IDEAS home Printed from https://ideas.repec.org/a/bla/obuest/v48y1986i2p99-120.html
   My bibliography  Save this article

Quantitative v. Qualitative Measures of Inflation Expectations

Author

Listed:
  • Batchelor, R A

Abstract

No abstract is available for this item.

Suggested Citation

  • Batchelor, R A, 1986. "Quantitative v. Qualitative Measures of Inflation Expectations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(2), pages 99-120, May.
  • Handle: RePEc:bla:obuest:v:48:y:1986:i:2:p:99-120
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    as
    1. Peter Reinhard Hansen & Asger Lunde & James M. Nason, 2003. "Choosing the Best Volatility Models: The Model Confidence Set Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 839-861, December.
    2. Jondeau, Eric & Rockinger, Michael, 2001. "Gram-Charlier densities," Journal of Economic Dynamics and Control, Elsevier, vol. 25(10), pages 1457-1483, October.
    3. León, à ngel & Mencía, Javier & Sentana, Enrique, 2009. "Parametric Properties of Semi-Nonparametric Distributions, with Applications to Option Valuation," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 176-192.
    4. Whitney K. Newey & Douglas G. Steigerwald, 1997. "Asymptotic Bias for Quasi-Maximum-Likelihood Estimators in Conditional Heteroskedasticity Models," Econometrica, Econometric Society, vol. 65(3), pages 587-600, May.
    5. Velasco, Carlos & Robinson, Peter M., 2001. "Edgeworth Expansions For Spectral Density Estimates And Studentized Sample Mean," Econometric Theory, Cambridge University Press, vol. 17(03), pages 497-539, June.
    6. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
    7. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    8. Awartani, Basel M.A. & Corradi, Valentina, 2005. "Predicting the volatility of the S&P-500 stock index via GARCH models: the role of asymmetries," International Journal of Forecasting, Elsevier, vol. 21(1), pages 167-183.
    9. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    10. Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 97-121.
    11. Morten B. Jensen & Asger Lunde, 2001. "The NIG-S&ARCH model: a fat-tailed, stochastic, and autoregressive conditional heteroskedastic volatility model," Econometrics Journal, Royal Economic Society, vol. 4(2), pages 1-10.
    12. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
    13. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    14. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    15. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    16. Jose A. Lopez, 1999. "Methods for evaluating value-at-risk estimates," Economic Review, Federal Reserve Bank of San Francisco, pages 3-17.
    17. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
    18. Sargan, J D, 1975. "Gram-Charlier Approximations Applied to t Ratios of k-Class Estimators," Econometrica, Econometric Society, vol. 43(2), pages 327-346, March.
    19. Robert JARROW & Andrew RUDD, 2008. "Approximate Option Valuation For Arbitrary Stochastic Processes," World Scientific Book Chapters,in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 1, pages 9-31 World Scientific Publishing Co. Pte. Ltd..
    20. Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-390, March.
    21. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    22. Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
    23. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    24. Leon, Angel & Rubio, Gonzalo & Serna, Gregorio, 2005. "Autoregresive conditional volatility, skewness and kurtosis," The Quarterly Review of Economics and Finance, Elsevier, vol. 45(4-5), pages 599-618, September.
    25. Ignacio Mauleon & Javier Perote, 2000. "Testing densities with financial data: an empirical comparison of the Edgeworth-Sargan density to the Student's t," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 225-239.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Breitung, Jörg & Schmeling, Maik, 2013. "Quantifying survey expectations: What’s wrong with the probability approach?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 142-154.
    2. Tomislav Globan & Vladimir Arčabić & Petar Sorić, 2014. "Inflation in New EU Member States: A Domestically or Externally Driven Phenomenon?," EFZG Working Papers Series 1405, Faculty of Economics and Business, University of Zagreb.
    3. Berlemann, Michael, 2001. "Forecasting inflation via electronic markets: Results from a prototype market," Dresden Discussion Paper Series in Economics 06/01, Technische Universität Dresden, Faculty of Business and Economics, Department of Economics.
    4. Tomislav Globan & Petar Sorić, 2017. "Financial integration before and after the crisis: Euler equations (re)visit European Union," EFZG Working Papers Series 1702, Faculty of Economics and Business, University of Zagreb.
    5. Jan Marc Berk, 1999. "Measuring inflation expectations: a survey data approach," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1467-1480.
    6. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    7. Paul Butzen & Catherine Fuss & Philip Vermeulen, 2002. "The impact of uncertainty on investment plans," Working Paper Research 24, National Bank of Belgium.
    8. Michael E. Trebing, 1998. "What's happening in manufacturing: "survey says..."," Business Review, Federal Reserve Bank of Philadelphia, issue Sep, pages 15-29.
    9. Silva Lopes, Artur, 1994. "A "hipótese das expectativas racionais": teoria e realidade (uma visita guiada à literatura até 1992)
      [The "rational expectations hypothesis": theory and reality (a guided tour
      ," MPRA Paper 9699, University Library of Munich, Germany, revised 23 Jul 2008.
    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. Frijters, Paul & Haisken-DeNew, John P. & Shields, Michael A., 2002. "Individual Rationality and Learning: Welfare Expectations in East Germany Post-Reunification," IZA Discussion Papers 498, Institute for the Study of Labor (IZA).
    12. Reckwerth, Jürgen, 1997. "Der Zusammenhang zwischen Inflation und Output in Deutschland unter besonderer Berücksichtigung der Inflationserwartungen," Discussion Paper Series 1: Economic Studies 1997,05, Deutsche Bundesbank.
    13. repec:mes:emfitr:v:52:y:2016:i:1:p:154-168 is not listed on IDEAS
    14. José Antonio Murillo Garza & Paula Sánchez Romeu, 2012. "Testing the Predictive Power of Mexican Consumers' Inflation Expectations," Working Papers 2012-13, Banco de México.
    15. Binder, Carola Conces, 2016. "Estimation of historical inflation expectations," Explorations in Economic History, Elsevier, vol. 61(C), pages 1-31.
    16. repec:fau:fauart:v:67:y:2017:i:3:p:221-249 is not listed on IDEAS
    17. Tomislav Globan & Vladimir Arčabić & Petar Sorić, 2016. "Inflation in New EU Member States: A Domestically or Externally Driven Phenomenon?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(1), pages 154-168, January.
    18. Loffler, Gunter, 2005. "Avoiding the rating bounce: why rating agencies are slow to react to new information," Journal of Economic Behavior & Organization, Elsevier, vol. 56(3), pages 365-381, March.
    19. Fuhrer, Jeff, 2017. "Expectations as a source of macroeconomic persistence: Evidence from survey expectations in a dynamic macro model," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 22-35.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:obuest:v:48:y:1986:i:2:p:99-120. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/sfeixuk.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.