Population age structure and private consumption in Spain

In this paper we study the effect of population age distribution upon private consumption expenditure in Spain from 1964 to 1997 using aggregate data. We obtain four main results. First, changes in the population pyramid have substantial effects upon the behaviour of private consumption. Second, the pattern of the coefficients of the demographic variables is not consistent with the simplest version of the life cycle hypothesis. Third, we estimate the impact of the demographic transition upon consumption and find positive values associated with episodes in which the shares of groups of individuals with expenditure levels higher (lower) than the mean increased (decreased). Fourth, the results are robust to alternative specifications for the population age distribution.

On the Benefits of Including Age-structure in Harvest Control Rules

This paper explores the benefits of including age-structure in the control rule (HCR) when decision makers regard their (age-structured) models as approximations. We find that introducing age structure into the HCR reduces both the volatility of the spawning biomass and the yield. Although at a fairly imprecise level the benefits are lower, there are still major advantages for actual assessment precision of the case study. Moreover, we find that when age-structure is included in the HCR the relative ranking of different policies in terms of variance in biomass and yield does not differ. These results are shown both theoretically and numerically by applying the model to the Southern Hake fishery.

Why Economists Reject Long-Term Fisheries Management Plans?

Most fisheries agencies conduct biological and economic assessments independently. This independent conduct may lead to situations in which economists reject management plans proposed by biologists. The objective of this study is to show how to find optimal strategies that may satisfy biologists and economists' conditions. In particular we characterize optimal fishing trajectories that maximize the present value of a discounted economic indicator taking into account the age-structure of the population as in stock assessment methodologies. This approach is applied to the Northern Stock of Hake. Our main empirical findings are: i) Optimal policy may be far away from any of the classical scenarios proposed by biologists, ii) The more the future is discounted, the higher the likelihood of finding contradictions among scenarios proposed by biologists and conclusions from economic analysis, iii) Optimal management reduces the risk of the stock falling under precautionary levels, especially if the future is not discounted to much, and iv) Optimal stationary fishing rate may be very different depending on the economic indicator used as reference.

Spatial-temporal excess mortality patterns of the 1918-1919 influenza pandemic in Spain

Background: The impact of socio-demographic factors and baseline health on the mortality burden of seasonal and pandemic influenza remains debated. Here we analyzed the spatial-temporal mortality patterns of the 1918 influenza pandemic in Spain, one of the countries of Europe that experienced the highest mortality burden. Methods: We analyzed monthly death rates from respiratory diseases and all-causes across 49 provinces of Spain, including the Canary and Balearic Islands, during the period January-1915 to June-1919. We estimated the influenza-related excess death rates and risk of death relative to baseline mortality by pandemic wave and province. We then explored the association between pandemic excess mortality rates and health and socio-demographic factors, which included population size and age structure, population density, infant mortality rates, baseline death rates, and urbanization. Results: Our analysis revealed high geographic heterogeneity in pandemic mortality impact. We identified 3 pandemic waves of varying timing and intensity covering the period from Jan-1918 to Jun-1919, with the highest pandemic-related excess mortality rates occurring during the months of October-November 1918 across all Spanish provinces. Cumulative excess mortality rates followed a south-north gradient after controlling for demographic factors, with the North experiencing highest excess mortality rates. A model that included latitude, population density, and the proportion of children living in provinces explained about 40% of the geographic variability in cumulative excess death rates during 1918-19, but different factors explained mortality variation in each wave. Conclusions: A substantial fraction of the variability in excess mortality rates across Spanish provinces remained unexplained, which suggests that other unidentified factors such as comorbidities, climate and background immunity may have affected the 1918-19 pandemic mortality rates. Further archeo-epidemiological research should concentrate on identifying settings with combined availability of local historical mortality records and information on the prevalence of underlying risk factors, or patient-level clinical data, to further clarify the drivers of 1918 pandemic influenza mortality.