其他摘要：Heterogeneity of local conditions and spatial dependencies are typical aspects of sociological phenomena. However, large-scale empirical data is often rather limited with regard to the spatial references that are (publicly) available to researchers. We describe several aspects of the problem and assess possibilities and potential errors associated with limited information. Our examples are returns to education and gender-based and migration-related wage gaps as popular research topics. We base our analyses upon widely used survey data from Germany, the GSOEP, which contains geographical information on various levels of aggregation. Our particular interest is in the decisions that have to be made with regard to problems of space and place in standard surveys, available options and consequences. We conclude with a number of practical suggestions for data users.
其他关键词：spatial analysis;survey data;GIS;multi-level model;spatial regression;territorial classification;returns to education;wage gap;labor market;GSOEP
