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P. A. V. B. Swamy

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P. A. V. B. Swamy
Bornc. 1934 (age 90–91)
NationalityIndian
Alma materUniversity of Wisconsin–Madison
Andhra University
Scientific career
FieldsStatistics
Econometrics
InstitutionsFederal Reserve System
Ohio State University
SUNY Buffalo
Doctoral advisorArthur Goldberger

Paravastu Aananta Venkata Bhattandha Swamy (born c. 1934) is an Indian-born statistician. For fifty-six years, Swamy's research has focused on econometric issues.[1]

Education

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After earning a B.A. in economics from Andhra University, India, in 1956, both an M.A. in economics and a M.S. in statistics from the same university in 1958, Swamy attended the University of Wisconsin–Madison. He finished his Ph.D. dissertation on random coefficient estimation under the supervision of Arthur Goldberger in 1968.


Career

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In 1967, Swamy joined the economics faculty at SUNY Buffalo as assistant professor, when he published his first article based on his dissertation on random coefficient estimation,[2] followed in 1970 by another on the subject,[3] and in 1971 by a much cited monograph,[4] the latter cementing his reputation as an authority on random coefficient estimation. In 1972 he became professor at Ohio State University. In 1974, he joined the Federal Reserve System, where he worked first as an Economist and then as a Senior Economist in the Division of Research and Statistics until 1995, when he joined the Office of the Comptroller of the Currency as a researcher, followed by an appointment to the Bureau of Labor Statistics in 2002, from which he retired in 2009.

As summarized by Stephen G. Hall, Nobel Laureate Lawrence Klein, George S. Tavlas, and Arnold Zellner in a special issue of the journal Economic Modelling[5] dedicated to his contributions up to 2010, Swamy's research agenda has been devoted to some of the most pressing issues in econometrics. These include (1) a prevailing ignorance of true functional forms in economic relationships, (2) the presence of unobserved variables underlying the need for error terms, (3) the difficulty of obtaining accurate estimates of a model's parameters if error terms and included variables are correlated, which they must be, given the presence of unobserved variables, and (4) the problem of errors in measurement. With the collaboration of a number of long-time colleagues, including Jatinder S. Mehta and George S. Tavlas, [Stephen G. Hall]], Peter Tinsley, I-Lok Chang, and Peter von zur Muehlen, Swamy's singular contribution to econometrics has been to devise a methodology, set down in numerous publications, that has enabled the profession to address these issues in a coherent and systematic manner.[5]

In 1975, with his long-time co-author Jatinder S. Mehta, Swamy extended his methodology to include crossectional data in a paper entitled "Estimation of Linear Models with Time and Cross-Sectionally Varying Coefficients"[6] In 1976, to render estimation of time-varying stationary stochastic coefficients models operational, Swamy and Peter A. Tinsley published a paper on linear prediction and estimation.[7] In 1985, in an examination of the probabilistic-logical foundations of econometrics, Swamy and Peter von zur Muehlen published a paper,[8] reprinted in a volume on the foundations of probability, econometrics, and economic games,[9] which developed themes that would animate much of his later work, including a paper on the nature and testability of causality.[10]

Applying standard principles of probability theory and lessons learned from random coefficient modeling, Swamy co-authored a paper with James R. Barth and Peter A. Tinsley that questioned the validity of conventional formulations of the rational expectations postulate as a violation of the axiomatic basis of modern statistical theory by confounding ‘objective’ and ‘subjective’ notions of probability.[11] In a subsequent paper, Swamy and George S. Tavlas derived conditions under which the predictions generated from time-varying coefficient models coincide with the predictions generated from the relevant economic theory thereby fulfilling the rational expectations postulate.[12]

A 1988 publication by John W. Pratt and Robert Schlaifer on the interpretation and observation of laws,[13] became a compelling leitmotif for most of Swamy's subsequent work on estimating economic models.[14][15] To implement Pratt and Schlaifer's and Robert Basmann's compelling definitions of an economic law and to solve the problem of uniqueness arising from a correlation between the error term and included variables in a regression, Swamy resorted to a novel practice of modeling regression coefficients themselves as functions of variables external to the model, called "coefficient drivers."[16][17][18]


Selected publications

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References

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  1. ^ "P.A.V.B.Swamy".
  2. ^ Swamy, P.A.V.B. (1967). "Statistical Inference in Random Coefficient Regression Models and its Application in Economic Analysis". Annals of Mathematical Statistics. 38 (2): 1940–1947.
  3. ^ Swamy, P. A. V. B. (March 1970). "Efficient Inference in a Random Coefficient Regression Model". Econometrica. 38 (2): 311–323. doi:10.2307/1913012. JSTOR 1913012.
  4. ^ Swamy, P.A.V.B (1971). "Statistical Inference in Random Coefficient Models". Lecture Notes in Operations Research and Mathematical Systems. Berlin Heidelberg New York: Springer Verlag. pp. 1–95. doi:10.1007/978-3-642-80653-7.
  5. ^ a b Hall, Stephen G.; Klein, Lawrence R.; Tavlas, George S.; Zellner, Arnold (2010). "Introduction: P. A. V. B. Swamy's contribution to Econometrics". Economic Modelling. 27 (6): 1338–1344. doi:10.1016/j.econmod.2010.07.018.
  6. ^ Swamy, P.A.V.B; Mehta, J.S. (March 1975). "Estimation of Linear Models with Time and Cross-Sectionally Varying Coefficients". Journal of the American Statistical Association. 72 (6): 890–898. doi:10.1080/01621459.1977.10479978-4.
  7. ^ Swamy, P.A.V.B; Tinsley,Peter A. (February 1980). "Linear prediction and estimation methods for regression models with stationary stochastic coefficients". Journal of Econometrics. 12 (2): 103–142. doi:10.1016/0304-4076(80)90001-9.
  8. ^ Swamy, P.A.V.B.; Conway, Roger; von zur Muehlen,Peter (1985). "The Foundations of Econometrics --- Are There Any?". Econometric Reviews. 4 (1): 1–61. doi:10.1080/07474938508800071. SSRN 4159787.
  9. ^ Swamy, P.A.V.B.; Conway, Roger; von zur Muehlen,Peter (1997). "The Foundations of Econometrics --- Are There Any?". In Hamouda,F. Omar, J.C.R. Rowley (ed.). Foundations of Probability, Econometrics and Economic Games Series. Cheltenham, UK: Edward Elgar Publishing. ISBN 978 1 85898 370 7.{{cite book}}: CS1 maint: multiple names: editors list (link)
  10. ^ Swamy, P.A.V.B; von zur Muehlen,Peter (February 1988). "Further Thoughts on Testing for Causality with Econometric Models". Journal of Econometrics. 39 (2): 105–147. doi:10.1016/0304-4076(88)90042-5.
  11. ^ Swamy, P.A.V.B; Barth, J.R.; Tinsley, P.A. (November 1982). "The rational expectations approach to economic modelling". Journal of Economic Dynamics and Control. 4: 125–147. doi:10.1016/0165-1889(82)90009-4.
  12. ^ Swamy, P.A.V.B; Tavlas, George S. (June 2006). "A note on Muth's Rational Expectations Hypothesis: a Time-Varying Coefficients Interpretation". Macroeconomic Dynamics. 10 (3): 425–425. doi:10.1017/S1365100506050267.
  13. ^ Pratt, John W.; Schlaifer, R. (October 1988). "On the interpretation and observation of laws". Journal of Econometrics. 39 (1–2): 23–52. doi:10.1016/0304-4076(88)90039-5.
  14. ^ Swamy, P.A.V.B; von zur Muehlen,Peter; Mehta, Jatinder S.; Chang, I-Lok (March 2022). "The State of Econometrics after John W. Pratt, Robert Schlaifer, Brian Skyrms, and Robert L. Basmann". Sankya B. 84 (2): 627–654. doi:10.1007/s13571-021-00273-y.
  15. ^ Swamy, P.A.V.B; von zur Muehlen,Peter; Mehta, Jatinder S.; Chang, I-Lok (January 2019). "Alternative approaches to the econometrics of panel data". Panel Data Econometrics. San Diego, California: Academic Press. pp. 289–344. ISBN 978-0-12-814367-4.
  16. ^ Hall, Stephen G.; Swamy, P. a. V. B.; Tavlas, George S. (July 2009). "Time-Varying Coefficient Models: A Proposal for Selecting the Coefficient Driver Sets". Macroeconomic Dynamics. 21 (5): 1158–1174. doi:10.1017/S1365100515000279. hdl:2381/32164. ISSN 1365-1005.
  17. ^ Swamy, P.A.V.B; Chang, I-Lok; von zur Muehlen,Peter; Achameesing, Amit (August 2022). "The Role of Coefficient Drivers of Time-Varying Coefficients in Estimating the Total Effects of a Regressor on the Dependent Variable of an Equation". Journal of Risk and Financial Management. 15 (8): 3–31. doi:10.3390/jrfm15080331.
  18. ^ Swamy, P.A.V.B; von zur Muehlen,Peter; Mehta, J.S.; Chang, I-Lok (February 2019). "A Feasible Generalized Least Squares Approach to Estimating Total Causal Effects in a Regression". SSRN: 35.
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