Hansen is best known for his work on thegeneralized method of moments. He is also a distinguishedmacroeconomist, focusing on the linkages between the financial sector and the macroeconomy. His current collaborative research develops and applies methods for pricing the exposure to macroeconomic shocks over alternative investment horizons and investigates the implications of the pricing of long-term uncertainty.
After graduating fromUtah State University (B.S. Mathematics, Political Science, 1974) and theUniversity of Minnesota (Ph.D. Economics, 1978), he served as assistant and associate professor atCarnegie Mellon University before moving to theUniversity of Chicago in 1981. He is currently the David Rockefeller Distinguished Service Professor in Economics, Statistics and the College at the University of Chicago. He is married to Grace Tsiang (Chinese:蒋人瑞;pinyin:Jiǎng Rénruì), who is the daughter of the famous economistSho-Chieh Tsiang. Together, Hansen and Tsiang have one son named Peter.[6] He has two brothers, Ted Howard Hansen, an immunologist at Washington University in St. Louis and Roger Hansen, an engineer in water resource management. His father, Roger Gaurth Hansen, served as provost of Utah State University and was a professor of biochemistry.
Hansen is best known as the developer of theeconometric techniquegeneralized method of moments (GMM) and has written and co-authored papers applying GMM to analyze economic models in numerous fields includinglabor economics,international finance,finance andmacroeconomics. This method has been widely adopted in economics and other fields and applications where fully specifying and solving a model of a complex economic environment is unwieldy or otherwise impractical. Hansen showed how to exploit moment conditions (e.g. relations where conditional expectations are known to be zero at true parameter values) to construct reasonable, reliable estimators (i.e. having desirable statistical properties such as consistency, asymptotic normality, and efficiency within the class of all asymptotic normal estimators) with less stringent maintained model assumptions than needed for maximum likelihood estimation. However, these estimators are mathematically equivalent to those based on "orthogonality conditions" (Sargan, 1958, 1959) or "unbiased estimating equations" (Huber, 1967; Wang et al., 1997). Moreover, maximum likelihood estimation methods provide guidance for devising more efficient instrumental variables estimators that take into account special features such as restrictions on the variance-covariance matrices of the errors (Bhargava and Sargan, 1983).
With several coauthors such as Kenneth J. Singleton, Scott F. Richard, and Robert Hodrick, Hansen applied GMM to study models of asset valuation. Together withRavi Jagannathan he showed that the ratio of anystochastic discount factor's standard deviation to its mean is at least as great as any asset'sSharpe ratio; this result is known as theHansen–Jagannathan bound. The fact that this often fails in practice due to theSharpe ratio of risky assets exceeding the ratio of the volatility of thestochastic discount factor to its expectation is known as theequity premium puzzle. Later work focused on the long-run risk-return tradeoff withJosé Scheinkman and the examination of the term structure of pricing risk shocks in dynamic macroeconomic models through the use of "dynamic valuation decomposition."
Thomas J. Sargent and Hansen coauthoredRobustness, which explores implications of robust control theory for macroeconomic modeling when the decision maker is skeptical of any single statistical model's ability to capture how decisions are linked to outcomes.
Hansen has focused on the difference between risk and uncertainty[7] (also known asKnightian uncertainty) and on the measurement of so-called systemic risk," its role in the2008 financial crisis,[8] and how it should be contained during the post-Great Recession recovery.[9] He frequently speaks publicly on the need to address uncertainty in the policy-making process.
His contributions and current research interests are outlined in a December 2015 interview[10] appearing inThe Region, a publication of the Federal Reserve Bank of Minneapolis.
Hansen is the inaugural director of theBecker Friedman Instituteand the current director of BFI's Macro Finance Research Program (MFR).[11] He was founding director of the Milton Friedman Institute, the predecessor of the Becker Friedman Institute. In 2018, Hansen wrote a retrospective essay[12] reflecting on the Beginnings of the Becker Friedman Institute for Research in Economics, With M.I.T. economistAndrew Lo, Hansen leads the Macro Financial Modeling Group, a network of macroeconomists working to develop improved models of the linkages between the financial and real sectors of the economy after the2008 financial crisis. He also is co-principal investigator on a research initiative studying the costs of uncertainty about economic policy.[13]
He is the co-winner of theFrisch Medal withKenneth Singleton in 1984 for his paper, "Generalized Instrumental Variables Estimation of Nonlinear Rational Expectations Models".[16] For his work in studying the properties of financial markets and macroeconomics, he was the 2006Erwin Plein Nemmers Prize in Economics recipient.[17] He was recognized for his use of statistical methods in economics by receiving the CME Group-MSRI Prize In Innovative Quantitative Applications in 2008.[18] In 2011, he was awarded theBBVA Foundation Frontiers of Knowledge Award in Economics, Finance, and Management "for making fundamental contributions to our understanding of how economic actors cope with risky and changing environments."[19] He holds honorary doctorates from Utah State University and honorary professorships from HEC Paris and Universidad del Pacífico awarded in 2015. On May 22, 2016, Hansen received an honorary degree fromColby College in Waterville, Maine.[20]
Hansen, L.P. and J. Borovička, "Term Structure of Uncertainty in the Macroeconomy," in "Handbook of Macroeconomics," Vol. 2, Part 2., eds. J.B. Taylor, H. Uhlig., December 2016.
Hansen, L.P., J. Borovička and J. Scheinkman "Misspecified Recovery," Journal of Finance, March 2016.
Hansen, L.P. and Sargent, T.J.Uncertainty Within Economic Models.[24] World Scientific Publishing 2014.
Hansen, L.P. "Uncertainty Inside and Outside Economic Models[25]" (Nobel Lecture)
Hansen, L.P. and Sargent, T.J.Recursive Models of Dynamic Linear Economies[26]. Princeton University Press 2013.
Hansen, L.P. and Sargent, T.J.Robustness[27] Princeton University Press 2007.
Hansen, L.P. "Challenges in Identifying and Measuring Systemic Risk," in Brunnermeier, M.K. and Krishnamurthy, A.:Risk Topography: Systemic Risk and Macro Modeling,[28] September 2012.
Hansen, L.P. "Generalized Methods of Moments: A Time Series Perspective," inInternational Encyclopedia of the Social and Behavior Sciences, 2000.
Hansen, L.P., (1982), "Large Sample Properties of Generalized Methods of Moments Estimators" inEconometrica, Vol. 50, page 1029–1054, where he proposed the GMM-procedure.
Hansen, L. P.; Singleton, K.J. (1982). "Generalized Instrumental Variables Estimation of Nonlinear Rational Expectations Models".Econometrica.50 (5):1269–86.doi:10.2307/1911873.JSTOR1911873.
Hansen, L.P.; Hodrick, R.J. (1980). "Forward Exchange-Rates As Optimal Predictors of Future Spot Rates - An Econometric-Analysis".Journal of Political Economy.88 (5):829–853.doi:10.1086/260910.S2CID152551684.
Bhargava, A., and Sargan, J.D. (1983). Estimating dynamic random effects from panel data covering short time periods. Econometrica, 51, 6, 1635–1659.
Huber, P. (1967). The behavior of maximum likelihood estimates under nonstandard conditions. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability 1, 221–233.
Sargan, J.D. (1958). The estimation of economic relationships using instrumental variables. Econometrica, 26, 393–415.
Sargan, J.D. (1959). The estimation of relationships with autocorrelated residuals by the use on instrumental variables. Journal of the Royal Statistical Society B, 21, 91–105.
Wang, C.Y., Wang, S., and Carroll, R. (1997). Estimation in choice-based sampling with measurement error and bootstrap analysis. Journal of Econometrics, 77, 65–86.