom Stark, 2000. "A real-time data set for macroeconomists: does data vintage matter for forecasting?," Working Papers 00-6, Federal Reserve Bank of Philadelphia.
  29. Sharif, Taimur & Bouteska, Ahmed & Zoynul Abedin, Mohammad & Cotturone, Saulo, 2025. "An enquiry into the monetary policy and stock market shocks in the US," International Review of Economics & Finance, Elsevier, vol. 98(C).
  30. Lin, Jilei & Eck, Daniel J., 2021. "Minimizing post-shock forecasting error through aggregation of outside information," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1710-1727.
  31. Kevin Lee & Nilss Olekalns & Kalvinder Shields, 2008. "Nowcasting, Business Cycle Dating and the Interpretation of New Information when Real Time Data are Available," Discussion Papers in Economics 08/17, Division of Economics, School of Business, University of Leicester.
  32. Andersson, Fredrik N. G. & Kilman, Josefin, 2021. "A Study of the Romer and Romer Monetary Policy Shocks Using Revised Data," Working Papers 2021:19, Lund University, Department of Economics.
  33. Steven P. Cassou & C. Patrick Scott & Jesús Vázquez, 2018. "Optimal monetary policy revisited: does considering US real-time data change things?," Applied Economics, Taylor & Francis Journals, vol. 50(57), pages 6203-6219, December.
  34. Knut Are Aastveit & Francesco Furlanetto & Francesca Loria, 2023. "Has the Fed Responded to House and Stock Prices? A Time-Varying Analysis," The Review of Economics and Statistics, MIT Press, vol. 105(5), pages 1314-1324, September.
  35. Ibarra-Ramírez Raúl, 2021. "The Yield Curve as a Predictor of Economic Activity in Mexico: The Role of the Term Premium," Working Papers 2021-07, Banco de México.
  36. James S. Fackler & W. Douglas McMillin, 2002. "Evaluating Monetary Policy Options," Southern Economic Journal, John Wiley & Sons, vol. 68(4), pages 794-810, April.
  37. Tsai, Chun-Li, 2011. "The reaction of stock returns to unexpected increases in the federal funds rate target," Journal of Economics and Business, Elsevier, vol. 63(2), pages 121-138.
  38. Casares, Miguel & Vázquez, Jesús, 2016. "Data Revisions In The Estimation Of Dsge Models," Macroeconomic Dynamics, Cambridge University Press, vol. 20(7), pages 1683-1716, October.
  39. Aymeric Ortmans, 2020. "Evolving Monetary Policy in the Aftermath of the Great Recession," Documents de recherche 20-01, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
  40. Garratt, Anthony & Koop, Gary & Mise, Emi & Vahey, Shaun P., 2009. "Real-Time Prediction With U.K. Monetary Aggregates in the Presence of Model Uncertainty," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 480-491.
  41. Tsai, Chun-Li, 2011. "The reaction of stock returns to unexpected increases in the federal funds rate target," Journal of Economics and Business, Elsevier, vol. 63(2), pages 121-138, March.
  42. Richard G. Anderson & Charles S. Gascon, 2009. "Estimating U.S. output growth with vintage data in a state-space framework," Review, Federal Reserve Bank of St. Louis, vol. 91(Jul), pages 349-370.
  43. Döpke, Jörg, 2004. "Real-time data and business cycle analysis in Germany," Discussion Paper Series 1: Economic Studies 2004,11, Deutsche Bundesbank.
  44. Bachmann, Rüdiger & Gödl-Hanisch, Isabel & Sims, Eric R., 2022. "Identifying monetary policy shocks using the central bank’s information set," Journal of Economic Dynamics and Control, Elsevier, vol. 145(C).
  45. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
  46. Gavin, William T. & Mandal, Rachel J., 2003. "Evaluating FOMC forecasts," International Journal of Forecasting, Elsevier, vol. 19(4), pages 655-667.
  47. Vázquez, Jesús & María-Dolores, Ramón & Londoño, Juan M., 2012. "The Effect of Data Revisions on the Basic New Keynesian Model," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 235-249.
  48. Thanaset Chevapatrakul & Juan Paez-Farrell, 2014. "Monetary Policy Reaction Functions in Small Open Economies: a Quantile Regression Approach," Manchester School, University of Manchester, vol. 82(2), pages 237-256, March.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.