Demography


Objective

Classic demography is formal in its essence and describes with mathematical means the empirical structure of a populations and their dynamics shaped by aging, fertility, mortality and migration. Social demography goes beyond the statistical description of a population and creates an interdisciplinary link to other, theoretically informed behavioural sciences with the goal to explain central demographic and socioeconomic phenomena with social behaviour and beyond.

In this course, we will learn about several important explanations for demographic behaviour and trends which are located on the population level, the intermetidate level, the individual level (macro-meso-micro) and even down to the molecular genetic level, which recently has been integrated in this field. We will learn, amongst others, about social networks effects, the importance of neighbourhoods, technological advancements and assume a life course perspective for the study of processes such as aging or the development of early life experiences. All of these social factors might interaction with an individual’s genome. Finally, we will discuss several (newly) available data sources including those, which stem from recent computational efforts tracing internet data from facebook or twitter. 

The students are expected to have an advanced knowledge of empirical social research and applied econometrics. After attending this course, students should be equipped with important analytical tools to understand the connection between the social world and central population and developmental indicators and have an overview over the current research frontiers.

Planning

Week 1: What is Social Demography? (Theory)

Week 2: Social Demography and Causality (Theory)

Week 3: Family and the life course (Methods: Event history analysis and sequence analysis)

Week 4: Fertility and Sexuality (Methods: Fixed-effects regression analysis)

Week 5: Health, Morbidity and Mortality (Methods: Event history analysis)

Week 6: New Demographic Thinking and Data (Methods: GWAS, Computational Methods)

Références

General:

 

Hirschman, C., S. Tolnay. (2005). Social Demography. In: Handbook of Population, eds. Dudley Poston and Michael Micklin, 419–449. New York: Kluwer Academic.

 

Mills, M. (2010). Introducing survival and event history analysis. Sage.

Livi Bacci, M. (2012) A Concise History of World Population, Wiley-Blackwell.

 

Fertility

 

Balbo, N., and N. Barban (2014) Does Fertility Spread among Friends? American

Sociological Review 79: 412-431

 

Balbo, N., Billari, F. C., & Mills, M. (2013). Fertility in advanced societies: A review of research. European Journal of Population/Revue européenne de Démographie29(1), 1-38.

 

Mills, M., Rindfuss, R. R., McDonald, P., & Te Velde, E. (2011). Why do people postpone parenthood? Reasons and social policy incentives. Human reproduction update17(6), 848-860.

 

Tropf, F. C., & Mandemakers, J. J. (2017). Is the Association Between Education and Fertility Postponement Causal? The Role of Family Background Factors. Demography, 54(1), 71–91. http://doi.org/10.1007/s13524-016-0531-5

 

Kohler, H.-P., and L. Mencarini (2016) The Parenthood Happiness Puzzle: An Introduction

to the Special Issue. European Journal of Population 32: 327–338.

 

Moore, M. R., and M. Stambolis-Ruhstorfer (2013) LGBT Sexuality and Families at the Start of the Twenty-First Century. Annual Review of Sociology, 39: 491-507

 

Health, Morbidity and Mortality

 

Goldman DP, Smith JP. (2002) Can Patient Self-Management Help Explain the SES Health Gradient? PNAS: Proceedings of the National Academy of Science,  99: 10929–10934.

 

Hessel, P., and J. S. Thomas (2016) An Education Gradient in Health, a Health Gradient in Education, or a Confounded Gradient in Both? Social Science and Medicine,158: 168-170.

 

Browning CR, Wallace D, Feinberg SL, and Cagney KA. (2006) Neighborhood Social Processes, Physical Conditions, and Disaster-Related Mortality: The Case of the 1995 Chicago Heat Wave. American Sociological Review; 71: 661–678.

 

Leventhal T and Brooks-Gunn J. (2003) Moving to Opportunity: An Experimental Study of

Neighborhood Effects on Mental Health. American Journal of Public Health, 93:

1576-1582.

 

Hayward, M.D. (2004) The Long Arm of Childhood: The Influence of Early-Life Social Conditions on Men’s Mortality. Demography 41(1): 87-107.

 

Myrskylä, M. (2010) The effects of shocks in early life mortality on later life expectancy and mortality compression: A cohort analysis. Demographic Research 22(12): 289-320.

 

Family and the life course

 

Baars, J. (2009) Problematic Foundations: Theorizing Time, Age, and Ageing. In V.L. Bengtson et al. (eds.), Handbook of Theories of Ageing. Springer: New York, 87-100.

 

Dannefer, D., Kelley-Moore (2009) Theorizing the Life Course: New Twists in the Paths. In V.L. Bengtson et al. (eds.), Handbook of Theories of Ageing. Springer: New York, 389-412.

Elder Jr., G. H., M. Kirpatrick Johnson, and R. Crosnoe  (2003) The Emergence and Development of Life Course Theory. Handbook of the Life Course, p.3-19.

Mayer, K.U. (2009) New Directions in Life Course Research. Annual Review of Sociology, 35: 413-433.

 

Sarkisian, N., N. Gerstel. (2016): Does singlehood isolate or integrate? Examining the link between marital status and ties to kind, friends, and neighbors. Journal of Social and Personal Relationships, 33 (3): 361-384.

 

New demographic thinking and data

 

Mills, M. C., and F. C. Tropf. Sociology, Genetics, and the Coming of Age of Sociogenomics. Annual Review of Sociology 46 (2020).

 

Mills, M. C., & Tropf, F. C. (2016). The Biodemography of Fertility: A Review and Future Research Frontiers. Kölner Zeitschrift Für Soziologie Und Sozialpsychologie, 55(Special Issues Demography), 397–424.

 

Cesare, N., Lee, H., McCormick, T., Spiro, E., & Zagheni, E. (2018). Promises and pitfalls of using digital traces for demographic research. Demography55(5), 1979-1999.

 

Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A. L., Brewer, D., … & Jebara, T. (2009). Computational social science. Science323(5915), 721-723.