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Moving Endpoints and the Internal Consistency of Agents' Ex Ante Forecasts

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  • Kozicki, Sharon
  • Tinsley, P A
Abstract
Forecasts by rational agents contain embedded initial and terminal boundary conditions. Standard time series models generate two types of long-run boundary values or steady-state "endpoints"--fixed endpoints and moving average endpoints. Neither can explain the shifting endpoints implied by postwar movements in the cross-section of forward rate forecasts in the term structure or by post-l979 changes in survey estimates of expected long-run inflation. Multiperiod forecasts by a broader class of "moving endpoint" time series models provide substantially improved tracking of the historical term structure and generally support the internal consistency of the ex ante long-run expectations of bond traders and survey respondents. Citation Copyright 1998 by Kluwer Academic Publishers.

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  • Kozicki, Sharon & Tinsley, P A, 1998. "Moving Endpoints and the Internal Consistency of Agents' Ex Ante Forecasts," Computational Economics, Springer;Society for Computational Economics, vol. 11(1-2), pages 21-40, April.
    • Handle: RePEc:kap:compec:v:11:y:1998:i:1-2:p:21-40
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    Cited by:

    1. Tallman, Ellis W. & Zaman, Saeed, 2020. "Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy," International Journal of Forecasting, Elsevier, vol. 36(2), pages 373-398.
    2. Glenn D. Rudebusch, 2001. "Is The Fed Too Timid? Monetary Policy In An Uncertain World," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 203-217, May.
    3. Kozicki, Sharon & Tinsley, P.A., 2005. "What do you expect? Imperfect policy credibility and tests of the expectations hypothesis," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 421-447, March.
    4. Brayton, Flint & Levin, Andrew & Lyon, Ralph & Williams, John C., 1997. "The evolution of macro models at the Federal Reserve Board," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 47(1), pages 43-81, December.
    5. Sharon Kozicki & P. A. Tinsley, 2006. "Survey-Based Estimates of the Term Structure of Expected U.S. Inflation," Staff Working Papers 06-46, Bank of Canada.
    6. Sharon Kozicki & Peter A. Tinsley, 2002. "Alternative sources of the lag dynamics of inflation," Research Working Paper RWP 02-12, Federal Reserve Bank of Kansas City.
    7. Todd E. Clark & Michael W. McCracken, 2006. "Forecasting of small macroeconomic VARs in the presence of instabilities," Research Working Paper RWP 06-09, Federal Reserve Bank of Kansas City.
    8. Doshi, Hitesh & Jacobs, Kris & Liu, Rui, 2018. "Macroeconomic determinants of the term structure: Long-run and short-run dynamics," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 99-122.
    9. Jondeau, E. & Sedillot, F., 1998. "La prevision des taux longs français et allemands a partir d'un modele a anticipations rationnelles," Working papers 55, Banque de France.
    10. Kozicki, Sharon & Tinsley, P. A., 2001. "Term structure views of monetary policy under alternative models of agent expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 25(1-2), pages 149-184, January.
    11. Sharon Kozicki & P. A. Tinsley, 2012. "Effective Use of Survey Information in Estimating the Evolution of Expected Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 145-169, February.
    12. Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
    13. Christopher F. Baum & Meral Karasulu, 1997. "Credible Disinflation Policy in a Dynamic Setting," Boston College Working Papers in Economics 375, Boston College Department of Economics.
    14. Bomfim, Antulio N & Rudebusch, Glenn D, 2000. "Opportunistic and Deliberate Disinflation under Imperfect Credibility," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 32(4), pages 707-721, November.
    15. Rautureau, Nicolas, 2004. "Measuring the long-term perception of monetary policy and the term structure," Bank of Finland Research Discussion Papers 12/2004, Bank of Finland.
    16. Sharon Kozicki, 2001. "Implications of real-time data for forecasting and modeling expectations," Research Working Paper RWP 01-12, Federal Reserve Bank of Kansas City.
    17. Todd E. Clark & Troy Davig, 2008. "An empirical assessment of the relationships among inflation and short- and long-term expectations," Research Working Paper RWP 08-05, Federal Reserve Bank of Kansas City.
    18. Kozicki, Sharon, 2002. "Comments on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 541-557, December.
    19. Kozicki, Sharon & Tinsley, P. A., 2002. "Dynamic specifications in optimizing trend-deviation macro models," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1585-1611, August.
    20. Clark, Todd E. & Kozicki, Sharon, 2005. "Estimating equilibrium real interest rates in real time," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 395-413, December.
    21. Pavol Povala & Anna Cieslak, 2012. "Understanding bond risk premia," 2012 Meeting Papers 771, Society for Economic Dynamics.
    22. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Research Working Paper RWP 11-16, Federal Reserve Bank of Kansas City.
    23. Peter A. Tinsley, 1998. "Short rate expectations, term premiums, and central bank use of derivatives to reduce policy uncertainty," Finance and Economics Discussion Series 1999-14, Board of Governors of the Federal Reserve System (U.S.).
    24. Eric Jondeau & Franck Sédillot, 1999. "Forecasting French and German long-term rates using a rational expectations model," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 135(3), pages 413-436, September.
    25. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.

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