SPATIAL ECONOMETRICS ADVANCED INSTITUTE
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The number of participants admitted is from a minimum of 20 to a maximum of 30.
Acceptance of students not attending the full course is conditional upon availability of places after all full-time students have been accepted. Fees include the subscription to the Spatial Econometrics Association, attendance to the courses and tutorship for the entire period, free access to the Mensa of the university, but exclude other living expenses and accommodation (for more information go to: location)
Deadlines and timetable
A degree (at least three years) either in economics, mathematics, statistics, quantitative geography, regional planning or similar. A mathematical background is strongly recommended. In particular it is assumed that the candidate has the essential basis in calculus, probability, statistics and econometrics. Students will be provided with precise textbook references for those that do not possess the pre-requisites (see below). Upon demand a pre-course on econometrics and R will take place the week before the starting of the courses.
Probability - Probability theory. Random variables, stochastic independence, conditional expectations and martingales. Stochastic processes. Markov processes. Stationary processes. Reference: G.R. Grimmett and D.R. Strizaker (2001) Probability and Random Processes, 3rd ed.
Statistics - Statistical inference. Likelihood, the general principles of inference (sufficiency, conditionality, invariance). Theory of point estimation (Fisher information and efficiency of estimators, properties of Maximum Likelihood Estimators, and Bayesian point estimators), interval estimation and hypothesis testing. The three tests based on likelihood. Pseudo Maximum Likelihood Estimation. References: Casella and R. L. Berger (2002) Statistical Inference, Second Edition, Duxbury Press, (CB); Davidson A. C. Statistical models, Cambridge university press; Pace L. and Salvan A. (1997) Principles of statistical inference from a neo-fisherian perspective, World Scientific; Young G.A., Smith R.L., (2005) Essentials of statistical inference, Cambridge, Cambridge University Press.
Econometrics - Linear Regression Model, the OLS estimator and the violation of the Gauss-Markov hypotheses. The generalized linear model, Instrumental variable estimation, non linear least squares, 2SLS. References: Davidson, R. and J. MacKinnon (1993): Estimation and Inference in Econometrics, Oxford University Press, Oxford. Greene, W. (2003): Econometric Analysis , Third Edition, Prentice Hall, Englewood Cliffs. Gouriéroux, C., and A. Monfort (1995): Statistics and Econometric Models, Volumes I and II, Cambridge University Press, Cambridge.
R and STATA - Participants to the SEAI are supposed to have basic practical experiences in R and some knowledge of STATA (http://www.stata.com). The R software and the introductory manual may be downloaded from http://www.r-project.org/.
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