Wim Jansen

Patterns and trends in occupational attainment of first jobs in the Netherlands, 1930-1995: ordinary least squares regression versus conditional multinomial logistic regression

Summary. This paper brings together the virtues of linear regression models for status attainment models formulated by second-generation social mobility researchers and the strengths of log-linear models formulated by third-generation researchers, into fourth-generation social mobility models, by using conditional multinomial logistic regression (CMLR). These CMLR models are capable of capturing the discrete and multidimensional nature of social mobility patterns (a characteristic of third-generation output) while reducing the number of parameters leading to parsimonious models (a characteristic of second-generation output). Using data from eight pooled surveys in the Netherlands, an extended Blau–Duncan status attainment model is formulated and analysed.The corresponding CMLR model is formulated incorporating general and specific inheritance effects.The final CMLR model gives a relatively parsimonious description of Dutch mobility patterns, similar to the extended Blau–Duncan model, at the same time offering the possibility of including specific effects where necessary. Effects of gender and education appear to be too complex to be captured by a single parameter.

Using covariates in loglinear models with sampling zeros; a cautionary note

Abstract When analyzing loglinear models, most computer packages will first construct the contingency table and subsequently fit the required loglinear model. Some computer packages allow the incorporation of covariates, such as age and/or income, into the loglinear model. In the SPSS modules LOGLINEAR and GENLOG this option is implemented by calculating for each pattern of the classifying variables the mean value(s) of the covariate(s), while this covariate vector is subsequently added to the design matrix describing the loglinear model. In this article it is shown that the use of covariates in the case of contingency tables containing sampling zeros will lead to incorrect results for the SPSS modules LOGLINEAR and GENLOG. Parameter estimates, deviances and the number of degrees of freedom may be highly incorrect. This is illustrated in the case of the loglinear uniform association model, using an example from a handbook on categorical data analysis. A second, more complex example is discussed where, as a result of this incorrect handling of covariates, wrong results have been published in the literature. It is concluded that (conditional) multinomial logit models should be used. While SPSS currently does not include such models, it is demonstrated how to obtain correct results for the case that covariates are functions of the classifying variables.

SELF-EMPLOYMENT IN POST-COMMUNIST ECONOMIES

ABSTRACT According to the market transition theory the economic success of individuals in post-communist countries is affected by both individual characteristics and structural contexts. We investigate this claim using data on self-employment in four post-communist countries (Bulgaria, Russia, Estonia and Hungary) in 1996 and 2005. We find support for a relationship between context-characteristics and self-employment; especially countries with lower levels of corruption show higher odds of self-employment. Unexpectedly, as the transformation process proceeded, human capital did not become a more important predictor for self-employment.

A class of models for the simultaneous analysis of square contingency tables.

A class of models is presented for the analysis of square contingency tables. The models fall in the class of loglinear models or models with logbilinear terms for the association. The models in this class differ in three ways: 1. the association is either assumed to be symmetric or asymmetric 2. the association is assumed to be completely different in each subtable, to have the same form but having different strength, or to be the same and having the same strength 3. for each subtable separately the association that is proposed is full, or has a logbilinear form, or is uniform. An example from research on social mobility will be discussed. The stability of the parameter estimates is studied with the jackknife.

Marshall and Gorman's Markov chain model for occupational prestige

Abstract This report scrutinizes the Markov chain model for occupational prestige proposed by K. P. Marshall and B. L. Gorman (1975, Social Science Research 4, 41–64). It is shown that the results of their application are highly unstable.

The Vienna Method in Amsterdam: Peter Alma's Office for Pictorial Statistics

Over the course of the 1930s, the Dutch artist and designer, Peter Alma, produced an extensive body of information graphics. Working for a wide variety of corporate clients seeking to provide social and economic information to general audiences, Alma was one of the principal Dutch practitioners and promoters of the approach to information design known as the “Vienna Method of Pictorial Statistics,” initially developed by the social scientist Otto Neurath and the graphic artist Gerd Arntz. In addition to providing an account of Almas role in the further development and dissemination of this method, this essay assesses the nature of Almas contribution to the field of visual education and considers the place of his pictorial statistics production within his broader artistic oeuvre.

Twintig jaar later...

In 1996, a group of Utrecht and Nijmegen based sociologists compiled a study on social segmentation in the Netherlands in 2015. In their contributions, they formulated testable predictions for 2015, based on the most up-to-date theories, models, and data. In this issue of Mens & Maatschappij, authors look back at and test these predictions, using data collected since 1996. Key findings are summarized in this contribution.