The Role of Social Interactions in Demography: An Agent Based - PowerPoint PPT Presentation

The Role of Social Interactions in Demography: An Agent Based Modelling Approach Workshop: Recent Developments and Future Directions in Agent-Based Modelling in Population Studies, KU Leuven 19 th September, 2014 Alexia Fürnkranz-Prskawetz Institute of Mathematical Methods in Economics, Vienna University of Technology Vienna Institute of Demography, Austrian Academy of Sciences Wittgenstein Centre for Demography and Global Human Capital Institute of Mathematical Methods in Economics Economics

Structure of the talk 1. Introduction 2. The gap between theory and techniques in demography 3. Three examples The Wedding Ring - Mate search and marriage Transition to parenthood – Social Interaction and Social networks Family policies – Social Structure 4. The potential role of agent-based computational demography Institute for Mathematical Methods in Economics Economics

1. Introduction ⇒ ABC uses computational approach to the study of human behavior. ⇒ ABC models do not aim to understand why specific rules are applied by humans BUT pre-suppose rules of behavior and verify whether these micro based rules can explain macroscopic regularities. ⇒ Emphasis on explanation rather than on prediction of behavior; models are based on individual agents ( agent-based modeling). Institute for Mathematical Methods in Economics Economics

1. Introduction „Whereas the purpose of induction is to find patterns in data and that of deduction is to find consequences of assumptions, the purpose of agent-based modelling is to aid intuition“ (Axelrod, 1997) Institute for Mathematical Methods in Economics Economics

2. The gap between theory and techniques in demography Two good examples: ⇒ micro-macro link (good theories of behavior and good statistical models but difficult link between them) ⇒ ‘subjective’ aspects (values, norms, psychological aspects, cognition, emotions) of demographic behavior Institute for Mathematical Methods in Economics Economics

2. The gap between theory and techniques in demography Some reasons for the gap: 1. Poor level of precision in theoretical constructs (especially in sociological-based theories). Sometimes theory is too vague. 2. Insufficient theoretical basis of statistical analyses and data collection. 3. Difficult observability of important theoretical pieces (e.g. values, norms). Institute for Mathematical Methods in Economics Economics

2. The gap between theory and techniques in demography Why is ABCD advantageous? 1. Precision: theoretical statements have to be written in a precise way to be implemented in a program (including subjective aspects). 2. Mathematical tractability is less a limit for formalized theoretical constructions. 3. Bottom-up approach (solving the micro-macro link allowing for interactions), using micro-based theories. Institute for Mathematical Methods in Economics Economics

3. Examples Billari, F., A. Prskawetz, B. Aparicio Diaz and T. Fent (2007) The Wedding-Ring”: An agent-based marriage model based on social interaction , Demographic Research, Vol. 17, 59-82. Aparicio Diaz, B., T. Fent, A. Prskawetz and L. Bernardi (2011) Transition to Parenthood: The Role of Social Interaction and Endogenous Networks , Demography 48, 559-579. Fent, T., B. Aparicio Diaz and A. Prskawetz (2013) Family policies in the context of low fertility and social structure , Demographic Research, Vol. 29, 963-998. Institute for Mathematical Methods in Economics Economics

Wedding Ring Timing of marriage has been studied from 2 different perspectives: Demographers : Explaining & modeling shape of age-at-marriage curves  mathematical and statistical macro-level models Psychologists and economists : Studying & modeling process of partner search  micro-level models Agent-based modeling : Models that account for macro-level marriage patterns starting from plausible micro-level assumptions and allowing for interactions between potential partners. Institute for Mathematical Methods in Economics Economics

Wedding Ring Benchmark against which we test our model: shape of the age-at-marriage hazard function 0.16 Norway Women, 1978 0.14 Romania Men, 1998 0.12 0.10 Romania 0.08 Women, 1998 Norway Men, 1978 0.06 0.04 Norway Men, 1998 0.02 Norway Women, 1998 0.00 18 23 28 33 38 43 48 Institute for Mathematical Methods in Economics Economics

Wedding Ring “observations” on social interaction and marriage  homogamy in marriage w.r.t. socioeconomic status, religion, ethnicity, etc. ( closeness matters )  number of relevant others increases with age during youth and adulthood, and decreases thereafter  social learning and social influence may trigger diffusion of marriage within social network ( share of married people in social network matters )  NOTE: highest incidence of marriage occurs within a social network of a relatively high share of both married and unmarried persons Institute for Mathematical Methods in Economics Economics

Wedding Ring An agent based model ϕ ∈ [0,2 π ] spatial location of each agent: additional coordinate: age x availability of mates desirability of marriage Institute for Mathematical Methods in Economics Economics

Wedding Ring Flow diagram starting at age 16 mutual search Institute for Mathematical Methods in Economics Economics

Wedding Ring Simulation results Hazard of marriage in a population of simulated agents with alternative settings for social pressure. WOMEN A: only social pressure, independent of age of agent, determines potential partners B: A + including age dependency of network size C: constant social pressure, ignores increase of social pressure with age D: linear instead of S-shaped social pressure Institute for Mathematical Methods in Economics Economics

Wedding Ring The macro-level shape of the age-at-marriage pattern emerges from the bottom up as an outcome of individual behavior and social interactions Including the age dependency of network size is a key determinant to obtain the emergence of the hazard function as empirically verified ! Institute for Mathematical Methods in Economics Economics

Transition to Parenthood • Fertility behavior of individuals depends not only on family background variables and life course paths but also on the behavior and characteristics of other individuals (social networks) • Social multiplier effects and multiple equilibria can be explained through social network effects • Within social networks: exchange information about childbearing choices learn about other’s preferences feel induced to conform to other’s norms, …. • Variation of network by marital and parental status  introduce agent-based model to study endogenous network structure Institute for Mathematical Methods in Economics Economics

Transition to Parenthood Model implementation Agents One sex model (only female agents) Age x Intended Education ie Parity p Social Network (peer group) Institute for Mathematical Methods in Economics Economics

Transition to Parenthood Initial population Age Structure: Austrian female age distribution Intended Education: Austrian education distribution at age 30 Parity: Austrian distribution by age, education and parity Social Network: probability of a link based on similarity of individuals Institute for Mathematical Methods in Economics Economics

Transition to Parenthood Micro-level dynamics Agent´s Individual Probability of having a Child empirical/average age- and parity specific bpr ( x , p ) birth probability at time t t multiplier to take social influence into si i account xc Age of youngest child, g(.) monotonically i decreases Institute for Mathematical Methods in Economics Economics

Transition to Parenthood Macro-level dynamics Update of birth probabilities at the macro level according to the average social influence multiplier = bpr ( x , p ) bpr ( x , p ) * si ( x , p ) + t 1 t t Institute for Mathematical Methods in Economics Economics

Transition to Parenthood Network typology distance among agents i and j = − + − ε d x x e e ij i j i j ε parameter to adjust for possible differences in age and education probability of choosing a certain distance d ( ) = exp − α pr ( d ) c d 1 Agent chooses d with respect to pr 1 (d) and then picks a friend uniformly among all individuals with distance d Institute for Mathematical Methods in Economics Economics

Transition to Parenthood Social influence 1  β π − π  exp( ( *)) 1 = + ξ − si   1 2 + β π − π   exp( * ( *)) ξ , β intensity of social influence π share of members of the peer group with parity ≥ p π * share of agents with parity ≥ p in the whole population Institute for Mathematical Methods in Economics Economics

Transition to Parenthood N=50000, average over 25 simulation runs Sensitivity w.r.t. parameters Plot of sum of absolute differences between simulated and observed age specific fertility rates in 2004. Institute for Mathematical Methods in Economics Economics

Transition to Parenthood Simulation without Social Interaction Simulation results for simulating 20 years starting from 1984 Institute for Mathematical Methods in Economics Economics

Transition to Parenthood Simulation with Social Interaction Simulation results for simulating 20 years starting from 1984 Institute for Mathematical Methods in Economics Economics