Spatial Regression Models Estimation for the poverty Rates In the districts of Iraq in 2012 - هادي سوسن قاسم; علي عمر عبد المحسن (Journal of Economics and Administrative Sciences, 2014)
The research took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide practical evidence that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial and that includes all of the spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. The spatial analysis had been applied to Iraq Household Socio-Economic Survey: IHSES 2012. To measure the preference models used in the research was the use of such standards compared: Root Mean Squares Error: RMSE, Mean Absolute Percentage Error: MAPE and, and Adjusted determinant coefficient: with different weight matrices (binary and modified) take into account the effect of neighborhoods of districts.