IDEAS home Printed from https://ideas.repec.org/p/zbw/vfsc15/113138.html
   My bibliography  Save this paper

Note on Higher-Order Statistics for the Pruned-State-Space of nonlinear DSGE models

Author

Listed:
  • Mutschler, Willi

Abstract

This note shows how to derive unconditional moments, cumulants and polyspectra of order higher than two for the pruned state-space of nonlinear DSGE models. Useful Matrix tools and computational aspects are also discussed.

Suggested Citation

  • Mutschler, Willi, 2015. "Note on Higher-Order Statistics for the Pruned-State-Space of nonlinear DSGE models," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113138, Verein für Socialpolitik / German Economic Association.
  • Handle: RePEc:zbw:vfsc15:113138
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/113138/1/VfS_2015_pid_158.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kan, Raymond, 2008. "From moments of sum to moments of product," Journal of Multivariate Analysis, Elsevier, vol. 99(3), pages 542-554, March.
    2. Michael K. Johnston & Robert G. King & Denny Lie, 2014. "Straightforward approximate stochastic equilibria for nonlinear rational expectations models," CAMA Working Papers 2014-59, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Giovanni Lombardo & Harald Uhlig, 2018. "A Theory Of Pruning," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(4), pages 1825-1836, November.
    4. Erickson, Timothy & Whited, Toni M., 2002. "Two-Step Gmm Estimation Of The Errors-In-Variables Model Using High-Order Moments," Econometric Theory, Cambridge University Press, vol. 18(3), pages 776-799, June.
    5. Elena Rusticelli & Richard Ashley & Estela Bee Dagum & Douglas Patterson, 2009. "A New Bispectral Test for NonLinear Serial Dependence," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 279-293.
    6. Dagenais, Marcel G. & Dagenais, Denyse L., 1997. "Higher moment estimators for linear regression models with errors in the variables," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 193-221.
    7. Hong Lan & Alexander Meyer-Gohde, 2013. "Pruning in Perturbation DSGE Models - Guidance from Nonlinear Moving Average Approximations," SFB 649 Discussion Papers SFB649DP2013-024, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Yong Bao, 2013. "On Sample Skewness and Kurtosis," Econometric Reviews, Taylor & Francis Journals, vol. 32(4), pages 415-448, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mutschler, Willi, 2015. "Identification of DSGE models—The effect of higher-order approximation and pruning," Journal of Economic Dynamics and Control, Elsevier, vol. 56(C), pages 34-54.
    2. Mutschler, Willi, 2018. "Higher-order statistics for DSGE models," Econometrics and Statistics, Elsevier, vol. 6(C), pages 44-56.
    3. Bonhomme, Stphane & Robin, Jean-Marc, 2009. "Consistent noisy independent component analysis," Journal of Econometrics, Elsevier, vol. 149(1), pages 12-25, April.
    4. Coën, Alain & Hübner, Georges, 2009. "Risk and performance estimation in hedge funds revisited: Evidence from errors in variables," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 112-125, January.
    5. Coen, Alain & Racicot, Francois-Eric, 2007. "Capital asset pricing models revisited: Evidence from errors in variables," Economics Letters, Elsevier, vol. 95(3), pages 443-450, June.
    6. Erickson, Timothy & Jiang, Colin Huan & Whited, Toni M., 2014. "Minimum distance estimation of the errors-in-variables model using linear cumulant equations," Journal of Econometrics, Elsevier, vol. 183(2), pages 211-221.
    7. Meijer, Erik & Spierdijk, Laura & Wansbeek, Tom, 2017. "Consistent estimation of linear panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 200(2), pages 169-180.
    8. Arthur Lewbel, 2010. "Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 67-80, December.
    9. Joseph J. Sabia, 2007. "Reading, Writing, And Sex: The Effect Of Losing Virginity On Academic Performance," Economic Inquiry, Western Economic Association International, vol. 45(4), pages 647-670, October.
    10. Eric Blankmeyer, 2018. "Measurement Errors as Bad Leverage Points," Papers 1807.02814, arXiv.org, revised Mar 2020.
    11. Biørn, Erik, 2017. "Identification and Method of Moments Estimation in Polynomial Measurement Error Models," Memorandum 01/2017, Oslo University, Department of Economics.
    12. Gospodinov, Nikolay & Komunjer, Ivana & Ng, Serena, 2017. "Simulated minimum distance estimation of dynamic models with errors-in-variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 181-193.
    13. Christian Calmès & Denis Cormier & Francois Éric Racicot & Raymond Théoret, 2012. "Firms' Accruals and Tobin’s q," RePAd Working Paper Series UQO-DSA-wp032012, Département des sciences administratives, UQO.
    14. Aydin Ozkan & Roberto J. Santillán‐Salgado & Yilmaz Yildiz & María del Rocío Vega Zavala, 2020. "What Happened To The Willingness Of Companies To Invest After The Financial Crisis? Evidence From Latin American Countries," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(2), pages 231-262, May.
    15. Klein, Roger & Vella, Francis, 2010. "Estimating a class of triangular simultaneous equations models without exclusion restrictions," Journal of Econometrics, Elsevier, vol. 154(2), pages 154-164, February.
    16. Stephen P. Ferris & Reza Houston & David Javakhadze, 2019. "It is a Sweetheart of a Deal: Political Connections and Corporate‐Federal Contracting," The Financial Review, Eastern Finance Association, vol. 54(1), pages 57-84, February.
    17. Machokoto, Michael & Areneke, Geofry, 2020. "Does innovation and financial constraints affect the propensity to save in emerging markets?," Research in International Business and Finance, Elsevier, vol. 52(C).
    18. Benjamin Born & Johannes Pfeifer, 2014. "Risk Matters: A Comment," CESifo Working Paper Series 4793, CESifo.
    19. Muñoz, Francisco, 2013. "Liquidity and firm investment: Evidence for Latin America," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 18-29.
    20. Susanne M. Schennach & Yingyao Hu & Arthur Lewbel, 2007. "Nonparametric identification of the classical errors-in-variables model without side information," Boston College Working Papers in Economics 674, Boston College Department of Economics.

    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:zbw:vfsc15:113138. 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: . General contact details of provider: https://edirc.repec.org/data/vfsocea.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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/vfsocea.html .

    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.