Spatial Autocorrelation of a Demographic Phenomenon: a Case of One-Family Households and One-Person Households

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F20%3A10434292" target="_blank" >RIV/00216208:11310/20:10434292 - isvavai.cz</a>

Result on the web

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=spRqGW-oxX" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=spRqGW-oxX</a>

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

Spatial Autocorrelation of a Demographic Phenomenon: a Case of One-Family Households and One-Person Households

Original language description

In recent decades, household and family patterns have changed significantly. On one hand, one can notice a smaller number of children living in families, as well as a reduction of family numbers in general as a result of the low fertility rate and the postponement of childbearing in Europe. On the other hand, there has been a significant increase in the proportion of one-person households and families without children among people at an older age because of population ageing. The research question is to what extent these changes in the structure of households are spatially homogeneous and whether the proportion of households of a given type in a given territory can be explained by other demographic variables such as age, education, marital status or economic activity. The above-mentioned principles can be demonstrated by the example of data for households, whose detection and subsequent analysis is an integral part of population censuses. To solve this problem, it is possible to use spatial data analysis methods, which can be defined as a quantitative data analysis, in which the explanation is dependent on explicit spatial variables when predicting the investigated phenomenon based on spatial autocorrelation. The assumption of spatial regression is the existence of autocorrelation. The results of both Moran&apos;s I and Geary&apos;s C show that the autocorrelation for both types of households was found to be statistically significant and increases as the distance between adjacent elements (i.e. municipalities) decreases. Age is an important factor affecting the structure of households. The results for both types of households show that the age groups with the greatest influence on the creation of one-person households or one-family households can also be used to create a spatial model. A similar claim applies to the average age. Education showed that the share of persons with primary education has no influence on spatial regression, unlike the share of persons with secondary or university education. In the case of marital status, there is a statistically significant spatial regression for one-person households, but not clearly for one-family households. Economic activity or employment is statistically significant for simple regression even in a small territory such as the Czech Republic. For the solution, it is possible to use several types of models offered by (econometrics) theory. In the case of households, the spatial Durbin model (SDM) is relatively widely used, because of the inclusion of both endogenous and exogenous interaction effects, based on the criteria chosen (Log Likelihood, AIC, SBC). However, the results for other models (SAR, SEM, SDEM) are not significantly different.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

50402 - Demography

Project

<a href="/en/project/GA18-12166S" target="_blank" >GA18-12166S: Spatial differentiation and visualisation of geodemographic processes with a focus on households in an ageing society in the Czech Republic</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Statistika: Statistics and Economy Journal

ISSN

1804-8765

e-ISSN

—

Volume of the periodical

99

Issue of the periodical within the volume

4

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

17

Pages from-to

417-433

UT code for WoS article

000503979300006

EID of the result in the Scopus database

2-s2.0-85082049917