Age, Biography and Wiki
Richard Baillie was born on 1948 in London, UK in 1948, is a British-American economist. Discover Richard Baillie's Biography, Age, Height, Physical Stats, Dating/Affairs, Family and career updates. Learn How rich is he in this year and how he spends money? Also learn how he earned most of networth at the age of 76 years old?
We recommend you to check the complete list of Famous People born on 1948.
He is a member of famous economist with the age 76 years old group.
Richard Baillie Height, Weight & Measurements
At 76 years old, Richard Baillie height not available right now. We will update Richard Baillie's Height, weight, Body Measurements, Eye Color, Hair Color, Shoe & Dress size soon as possible.
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Dating & Relationship status
He is currently single. He is not dating anyone. We don't have much information about He's past relationship and any previous engaged. According to our Database, He has no children.
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Richard Baillie Net Worth
His net worth has been growing significantly in 2023-2024. So, how much is Richard Baillie worth at the age of 76 years old? Richard Baillie’s income source is mostly from being a successful economist. He is from United States. We have estimated Richard Baillie's net worth, money, salary, income, and assets.
| Net Worth in 2024 |
$1 Million - $5 Million |
| Salary in 2024 |
Under Review |
| Net Worth in 2023 |
Pending |
| Salary in 2023 |
Under Review |
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Not Available |
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Not Available |
| Source of Income |
economist |
Richard Baillie Social Network
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Timeline
Richard T. Baillie is a British–American economist and statistician who is currently the A J Pasant Professor of Economics at the Michigan State University.
He is also part time professor at King's College, London, and Senior Scientific Officer for the Rimini Center for Economic Analysis in Italy, and also on the Executive Council of the Society for Nonlinear Dynamics in Econometrics (SNDE).
Baillie obtained his PhD from the London School of Economics & Political Science, where his doctoral advisors were Kenneth F. Wallis and James Durbin.
He also has an MSc from the University of Kent and a BSc from Middlesex University.
He is an elected fellow of the American Statistical Association, the Journal of Econometrics and also the International Institute for Applied Econometrics.
He was also given the Distinguished Faculty Award at Michigan State University.
He has held full time appointments at the University of Birmingham, Georgetown University, Queen Mary University of London and the Michigan State University.
He has been Research Fellow at the Australian National University also been visiting professor at the University of California San Diego, University of Toronto, Wayne State University and Arizona State University.
His research is mainly on time series econometrics; and he has made both theoretical and applied contributions.
He has also worked extensively on international finance and more general asset pricing issues in financial markets.
He was one of the five founding editors of the Journal of Empirical Finance.
He has over 19,000 citations on Google Scholar and an h statistic of 46.
Baillie's main area of research has been the development and application of time series analysis in econometrics.
His early work was on properties of predictions from dynamic models, including regressions with autocorrelated errors and Vector Autoregressions (VARs).
This work derived results for optimal predictors and evaluated the uncertainty introduced by parameter estimation.
He also did related work on inference from Impulse Response Functions from various dynamic models.
Baillie has also published contributions to testing the theory of rational expectations in financial markets; most notably advocating VAR approaches over single equation methodology.
He has published work on models of volatility, particularly with GARCH models, including applications to modeling risk premium, and various applications in international finance including the effectiveness of sterilized central bank intervention.
Baillie has published extensively on long memory processes, and also has highly cited survey article and the long memory FIGARCH model with Tim Bollerslev and Mikkelsen, been widely used in empirical work and has also been the seed of a large theoretical literature.
