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Despite the overwhelming evidence that shows the persistence of intra-annual variations on demographic events (deaths, birth dates and migration flows), life tables are computed and provided on an annual basis. This paper develops a new estimator for estimating sub-annual death rates that, considering the exact moment of occurrence (exact age and day) of events, concurrently accounts for ageing and calendar fluctuations. This paper also shows how modelling the intra-annual variations of death rates, through specific seasonal-ageing indexes, can be used as a tool for constructing new sub-annual tables from annual tables. This new methodology is exemplified using a real database of Spain made up of 186 million demographic events (1.5 million of which are deaths), from which seasonal-ageing indexes are estimated and conclusions drawn. First, seasonal effects are, as a rule, stronger than ageing effects. For a given integer age, season has a higher impact on increasing or decreasing the average risk of death at that age than the actual age of the exposed-to-risk. Second, the intensity of the effects varies among seasons and age-quarters. Third, neither seasonal nor ageing effects are age-stationary.

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Inferring electoral individual behaviour from aggregated data is a very active research area, with ramifications in sociology and political science. In this paper, a new approach based on linear programming is proposed to estimate voter transitions among parties (or candidates) between two elections. In contrast to other similar models previously suggested in the literature, our approach presents two important innovations. First, it explicitly deals with new entries and exits in the election census without assuming unrealistic hypotheses, enabling a reasonable estimation of vote transfers for young electors voting for the first time. We illustrate this in a real instance. Secondly, by exploiting the information contained in the model residuals, we develop a procedure to assess the level of uncertainty in the estimates. This significantly distinguishes our model from other linear and quadratic programming methods previously published. The method is illustrated estimating the vote transfer matrix between the first and second round of the 2017 French Presidential election and measuring its level of uncertainty. Likewise, compared to the most current alternatives based on ecological regression, our approach is considerably simpler and faster, and has provided reasonable results in all the actual elections to which it has been applied. Interested scholars can easily use our procedure with the aid of the 𝑅-function described at the bottom of this paper.