Country and Consumer Segmentation: Multi-Level Latent Class Analysis of Financial Product Ownership

The financial services sector has internationalized over the last few decades.Important differences and similarities in financial behavior can be anticipated between both consumers within a particular country and those living in different countries.For companies in this market, the appropriate choice between strategic options and the resulting international performance may critically depend on the cross-national demand structure for the various financial products.Insight into country segments and international consumer segments based on domain-specific behavioral variables will therefore be of key strategic importance.We present a multi-level latent class framework for obtaining simultaneously such country and consumer segments.In an empirical study we apply this methodology to data on ownership of eight financial products.Information is available for fifteen European countries, with a sample size of about 1000 consumers per country.We find that both country segments and consumer segments are highly interpretable.Furthermore, consumer segmentation is related to demographic variables such as age and income.Our conclusions feature implications, both academic and managerial, and directions for future research.market segmentation;finance

Extending dynamic segmentation with lead generation: A latent class Markov analysis of financial product portfolios

A recent development in marketing research concerns the incorporation of dynamics in consumer segmentation.This paper extends the latent class Markov model, a suitable technique for conducting dynamic segmentation, in order to facilitate lead generation.We demonstrate the application of the latent Markov model for these purposes using a database containing information on the ownership of twelve financial products and demographics for explaining (changes in) consumer product portfolios.Data were collected in four bi-yearly measurement waves in which a total of 7676 households participated.The proposed latent class Markov model defines dynamic segments on the basis of consumer product portfolios and shows the relationship between the dynamic segments and demographics.The paper demonstrates that the dynamic segmentation resulting from the latent class Markov model is applicable for lead generation.market segmentation;Markov chains;marketing;demography;measurement

The Lazy Bootstrap. A Fast Resampling Method for Evaluating Latent Class Model Fit

The latent class model is a powerful unsupervised clustering algorithm for categorical data. Many statistics exist to test the fit of the latent class model. However, traditional methods to evaluate those fit statistics are not always useful. Asymptotic distributions are not always known, and empirical reference distributions can be very time consuming to obtain. In this paper we propose a fast resampling scheme with which any type of model fit can be assessed. We illustrate it here on the latent class model, but the methodology can be applied in any situation. The principle behind the lazy bootstrap method is to specify a statistic which captures the characteristics of the data that a model should capture correctly. If those characteristics in the observed data and in model-generated data are very different we can assume that the model could not have produced the observed data. With this method we achieve the flexibility of tests from the Bayesian framework, while only needing maximum likelihood estimates. We provide a step-wise algorithm with which the fit of a model can be assessed based on the characteristics we as researcher find important. In a Monte Carlo study we show that the method has very low type I errors, for all illustrated statistics. Power to reject a model depended largely on the type of statistic that was used and on sample size. We applied the method to an empirical data set on clinical subgroups with risk of Myocardial infarction and compared the results directly to the parametric bootstrap. The results of our method were highly similar to those obtained by the parametric bootstrap, while the required computations differed three orders of magnitude in favour of our method.Comment: This is an adaptation of chapter of a PhD dissertation available at https://pure.uvt.nl/portal/files/19030880/Kollenburg_Computer_13_11_2017.pd

Wage Mobility in Europe. A Comparative Analysis Using restricted Multinomial Logit Regression

In this paper, we investigate cross-country differences in wage mobility in Europe using the European Community Household Panel. The paper is particularly focused on examining the impact of economic conditions, welfare state regimes and employment regulation on wage mobility. We apply a log-linear approach that is very much similar to a restricted multinomial logit model and much more flexible than the standard probit approach. It appears that regime, economic conditions and employment regulation explain a substantial part of the cross-country variation. The findings also confirm the existence of an inverse U-shape pattern of wage mobility, showing a great deal of low and high-wage persistence in all countries.wages; wage mobility; wage dynamics; multinomial logit regression; loglinear models; welfare states