Abstract
Recent research has provided strong evidence that, in the United States in particular and in high- or middle-income economies in general, mortality tends to evolve better in recessions than in expansions. It has been suggested that Sweden may be an exception to this pattern. The present investigation shows, however, that in the period 1968–2003 mortality oscillated procyclically in Sweden, deviating from its trend upward during expansions and downward during recessions. This pattern is evidenced by the oscillations of life expectancy, total mortality, and age- and sex-specific mortality rates at the national level, and also by regional mortality rates for the major demographic groups during recent decades. Results are robust for different economic indicators, methods of detrending, and models. In lag regression models macroeconomic effects on annual mortality tend to appear lagged 1 year. As in other countries, traffic mortality rises in expansions and declines in recessions, and the same is found for total cardiovascular mortality. However, macroeconomic effects on ischemic heart disease mortality appear at lag two and are hard to interpret. Reasons for the procyclical oscillations of mortality, for inconsistent results found in previous studies, as well as for the differences observed between Sweden and the United States are discussed.
Résumé
Des recherches récentes ont apporté de solides preuves que dans les économies présentant des revenus élevés ou moyens, et aux Etats-Unis en particulier, la mortalité tend à diminuer pendant les périodes de récession plutôt que pendant les périodes d’expansion. Il a été suggéré que la Suède pouvait être une exception à cette tendance générale. Cette recherche montre cependant qu’au cours de la période 1968–2003 la mortalité a oscillé de manière procyclique en Suède, déviant de ses tendances pour augmenter pendant les périodes d’expansion économique et pour diminuer pendant les périodes de récession. Ce schéma est mis en évidence par les variations de l’espérance de vie, de la mortalité totale, des taux de mortalité par âge et par sexe au niveau national, mais aussi des taux régionaux de mortalité des grands groupes démographiques au cours des récentes décennies. Les résultats sont robustes pour les différents indicateurs socio-économiques, les méthodes de décomposition des séries chronologiques pour éliminer les tendances et les modèles utilisés. Dans les modèles de régression avec retard, des effets macroéconomiques sur la mortalité annuelle tendent à apparaître avec un retard d’une année. Comme dans les autres pays, la mortalité par accidents de la route augmente pendant les périodes d’expansion et diminue pendant les périodes de récession. Il en est de même pour la mortalité cardio-vasculaire totale. Cependant les effets macroéconomiques sur la mortalité par cardiopathie ischémique apparaissent avec un retard de deux années et sont difficiles à interpréter. Les raisons des oscillations procycliques de mortalité, des résultats instables observés dans les études antérieures, ainsi que des différences observées entre la Suède et les Etats-Unis sont discutées.
Notes
In the HFA database age-standardized rates are computed with the direct method, applying age-specific rates for 5-year age-strata (0–4, 5–9, etc.) to a standard European population. For instance, the standardized rate of cancer mortality at ages 0–64 represents what the age-specific cancer mortality rate at ages 0–64 would have been if the Swedish population aged 0–64 had the same age distribution as the standard European population.
We used the HP filter applied with γ = 10, and the band-pass filter BP(2,8), recommended by Baxter and King (1999).
Business cycle data for the United States and other industrialized countries show average working hours in manufacturing as a procyclical indicator; in Sweden, however, its strong positive correlation with unemployment shows that it is clearly a countercyclical one. We comment on the potential causes of this difference in the discussion.
In fact, there is an exception to this rule, because in some models first differences in e 0 or mortality are regressed on the rate of growth of GDP. GDP growth is a major dynamic index of business conditions and, moreover, because of the exponential growth of real GDP, first differences tend to present exploding heteroskedasticity when the series exceeds a few observations.
The other three manufacturing indicators (aggregate hours, output, and employment) and the index of industrial production correlate similarly with mortality and e 0. The confidence indicator has erratic correlations with both the other business cycle indicators and with the health indicators.
Table 4 and other tables omit the results for cancer, respiratory disease, infectious disease, flu, suicide and homicide, causes for which we could not find a conclusive relation with macro-economic fluctuations.
In only a few cases d is large enough to suggest negative autocorrelation (see footnote in Table 5). Adjusting for autocorrelation of the residuals did, as expected, produce similar parameter estimates with some additional statistical significance. To avoid the need to justify selection of a specific autocorrelated model, we simply present the conservative unadjusted values.
In regional panel models not including a random effect for year, the unemployment effects were greater in size and much more significant than those reported in Table 7. However, we consider them probably biased by spatial autocorrelation.
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Tapia Granados, J.A., Ionides, E.L. Mortality and Macroeconomic Fluctuations in Contemporary Sweden. Eur J Population 27, 157–184 (2011). https://doi.org/10.1007/s10680-011-9231-4
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DOI: https://doi.org/10.1007/s10680-011-9231-4