Clive W.J.Granger

Clive W.J.Granger, a Welsh economist (resident of Wales) was the co-recipient of the Nobel Prize with Robert F. Engle of U.S. for Economics in 2003. He will be remembered for his work on development of techniques for analyzing time series data with common trends. Clive W.J.Granger was born on 4th September,1934 at Swansea, Wales. [br]

Clive W.J.Granger, a Welsh economist (resident of Wales) was the co-recipient of the Nobel Prize with Robert F. Engle of U.S. for Economics in 2003. He will be remembered for his work on development of techniques for analyzing time series data with common trends. Clive W.J.Granger was born on 4th September,1934 at Swansea, Wales. [br]

Personal and career profiles:

Clive W.J.Granger, son of Edward John Granger and Evelyn Granger was born in Swansea, SC Wales, UK. In 1951, he was a student of West Bridgeford Grammar School, London, UK. After high school, Granger registered his name at the University of Nottingham for a joint degree in economics and mathematics. In the second year of his university he changed over to full mathematics and after getting B.A. degree in 1955, he continued his study at the University of Nottingham for a Ph.D in statistics under the guidance of Harry Pitt and in 1959, he was awarded Ph.D. in statistics for his thesis on “Testing for Non-stationarity”. Clive W.J.Granger was engaged as a scholar of economics at Princeton University in the period of 1959-60 and during 1959-60, he was engaged as a teacher of statistics at the University of Nottingham. During 1966-74, he was the professor of Applied Statistics and Econometrics at the University of Nottingham. He spent 22 years altogether at the University of Nottingham before leaving for UCSD (University of California at San Diego) in 1974. 

Honors and Awards

• In 1988 ( from January to June), Clive W.J.Granger was elected as Guggenheim Fellow.
• In 1992, University of Nottingham rewarded him with Honorary D.Sc. Degree. In 1994, he became the Fellow of American Academy of Arts and Sciences and adorned Chancellor’s Associates Chair in Economics.
• During 2002-03, he was the president of Western Economic Association. In 2002, he was the Distinguished Fellow, American Economic Association and was awarded Honorary D.Sc. Degree from University of Loughborough.
• In 2003, Clive W.J.Granger shared the Nobel Prize for Economics with Robert F Engle. He was awarded the Nobel Prize for the work on using statistics to anticipate the future. The study was basically on methods of analyzing economic time series with common trends, termed as cointegration.
• In 2005, he became the Knight of the British Empire.

Publications [br]

• Some of the selected works of Clive W.J.Granger include:
  
• Granger, C. W. J. and Hatanaka, M. (1964): Spectral Analysis of Economic Time Series. Princeton University Press, Princeton, NJ. ISBN 0-691-04177-6
• Granger, C. W. J. (1966): “The typical spectral shape of an economic variable”. Econometrica 34: 150-161
• Granger, C. W. J. (1969): “Investigating causal relations by econometric models and cross-spectral methods”. Econometrica 37: 424—438
• Granger, C. W. J. and Bates, J. (1969): “The combination of forecasts”. Operations Research Quarterly 20: 451—468
• Granger, C. W. J. and Newbold, P. (1974): “Spurious regressions in econometrics”. Journal of Econometrics 2: 111—120
• Granger, C. W. J. and Newbold, P. (1977): Forecasting Economic Time Series. Academic Press; second edition: 1986
• Granger, C. W. J. and Joyeux, R. (1980): “An introduction to long-memory time series models and fractional differencing”. Journal of Time Series Analysis 1: 15—30
• Engle, R. F. and Granger, C. W. J. (1987): “Co-integration and error-correction: Representation, estimation and testing”. Econometrica 55: 251—276

Books by Clive W.J.Granger

Spectral Analysis of Economic Time Series (Princeton Studies in Mathematical Economics)
Essays in Econometrics: Collected Papers of Clive W. J. Granger (Econometric Society Monographs) (Volume 1)
Modelling Nonlinear Economic Relationships (Advanced Texts in Econometrics)
Empirical Modelling in Economics: Specification and Evaluation

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