Socio-economic data on grid level (Wave 7). Ethno

• RWI
• microm

• RWI-GEO-GRID

• Budde, Rüdiger (RWI – Leibniz-Institut für Wirtschaftsforschung) (Contact Person)
• Eilers, Lea (RWI – Leibniz-Institut für Wirtschaftsforschung) (Researcher)
• microm Micromarketing-Systeme und Consult GmbH (Data Collector)
• RWI – Leibniz-Institut für Wirtschaftsforschung (Editor)

• JEL:
  • International Migration (F22)
  • Economics of Minorities, Races, Indigenous Peoples, and Immigrants, Non-labor Discrimination (J15)
  • Regional Labor Markets, Population, Neighborhood Characteristics (R23)

• Abstract

  The variable group ethno is based an analysis of fore- and surnames with respect to their linguistic origin. The evaluation is based on lists of names and their origin, which are supplemented by international name roll of names. It only considers the head of the households. Thus, this does not allow for conclusions about the actual number of persons with a foreign origin, how long the individuals have already been Germany, and how strong the social integration is. For the variable ethno the following linguistic origins can be formed: Turkey, Italy, Greece, Span/Portugal/Latin America, ethnic German repatriates (Spätaussiedler) from the former Soviet Union, Eastern Europe, the Balkans, Africa south of the Sahara, non-European Islamic states, South-, East- and Southeast-Asia (microm 2016, p. 40). This variable group is originally calculated on the “8-digit postcode” (PLZ8) level and is disaggregated to the raster used by this dataset (mircom 2016, p. 40).

• 2005
• 2009
• 2010
• 2011
• 2012
• 2013
• 2014
• 2015
• 2016

• Germany (DE)

Microm uses more than a billion individual datapoints for the aggregation of the microm dataset. These are anonymised and stem from various data sources. The datata points are are available for all 40.9 million households in Germany, while the final data product contains information on approximately 20 million houses (microm 2016, p. 8).

• Cross-section

• Other
  For data privacy reasons, houses within a residential environment are summed up to a "virtual" micro-geographic segment (so-called micro-cell), which on average comprises eight, but at least five households. Houses in which at least five households live become a distinct micro-cell, while houses with less than five households are combined with similar houses on the same street. Combined houses are as close as possible in spatial terms. Structural indicators are aggregated on the micro cell level and subsequently computed household level averages are computed (microm 2016, p.8). If such data exist, the calculated data is made consistent with official data sources (microm 2014, p. 2). Additionally, due to the cooperation with SOEP, it is possible to validate the small-scale regional data of microm (microm 2016, p. 8). The dataset is based on the variable group microm-Basis which is comprised of four categories: number of households, number of business enterprises, number of houses (incl. those purely used for business), and number of residential houses (excl. those purely used for business) (cf. microm 2016, p. 26). The number of houses on the street segment level is the basis for all aggregations to other regional levels. Based on business registers, the number of enterprises in each house is determined.

• Unit Type: Geographic Unit
  Number of Units: 1515276
  Number of Variables: 18
  Type of Data: Microdata
  
  • File Name: 107807_microm_ethno_V7.dta
    File Format: Stata
    File Size: 219241 KB
    

• Continues
  DOI: 10.7807/microm:ethno:V6 (Dataset)
  
• Is supplemented by
  DOI: 10.7807/microm:hstruktur:v7 (Dataset)
  
• Is supplemented by
  DOI: 10.7807/microm:pkwseg:suf:v7:1 (Dataset)
  
• Is supplemented by
  DOI: 10.7807/microm:kaufkraft:v7 (Dataset)
  
• Is supplemented by
  DOI: 10.7807/microm:pkwmarken:suf:v7:1 (Dataset)
  
• Is supplemented by
  DOI: 10.7807/microm:auslaender:v7 (Dataset)
  
• Is supplemented by
  DOI: 10.7807/microm:haustyp:v7 (Dataset)
  
• Is supplemented by
  DOI: 10.7807/microm:kinder:v7 (Dataset)
  
• Is supplemented by
  DOI: 10.7807/microm:einwohner:v7 (Dataset)
  
• Is supplemented by
  DOI: 10.7807/microm:einwGeAl:v7 (Dataset)
  
• Is supplemented by
  DOI: 10.7807/microm:alq:v7 (Dataset)
  
• Is supplemented by
  DOI: 10.7807/microm:zahlindex:v7 (Dataset)
  

• Budde, R.; Eilers, L. (2014): Sozioökonomische Daten auf Rasterebene – Datenbeschreibung der microm-Rasterdaten. RWI Materialien 077. Essen: RWI.

  • ID: http://hdl.handle.net/10419/97627 (Handle)

• Bauer, T. K.; Budde, R.; Micheli, M.; Neumann, U. (2015): Immobilienmarkteffekte des Emscherumbaus? Raumforschung und Raumordnung 73(4): 269-283.

  • ID: 10.1007/s13147-015-0356-5 (DOI)

• Hentschker, C., and A. Wübker (2016). The impact of technology diffusion in health care markets: Evidence from heart attack treatment. Ruhr Economic Papers #632. Essen: RWI.

  • ID: 10.4419/86788734 (DOI)

• microm Consumer Marketing (2016), Datenhandbuch: Arbeitsunterlagen für microm MARKET amp; GEO. Neuss: microm GmbH, Neuss.