Statistics Seminar（2014-02）

Topic:Non-Nested Testing of Spatial Correlation

Speaker:Peter M. Robinson, London School of Economics

Time:Wednesday, 25 March, 14:00-15:30

Location:Room 216, Guanghua Building 2

Abstract：We develop non-nested tests in a general spatial, spatio-temporal or panel data context. The spatial aspect can be interpreted quite generally, in either a geographical sense, or employing notions of economic distance, or even when parametric modelling arises in part from a common factor or other structure. In the former case, observations may be regularly-spaced across one or more dimensions, as is typical with much spatio-temporal data, or irregularly-spaced across all dimensions; both isotropic models and non-isotropic models can be considered, and a wide variety of correlation structures. In the second case, models involving spatial weight matrices are covered, such as "spatial autoregressive models". The setting is sufficiently general to potentially cover other parametric structures such as certain factor models, and vector-valued observations, and here our preliminary asymptotic theory for parameter estimates is of some independent value. The test statistic is based on a Gaussian pseudo-likelihood ratio, and is shown to have an asymptotic standard normal distribution under the null hypothesis that one of the two models is correct. A small Monte Carlo study of finite-sample performance is included.

About the speaker：Peter M. Robinson is the Tooke Professor of Economic Science and Statistics at the London School of Economics. He is an elected Fellow of the Econometric Society. Prof. Robinson has served as editor for Econometrica, Journal of Econometrics, and Econometric Theory, etc. He has also been the associate editor for Annals of Statistics, Journal of the American Statistical Association, Journal of Time Series Analysis, etc. Prof. Robinson's main research areas are time series analysis, spatial econometrics, estimation and inference in nonparametric and semiparametric models, etc. He has published around two hundreds academic articles and has made many fundational contributions in both the econometric and statistical research.