APPLIED ECONOMETRICS

at the

Department of Agricultural & Resource Economics

University of California, Berkeley

 

Subject

Applied Econometrics is concerned with providing a basis for reasoning and learning from samples of economic data. To provide a basis for processing and recovering information from samples of economic data applied econometrics is grounded in probability theory and the principles of estimation and statistical inference. Applied Econometrics, like economic theory, is basic to the pursuit of knowledge in the various subject areas of Agriculture and Resource Economics. Consequently, an applied econometrics component is encouraged in the course and research program of every student.  From a historical perspective, econometrics was started on the Berkeley campus by ARE faculty in the 1940's.  Building on this legacy, a vigorous teaching and research program in Applied Econometrics evolved and this field emphasis continues today.

 

Faculty

The focus of research in Applied Econometrics is on developing a new basis for estimation and inference and with sorting out problems with existing econometric tools and in developing methods that may be used in analyzing real economic-ecological problems. The list of faculty in this area and their research interests are listed below.

Maximilian Auffhammer :

Forecasting, time series analysis, spatial modelling, zero-inflated models. Applications of econometrics to environmental and natural resource problems in the developing country context.

Jeffrey LaFrance:

Producer and consumer choice models, information theory and entropy econometrics, and time series analysis.

Michael L. Anderson:

Applied econometrics, with particular emphasis on causality and the evaluation of social programs.

George Judge :

Improved methods of estimation and inference, recovering information from ill posed underdetermined inverse problems, combining estimation problems and ecological inference

Ethan Ligon

Cross-sectional dependence, with applications involving the provision of incentives and the sharing of risk.

Jeffrey Perloff :

Developing new maximum entropy procedures; applying econometrics to labor and industrial organization problems.

Gordon Rausser :

Financial econometric applications to contract markets (futures, forwards, and derivatives), and econometric applications to political causal mechanisms.

Sofia Villas-Boas:

Applied Econometrics, multi-category discrete choice modelling.

Arnold Zellner:

(Adjunct Professor, teaches a Bayesian Econometrics course at ARE each spring semester)

Bayesian inference.

The faculty noted above are actively involved in research in the theory and practice of econometrics and in working with students regarding the quantitative aspects of their research problems. In fact virtually all of the faculty in the department are applied econometricians and are keenly aware of the role of applied econometrics in the teaching, learning and research process. Building on the departmental base in applied econometrics, there is a world class group of econometricians in the economics department that have a natural interest in Applied Econometrics.

Information Theoretic, Maximum Entropy and Empirical Likelihood Methods

The faculty in ARE have played a leading role in developing and applying Information Theoretic Methods to econometric problems. In particular they have demonstrated the usefulness of the maximum entropy principle and the empirical likelihood method to a range of measurement problems encountered in economics. These semi-nonparametric formulations that are often likelihood-based, permit the joint distribution of the economic data to be unspecified apart from a finite set of moment conditions or conditional moments. Some of the contributions of the ARE faculty to these areas are listed under the topics of Maximum Entropy Econometrics, Empirical Likelihood Methods, Bayesian Method of Moments.

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Copyright 2006, UC Regents, Please send comments or questions about this site to Sofia B. Villas-Boas.
Last Edited: Spring 2007