CMStatistics 2016: Start Registration
View Submission - CMStatistics
B1302
Title: Spatial weight matrix estimation and financial applications Authors:  Cheng Qian - London School of Economics and Political Science (United Kingdom) [presenting]
Abstract: Spatial econometrics focus on cross sectional interaction between physical or economic units. However, most of studies apply a prior knowledge about spatial weight matrix in spatial econometrics model. Therefore misspecification on spatial weight matrix could affect significantly accuracy of model estimation. An error upper bound for the spatial regression parameter estimators in a spatial autoregressive model has been recently provided, showing that misspecification can indeed introduce large bias in the final estimates. Meanwhile, new researches on spatial weight matrix estimation only consider static effects but not include dynamic effects between spatial units. Our model firstly use the different linear combinations of same spatial weight matrix specifications for different time-lag responds in proposed spatial econometrics model. Moveover, by introducing penalization on the coefficients of the linear combination of spatial weight matrix specifications, the best specification or the best linear combination of specifications for different lag spatial effect can be selected. To overcome endogeneity from autoregression, instrumental variables are introduced. The model we use can also find fixed effects and spillover effects. Finally, we also develop asymptotic normality for our estimation under the framwork of a previous functional dependence measure. The proposed methods are illustrated using both simulated and financial data.