| Summary: | The paper investigates the importance of spatial scale for changes in earnings at the workplace by using spatial regression applied to workplace-level micro data in an exploratory purpose. A floating grid technique is used to define equal-sized workplaces and their daily-reach surrounding zones as divided into three spatial entities: working-square, local area and hinterland. On the basis of geo-referenced information on workplaces and places of residence along with numerous individual-level socio-economic indicators, the results of the regression models reveal that the indicators of the daily-reach area play a dominant role and that their contribution varies over spatial entities. Among the spatial entities, the working-square (km square) surrounding the workplace is more important than the workplace itself, the local area and the hinterland. Moreover, the results suggest that internal factors related to population size, diversity of trade and industry and educational level contribute to about one-third of changes in work income at the workplace level. It can be concluded that knowledge, learning and human capital are strongly associated with increased earnings.
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