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Evolution of Life Expectancy at Birth in French Départements Over the Period 1833–1982

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Abstract

This paper deals with spatial aspects of trends in life expectancy at birth in the French metropolitan départements over the nineteenth and twentieth centuries. Data from the censuses conducted from 1833 to 1982 were used to calculate the life expectancy at birth for both sexes togheter, \(e_0\). The overall fertility index (\(I_f\)), marital fertility index (\(I_g\)) and nuptiality index (\(I_m\)) were also calculated for each 5-year period within the same time span. The analysis has two facets: a first, descriptive part in which we establish clusters of départements with similar or different patterns of evolution over the period above mentioned; and a second part in which the effect of covariables in changes in \(e_0\) are examined. In addition their coefficients were interpreted including the direct and spatial spillover effects. Unlike earlier studies, in which a spatio-temporal analysis was performed, the time function showing changes in \(e_0\) is reduced to a single value which measures the distance or affinity between the functions of time in each département, which enables us to carry out an exploratory spatial data analysis and apply spatial econometric models.

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Notes

  1. Only in the cases of Italy and, especially, Spain, was this general increase in the nuptiality indicators interrupted at the end of the twentieth century by several years of contraction.

  2. We took into account the mean number of deaths found around the census year in order to avoid the problem of possible random variations associated with sparsely populated départements.

  3. For example, the life expectancy at birth for men in France as a whole in the year 1931 calculated by the Human Mortality Database at Berkeley University is 54.5 years. Our calculations give the figure 54.6 years. That is, the difference between the two is only 0.22%. Similar results were obtained for other years and both sexes.

References

  • Angeles, L. (2010). Demographic transitions: Analyzing the effects of mortality on fertility. Population Economics, 23, 99–120.

    Article  Google Scholar 

  • Angeles, L. (2015). Tracking how mortality affects fertility along the demographic transition. In 11th European historical economics society conference 2015, Pisa, Italy, 4–5 September 2015.

  • Anselin, L. (1988). Spatial econometrics: Methods and models. Dordrecht: Kluwer.

    Book  Google Scholar 

  • Anselin, L. (1995). Local indicators of spatial association LISA. Geographical Analysis, 27(2), 93–115.

    Article  Google Scholar 

  • Bálint, L. (2012). Spatial gender differences in life expectancy at birth. Regional Statistics, 2(1), 108–128.

    Article  Google Scholar 

  • Balk, D., Pullum, T., Storeygard, A., Greenwell, F., & Neuman, M. (2004). A spatial analysis of childhood mortality in West Africa. Population, Space and Place, 10(2), 175–216. doi:10.1002/psp.328.

    Article  Google Scholar 

  • Barbieri, M. (2013). Mortality in France by département. Population, 68(3), 375–417.

    Article  Google Scholar 

  • Bivand, R. (2012). spdep: Spatial dependence: Weighting schemes, statistics and models. R package version 0.5-53. http://CRAN.R-project.org/package=spdep.

  • Blayo, C., & Egidi, V. (1970). Mortalité selon les départements en 1961–1963. Population, 25(2), 410–420.

    Article  Google Scholar 

  • Bonneuil, N. (1997). Transformation of the French demographic landscape 1806–1906. Oxford: Clarendon Press. http://table_mortalite_bonneuil.site.ined.fr/en/presentation/.

  • Brazil, N. (2015). Spatial variation in the Hispanic Paradox: Mortality rates in new and established hispanic US destinations. Population, Space and Place.. doi:10.1002/psp.1968.

    Article  Google Scholar 

  • Caselli, G., & Egidi, V. (1986). Cadre général de lanalyse géographique. In Vallin, J., Meslé, F. (eds). Les causes de décs en France de 1925 1978. INED, Cahier no. 115., Paris.

  • Caselli, G., & Vallin, J. (2002). Geographic variations of mortality. In I. I. Volume, G. Caselli, & J. Vallin (Eds.), Demography: Analysis and synthesis (pp. 207–234). Paris: INED.

    Google Scholar 

  • Castro, M. (2007). Spatial demography: An opportunity to improve policy making at diverse decision levels. Population Research and Policy Review, 26(5), 477–509.

    Article  Google Scholar 

  • Cleland, J. (2001). The effects of improved survival on fertility: A reassessment. Population and Development Review, 27(Supplement), 60–92.

    Google Scholar 

  • Cliff, A., & Ord, J. (1973). Spatial autocorrelation. London: Pion.

    Google Scholar 

  • Coale, A. & Watkins, S. (1986). The decline of fertility in Europe. Princeton: Princeton University Press. http://opr.princeton.edu/archive/pefp/.

  • Daguet, F. (2005). Données de démographie régionale 1954 1999 (p. 49). Insee Résultats, Société.

  • Doepke, M. (2005). Child mortality and fertility decline: Does the Barro-Becker model fit the facts? Journal of Population Economics, 18(2), 337–366.

    Article  Google Scholar 

  • Draper, N. R., & Smith, H. (1998). Applied regression analysis (3rd ed.). New York: Wiley.

    Google Scholar 

  • Dyson, T. (2010). Population and development: The demographic transition. London: Zed Books.

    Google Scholar 

  • Elhorst, J. P. (2014). Spatial econometrics: From cross-sectional data to spatial panels. Heidelberg: Springer.

    Book  Google Scholar 

  • Fernández-Villaverde, J. (2001). Was Malthus right? Economic growth and population dynamics. Working Paper, Department of Economics, University of Pennsylvania.

  • Florax, R., & Yoon, M. J. (1996). Simple diagnostic tests for spatial dependence. Regional Science and Urban Economics, 26, 77–104.

    Article  Google Scholar 

  • Gaimard, M. (2005). Les disparités géographiques de la mortalité en France depuis la Secunde Guerre mondiale. In C. Bergouignan, et al. (Eds.), La population de la France. Évolutions démographiques depuis 1946 (Vol. II, pp. 497–538). Bordeaux: CUDEP.

    Google Scholar 

  • Galloway, P., Lee, R., & Hammel, E. (1998). Infant mortality and the fertility transition. In M. Montgomery & B. Cohen (Eds.), From death to birth: Mortality decline and reproductive change (pp. 182–226). Washington, DC: National Academy Press.

    Google Scholar 

  • Goodwin-White, J. (2015). Is social mobility spatial? Characteristics of immigrant metros and second generation outcomes: 19401970 and 19702000. Population, Space and Place. doi:10.1002/psp.1960.

    Article  Google Scholar 

  • Haandrikman, K., Harmsen, C., van Wissen, L. J. G., & Hutter, I. (2008). Geography matters: Patterns of spatial homogamy in the Netherlands. Population, Space and Place, 14, 387–405. doi:10.1002/psp.487.

    Article  Google Scholar 

  • Haines, M. (1998). The relationship between infant and child mortality and fertility: Some historical and contemporary evidence from the United States. In M. Montgomery & B. Cohen (Eds.), From death to birth: Mortality decline and reproductive change (pp. 227–253). Washington, DC: National Academy Press.

    Google Scholar 

  • Hanal, J. (1965). European marriage patterns in perspective. In D. Glass & D. Eversley (Eds.), Population in history: Essays in historical demography (pp. 101–43). London: Edward Arnold.

    Google Scholar 

  • Herzer, D., Strulik, H., & Vollmer, S. (2012). The long-run determinants of fertility: One century of demographic change 1900–1999. Journal of Economic Growth, 17, 357–385.

    Article  Google Scholar 

  • Kesztenbaum, L., & Rosenthal, J. L. (2014). Income versus sanitation: Mortality decline in Paris, 1880–1914. PSE Working Papers no. 2014-26.

  • Knodel, J. (1974). The decline of fertility in Germany, 1871–1939. Princeton: Princeton University Press.

    Google Scholar 

  • Kulu, H. (2012). Spatial variation in divorce and separation: Compositional or contextual effects? Population, Space and Place, 18, 1–15. doi:10.1002/psp.671.

    Article  Google Scholar 

  • Leclerc, A., Fassin, D., Granjean, H., Kaminski, M., & Lang, T. (Eds.). (2010). Les inégalités sociales de santé (p. 448). La Découverte: INSERM.

  • LeSage, J., & Pace, R. K. (2009). Introduction to spatial econometrics. Boca Rato, FL: Chapman & Hall/CRC.

    Book  Google Scholar 

  • Lesthaeghe, R. (1977). The decline of Belgian fertility, 1800–1970. Princeton: Princeton University Press.

    Google Scholar 

  • Lincot, L., & Lutinier, B. (1998). Les évolutions démographiques départementales et régionales entre 1975 et 1994. INSEE-RESULTATS 600-601, Démographie et société, pp. 67–68.

  • Malczewski, J. (2010). Exploring spatial autocorrelation of life expectancy in Poland with global and local statistics. GeoJournal, 75(1), 79–92.

    Article  Google Scholar 

  • Mason, K. (1997). Explaining fertility transitions. Demography, 34(4), 443–454.

    Article  Google Scholar 

  • Matthews, S., & Parker, D. (2013). Progress in spatial demography. Demographic Research, 28, 271–311.

    Article  Google Scholar 

  • Meslé, F., & Vallin, J. (1998). Évolution et variations géographiques de la surmortalité masculine. Du paradoxe franais la logique russe. Population, 53(6), 1079–1101.

    Article  Google Scholar 

  • Moran, P. A. P. (1950a). Notes on continuous stochastic phenomena. Biometrika, 37, 17–23.

    Article  Google Scholar 

  • Moran, P. A. P. (1950b). A test for the serial dependence of residuals. Biometrika, 37, 178–181.

    Article  Google Scholar 

  • Murphy, T. (2009). Old habits die hard (sometimes): What can deprtement heterogeneity tell us about the French fertility decline?. Thecnical report, MIMEO.

  • Murtin, F. (2013). The long-term determinants of the demographic transition, 1870–2000. The Review of Economics and Statistics, 95(2), 617–631.

    Article  Google Scholar 

  • Nizard, A., & Prioux, F. (1975). La mortalité départementale en France. Population, 30(4–5), 781–824.

    Article  Google Scholar 

  • Noin, D. (1973). Géographie démographique de la France. Paris: PUF.

    Google Scholar 

  • Norman, P., & Riva, M. (2012). Population health across space and time: The geographical harmonisation of the Office for National Statistics Longitudinal Study for England and Wales. Population, Space and Place, 18, 483–502. doi:10.1002/psp.1705.

    Article  Google Scholar 

  • O’brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & Quantity, 41(5), 673–690.

    Article  Google Scholar 

  • O’brien, R. M. (2016). Dropping highly collinear variables from a model: Why it typically is not a good idea. Social Science Quarterly. doi:10.1111/ssqu.12273.

    Article  Google Scholar 

  • Omran, A. R. (1998). The epidemiologic transition theory revisited thirty years later. World Health Statistics Quarterly, 51, 99–119.

    Google Scholar 

  • Padilla, C. M., Deguen, S., Lalloue, B., Blanchard, O., Beaugard, C., Troude, F., et al. (2013). Cluster analysis of social and environment inequalities of infant mortality. A spatial study in small areas revealed by local disease mapping in France. Science of the Total Environment, 454–455, 433–441.

    Article  Google Scholar 

  • Padilla, C. M., Kihal-Talantikit, W., Vieira, V. M., & Deguen, S. (2016). City-specific spatiotemporal infant and neonatal mortality clusters: Links with socioeconomic and air pollution spatial patterns in France. International Journal of Enviromental Research and Public Health, 13, 624.

    Article  Google Scholar 

  • Reher, D., & Sanz-Gimeno, A. (2007). Rethinking historical reproductive change: Insights from longitudinal data for a Spanish town. Population and Development Review, 33(4), 703–727.

    Article  Google Scholar 

  • Salem, G., Rican, S., & Jougla, É. (2000). Atlas de la santé en France, Vol. 1 Les causes de décs. Montrouge: John Libbey Eurotext.

    Google Scholar 

  • Sánchez-Barricarte, J. J. (2017). The long-term determinants of marital fertility in the developed world (19th and 20th centuries): The role of welfare policies. Demographic Research, 36, 1255–1298. doi:10.4054/DemRes.2017.36.42.

    Article  Google Scholar 

  • Schellekens, J., & van Poppel, F. (2012). Marital fertility decline in the Netherlands: Child mortality, real wages, and unemployment, 1860–1939. Demography, 49, 965–988.

    Article  Google Scholar 

  • Sparks, P. J., & Sparks, C. S. (2010). An application of spatially autoregressive models to the study of US county mortality rates. Population, Space and Place, 16, 465–481. doi:10.1002/psp.564.

    Article  Google Scholar 

  • Tobler, W. (1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 46(2), 234–240.

    Article  Google Scholar 

  • Tsimbos, C., Kalogirou, S., & Verropoulou, G. (2014). Estimating spatial differentials in life expectancy in greece at local authority level. Population, Space and Place, 20, 646–663. doi:10.1002/psp.1800.

    Article  Google Scholar 

  • Tsimbos, C., Kotsifakis, G., Verropoulou, G., & Kalogirou, S. (2011). Life expectancy in Greece 1991–2007: Regional variations and spatial clustering. Journal of Maps, 7(1), 280–290.

    Article  Google Scholar 

  • Van de Kaa, D. (1996). Anchored narratives: The story and findings of the half a century of research into the determinants of fertility. Population Studies, 50(3), 389–432.

    Article  Google Scholar 

  • Van de Walle, F. (1986). Infant mortality and the European demographic transition. In A. Coale & S. Watkins (Eds.), The decline of fertility in Europe (pp. 201–233). Princeton: Princeton University Press.

    Google Scholar 

  • Van Poppel, F., Reher, D., Sanz-Gimeno, A., Snchez-Domnguez, M., & Beekink, E. (2012). Mortality decline and reproductive change during the Dutch demographic transition: Revisiting a traditional debate with new data. Demographic Research, 27, 299–338.

    Article  Google Scholar 

  • Vitali, A., & Billari, F. C. (2015). Changing determinants of low fertility and diffusion: A spatial analysis for Italy. Population, Space and Place. doi:10.1002/psp.1998.

    Article  Google Scholar 

  • Voss, P. (2007a). Demography as a spatial social science. Population Research and Policy Review, 26(5–6), 457–476.

    Article  Google Scholar 

  • Voss, P. (2007b). Introduction to the special issue on spatial demography. Population Research and Policy Review, 26(5–6), 455–476.

    Article  Google Scholar 

  • Wachter, K. W. (2005). Spatial demography. Proceedings of the National Academy of Sciences, 102(43), 15299–15300.

    Article  Google Scholar 

  • Ward, M. D., & Gleditsch, K. S. (Eds.). (2008). Spatial regression models. Thousand Oaks, CA: SAGE Publications.

    Google Scholar 

  • Watkins, S. (1986). Conclusions. In A. Coale & S. Watkins (Eds.), The decline of fertility in Europe (pp. 420–449). Princeton: Princeton University Press.

    Google Scholar 

  • Weeks, J. (2004). The role of spatial analysis in demographic research. In M. Goodchild & D. Janelle (Eds.), Spatially integrated social science (pp. 381–399). New York: Oxford University Press.

    Google Scholar 

  • Windenberger, F., Rican, S., Jougla, E., & Rey, G. (2012). Spatiotemporal association between deprivation and mortality: Trends in France during the nineties. The European Journal of Public Health, 22(3), 347–353.

    Article  Google Scholar 

  • Wrigley, E. (1978). Marital fertility in seventeenth-century Colyton: A note. Economic History Review, 31(3), 429–436.

    Article  Google Scholar 

  • Yang, T.-C., Noah, A. J., & Shoff, C. (2015). Exploring geographic variation in US mortality rates using a spatial Durbin approach. Population, Space and Place, 21, 18–37. doi:10.1002/psp.1809.

    Article  Google Scholar 

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Acknowledgements

Jesús J. Sánchez-Barricarte is supported by the Spanish Ministry of Economy and Competitiveness of Spain (grant CSO2012-31206) and Autonomous Community of Madrid (grant H2015/HUM-3321). Patricia Carracedo and Ana Debón are supported by the Spanish Ministerio de Economía y Competitividad (grant MTM2013-45381-P). Adina Iftimi is supported by the Spanish Ministerio de Educación, Cultura y Deporte (grant FPU12/04 531) and Spanish Ministerio de Economía y Competitividad (grant MTM2016-78917-R). Francisco Montes is supported by the Spanish Ministerio de Economía y Competitividad (grants MTM2013-45381-P, MTM2016-78917-R).

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Appendix

Appendix

1.1 Summary of H–H Clusters

See Tables 12 and 13.

Table 12 H–H clusters and neighbors for Euclidean distance
Table 13 H–H clusters and neighbors for Manhattan distance

1.2 Summary of L–L Clusters

See Tables 14 and 15.

Table 14 L–L clusters and neighbors for Euclidean distance
Table 15 L–L clusters and neighbors for Manhattan distance

1.3 Summary of H–H Clusters for Data Subsets

See Tables 16 and 17.

Table 16 H–H clusters and neighbors for the period 1908—1982 for Euclidean distance
Table 17 H–H clusters and neighbors for the period 1908–1982 for Manhattan distance

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Sánchez-Barricarte, J.J., Carracedo, P., Iftimi, A. et al. Evolution of Life Expectancy at Birth in French Départements Over the Period 1833–1982. Spat Demogr 6, 89–120 (2018). https://doi.org/10.1007/s40980-017-0035-y

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