Recursive Utility in a Markov Environment with Stochastic Growth

2012 ◽  
Author(s):  
Lars Peter Hansen ◽  
Jose A. Scheinkman
2012 ◽  
Vol 109 (30) ◽  
pp. 11967-11972 ◽  
Author(s):  
Lars Peter Hansen ◽  
José A. Scheinkman

2020 ◽  
Vol 17 (4) ◽  
pp. 314-329
Author(s):  
Johan Burgaard ◽  
Mogens Steffensen

Risk aversion and elasticity of intertemporal substitution (EIS) are separated via the celebrated recursive utility building on certainty equivalents of indirect utility. Based on an alternative separation method, we formulate a questionnaire for simultaneous and consistent estimation of risk aversion, subjective discount rate, and EIS. From a representative group of 1,153 respondents, we estimate parameters for these preferences and their variability within the population. Risk aversion and the subjective discount rate are found to be in the orders of 2 and 0, respectively, not diverging far away from results from other studies. Our estimate of EIS in the order of 10 is larger than often reported. Background variables like age and income have little predictive power for the three estimates. Only gender has a significant influence on risk aversion in the usually perceived direction that females are more risk-averse than males. Using individual estimates of preference parameters, we find covariance between preferences toward risk and EIS. We present the background reasoning on objectives, the questionnaire, a statistical analysis of the results, and economic interpretations of these, including relations to the literature.


2013 ◽  
Vol 79 (7) ◽  
pp. 2294-2301 ◽  
Author(s):  
Konstantinos P. Koutsoumanis ◽  
Alexandra Lianou

ABSTRACTConventional bacterial growth studies rely on large bacterial populations without considering the individual cells. Individual cells, however, can exhibit marked behavioral heterogeneity. Here, we present experimental observations on the colonial growth of 220 individual cells ofSalmonella entericaserotype Typhimurium using time-lapse microscopy videos. We found a highly heterogeneous behavior. Some cells did not grow, showing filamentation or lysis before division. Cells that were able to grow and form microcolonies showed highly diverse growth dynamics. The quality of the videos allowed for counting the cells over time and estimating the kinetic parameters lag time (λ) and maximum specific growth rate (μmax) for each microcolony originating from a single cell. To interpret the observations, the variability of the kinetic parameters was characterized using appropriate probability distributions and introduced to a stochastic model that allows for taking into account heterogeneity using Monte Carlo simulation. The model provides stochastic growth curves demonstrating that growth of single cells or small microbial populations is a pool of events each one of which has its own probability to occur. Simulations of the model illustrated how the apparent variability in population growth gradually decreases with increasing initial population size (N0). For bacterial populations withN0of >100 cells, the variability is almost eliminated and the system seems to behave deterministically, even though the underlying law is stochastic. We also used the model to demonstrate the effect of the presence and extent of a nongrowing population fraction on the stochastic growth of bacterial populations.


2016 ◽  
Vol 22 (11) ◽  
pp. 1732-1746 ◽  
Author(s):  
Ferhan M. Atıcı ◽  
Gang Cheng ◽  
Alex Lebedinsky

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
J. R. Nicolás-Carlock ◽  
J. L. Carrillo-Estrada ◽  
V. Dossetti

Sign in / Sign up

Export Citation Format

Share Document