IDEAS home Printed from https://ideas.repec.org/p/trb/wpaper/2010.05.html
   My bibliography  Save this paper

Applying shape and phase restrictions in generalized dynamic categorical models of the business cycle

Author

Listed:
  • Don Harding

    (School of Economics, La Trobe University)

Abstract

To match the NBER business cycle features it is necessary to employ Generalised dynamic categorical (GDC) models that impose certain phase restrictions and permit multiple indexes. Theory suggests additional shape restrictions in the form of monotonicity and boundedness of certain transition probabilities. Maximum likelihood and constraint weighted bootstrap estimators are developed to impose these restrictions. In the application these estimators generate improved estimates of how the probability of recession varies with the yield spread.

Suggested Citation

  • Don Harding, 2010. "Applying shape and phase restrictions in generalized dynamic categorical models of the business cycle," Working Papers 2010.05, School of Economics, La Trobe University.
    • Handle: RePEc:trb:wpaper:2010.05
    as

    Download full text from publisher

    File URL: http://www.latrobe.edu.au/__data/assets/pdf_file/0016/130921/2010.05.pdf
    File Function: First version, 200
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Harding, Don & Pagan, Adrian, 2011. "An Econometric Analysis of Some Models for Constructed Binary Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 86-95.
    2. Daniel J. Henderson & Christopher F. Parmeter, 2009. "Imposing economic constraints in nonparametric regression: survey, implementation, and extension," Advances in Econometrics, in: Nonparametric Econometric Methods, pages 433-469, Emerald Group Publishing Limited.
    3. Racine, Jeffrey S., 2008. "Nonparametric Econometrics: A Primer," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(1), pages 1-88, March.
    4. Jeffrey Racine, 2008. "Nonparametric econometrics: a primer (in Russian)," Quantile, Quantile, issue 4, pages 7-56, March.
    5. Clifford M. Hurvich & Jeffrey S. Simonoff & Chih‐Ling Tsai, 1998. "Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(2), pages 271-293.
    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. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Interactions between eurozone and US booms and busts: A Bayesian panel Markov-switching VAR model," Working Paper 2013/20, Norges Bank.

    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. Chu, Chi-Yang & Henderson, Daniel J. & Parmeter, Christopher F., 2017. "On discrete Epanechnikov kernel functions," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 79-105.
    2. Tomasz Czekaj & Arne Henningsen, 2013. "Panel Data Specifications in Nonparametric Kernel Regression: An Application to Production Functions," IFRO Working Paper 2013/5, University of Copenhagen, Department of Food and Resource Economics.
    3. Mengistu Assefa Wendimu & Arne Henningsen & Tomasz Gerard Czekaj, 2017. "Incentives and moral hazard: plot level productivity of factory-operated and outgrower-operated sugarcane production in Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 48(5), pages 549-560, September.
    4. Valeva, Silviya & Hewitt, Mike & Thomas, Barrett W. & Brown, Kenneth G., 2017. "Balancing flexibility and inventory in workforce planning with learning," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 194-207.
    5. Olsen, Jakob Vesterlund & Czekaj, Tomasz Gerard & Henningsen, Arne & Schou, Jesper Sølver, 2017. "The Effect Of Land Fragmentation On Farm Performance: A Comprehensive Farm-Level Study From Denmark," 2017 International Congress, August 28-September 1, 2017, Parma, Italy 260900, European Association of Agricultural Economists.
    6. Baranyi, Máté & Bolla, Marianna, 2021. "Iterated conditional expectation algorithm on DAGs and regression graphs," Econometrics and Statistics, Elsevier, vol. 20(C), pages 131-152.
    7. Tomasz Gerard Czekaj & Arne Henningsen, 2012. "Comparing Parametric and Nonparametric Regression Methods for Panel Data: the Optimal Size of Polish Crop Farms," IFRO Working Paper 2012/12, University of Copenhagen, Department of Food and Resource Economics.
    8. Halkos, George & Tzeremes, Nickolaos, 2011. "Investigating the cultural patterns of corruption: A nonparametric analysis," MPRA Paper 32546, University Library of Munich, Germany.
    9. Roberto Martino & Phu Nguyen-Van, 2014. "Labour market regulation and fiscal parameters: A structural model for European regions," Working Papers of BETA 2014-19, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    10. George Halkos & Roman Matousek & Nickolaos Tzeremes, 2016. "Pre-evaluating technical efficiency gains from possible mergers and acquisitions: evidence from Japanese regional banks," Review of Quantitative Finance and Accounting, Springer, vol. 46(1), pages 47-77, January.
    11. Rik Chakraborti & Gavin Roberts, 2023. "How price-gouging regulation undermined COVID-19 mitigation: county-level evidence of unintended consequences," Public Choice, Springer, vol. 196(1), pages 51-83, July.
    12. George Halkos & Nickolaos Tzeremes, 2012. "Measuring German regions’ environmental efficiency: a directional distance function approach," Letters in Spatial and Resource Sciences, Springer, vol. 5(1), pages 7-16, March.
    13. Minviel, Jean Joseph & De Witte, Kristof, 2017. "The influence of public subsidies on farm technical efficiency: A robust conditional nonparametric approach," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1112-1120.
    14. Daraio, Cinzia & Bonaccorsi, Andrea & Simar, Léopold, 2015. "Efficiency and economies of scale and specialization in European universities: A directional distance approach," Journal of Informetrics, Elsevier, vol. 9(3), pages 430-448.
    15. Halkos, George E. & Tzeremes, Nickolaos G., 2013. "Economic growth and environmental efficiency: Evidence from US regions," Economics Letters, Elsevier, vol. 120(1), pages 48-52.
    16. Daniel Wikström, 2015. "A finite sample improvement of the fixed effects estimator applied to technical inefficiency," Journal of Productivity Analysis, Springer, vol. 43(1), pages 29-46, February.
    17. Halkos, George E. & Tzeremes, Nickolaos G., 2014. "The effect of electricity consumption from renewable sources on countries׳ economic growth levels: Evidence from advanced, emerging and developing economies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 166-173.
    18. Helmi Jedidi & Georges Dionne, 2024. "Nonparametric Testing for Information Asymmetry in the Mortgage Servicing Market," Risks, MDPI, vol. 12(12), pages 1-40, November.
    19. Subal Kumbhakar & Christopher Parmeter, 2015. "Introduction," Empirical Economics, Springer, vol. 48(1), pages 1-8, February.
    20. Halkos, George E. & Tzeremes, Nickolaos G., 2014. "Public sector transparency and countries’ environmental performance: A nonparametric analysis," Resource and Energy Economics, Elsevier, vol. 38(C), pages 19-37.

    More about this item

    Keywords

    Generalized dynamic categorical model; Business cycle; binary variable; Markov process; probit model; yield curve;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    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:trb:wpaper:2010.05. 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: Stephen Scoglio The email address of this maintainer does not seem to be valid anymore. Please ask Stephen Scoglio to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/sblatau.html .

    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.