PROGRAM (click here to download an updated version of the schedule)

Week I (16th-20th May)

Theoretical Spatial Economics (9 hours) - J.H.P. Paelinck, George Mason University, Fairfax, Viginia.
As not all of the potential students would have attended a class in theoretical spatial economics, this course would allow the group to get familiarized with essential theoretical notions. These would include: the structures of TSE, various distances, equilibria (comprising Tinbergen-Bos Systems), location theory, spatial pricing, spatial input-output analysis, shopping models and spatial dynamics. References: Paelinck, J.H.P. and Nijkamp, P., (1975) Operational Theory and Method in Regional Economics, Saxon House, Farnborough. Paelinck, J.H.P., with the assistance of J.‑P. Ancot and J.H. Kuiper, (1977) Formal Spatial Economic Analysis, Gower Press, Aldershot. Paelinck, J.H.P., avec le concours de J.-P. Ancot, J.H. Kuiper et M. ten Raa, (1985) Eléments d'Analyse Economique Spatiale, Editions Régionales Européennes, Genève, et Editions Anthropos, Paris. Other, more recent material, will be made available.

Spatial Statistics (11 hours) - G. Arbia, University “G. D’Annunzio” of Chieti.
Point processes theory (complete spatial randomness, distance methods, k-functions), multivariate point processes, marked point processes, space-time point patterns. Random fields theory, conditional and simultaneous Gaussian fields, Markov random fields, non Markov random fields, dynamic fields, separable and non-separable space-time models. Stationary processes on a continuous space: variogram and co-variogram, the spectral representation, spatial prediction and krieging. References: Banerjee, S., Carlin, B. P., and Gelfand, A. E. (2004). Hierarchical Modeling and Analysis for Spatial Data. Chapman & Hall/CRC, Boca Raton, FL. Cressie, N (1993) Statistics for spatial data, Wiley. Diggle, P.J. (2003). Statistical Analysis of Spatial Point Patterns (second edition). London: Edward Arnold. Diggle, P.J. and Ribeiro, P.J. Jnr (2007). Model-based Geostatistics. New York: Springer. Guyon X. (1995) Random fields on a network: modeling, statistics, and applications, Springer Verlag. Haining R P (2001) Spatial Data Analysis: Theory and Practice, Cambridge University Press.

Week II (23rd-27th May)

Spatial econometrics I (15 hours) - Harry H. Kelejian, University of Maryland, College Park, Maryland.
Elements of large sample theory, single equation Cliff-Ord type models and variations, illustrations, specification, weighting matrix and parameter space issues, estimation including MLE, GMM, GLS, GS2SLS, large sample results and corresponding inferences, emanating and self feedback effects implied by the models, various estimation problems including border issues, uniform weights, and parameterized weighting matrices, a spatial J-Test of specifications. References: Anselin, L. (1988), Spatial Econometrics: Methods and Models. Boston: Kluwer Academic Publishers; Arbia, G. (2006), Spatial Econometrics: Statistical Foundations and Applications to Regional Growth Convergence, New York: Springer; Cliff, A. and Ord, J. (1981), Spatial Processes, Models and Applications. London: Pion; Cressie, N.A.C. (1993), Statistics of Spatial Data. New York: Wiley; Green, W. (2003), Econometric Analysis, Englewood Cliffs: Prentice Hall.

Week III (30th May - 3rd June)

Spatial econometrics II (15 hours) - Ingmar Prucha, University of Maryland, College Park, Maryland.
Further discussion of single equation Cliff-Ord type models, efficient instruments and best GS2SLS, prediction, estimation in case of heteroskedastic innovations by MLE, GMM, GS2SLS, large and small sample results. Simultaneous equation Cliff-Ord type models, estimation theory for limited and full information estimators. Spatial HAC variance covariance matrix estimation. Testing for spatial dependence, classical Moran I test and extensions. Recent developments towards estimation theory for nonlinear models, if time permits. References: Anselin, L. (1988), Spatial Econometrics: Methods and Models. Boston: Kluwer Academic Publishers; Arbia, G. (2006), Spatial Econometrics: Statistical Foundations and Applications to Regional Growth Convergence, New York: Springer; Cliff, A. and Ord, J. (1981), Spatial Processes, Models and Applications. London: Pion; Cressie, N.A.C. (1993), Statistics of Spatial Data. New York: Wiley; Green, W. (2003), Econometric Analysis, Englewood Cliffs: Prentice Hall; articles.

Week IV (6th-10th June)

Panel data (15 hours) - Badi H. Baltagi, Syracuse University, Syracuse, New York.
Panel data models: fixed effects and random effects. Temporal Heterogeneity. Spatial Seemingly Unrelated Regressions. Spatio-Temporal Models. Error Components with Space-Time Dependence. Specification of spatial panel models. Estimation of Spatial Panel Models: Maximum Likelihood Estimation, Instrumental Variables and GMM. Testing for spatial dependence in spatial panels. References: Anselin, L., Le Gallo, J., and Jayet, J. (2007) Spatial Panel Econometrics, In L. Matyas and P. Sevestre (Eds.), The Econometrics of Panel Data, Fundamentals and Recent Developments in Theory and Practice (3rd Edition). Dordrecht, Kluwer. Baltagi, B. H. (2005). Econometric Analysis of Panel Data. John Wiley & Sons, Chichester, United Kingdom. Baltagi, B. H., Song, Seuck H., and Koh, W. (2003b). Testing panel data regression models with spatial error correlation. Journal of Econometrics, 117:123–150. It is required that all students have a copy of the book: Baltagi, 2005.

Computer labs:

Practical experiences in spatial statistics using the R software (17th-19th May) - D. Giuliani (8 hours).

Practical experiences in spatial econometrics using the R software (23rd-27th May, 2nd-10th June) - R. Bivand (24 hours). Handling and visualizing spatial data, Spatial point pattern analysis, Geostatistics and interpolation, Basic aspatial econometrics, Creating spatial weights and tests for spatial autocorrelation, Basic spatial econometrics: ML estimation, Basic spatial econometrics: GMM, S2SLS and GS2SLS estimation, Measures of impact: Monte Carlo tests, Calculating the Jacobian in ML estimation, Fitting spatial HAC models, Fitting panel models, Fitting spatial panel models References: Bivand, R. S., Pebesma, E. J., and Gómez-Rubio, V. (2008) Applied Spatial Data Analysis with R. Springer. Elhorst, J. P., (2010) Applied Spatial Econometrics: Raising the Bar. Spatial Economic Analysis 5, pp. 9-28. Gaetan, C., and Guyon, X. (2010) Spatial Statistics and Modeling. Springer. LeSage, J., and Pace, R. K. (2009) Introduction to Spatial Econometrics. CRC Press. Millo, G., and Croissant, Y. (2008) Panel Data Econometrics in R: The plm Package. Journal of Statistical Software, 27, jstatsoft. Piras, G., (2010) sphet: Spatial Models with Heteroskedastic Innovations in R. Journal of Statistical Software, 35, jstatsoft.

Practical experiences in spatial econometrics using the STATA software (30th May - 1st June) - D. Drukker (6 hours).

Seminars on spatial topics by Bill Greene and Hashem Pesaran

William Greene (23rd May) - Discrete choices in space -

Hashem Pesaran (1st June) - Diffusion of house prices in the UK -

For more information: arbia@unich.it

Via del Castro Laurenziano 9, 00161 – Roma. Tel. +39 06 49766778; Fax +39 06 4957606