Learning to save in a voluntary pension system: toward an agent-based model by András SIMONOVITS and Balázs KIRÁLY was published in Journal of Economic Interaction and Coordination.
Mandatory pension systems partially replace old-age income, therefore the government matches additional life-cycle savings in a voluntary pension system. Though the individual saving decisions are apparently independent, the earmarked taxes (paid to finance the matching) connect them. Previous models either neglected the endogenous tax expenditures (e.g. Choi et al., in: Wise (ed) Perspectives in the economics of aging, University of Chicago Press, Chicago, pp 81–121, 2004) or assumed very sophisticated saving strategies (e.g. Fehr et al. in FinanzArchiv Pub Finance Anal 64:171–198, 2008). We create twin models: myopic workers learn (i) from farsighted workers using public information (analytic model) and (ii) also from each other (agent-based model). These models provide more realistic results on saving behavior and the impact of matching on the income redistribution than the earlier models.
Venue: MTA HTK 1097 Budapest Tóth Kálmán u. 4. fszt. K0.11-12 István KÓNYA, Judit KREKÓ, Gábor OBLATH Labor shares in the EU sectoral effects and the role of relative prices The paper studies the labor ... Details »
Venue: MTA HTK 1097 Budapest Tóth Kálmán u. 4. fszt. K0.11-12 Róbert SOMOGYI: Prioritization vs Zero-rating: Discrimination on the Internet Abstract: This paper analyzes two business practices on the mobile internet market, paid prioritization and zero-rating. ... Details »
“Do CAP subsidies stabilise farm income in Hungary and Slovenia?” by Imre FERTŐ and Stefan BOJNEC in Agricultural Economics: Do CAP subsidies stabilise farm ... Details »
Learning to save in a voluntary pension system: toward an agent-based model by András SIMONOVITS and Balázs KIRÁLY was published in Journal of Economic ... Details »
Ambient temperature and sexual activity: Evidence from time use surveys by Tamás HAJDU and Gábor HAJDU was published in Demographic Research. Abstract Background: Previous ... Details »