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Global Hemispheric Temperatures and Co–Shifting: A Vector Shifting–Mean Autoregressive Analysis

Author

Listed:
  • Matthew T. Holt

    (University of Alabama, Department of Economics, Finance & Legal Studies)

  • Timo Teräsvirta

    (Aarhus University and CREATES, C.A.S.E., Humboldt-Universität zu Berlin)

Abstract

This paper examines local changes in annual temperature data for the northern and southern hemispheres (1850-2014) by using a multivariate generalisation of the shifting-mean autoregressive model of González and Teräsvirta (2008). Univariate models are first fitted to each series by using the QuickShift methodology. Full information maximum likelihood estimates of a bivariate system of temperature equations are then obtained and asymptotic properties of the corresponding estimators considered. The system is then used to perform formal tests of co-movements, called co-shifting, in the series. The results show evidence of co-shifting in the two series. Forecasting this pair of series is considered as well.

Suggested Citation

  • Matthew T. Holt & Timo Teräsvirta, 2017. "Global Hemispheric Temperatures and Co–Shifting: A Vector Shifting–Mean Autoregressive Analysis," CREATES Research Papers 2017-05, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:create:2017-05
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    References listed on IDEAS

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    1. Søren Johansen, 2010. "The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration with an Application to Annual Mean Temperature and Sea Level," Discussion Papers 10-27, University of Copenhagen. Department of Economics.
    2. Eklund, Bruno & Terasvirta, Timo, 2007. "Testing constancy of the error covariance matrix in vector models," Journal of Econometrics, Elsevier, vol. 140(2), pages 753-780, October.
    3. Barry K. Goodwin & Matthew T. Holt & Jeffrey P. Prestemon, 2011. "North American Oriented Strand Board Markets, Arbitrage Activity, and Market Price Dynamics: A Smooth Transition Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(4), pages 993-1014.
    4. Hillebrand Eric & Medeiros Marcelo C. & Xu Junyue, 2013. "Asymptotic Theory for Regressions with Smoothly Changing Parameters," Journal of Time Series Econometrics, De Gruyter, vol. 5(2), pages 133-162, April.
    5. Stephen Leybourne & Paul Newbold & Dimitrios Vougas, 1998. "Unit roots and smooth transitions," Journal of Time Series Analysis, Wiley Blackwell, vol. 19(1), pages 83-97, January.
    6. Hendry, David F. & Massmann, Michael, 2007. "Co-Breaking: Recent Advances and a Synopsis of the Literature," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 33-51, January.
    7. Candelon, Bertrand & Lutkepohl, Helmut, 2001. "On the reliability of Chow-type tests for parameter constancy in multivariate dynamic models," Economics Letters, Elsevier, vol. 73(2), pages 155-160, November.
    8. David Harvey & Terence Mills, 2002. "Unit roots and double smooth transitions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(5), pages 675-683.
    9. Andrés González & Kirstin Hubrich & Timo Teräsvirta, 2009. "Forecasting inflation with gradual regime shifts and exogenous information," CREATES Research Papers 2009-03, Department of Economics and Business Economics, Aarhus University.
    10. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521839198, September.
    11. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    12. Robert K. Kaufmann & David I. Stern, 1997. "Evidence for human influence on climate from hemispheric temperature relations," Nature, Nature, vol. 388(6637), pages 39-44, July.
    13. Trevor Breusch & Farshid Vahid, 2008. "Global Temperature Trends," ANU Working Papers in Economics and Econometrics 2008-495, Australian National University, College of Business and Economics, School of Economics.
    14. Perron, Pierre, 1990. "Testing for a Unit Root in a Time Series with a Changing Mean," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 153-162, April.
    15. Anderson, Heather M. & Vahid, Farshid, 1998. "Testing multiple equation systems for common nonlinear components," Journal of Econometrics, Elsevier, vol. 84(1), pages 1-36, May.
    16. Terasvirta, Timo & Tjostheim, Dag & Granger, Clive W. J., 2010. "Modelling Nonlinear Economic Time Series," OUP Catalogue, Oxford University Press, number 9780199587155.
    17. Grayham E. Mizon & David F. Hendry, 1998. "Exogeneity, causality, and co-breaking in economic policy analysis of a small econometric model of money in the UK," Empirical Economics, Springer, vol. 23(3), pages 267-294.
    18. Dick van Dijk 1 & Birgit Strikholm & Timo Teräsvirta, 2003. "The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 79-98, June.
    19. Francisco Estrada & Luis Filipe Martins & Pierre Perron, 2017. "Characterizing and attributing the warming trend in sea and land surface temperatures," Boston University - Department of Economics - Working Papers Series WP2017-009, Boston University - Department of Economics.
    20. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, September.
    21. Mads Faurschou Knudsen & Bo Holm Jacobsen & Marit-Solveig Seidenkrantz & Jesper Olsen, 2014. "Evidence for external forcing of the Atlantic Multidecadal Oscillation since termination of the Little Ice Age," Nature Communications, Nature, vol. 5(1), pages 1-8, May.
    22. Saikkonen, Pentti, 2001. "Consistent Estimation In Cointegrated Vector Autoregressive Models With Nonlinear Time Trends In Cointegrating Relations," Econometric Theory, Cambridge University Press, vol. 17(2), pages 296-326, April.
    23. Ripatti, Antti & , Pentti, 2001. "Vector Autoregressive Processes With Nonlinear Time Trends In Cointegrating Relations," Macroeconomic Dynamics, Cambridge University Press, vol. 5(4), pages 577-597, September.
    24. Hui Liu & Gabriel Rodriguez, 2003. "Human Activities and Global Warming: A Cointegration Analysis," Working Papers 0307E, University of Ottawa, Department of Economics.
    25. Luis A. Gil-Alana, 2008. "Time trend estimation with breaks in temperature time series," Faculty Working Papers 09/08, School of Economics and Business Administration, University of Navarra.
    26. James E. H. Davidson & David B. Stephenson & Alemtsehai A. Turasie, 2016. "Time series modeling of paleoclimate data," Environmetrics, John Wiley & Sons, Ltd., vol. 27(1), pages 55-65, February.
    27. Lin, Chien-Fu Jeff & Terasvirta, Timo, 1994. "Testing the constancy of regression parameters against continuous structural change," Journal of Econometrics, Elsevier, vol. 62(2), pages 211-228, June.
    28. White, Halbert, 2006. "Approximate Nonlinear Forecasting Methods," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 9, pages 459-512, Elsevier.
    29. Robert Kaufmann & Heikki Kauppi & Michael Mann & James Stock, 2013. "Does temperature contain a stochastic trend: linking statistical results to physical mechanisms," Climatic Change, Springer, vol. 118(3), pages 729-743, June.
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    Cited by:

    1. C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "Temperature in the Iberian Peninsula: Trend, seasonality, and heterogeneity," Papers 2406.14145, arXiv.org.
    2. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model," Journal of Econometrics, Elsevier, vol. 239(1).
    3. Friedrich, Marina & Lin, Yicong, 2024. "Sieve bootstrap inference for linear time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 239(1).
    4. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Marc Gronwald, 2023. "Explosive Temperatures," CESifo Working Paper Series 10680, CESifo.

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    More about this item

    Keywords

    Co-breaking; Hemispheric temperatures; Vector nonlinear model; Testing linearity; Structural change;
    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
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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