Abstract
Classical panel studies, such as the German Socio-Economic Panel (GSOEP), the US Panel Study of Income Dynamics (PSID), and the British Household Panel Study (BHPS), are based either on households or persons in households. Any attempts to break down such data into smaller spatial units such as neighbourhoods, due migration and changes in a specific sample can only be described by the stayers and the out-movers. With the exception of new members in stayer households, there is no information on households moving into a given neighbourhood. Consequently, when using classical panel data, it is not possible to analyse appropriately changes in small areas.
In order to solve the problem of population changes in small spatial units such as neighbourhoods, we recommend using an alternative sampling unit: instead of households, we suggest focusing on dwellings and houses. The dwelling panel allows us to examine processes, such as gentrification, poverty and voting behaviour in small urban areas.
Drawing on an ongoing study, we shall discuss methodological issues and show how a dwelling panel can be constructed and maintained in several waves. In the process, we shall discuss panel attrition and compare possible replacement strategies in classical panels with those in dwelling panels.
Zusammenfassung
Klassische Panelstudien wie das deutsche Sozio-ökonomische Panel (SOEP), die US-amerikanische Panel Study Income Dynamics (PSID) und die British Household Panel Study (BHPS) haben als Zielpersonen Haushalte oder Personen in Haushalten. Ist man an kleinräumlichen Einheiten, z. B. Wohnvierteln, interessiert, können Veränderungen über die Zeit nur über die fortgezogenen und die verbliebenen Haushalte bzw. Personen beschrieben werden. Abgesehen von neuen Haushaltsmitgliedern, die in bestehende Haushalte einziehen, gibt es keine Information über diejenigen Haushalte, die in diese Wohnviertel einziehen. Wendet man klassische Panelstudien an, ist es daher nicht möglich, Veränderungen im Wohnviertel angemessen zu analysieren.
Um dieses Problem der Veränderungen in kleinräumlichen Einheiten zu beschreiben, schlagen wir als Alternative eine neue Untersuchungseinheit vor: anstelle von Haushalten die Wohnung (oder das Einfamilienhaus) zu verwenden. Das Wohnungspanel gestattet es, kleinräumliche städtische Prozesse zu untersuchen, z. B. Gentrification, Armut oder Wahlverhalten.
Am Beispiel einer laufenden Studie stellen wir die methodischen Annahmen dar und zeigen, wie ein Wohnungspanel konstruiert werden kann, das über mehrere Wellen läuft. Dabei diskutieren wir auch Panelausfälle und vergleichen mögliche Strategien, diese Ausfälle im klassischen und im Wohnungspanel zu ersetzen.
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Notes
Both MTO and HOPE VI are field experiments which relocate households from poor to less poor or non-poor neighbourhoods by random assignment. The aim of both panel studies was to explore the effects on households moving into better neighbourhoods with a variety of outcomes, e.g., employment, income, school achievement, etc. MTO (1994–2010) was composed of households in Baltimore, Boston, Chicago, Los Angeles and New York. HOPE VI (1992–2002) comprised grants from the US Department of Housing (HUD) to distressed areas in 165 cities.
See www.neighbourhood.statistics.gov.uk; retrieved April 2, 2015.
To the best of our knowledge, the only survey that comes closest to our dwelling panel is the New York City Housing and Vacancy Survey (NYCHVS). The survey is conducted every 3rd year and comprises 19,000 “housing units”. But these are not fully identical in each wave; it is, therefore, not a panel in the strict sense (see www.census.gov/housing/nychvs/; retrieved April 20, 2015).
See http://psidonline.isr.umich.edu/; retrieved March 10, 2015.
In case of sub-renters not listed on the bell-board, they cannot be identified in the first wave—unless s/he is in the random sample.
We discussed applying the next (last) birthday method as proposed in AAPOR (2007). However, we are aware that this instruction is hard to implement for an interviewer; furthermore, in face-to-face interviews it is almost impossible to establish whether the interviewers have complied with this instruction. In Germany, at least, the date of birth is considered sensitive information related to data security issues and people will not necessarily understand what this information is for. To start with, this question would increase the number of refusals, either because people simply do not want to answer certain questions and therefore refuse to participate, or because the eligible person is not at home at the time of contact. Furthermore, many interviewees who had participated refused to answer control questions of this nature on the telephone to an anonymous person from an institute, and finally, there might be a change in the “next birthday” in the time period between the interview and the control call (cf. Blasius/Thiessen 2013).
The Schelling model simulates spatial segregation processes. It consists of a checkerboard with, for instance, 35 white and 20 black households randomly distributed over the 64 squares. By setting preferences for both groups on the number of households with the same ethnicity they desire as neighbours (adjacent squares), households are moved on the checkerboard, which results in an unanticipatedly high spatial segregation among both groups.
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Friedrichs, J., Blasius, J. The Dwelling Panel – A New Research Method for Studying Urban Change. Raumforsch Raumordn 73, 377–388 (2015). https://doi.org/10.1007/s13147-015-0369-0
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DOI: https://doi.org/10.1007/s13147-015-0369-0