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Econometrics

 

Econometrics is the application of statistical methodology to economics.  Used in virtually every area of economics, econometrics is often a second field for people doing empirical research.  The Triangle area includes large number of econometricians covering a wide range of theoretical and applied interests in the field.  The Econometrics Workshop is run jointly by the University of North Carolina - Chapel Hill, Duke University, North Carolina State University, and the SAS Institute.  The group also holds the annual Harold Hotelling Triangle Economics Conference.  

UNC Faculty

 

Ron Gallant

Ron Gallant is Henry A. Latane Distinguished Professor of Economics and Adjunct Professor of Statistics at the University of North Carolina at Chapel Hill and Research Professor of Economics at Duke University. Before joining the UNC faculty, he was, successively, Assistant, Associate, Full, and Drexel Professor of Statistics and Economics at North Carolina State University. Gallant has held visiting positions at the University of Chicago, Duke University, and Northwestern University. He received his A.B. in mathematics from San Diego State University, his M.B.A. in marketing from the University of California at Los Angeles, and his Ph.D. in statistics from Iowa State University. He is a Fellow of both the Econometrics Society and the American Statistical Association. He serves on the Board of Directors of the National Bureau of Economic Research and has served on the Board of Directors of the American Statistical Association and on the Board of Trustees of the National Institute of Statistical Sciences. He is co-editor of the Journal of Econometrics and past editor of The Journal of Business and Economic Statistics.

Gallant is interested in fitting models from the sciences to data for the purpose of statistical inference. Typically these models will involve a nonlinear parametric component that describes features of the model where the underlying scientific theory is explicit and a nonparametric component that accounts for features where the scientific theory is vague. Appropriate statistical methods for these problems are usually computationally intensive. Methodological interests are in developing statistical methods and numerical algorithms for fitting these models. Theoretical interests are in deriving the statistical properties of proposed methods, particularly the asymptotic properties of estimators of functionals of the nonparametric component. Applied interests are primarily within economics and finance.

 

David Guilkey

 

David Guilkey, Professor and Chair of Economics, is an econometrician interested in statistical problems associated with large survey data sets. His current work involves the development of estimation methods to predict outcomes such as contraceptive choice and recent fertility. His primary measurement focus is on correctly estimating the effects of external factors such as resource inputs on ultimate outcomes. He is working with Thomas Mroz and Gustavo Angeles to extend economic structural models for use in the study of the determinants of fertility when government program placement is targeted. They are applying their methods to data sets from Peru and Tanzania and presented a paper on this topic at the 1998 PAA meeting. Guilkey is currently on the Carolina Population Center Advisory Council and is one of the CPC statistical advisors.

 

William R. Parke

William Parke (Yale (1980, Economics) and University of Washington (1973, Mathematics)) is currently working on his third contribution to econometrics.  "What is Fractional Integration," Review of Economics and Statistics (forthcoming, 1999), opens a discussion of the relation between fractional integration, which is a generalization of the notion of a unit root, and structural change.  The former has to this point been mainly a technical econometric concept and the latter has been primarily a matter of substantial practical importance.  Parke introduces a new construction, known as an error duration model, that is an alternative to ARMA models for a certain class of time series processes. A fractionally integrated process has a surprisingly elegant representation as an error duration model.   Parke shows that fractional integration and structural change are essentially two views of one process. This paper is available in pdf format from the Department's working paper series.   

"An Algorithm for FIML and 3SLS Estimation of Large Nonlinear Models," Econometrica 50 (1982), 81-95, provides a solution to the longstanding numerical challenge of FIML estimation of large simultaneous equations models.  Related papers (Journal of Econometrics (1980), Annals of Statistics (1986), International Economic Review (1986)) demonstrate the algorithm and investigation theoretical issues related to techniques for estimating subvectors of a large parameter vector.  Parke's FIML algorithm and other econometrics for large simultaneous equations models are in the Fair-Parke Program, which you can find at fairmodel.econ.yale.edu/fp/fp.htm

"Asymptotic Likelihood Based-Prediction Functions" (with Thomas F. Cooley) Econometrica, 58 (1990), 1215-1234, and related papers (Journal of Econometrics (1987, 1989), propose a theory of predictive likelihood that complements the notion of likelihood in estimation theory.  Existing forecasting methodologies relied either on linear models or simulation techniques to contruct predictive confidence intervals.  The predictive likelihood approach constructs a predictive likelihood function for general nonlinear models.  

Other research topics have included empirical work on stock price volatility (American Economic Review, 1992) and the pre-WWI gold standard era (Journal of Money, Credit, and Banking, 1995).  Several of these papers are available at www.jstor.org.   Parke is also the architect of the EconModel project at www.econmodel.com.  

 

 

Graduate Students

 

Garland Durham

 

Garland Durham is interested in the estimation of continuous time models for financial data. A working paper discussing numerical techniques for implementing a simulation-based maximum likelihood estimator for scalar, fully-observed stochastic differential equations is available at www.unc.edu/~gdurham. Future work will extend these results to multivariate and partially observed systems.

 

Ken Hightower

 

Ken Hightower is developing extensions of Parke's error duration ideas.  His results help to show the relation between fractional integration and common notions of structural change.  

 

 

Other Triangle Econometricians

 

An, Tauchen, Bollerslev, Hall, Dickey, ...

 

Graduate Econometrics Courses
 
271 Introduction to Econometric Theory
Probability theory, expectation, conditional expectation, modes of convergence, limit and interchange theorems, and the asymptotics of maximum likelihood, generalized method of moments, and efficient method of moments. Fall. Gallant, Parke.
272 Econometrics
 
 
Prerequisite, Economics 271 or equivalent. One semester coverage of basic econometrics. Topics include: regression under ideal and nonideal conditions; special models, including simultaneous equations models; and applications and econometric computer programs. Spring. Guilkey, Mroz, Parke.
 
273 Advanced Econometrics
 
Prerequisites, Economics 271 and Mathematics 147. Economics 273 constitutes a one-semester treatment of the fundamental theory of econometrics. Topics covered include asymptotic distribution theory, linear and nonlinear models, specification testing techniques, and simultaneous equations models. Fall. Guilkey, Parke.
 
274 Time Series Econometrics
 
Prerequisite, Economics 273. Covers stationary univariate and multivariate time series models, spectral analysis methods, nonstationary models with time trends, unit roots and cointegration, and special topics such as conditional volatility, the Kalman filter and changes of regime. Spring. Gallant, Parke.
 
275 Nonlinear Econometric Methods
 
 
Prerequisite, Economics 273. Density estimation, nonparametric regression, neural nets, nonlinear regression, generalized method of moments, seminonparametric time series, estimating stochastic differential equations and nonlinear latent variables. Fall or Spring. Gallant.
 
276 Cross Sectional Econometrics
 
Prerequisite, Economics 273. Maximum likelihood methods for limited dependent variables. Longitudinal data models and methods. Hazard models. Multivariate models with limited dependent variables. Fall or Spring. Guilkey, Mroz.
 
371 Research in Econometrics
 
 
Prerequisites, Economics 273 and Economics 274, 275, or 276. Seminar on special topics in econometrics. Spring. Gallant, Guilkey, Parke.