“Panelizing” Repeated Cross Sections

This paper considers the implementation of a non-stationary, heterogeneous Markov model for the analysis of binary dependent variables in a time series of repeated cross-sectional (RCS) surveys. The model offers the opportunity to estimate entry and exit transition probabilities and to examine the effects of time-constant and time-varying covariates on the hazards. We show how maximum likelihood estimates of the parameters can be obtained by Fishers method-of-scoring and how to estimate both fixed and time-varying covariate effects. The model is exemplified with an analysis of the labor force participation decision of Dutch and West German women using ISSP (and other) data from 10 annual Dutch surveys conducted between 1987 and 1996 and 7 annual West German surveys conducted between 1988 and 1994. Some open problems concerning the application of the model are discussed.     

The equity impacts of bus rapid transit: A review of the evidence and implications for sustainable transport

The paper offers an analysis of empirical evidence on the equity impacts of operational Bus Rapid Transit (BRT) systems in the Global South. The focus is on vertical equity, i.e. whether BRT systems achieve progressive benefits for poorer segments of the population. Findings from Africa, Asia, and Latin America all suggest that BRT does offer significant benefits to low-income groups, in terms of travel time and cost savings, access enhancement, and safety and health benefits. However benefits are often skewed toward medium-income users and thus less progressive than they might be. Two primary reasons for this are insufficient spatial coverage and inappropriate fare policies. While many features of BRT potentially allow it to deliver pro-poor outcomes, such outcomes only materialize if BRT implementers pay specific and sustained attention to equity. The paper identifies key issues that need to be addressed to steer BRT implementation toward more socially sustainable outcomes—including better integration with other transit, paratransit, and nonmotorized transport services, and with the housing sector.     

Claims Reserving with a Stochastic Vector Projection

In the last three decades, a variety of stochastic reserving models have been proposed in the general insurance literature mainly using (or reproducing) the well-known Chain-Ladder claims-reserving estimates. In practice, when the data do not satisfy the Chain-Ladder assumptions, high prediction errors might occur. Thus, in this article, a combined methodology is proposed based on the stochastic vector projection method and uses the regression through the origin approach of Murphy, but with heteroscedastic errors instead, and different from those that used by Mack. Furthermore, the Mack distribution-free model appears to have higher prediction errors when compared with the proposed one, particularly, for data sets with increasing (regular) trends. Finally, three empirical examples with irregular and regular data sets illustrate the theoretical findings, and the concepts of best estimate and risk margin are reported.     

Einzelbesprechungen

Ohne ZusammenfassungÜbersetzt von Hans Fried, Wien.