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on Computational Economics |
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Issue of 2005‒01‒09
four papers chosen by |
| By: | Katarzyna Miakisz; Edward W. Piotrowski; Jan Sladkowski |
| Abstract: | On grounds of the discussed material, we reason about possible future development of quantum game theory and its impact on information processing and the emerging information society. The idea of quantum artificial intelligence is explained. |
| URL: | http://d.repec.org/n?u=RePEc:sla:eakjkl:21&r=cmp |
| By: | Bargain, Olivier (IZA Bonn and DELTA, Paris); Moreau, Nicolas (Université Laval and CIRPÉE) |
| Abstract: | The literature on household behavior contains hardly any empirical research on the withinhousehold distributional effect of tax-benefit policies. We simulate this effect in the framework of a collective model of labor supply when shifting from a joint to an individual taxation system in France. We show that the net-of-tax relative earning potential of the wife is a significant determinant of intrahousehold negotiation but with very low elasticity. Consequently, the labor supply responses to the reform are entirely driven by the traditional substitution and income effects as in a unitary model. For some households only, the reform alters the intrahousehold distribution in a way that tends to change normative conclusions. A sensitivity analysis shows that the collective model would be required if the tax reform was both radical and of extended scope. |
| Keywords: | collective model, intrahousehold allocation, household labor supply, tax reform |
| JEL: | C71 D11 D12 H31 J22 |
| Date: | 2005–01 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp1451&r=cmp |
| By: | Enriqueta Aragones (Autonomous University of Barcelona - Institut d'Anàlisi Econòmica (CSIC)); Itzhak Gilboa (Eitan Berglas School of Economics, Tel Aviv University); Andrew Postlewaite (Department of Economics, University of Pennsylvania); David Schmeidler (Eitan Berglas School of Economics, Tel Aviv University) |
| Abstract: | People may be surprised by noticing certain regularities that hold in existing knowledge they have had for some time. That is, they may learn without getting new factual information. We argue that this can be partly explained by computational complexity. We show that, given a knowledge base, finding a small set of variables that obtain a certain value of R2 is computationally hard, in the sense that this term is used in computer science. We discuss some of the implications of this result and of fact-free learning in general. |
| Keywords: | Learning, Behavioral Economics |
| JEL: | D11 |
| Date: | 2003–10–01 |
| URL: | http://d.repec.org/n?u=RePEc:pen:papers:05-002&r=cmp |
| By: | Jesús Fernández-Villaverde; Juan F. Rubio-Ramirez; Manuel Santos |
| Date: | 2005–01–04 |
| URL: | http://d.repec.org/n?u=RePEc:cla:levrem:122247000000000822&r=cmp |