Course ObjectiveThis course introduces students to advanced econometric theory and
methods. Students will be guided through the frontier of econometric
theory and become familiar with state-of–the-art econometric models and
By the end of this course, participants will:
(1) have gained a profound and detailed understanding of advanced
econometric theory and methods;
(2) know how to design, estimate and analyze complex nonlinear dynamic
(3) have solved advanced theoretical and practical econometric
(4) understand the interplay between econometric techniques and modeling
(5) understand the proofs of asymptotic properties of important
estimators and test statistics.
Course ContentThis course covers both theoretical and practical aspects of complex
dynamic econometric models that are used in the industry, by central
banks, governments, think tanks, and other research institutes.
The students will be introduced to stochastic theory that allows them to
fully understand the dynamic properties of complex models featuring
nonlinearities, time-varying parameters and latent variables. Important
concepts include invertibility, stationarity, dependence, ergodicity and
The students will also be introduced to advanced estimation theory that
allows them to bring state-of-the-art models to the data and conduct
inference on parameters under very general conditions. Important topics
include the existence, measurability, consistency and asymptotic
normality of extremum, M and Z estimators. We also cover advanced topics
in nonlinear model selection and specification, estimation and inference
under incorrect specification, metric selection, structure and causality
From a practical perspective, the advanced methods and state-of-the-art
models are used for forecasting and policy analysis in a wide number of
applications ranging from finance to macroeconomics and data science.
Teaching MethodsLectures and tutorials
Method of AssessmentFinal exam and group assignment with Individual assessment.
LiteratureLecture notes on "Advanced Econometrics" written by the lecturer F.
Davidson J., "Econometric Theory", Blackwell Publishing, 2000.
van der Vaart A., "Asymptotic Statistics". Cambridge Series in
and Probabilistic Mathematics. Cambridge University Press, 2000.
White H., "Estimation, Inference and Specication Analysis". Econometrics
Society Monographs, 1996.
Lütkepohl H., "New Introduction to Multiple Time Series Analysis",
Hamilton J. D., "Time Series Analysis", Princeton University Press.
Davidson J., "Stochastic Limit Theory". Advanced Texts in Econometrics,
Oxford University Press, 1994.
B. Potscher and I.R. Prucha, "Dynamic Nonlinear Econometric Models:
Asymptotic Theory". Springer-Verlag, 1997.
R. Gallant and H. White, "A Uni
ed Theory of Estimation and Inference
for Nonlinear Dynamic Models", Basil Blackwell Ltd., Oxford, 1987.
Hansen, B E, Econometrics. Manuscript, University of Wisconsin.2009.
Current URL: www.ssc.wisc.edu/~bhansen/econometrics/
Recommended background knowledgeThis course presumes that students are familiar with basic probability
The theory and practice behind the simple linear
regression model should be well understood. Furthermore, the students
should have been introduced to time-series analysis. In particular, the
concept of stationarity and ARMA models should be familiar.
|Language of Tuition||English|
|Faculty||School of Business and Economics|
|Course Coordinator||dr. F. Blasques Albergaria Amaral|
|Examiner||dr. F. Blasques Albergaria Amaral|
dr. F. Blasques Albergaria Amaral
You need to register for this course yourself
|Teaching Methods||Lecture, Study Group|
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