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Socio-economic data on grid level (SUF 6.1). Residents by age and gender

Version
1
Resource Type
Dataset
Creator
  • RWI
  • microm
Collective Title
  • RWI-GEO-GRID
Publication Date
2018-08-13
Publication Place
Essen
Contributor
  • 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)
Language
German
Classification
  • JEL:
    • Regional Labor Markets, Population, Neighborhood Characteristics (R23)
Free Keywords
population structure; age structure; population by gender; raster data; RWI-GEO-Grid; residents
Description
  • Abstract

    The gender and age structure indicates the share of residents in an area and can be differentiated with respect to sex and 17 age groups. Age between 20 and 75 is divided into categories of 5 years each to build the age groups. For the elderly, the group is “75 years and older”. For children, microm uses the following categories: infants and toddlers in the age range 0-3 years; kindergarteners of the age 3-6 years; primary school children (6-10 years), and middle school children (10-15 years). At 15, it is possible to finish general schooling and start a vocational training, or proceed with school and obtain a high school degree (Abitur). Individuals in this group constitute two further age groups, one ranging from 15-18 years and the other from 18-20 years (microm 2016, p. 42).The age groups are available as percentage shares of all residents in a raster cell. In addition, the absolute number of residents is available as a separate dataset which can be found under DOI 10.7807/microm:einwohner:suf:V5:1.

    For children, microm uses the following categories: infants and toddlers in the age range 0-3 years; kindergarteners of the age 3-6 years; primary school children (6-10 years), and middle school children (10-15 years). At 15, it is possible to finish general schooling and start a vocational training, or proceed with school and obtain a high school degree (Abitur). Individuals in this group constitute two further age groups, one ranging from 15-18 years and the other from 18-20 years (microm 2016, p. 42).

    The age groups are available as percentage shares of all inhabitants in a raster cell. In addition, the absolute number of inhabitants is available as a separate dataset which can be found under DOI 10.7807/microm:einwohner:suf:V6:1.

Temporal Coverage
  • 2005
  • 2009
  • 2010
  • 2011
  • 2012
  • 2013
  • 2014
  • 2015
Geographic Coverage
  • Germany (DE)
Sampled Universe

Microm uses more than a billion individual data points for the aggregation of the microm dataset. These are anonymised and stem from various data sources. The data points 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).

Time Dimension
  • Cross-section
Collection Mode
  • 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 (including those purely used for business), and number of residential houses (excluding 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.

Data and File Information
  • Unit Type: Geographic Unit
    Number of Units: 1515276
    Number of Variables: 40
    Type of Data: Microdata
    • File Name: 107807_microm_einwGeAl_suf_V6-1.dta
      File Format: Stata
      File Size: 430657 KB
Note
Besides information on the population shares by age and gender, the dataset contains the geographical key of the raster point as well as the variables of the group microm-Basis. These variables are data provided for scientific use by the FDZ Ruhr at RWI. Data on such a small regional scale (1km²) is not collected directly for all parts of Germany, which makes this dataset a valuable addition for small-scale regional analyses. A basic description on the data collection of the individual variables is found in the microm handbook (microm 2016). Details on the data generation are not publicly available, however the procedure of collecting particular data is known (cf. procedure of data collection). Screenings of the FDZ Ruhr do not indicate issues with data quality. The scientific use file described here differs from the original data only in its degree of anonymisation: If the variables on residents and households exhibit less than 20 observations in a square kilometre, they are not contained. In addition, purchasing power, and number of children are anonymised if there are less than 20 observations in a square kilometre.
Availability
Delivery
Rights
microm Micromarketing-Systeme und Consult GmbH
Relations
  • Is supplemented by
    DOI: 10.7807/microm:hstruktur:suf:v6:1 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:pkwseg:suf:v6:1 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:kaufkraft:suf:v6:1 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:pkwmarken:suf:v6:1 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:auslaender:suf:v6:1 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:haustyp:suf:v6:1 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:alq:suf:v6:1 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:kinder:suf:v6:1 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:einwohner:suf:v6:1 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:ethno:suf:v6:1 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:zahlindex:suf:v6:1 (Dataset)
  • Continues
    DOI: 10.7807/microm:einwGeAl:suf:V5:1 (Dataset)
  • Is variant form of
    DOI: 10.7807/microm:einwGeAl:V6 (Dataset)
Publications
  • microm Consumer Marketing (2016), Datenhandbuch: Arbeitsunterlagen für microm MARKET & GEO. Neuss: microm GmbH, Neuss.

  • 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)

Update Metadata: 2019-03-18 | Issue Number: 1 | Registration Date: 2019-03-18

RWI; microm (2018): Sozioökonomische Daten auf Rasterebene (SUF 6.1). Einwohner nach Geschlecht und Alter. RWI-GEO-GRID. Version: 1. RWI – Leibniz-Institut für Wirtschaftsforschung. Dataset. https://doi.org/10.7807/microm:einwGeAl:suf:V6:1