Skip to main content
Log in

Testing for linear Granger causality from natural/anthropogenic forcings to global temperature anomalies

  • Original Paper
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

In this paper, we analyze the Granger causality from natural or anthropogenic forcings to global temperature anomalies. The lag-augmented Wald test is performed, and its robustness is also evaluated considering bootstrap method. The results show there is no-evidence of Granger causality from natural forcings to global temperature. On the contrary, a detectable Granger causality is found from anthropogenic forcings to global temperature confirming that greenhouse gases have an important role on recent global warming.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. The results are available from the author upon request.

References

  • Attanasio A, Pasini A, Triacca U (2012) A contribution to attribution of recent global warming by out-of-sample Granger-causality analysis. Atmos Sci Lett 13:67–72

    Article  Google Scholar 

  • Attanasio A, Triacca U (2011) Detecting human influence on climate using neural networks based Granger causality. Theor Appl Climatol 103:103–107

    Article  Google Scholar 

  • Clark T (2004) Can out-of-sample forecast comparisons help prevent overfitting? J Forecasting 23:115–139

    Article  Google Scholar 

  • Chao J, Corradi V, Swanson N (2001) Out-of-sample test for Granger causality. Macroecon Dyn 5:598–620

    Google Scholar 

  • Dickey D, Fuller WA (1981) Likelihood ratio statistic for autoregressive time series with a unit root. Econometrica 49:427–431

    Article  Google Scholar 

  • Elsner JB (2007) Granger causality and Atlantic hurricanes. Tellus 59:476–485

    Article  Google Scholar 

  • Engle RF, Granger CWJ (1987) Co-integration and error correction: representation, estimation, and testing. Econometrica 55:251–276

    Article  Google Scholar 

  • Gelper S, Croux C (2007) Multivariate out-of-sample tests for Granger causality. Comput Stat Data An 51:3319–3329

    Article  Google Scholar 

  • Giles DEA (1997) Causality between the measured and underground economies in New Zealand. Appl Econ Lett 4:63–67

    Article  Google Scholar 

  • Granger CWJ (1969) Investigating causal relations by econometric methods and cross-spectral methods. Econometrica 37:424–438

    Article  Google Scholar 

  • Granger CWJ (1981) Some properties of time series data and their use in econometric model specification. J Econometrics 16:121–130

    Article  Google Scholar 

  • Granger CWJ (1988) Causality, cointegration, and control. J Econ Dyn 12:551–559

    Article  Google Scholar 

  • Hacker RS, Hatemi-J A (2006) Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application. Appl Econ 38:1489–1500

    Article  Google Scholar 

  • Haldrup N, Lildholdt P (2002) On the robustness of unit root tests in the presence of double unit roots. J Time Ser Anal 23:155–171

    Article  Google Scholar 

  • Hamilton JD (1994) Time series analysis. Princeton University Press, Princeton, NJ.

    Google Scholar 

  • Hatemi-J A, Shukur G (2002) Multivariate-based causality tests of twin deficits in the US. J Appl Stat 29:817–824

    Article  Google Scholar 

  • Kaufmann RK, Stern DI (1997) Evidence for human influence on climate from hemispheric temperature relations. Nature 388:39–44

    Article  Google Scholar 

  • Kodra E, Chatterjee S, Ganguly AR (2011) Exploring Granger causality between global average observed time series of carbon dioxide and temperature. Theor Appl Climatol 104:325–335

    Article  Google Scholar 

  • Inoue A, Kilian L (2004) In-sample or out-of-sample tests of predictability: which one should we use? Economet Rev 23:371–402

    Article  Google Scholar 

  • IPCC (2001) Climate change 2001: the scientific basis. Cambridge University Press, Cambridge, UK and New York, NY, USA

    Google Scholar 

  • Liu H, Rodriguez G (2005) Human activities and global warming: a cointegration analysis. Environ Modell Softw 20:761–773

    Article  Google Scholar 

  • Lukasz L (2010) Application of bootstrap methods in investigation of size of the Granger causality test for integrated VAR systems. Manag Glob Transit 8:167–186

    Google Scholar 

  • Lutkepohl H, Kratzig M (2004) Applied time series econometrics. Cambridge University Press, Cambridge, UK

    Book  Google Scholar 

  • Mantalos P (2000) A graphical investigation of the size and power of the Granger-causality tests in integrated-cointegrated VAR systems. Stud Nonlinear Dyn E 4:17–33

    Article  Google Scholar 

  • Mavrotas G, Kelly R (2001) Old wine in new bottles: testing causality between savings and growth. Manch Sch 69:97–105

    Article  Google Scholar 

  • Mokhov II, Smirnov DA (2008) Diagnostics of a cause-effect relation between solar activity and the Earth’s global surface temperature. Izv Atmos Ocean Phys 44:263–272

    Article  Google Scholar 

  • Pasini A, Lorè M, Ameli F (2006) Neural network modelling for the analysis of forcings/temperatures relationships at different scales in the climate system. Ecol Model 191:58–67

    Article  Google Scholar 

  • Phillips PCB, Ouliaris S (1990) Asymptotic properties of residual based tests for cointegration. Econometrica 58:165–193

    Article  Google Scholar 

  • Reichel R, Thejll P, Lassen K (2001) The cause-and-effect relationship of solar cycle length and the Northern Hemisphere air surface temperature. J Geophys Res 106:635–641

    Article  Google Scholar 

  • Shukur G, Mantalos P (2000) A simple investigation of the Granger-causality test in integrated-cointegrated VAR systems. J Appl Stat 27:1021–1031

    Article  Google Scholar 

  • Sims CA, Stock JH, Watson MW (1990) Inference in linear time series models with some unit roots. Econometrica 58:113–144

    Article  Google Scholar 

  • Stern DI, Kaufmann RK (1999) Econometric analysis of global climate change. Environ Modell Softw 14:597–605

    Article  Google Scholar 

  • Stock JH, Watson MW (1989) Interpreting the evidence on money-income causality. J Econom 40:161–81

    Article  Google Scholar 

  • Sun L, Wang M (1996) Global warming and global dioxide emission: an empirical study. J Environ Manage 46:327–343

    Article  Google Scholar 

  • Toda HY, Yamamoto T (1995) Statistical inference in vector autoregression with possibly integrated processes. J Econometrics 66:225–250

    Article  Google Scholar 

  • Triacca U (1998) Non-causality: the role of the omitted variables. Econ Lett 60:317–320

    Article  Google Scholar 

  • Triacca U (2001) On the use of Granger causality to investigate the human influence on climate. Theor Appl Climatol 69:137–138

    Article  Google Scholar 

  • Triacca U (2002) Selection of the relevant information set for predictive relationships analysis between time series. J Forecasting 21:595–599

    Article  Google Scholar 

  • Triacca U (2005) Is Granger causality analysis appropriate to investigate the relationship between atmospheric concentration of carbon dioxide and global surface air temperature? Theor Appl Climatol 81:133–135

    Article  Google Scholar 

Download references

Acknowledgements

I am grateful to anonymous referees for their valuable comments. I would like to thank Prof. U. Triacca and Dr. A. Pasini for the useful discussions and suggestions on a preliminary version of this paper, andM.E. Basilici for the advice on the language. All statistical computations were done using gret. Any remaining lack of clarity are my own responsibility.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alessandro Attanasio.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Attanasio, A. Testing for linear Granger causality from natural/anthropogenic forcings to global temperature anomalies. Theor Appl Climatol 110, 281–289 (2012). https://doi.org/10.1007/s00704-012-0634-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-012-0634-x

Keywords

Navigation