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on Evolutionary Economics |
| By: | Paolo Melindi Ghidi (BETA - Bureau d'Economie Théorique et Appliquée - Université de Strasbourg - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - Université de la Méditerranée - Aix-Marseille 2 - Université Paul Cézanne - Aix-Marseille 3 - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - Ecole Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique); Thomas Seegmuller (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - Université de la Méditerranée - Aix-Marseille 2 - Université Paul Cézanne - Aix-Marseille 3 - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - Ecole Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | As illustrated by some French departments, how can we explain the existence of equilibria with different fertility and growth rates in economies with the same fundamentals, preferences, technologies and initial conditions? To answer this question we develop an endogenous growth model with altruism and love for children. We show that independently from the type of altruism, a multiplicity of equilibria might emerge if the degree of love for children is high enough. We refer to this condition as the love for children hypothesis. Then, the fertility rate is determined by expectations on the future growth rate and the dynamics are not path-dependent. Our model is able to reproduce different fertility behaviours in a context of completed demographic transition independently from fundamentals, preferences, technologies and initial conditions. |
| Keywords: | fertility,love for children,expectations,endogenous growth,balanced growth path |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-01498173&r=evo |
| By: | Bohren, Aislinn; Hauser, Daniel |
| Abstract: | We explore model misspecification in an observational learning framework. Individuals learn from private and public signals and the actions of others. An agent's type specifies her model of the world. Misspecified types have incorrect beliefs about the signal distribution, how other agents draw inference and/or others' payoffs. We establish that the correctly specified model is robust in that agents with approximately correct models almost surely learn the true state asymptotically. We develop a simple criterion to identify the asymptotic learning outcomes that arise when misspecification is more severe. Depending on the nature of the misspecification, learning may be correct, incorrect or beliefs may not converge. Different types may asymptotically disagree, despite observing the same sequence of information. This framework captures behavioral biases such as confirmation bias, false consensus effect, partisan bias and correlation neglect, as well as models of inference such as level-k and cognitive hierarchy. |
| Keywords: | bounded rationality; model misspecification; Social learning |
| JEL: | D82 D83 |
| Date: | 2017–05 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:12036&r=evo |
| By: | Siwan Anderson; Debraj Ray |
| Abstract: | o developed countries, there are far fewer women than men in parts of the developing world. Estimates suggest that more than 200 million women are demographically missing’ worldwide. To explain the global ‘missing women’ phenomenon, research has mainly ocused on excess female mortality in Asia. However, as emphasized in our earlier research, at least 0 per cent of the missing women are ‘missing’ from Africa. This paper employs a novel ethodology to determine how the phenomenon of missing women is distributed across Africa. oreover, it provides estimates of the extent of excess female mortality within different age groups nd by disease category. The empirical results reiterate the importance of excess female mortality or women in Africa. |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:unu:wpaper:wp2017-116&r=evo |