Which Progress for Poverty Studies can we expect from new large Data Sources?
AbstractLarge data sources would allow us to test the impact of neighborhood characteristics, such as poverty rates , on the attitudes and behavior ot residents. The article explores the feasibility of existing large date sets for such a purpose. Unfortunately, none of the three sets reviewed, the Microcensus, the ALLBUS and the SOUP, allows for such multi-level analyses, because data cannot be regionalized due to data protection or insufficient sample size. To overcome these problems in a limited sense, it is suggested to pursue a “puzzle strategy” to combine data from different existing data sets.
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Bibliographic InfoArticle provided by Duncker & Humblot, Berlin in its journal Schmollers Jahrbuch.
Volume (Year): 128 (2008)
Issue (Month): 1 ()
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Web page: http://www.duncker-humblot.de
Find related papers by JEL classification:
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
- C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
- I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
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