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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, 2012. "A Continuous Time Econometric Model of the United Kingdom with Stochastic Trends," Cambridge Books, Cambridge University Press, number 9781107411234.
    • Handle: RePEc:cup:cbooks:9781107411234
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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. Britta Förster & Bernd Hayo, 2018. "Monetary and Fiscal Policy in Times of Crisis: A New Keynesian Perspective in Continuous Time," Manchester School, University of Manchester, vol. 86(1), pages 21-48, January.
    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. Wymer, Clifford R. & Saltari, Enrico & Federici, Daniela, 2019. "Endogenizing The Ict Sector: A Multisector Approach," Macroeconomic Dynamics, Cambridge University Press, vol. 23(S1), pages 25-58, September.
    5. Joanne S. Ercolani, 2007. "Cyclical Trends in Continuous Time Models," Discussion Papers 07-13, Department of Economics, University of Birmingham.
    6. Milena Hoyos, 2020. "Mixed First‐ and Second‐Order Cointegrated Continuous Time Models with Mixed Stock and Flow Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 249-267, March.
    7. 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), vol. 45(1), pages 99-128, October.
    8. Peter C.B.Phillips & Jun Yu, "undated". "Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance," Working Papers CoFie-08-2009, Singapore Management University, Sim Kee Boon Institute for Financial Economics.
    9. Koo, Bonsoo & Linton, Oliver, 2012. "Estimation of semiparametric locally stationary diffusion models," Journal of Econometrics, Elsevier, vol. 170(1), pages 210-233.
    10. 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.
    11. 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.
    12. 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(4), pages 737-774, August.
    13. K.B. Nowman & S. Van Dellen, 2012. "Forecasting Overseas Visitors to the UK Using Continuous Time and Autoregressive Fractional Integrated Moving Average Models with Discrete Data," Tourism Economics, , vol. 18(4), pages 835-844, August.
    14. 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.
    15. 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.
    16. 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.
    17. Enrico Saltari & Clifford Wymer & Daniela Federici & Marilena Giannetti, 2011. "The impact of ICT on the Italian productivity dynamics," Working Papers in Public Economics 149, University of Rome La Sapienza, Department of Economics and Law.
    18. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310, Edward Elgar Publishing.
    19. P. Dontis-Charitos & S. R. Jory & T. N. Ngo & K. B. Nowman, 2013. "A multi-country analysis of the 2007--2009 financial crisis: empirical results from discrete and continuous time models," Applied Financial Economics, Taylor & Francis Journals, vol. 23(11), pages 929-950, June.
    20. 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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