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Statistical Modelling of Temperature Risk

Author

Listed:
  • Zografia Anastasiadou
  • BrendaLópez-Cabrera

Abstract

Recently the topic of global warming has become very popular. The literature has concentrated its attention on the evidence of such eect, either by detecting regime shifts or change points in time series. The majority of these methods are designed to nd shifts in mean, but only few can do this for the variance. In this paper we attempt to investigate the statistical evidence of global warming by identi- fying shifts in seasonal mean of daily average temperatures over time and in seasonal variance of temperature residuals. We present a time series approach for modelling temperature dynamics. A seasonal mean Lasso-type technique based with a multi- plicative structure of Fourier and GARCH terms in volatility is proposed. The model describes well the stylised facts of temperature: seasonality, intertemporal correla- tions and the heteroscedastic behaviour of residuals. The application to European temperature data indicates that the multiplicative model for the seasonal variance performs better in terms of out of sample forecast than other models proposed in the literature for modelling temperature dynamics. We study the dynamics of the seasonal variance by implementing quantile and expectile functions with condence corridor to detrended and deseasonalized residuals. We show that shifts in seasonal mean and variance vary from location to location, indicating that all sources of trends other than mean and variance would rise trends over spatial scales. The local eects of temperature risk support the existence of global warming.

Suggested Citation

  • Zografia Anastasiadou & BrendaLópez-Cabrera, 2012. "Statistical Modelling of Temperature Risk," SFB 649 Discussion Papers SFB649DP2012-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Handle: RePEc:hum:wpaper:sfb649dp2012-029
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    Cited by:

    1. Paul I. Ojeaga & Emmanuel O. George & Oluwatoyin Mathew & Adetunji Adekola, 2016. "What does FDI inflow mean for emerging african economies? Measuring the regional effects of FDI in Africa," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 4(1), pages 29-46, June.
    2. Karakosta, Charikleia & Flouri, Maria & Dimopoulou, Stamatia & Psarras, John, 2012. "Analysis of renewable energy progress in the western Balkan countries: Bosnia–Herzegovina and Serbia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 5166-5175.
    3. Bai, Attila & Durkó, Emília & Tar, Károly & Tóth, József Barnabás & Lázár, István & Kapocska, László & Kircsi, Andrea & Bartók, Blanka & Vass, Róbert & Pénzes, János & Tóth, Tamás, 2016. "Social and economic possibilities for the energy utilization of fitomass in the valley of the river Hernád," Renewable Energy, Elsevier, vol. 85(C), pages 777-789.
    4. Anandarajah, Gabrial & Gambhir, Ajay, 2014. "India’s CO2 emission pathways to 2050: What role can renewables play?," Applied Energy, Elsevier, vol. 131(C), pages 79-86.
    5. Abrell, Jan & Rausch, Sebastian, 2016. "Cross-country electricity trade, renewable energy and European transmission infrastructure policy," Journal of Environmental Economics and Management, Elsevier, vol. 79(C), pages 87-113.
    6. Fang, Xiande & Li, Dingkun, 2013. "Solar photovoltaic and thermal technology and applications in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 330-340.

    More about this item

    Keywords

    Weather; temperature; seasonality; variance; global warming; expectile; quantile;

    JEL classification:

    • G19 - Financial Economics - - General Financial Markets - - - Other
    • G29 - Financial Economics - - Financial Institutions and Services - - - Other
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • N23 - Economic History - - Financial Markets and Institutions - - - Europe: Pre-1913
    • N53 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries - - - Europe: Pre-1913
    • Q59 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Other

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