An Analytical Paradigm for the Analysis of National Inmigration Patterns

Bibliographic Data

ID9953516
AuthorsY Weisberg (Bar-Ilan University, corresponding author), A Solomon Eaglstein
Year1988
Volume26
Issue3
Pages253-266
Publication date1988-07-01
Open AccessYes
TypeARTICLE
VenueInternational Migration (JOURNAL)
Journal identifiersISSN: 0020-7985 • E-ISSN: 1468-2435
PublisherWiley (PUBLISHER • GB)
DOI10.1111/j.1468-2435.1988.tb00648.x
PMID12342067
OpenAlexW1992076008
LanguageEN
Citations received2
References cited10

This study proposes and demonstrates an analytic paradigm based upon a substantive categorization of a set of inmigration correlates. It exemplifies the notion of categorizing, analyzing according to the categorization, and subsequently discussing the phenomenon in more depth. The paradigm has 2 steps: 1) the variables are categorized according to the cells resulting from the intersection of a preferably small number of nominal dimensions and 2) the data are analyzed, directly anchored in the prior categorization. The data used is Israel's 1983 census macro-data gathered from the Central Bureau of Statistics for the Israeli towns with populations of at least 5000. The authors defined 6 variables as push variables and 4 as pull variables. Results of the regression employing push variables show that 4 variables accounting for 72% of inmigration were found to significantly predict inmigration: 1) unemployment, 2) percentage of Asians-Africans, 3) town size, and 4) religiosity. Within the pull classification, the regression analysis reveals that 2 of the 4 variables explain 31% of the inmigration variance: 1) educational level (26%) and 2) income (5%). The 1st regression analysis on the 2nd dimension shows that the percentage of Asian-African origin and town population size account for 32% of the immigration variance. In the 2nd regression analysis, unemployment explains 48% of the inmigration variance and educational level explains 8%. In the 3rd regression, only home crowding explains a significant amount of the immigration variance (19%). Results of a multiple regression analysis show that unemployment level, percentage of Asian-Africans, population size, and level of religiosity account for 72% of the inmigration variance. Thus, the characteristics of a town inmigrating (push variables) are demographic, economic, and social. However, the attractive features of a town are only economic. Among all economic factors, unemployment is primary. In addition, not only are both percentage of Asians-Africans and population size significantly deflective of inmigration, but each also plays a separate and independent role

Categorization · Demographic economics · Dimension (graph theory · Econometrics · Economic growth · Economics · Explained variation · Population · Regression · Regression analysis · Religiosity · Sociology · Statistics · Unemployment · Variables · Variance (accounting · Computer Science · Demography · Mathematics · Migration and Labor Dynamics · Migration, Ethnicity, and Economy · Psychology · Social Psychology · Urban, Neighborhood, and Segregation Studies

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