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Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors. (2017). Mertens, Elmar ; McCracken, Michael ; Clark, Todd.
In: Working Papers.
RePEc:fip:fedlwp:2017-026.

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  1. Assessing the uncertainty in central banks’ inflation outlooks. (2019). Knüppel, Malte ; Schultefrankenfeld, Guido ; Knuppel, Malte.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:35:y:2019:i:4:p:1748-1769.

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  2. Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach. (2019). Tulip, Peter ; Reifschneider, David.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:35:y:2019:i:4:p:1564-1582.

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  3. Identifying and Estimating the Effects of Unconventional Monetary Policy in the Data: How to Do It and What Have We Learned?. (2019). Rossi, Barbara.
    In: Working Papers.
    RePEc:bge:wpaper:1081.

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  4. Identifying and estimating the effects of unconventional monetary policy in the data: How to do It and what have we learned?. (2018). Rossi, Barbara.
    In: Economics Working Papers.
    RePEc:upf:upfgen:1641.

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  5. Forecast-error-based estimation of forecast uncertainty when the horizon is increased. (2018). Knüppel, Malte ; Knuppel, Malte.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:34:y:2018:i:1:p:105-116.

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  6. Inflation, real economic growth and unemployment expectations: An empirical analysis based on the ECB Survey of Professional Forecasters. (2017). Sosvilla-Rivero, Simon ; del Carmen, Mara.
    In: Working Papers.
    RePEc:aee:wpaper:1702.

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References

References cited by this document

  1. Clark, Todd E. (2011), “Real-time Density Forecasts from BVARs with Stochastic Volatility, ” Journal of Business and Economic Statistics 29, 327-341. https://doi.org/10. 1198/jbes.2010.09248 Clark, Todd E. and Francesco Ravazzolo (2015), “Macroeconomic Forecasting Performance under Alternative Specifications of Time-Varying Volatility,” Journal of Applied Econometrics 30, 551-575. https://doi.org/10.1002/jae.2379 Clements, Michael P. (2014), “Forecast Uncertainty Ex Ante and Ex Post: U.S. Inflation and Output Growth,” Journal of Business and Economic Statistics 32, 206-216. https: //doi.org/10.1080/07350015.2013.859618 Clements, Michael P. (2016), “Are Macroeconomic Density Forecasts Informative?” Discussion Paper ICM-2016-02, Henley Business School, University of Reading.

  2. Cogley, Timothy, and Thomas J. Sargent (2005), “Drifts and Volatilities: Monetary Policies and Outcomes in the Post-World War II U.S.,” Review of Economic Dynamics 8, 262302. https://doi.org/10.1016/j.red.2004.10.009 Cogley, Timothy, Sergei Morozov, and Thomas J. Sargent (2005), “Bayesian Fan Charts for U.K. Inflation: Forecasting and Sources of Uncertainty in an Evolving Monetary System,” Journal of Economic Dynamics and Control 29, 1893-1925. https://doi. org/10.1016/j.jedc.2005.06.005 Coibion, Olivier, and Yuriy Gorodnichenko (2015), “Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts,” American Economic Review 105, 2644-2678. https://doi.org/10.1257/aer.20110306 Croushore, Dean (2006), “Forecasting with Real-Time Macroeconomic Data,” in Handbook of Economic Forecasting, G. Elliott G, C. Granger C, and A. Timmermann (eds), North Holland: Amsterdam.

  3. Croushore, Dean (2010), “An Evaluation of Inflation Forecasts from Surveys Using Real31 Time Data,” BE Journal of Macroeconomics: Contributions 10, Article 10.

  4. Croushore, Dean, and Tom Stark (2001), “A Real-Time Data Set for Macroeconomists,” Journal of Econometrics 105, 111-130. https://doi.org/10.1016/S0304-4076(01) 00072-0 Curdia, Vasco, Marco Del Negro, and Daniel Greenwald (2015), “Rare Shocks, Great Recessions, ” Journal of Applied Econometrics 29, 1031-1052. https://doi.org/10.1002/ jae.2395 D’Agostino, Antonello, Luca Gambetti, and Domenico Giannone (2013), “Macroeconomic Forecasting and Structural Change,” Journal of Applied Econometrics 28, 82-101. https://doi.org/10.1002/jae.1257 D’Amico, Stefania, and Athanasios Orphanides (2008), “Uncertainty and Disagreement in Economic Forecasting,” Finance and Economics Discussion Series Working Paper 200856, Federal Reserve Board of Governors.

  5. Del Negro, Marco, and Giorgio E. Primiceri (2015), “Time Varying Structural Vector Autoregressions and Monetary Policy: a Corrigendum,” Review of Economic Studies 82, 1342-1345. https://doi.org/10.1093/restud/rdv024 Diebold, Francis X., and Roberto S. Mariano (1995), “Comparing Predictive Accuracy,” Journal of Business and Economic Statistics 13, 253-263.

  6. Diebold, Francis X., Frank Schorfheide, and Minchul Shin (2016), “Real-Time Forecast Evaluation of DSGE Models with Stochastic Volatility,” Journal of Econometrics, forthcoming.

  7. Lahiri, Kajal, and Xuguang Sheng (2010), “Measuring Forecast Uncertainty by Disagreement: the Missing Link,” Journal of Applied Econometrics 25, 514-538. https://doi. org/10.1002/jae.1167 Mertens, Elmar, and James M. Nason (2015), “Time-varying Stickiness in Professional Inflation Forecasts,” manuscript.

  8. Reifschneider, David, and Peter Tulip (2007), “Gauging the Uncertainty of the Economic Outlook from Historical Forecasting Errors,” FEDS working paper 2007-60, Federal Reserve Board of Governors.
    Paper not yet in RePEc: Add citation now
  9. Reifschneider, David, and Peter Tulip (2017), “Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors: The Federal Reserve’s Approach,” FEDS working paper 2017-20, Federal Reserve Board of Governors.
    Paper not yet in RePEc: Add citation now

  10. Romer, Christina D., and David H. Romer (2000), “Federal Reserve Information and the Behavior of Interest Rates,” American Economic Review 90, 429-457. https://doi. org/10.1257/aer.90.3.429 Sims, Christopher A. (2002), “The Role of Models and Probabilities in the Monetary Policy Process,” Brookings Papers on Economic Activity 2, 1-40. https://doi.org/10.1353/ eca.2003.0009 Stock, James H., and Mark W. Watson (2007), “Has U.S. Inflation Become Harder to Forecast?” Journal of Money, Credit, and Banking 39, 3-33. https://doi.org/10. 1111/j.1538-4616.2007.00014.x Stock, James H., and Mark W. Watson (2016), “Core Inflation and Trend Inflation,” Review of Economics and Statistics 98, 770-784. https://doi.org/10.1162/REST_a_00608

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