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A Continuous Time Econometric Model of the United Kingdom with Stochastic Trends

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  • Bergstrom,Albert Rex
  • Nowman,Khalid Ben

Abstract

Over the last thirty years there has been extensive use of continuous time econometric methods in macroeconomic modelling. This monograph presents a continuous time macroeconometric model of the United Kingdom incorporating stochastic trends. Its development represents a major step forward in continuous time macroeconomic modelling. The book describes the model in detail and, like earlier models, it is designed in such a way as to permit a rigorous mathematical analysis of its steady-state and stability properties, thus providing a valuable check on the capacity of the model to generate plausible long-run behaviour. The model is estimated using newly developed exact Gaussian estimation methods for continuous time econometric models incorporating unobservable stochastic trends. The book also includes discussion of the application of the model to dynamic analysis and forecasting.

Suggested Citation

  • Bergstrom,Albert Rex & Nowman,Khalid Ben, 2007. "A Continuous Time Econometric Model of the United Kingdom with Stochastic Trends," Cambridge Books, Cambridge University Press, number 9780521875493, March.
  • Handle: RePEc:cup:cbooks:9780521875493
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    Citations

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    Cited by:

    1. Peter Phillips, 2010. "Two New Zealand pioneer econometricians," New Zealand Economic Papers, Taylor & Francis Journals, vol. 44(1), pages 1-26.
    2. Bernd Hayo & Britta Niehof, 2014. "Monetary and Fiscal Policy in Times of Crises: A New Keynesian Perspective in Continuous Time," MAGKS Papers on Economics 201455, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    3. Jun Yu, 2009. "Econometric Analysis of Continuous Time Models : A Survey of Peter Phillips’ Work and Some New Results," Microeconomics Working Papers 23046, East Asian Bureau of Economic Research.
    4. Federici, Daniela & Saltari, Enrico & Wymer, Clifford, 2015. "Endogenizing the ICT sector: A multi-sector approach," MPRA Paper 66723, University Library of Munich, Germany.
    5. Joanne S. Ercolani, 2007. "Cyclical Trends in Continuous Time Models," Discussion Papers 07-13, Department of Economics, University of Birmingham.
    6. William Barnett & Evgeniya Duzhak, 2010. "Empirical assessment of bifurcation regions within New Keynesian models," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), pages 99-128.
    7. Peter C. B. Phillips & Jun Yu, 2006. "Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance," Development Economics Working Papers 22471, East Asian Bureau of Economic Research.
    8. Koo, Bonsoo & Linton, Oliver, 2012. "Estimation of semiparametric locally stationary diffusion models," Journal of Econometrics, Elsevier, vol. 170(1), pages 210-233.
    9. repec:eee:dyncon:v:79:y:2017:i:c:p:48-65 is not listed on IDEAS
    10. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    11. Yu, Jun, 2014. "Econometric Analysis Of Continuous Time Models: A Survey Of Peter Phillips’S Work And Some New Results," Econometric Theory, Cambridge University Press, vol. 30(04), pages 737-774, August.
    12. Robinson, Peter, 2007. "On discrete sampling of time-varying continuous-time systems," LSE Research Online Documents on Economics 6795, London School of Economics and Political Science, LSE Library.
    13. Nowman, K. Ben, 2011. "Gaussian estimation of continuous time diffusions of UK interest rates," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(8), pages 1618-1624.
    14. Peter Robinson, 2007. "On Discrete Sampling Of Time-Varyingcontinuous-Time Systems," STICERD - Econometrics Paper Series 520, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    15. E. et al. Saltari, 2011. "The impact of ICT on the Italian productivity dynamics," Working Papers 149, University of Rome La Sapienza, Department of Public Economics.
    16. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters,in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310 Edward Elgar Publishing.
    17. Thornton, Michael A. & Chambers, Marcus J., 2017. "Continuous time ARMA processes: Discrete time representation and likelihood evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 48-65.
    18. Thornton, Michael A. & Chambers, Marcus J., 2016. "The exact discretisation of CARMA models with applications in finance," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 739-761.

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