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

Version
1
Resource Type
Dataset
Creator
  • RWI
  • microm
Collective Title
  • RWI-GEO-GRID
Publication Date
2018-10-23
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:
    • Personal Income, Wealth, and Their Distributions (D31)
    • Regional Labor Markets, Population, Neighborhood Characteristics (R23)
Free Keywords
purchasing power; household income; raster data; RWI-GEO-Grid
Description
  • Abstract

    The purchasing power reflects the household income.  It comprises information on labour supply, capital wealth, rental and leasing income minus taxes and social security contributions, including social transfers such as unemployment benefits, child-allowances and pensions. Regular payments, e.g. for rent, electricity or insurance premiums are not subtracted from the purchasing power. Microm computes the purchasing power in cooperation with Michael Bauer Research GmbH. The computation is based on statistical models on a small regional scale. This allows for small-scale purchasing power information on the street segment and postcode (PLZ8) level. As explanatory variables for the econometric models, many microm variables are used, such as typology, age, status and the car variables. Due to persistent differences between East and West Germany, the purchasing power was modelled separately for both parts (microm 2016, p. 106).

Temporal Coverage
  • 2005
  • 2009
  • 2010
  • 2011
  • 2012
  • 2013
  • 2014
  • 2015
  • 2016
Geographic Coverage
  • Germany (DE)
Sampled Universe

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 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 (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.

Data and File Information
  • Unit Type: Geographic Unit
    Number of Units: 1515276
    Type of Data: Microdata
    • File Name: 107807_microm_kaufkraft_V7.dta"
      File Format: Stata
      File Size: 43849 KB
Note
Besides information on the purchasing power 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.
Availability
On-site
Rights
microm Micromarketing-Systeme und Consult GmbH
Relations
  • Continues
    DOI: 10.7807/microm:kaufkraft:v6 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:kinder:v7 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:pkwseg:suf:v7:1 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:pkwmarken:suf:v7:1 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:haustyp:v7 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:auslaender:v7 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:hstruktur:v7 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:alq: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:ethno:v7 (Dataset)
  • Is supplemented by
    DOI: 10.7807/microm:zahlindex:v7 (Dataset)
Publications
  • 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 & GEO. Neuss: microm GmbH, Neuss.

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

RWI; microm (2018): Sozioökonomische Daten auf Rasterebene (Welle 7). Kaufkraft. RWI-GEO-GRID. Version: 1. RWI – Leibniz-Institut für Wirtschaftsforschung. Dataset. https://doi.org/10.7807/microm:kaufkraft:v7