Killing off cohorts: Forecasting mortality of non-extinct cohorts with the penalized composite link model

Mortality forecasting has crucial implications for insurance and pension policies. A large amount of literature has proposed models to forecast mortality using cross-sectional (period) data instead of longitudinal (cohort) data. As a consequence, decisions are generally based on period life tables and summary measures such as period life expectancy, which reflect hypothetical mortality rather than the mortality actually experienced by a cohort. This study introduces a novel method to forecast cohort mortality and the cohort life expectancy of non-extinct cohorts. The intent is to complete the mortality profile of cohorts born up to 1960. The proposed method is based on the penalized composite link model for ungrouping data. The performance of the method is investigated using cohort mortality data retrieved from the Human Mortality Database for England & Wales, Sweden, and Switzerland for male and female populations.     

Raising the Bar (3)

This editorial summarizes and comments on the papers published in issue 11(3) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper proposes spatial and a-spatial indicators to describe the networks of airline companies around the world. The second paper sets forth a two-regime gravity-type model with an endogenous threshold parameter to assess the effect of labour market conditions on interregional migration flows. The third paper utilizes micro-data to explain student migration flows to higher education institutions. The fourth paper is among the first to make use of simulation-based location quotients in a multiregional input–output model. Finally, the last paper provides a purely economic–theoretical model on cooperative limit pricing in the context of spatial competition.     

Raising the bar (4)

This editorial summarizes and comments on the papers published in issue 11(4) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper deals with common factors and spatial dependence in the error term specification of a production function model. The second paper sets forth a New Economic Geography (NEG) model with production activities that vary in their complexity, so as to analyse the impact on specialization patterns across different regions. The third paper measures the efficiency of local public investments using a relatively unknown econometric technique in which the time span over which the variables in the regression equation are measured is increased by one time period every run. The fourth paper adopts a conditional quantile regression approach to determine the impact of people employed in informal jobs on the wage distribution in Colombia and five of its regions. Finally, the last paper proposes and tests two new Bayesian variable selection approaches for spatial econometric models.