IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i24p3245-d702823.html
   My bibliography  Save this article

Bayesian Inference for Stochastic Cusp Catastrophe Model with Partially Observed Data

Author

Listed:
  • Ding-Geng Chen

    (College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA
    Department of Statistics, University of Pretoria, Pretoria 0002, South Africa)

  • Haipeng Gao

    (Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC 27599, USA
    PayPal, Inc., San Jose, CA 95131, USA)

  • Chuanshu Ji

    (Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC 27599, USA)

Abstract

The purpose of this paper is to develop a data augmentation technique for statistical inference concerning stochastic cusp catastrophe model subject to missing data and partially observed observations. We propose a Bayesian inference solution that naturally treats missing observations as parameters and we validate this novel approach by conducting a series of Monte Carlo simulation studies assuming the cusp catastrophe model as the underlying model. We demonstrate that this Bayesian data augmentation technique can recover and estimate the underlying parameters from the stochastic cusp catastrophe model.

Suggested Citation

  • Ding-Geng Chen & Haipeng Gao & Chuanshu Ji, 2021. "Bayesian Inference for Stochastic Cusp Catastrophe Model with Partially Observed Data," Mathematics, MDPI, vol. 9(24), pages 1-9, December.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:24:p:3245-:d:702823
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/24/3245/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/24/3245/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cobb, Loren, 1980. "Estimation Theory for the Cusp Catastrophe Model," MPRA Paper 37548, University Library of Munich, Germany, revised 05 Jun 2010.
    2. Eckhard Platen, 1999. "An Introduction to Numerical Methods for Stochastic Differential Equations," Research Paper Series 6, Quantitative Finance Research Centre, University of Technology, Sydney.
    3. Sims,Christopher A. (ed.), 1996. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521566094, November.
    4. Ding-Geng Chen & Haipeng Gao & Chuanshu Ji & Xinguang Chen, 2021. "Stochastic cusp catastrophe model and its Bayesian computations," Journal of Applied Statistics, Taylor & Francis Journals, vol. 48(13-15), pages 2714-2733, November.
    5. Grasman, Raoul & van der Maas, Han L.J. & Wagenmakers, Eric-Jan, 2009. "Fitting the Cusp Catastrophe in R: A cusp Package Primer," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i08).
    6. Sims,Christopher A. (ed.), 1996. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521566100, November.
    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. KONISHI Yoko & NISHIMURA Yoshihiko, 2013. "A Note on the Identification of Demand and Supply Shocks in Production: Decomposition of TFP," Discussion papers 13099, Research Institute of Economy, Trade and Industry (RIETI).
    2. Carlsson, Mikael & Westermark, Andreas, 2011. "The New Keynesian Phillips Curve and staggered price and wage determination in a model with firm-specific labor," Journal of Economic Dynamics and Control, Elsevier, vol. 35(4), pages 579-603, April.
    3. Aguiar, Victor H. & Kashaev, Nail & Allen, Roy, 2023. "Prices, profits, proxies, and production," Journal of Econometrics, Elsevier, vol. 235(2), pages 666-693.
    4. Hülya Eraslan & Gizem Koşar & Wenli Li & Pierre‐Daniel Sarte, 2017. "An Anatomy Of U.S. Personal Bankruptcy Under Chapter 13," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 58(3), pages 671-702, August.
    5. Hansen, Thorsten, 2010. "Tariff Rates, Offshoring and Productivity: Evidence from German and Austrian Firm-Level Data," Discussion Papers in Economics 11465, University of Munich, Department of Economics.
    6. Yin Germaschewski, 2016. "Getting help from abroad: The macroeconomics of foreign direct investment in infrastructure in low‐income countries," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 49(4), pages 1502-1535, November.
    7. Pascal St-Amour, 2004. "Ratchet vs Blasé Investors and Asset Markets," CIRANO Working Papers 2004s-11, CIRANO.
    8. Ioannis Bournakis & Sushanta Mallick & David Kernohan & Dimitris A.Tsouknidis, 2013. "Measuring Firm-Level Productivity Convergence in the UK: The Role of Taxation and R&D Investment," Working Papers 45, Queen Mary, University of London, School of Business and Management, Centre for Globalisation Research.
    9. Marc-Andreas Muendler, 2004. "Estimating Production Functions When Productivity Change is Endogenous," CESifo Working Paper Series 1143, CESifo.
    10. Joshua D. Angrist & Sydnee Caldwell & Jonathan V. Hall, 2017. "Uber vs. Taxi: A Driver’s Eye View," NBER Working Papers 23891, National Bureau of Economic Research, Inc.
    11. Chih-Nan Chen & Tai-Hsin Huang & Chien-Hsiu Lin, 2013. "Financing Decision and Productivity Growth for the Venture Capital Industry in Taiwan," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 16(02), pages 1-19.
    12. Hansen, Thorsten, 2010. "Exports and Productivity: An Empirical Analysis of German and Austrian Firm-Level Performance," Discussion Papers in Economics 11466, University of Munich, Department of Economics.
    13. Jozef Barunik & Jiri Kukacka, 2015. "Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 959-973, June.
    14. John Asker & Allan Collard-Wexler & Jan De Loecker, 2014. "Dynamic Inputs and Resource (Mis)Allocation," Journal of Political Economy, University of Chicago Press, vol. 122(5), pages 1013-1063.
    15. Barker, Andrew & Murray, Tim & Salerian, John, 2010. "Developing a Partial Equilibrium Model of an Urban Water System," Staff Working Papers 102, Productivity Commission, Government of Australia.
    16. Germaschewski, Yin & Wang, Shu-Ling, 2022. "Fiscal stabilization in high-debt economies without monetary independence," Journal of Macroeconomics, Elsevier, vol. 72(C).
    17. Mohamed M. Mostafa, 2020. "Catastrophe Theory Predicts International Concern for Global Warming," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 709-731, September.
    18. Pascal St-Amour, 2005. "Direct Preference Wealth in Aggregate Household Portfolios," FAME Research Paper Series rp136, International Center for Financial Asset Management and Engineering.
    19. Germaschewski, Yin, 2020. "Stabilization policy, infrastructure investment, and welfare in a small open economy," Economic Modelling, Elsevier, vol. 84(C), pages 322-339.
    20. Seyed Morteza Emadi & Bradley R. Staats, 2020. "A Structural Estimation Approach to Study Agent Attrition," Management Science, INFORMS, vol. 66(9), pages 4071-4095, September.

    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:gam:jmathe:v:9:y:2021:i:24:p:3245-:d:702823. See general information about how to correct material in RePEc.

    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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.