Background
SARGAN, John was born on August 23, 1924 in Doncaster. Son of H. and G. A. Sargan.
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SARGAN, John was born on August 23, 1924 in Doncaster. Son of H. and G. A. Sargan.
Bachelor of Arts (Mathematics), Master of Arts (Mathematics), Bachelor of Arts University of Cambridge, Cambridge, United Kingdom, 1944, 1946, 1948.
Lector, University Leeds, 1948-1963. Visiting Professor, University Minnesota, 1958-1959, 1959-1960. Assistant Professor, University Chicago,
60.
Reader, Professor Econometrica, London School of Economies and Political Science, London, United Kingdom,
4, 1964-1984. Visiting Professor, Yale University, 1974, Florida, 1982. Professor Emeritus, London School of Economies and Political Science, London, United Kingdom,
.
Ex-Association Editor, Econometrica. Ex-Editor, Review of Economic Studies.
(Denis Sargan's work in econometrics has provided much of ...)
( When learning econometrics, what better way than to be ...)
Author: Contributions to Econometrics, vols. I and II, 1988, Advanced Econometric Theory, 1988.
I had an
early interest in economic theory and econometrics, but after my first visit to the United States of America I decided to concentrate on econometric theory and applied econometric work on inflation. My first two articles listed above contain the econometric theory relevant to the empirical work of the third article. I came back to wage inflation in No.
6 above. I still regard the idea that workers strive for a target value of real wages as an important explanation of current inflationary behaviour. The use of instrumental
variables to give a general technique for estimating economic relationships is now widely adopted.
A second development was based upon the fear that asymptotic (large sample) theory gives poor approximations in estimating some econometric models where sample sizes are less than one hundred. It is very difficult to discuss the exact distributions of estimations and test statistics from econometric models, but my 1976 article (No.
4 above) does contain some theoretical results, which however lead to difficult numerical computations. A much simpler alternative is to use approximation distributions, which consist of series of approximation terms in which each term is relatively small compared with the next earlier term, and the error in the approximation is of order equal to some initial power of the sample size. For sufficiently large sample size, these approximations may be sufficiently good to give a much better approximation to the exact distribution than the standard asymptotic distribution.
For estimations it is almost always possible to make use of the Edgeworth expansion, and for test statistics to make use of the chi-squared expansions. The practical problem is to develop computer programs to compute these approximations in sufficiently realistic models. Such programs have been written and implemented successfully by me and my students.
Fellow British Academy, London School Economic (honorary). Member Econometric Society (president 1980), American Academy Arts and Sciences.
Theatre, music.
Son of Harry and Gertrude Amy (Porter) S. Married Phyllis Mary Millard, July 10, 1963. Children: John Malcolm, David Richard, Barbara Annual.