|
on Computational Economics |
|
Issue of 2016‒05‒14
four papers chosen by |
| By: | Lance Taylor (New School for Social Research); Özlem Ömer (New School for Social Research); Armon Rezai (Vienna University of Economics) |
| Abstract: | US household wealth concentration is not likely to decline in response to fiscal interventions alone. Creation of an independent public wealth fund could lead to greater equality. Similarly, once-off tax/transfer packages or wage increases will not reduce income inequality significantly; on-going wage increases in excess of productivity growth would be needed. These results come from the accounting in a simulation model based on national income and financial data. The theory behind the model borrows from ideas that originated in Cambridge UK (especially from Luigi Pasinetti and Richard Goodwin). |
| Keywords: | Wealth distribution, income distribution, Cambridge theory. |
| JEL: | D31 D33 D58 B50 |
| URL: | http://d.repec.org/n?u=RePEc:thk:wpaper:17&r=cmp |
| By: | Latynskiy, Evgeny; Berger, Thomas |
| Abstract: | In the recent past the coffee production sector witnessed a rapid expansion of certification programs promoting voluntary sustainability standards, one of which is UTZ Certified. In this article we assess the impact that this program has on participating smallholder farmers by reviewing the results of an agent-based simulation for modeling rural producer organizations. We present the developed empirical simulation model by sharing the common protocol, which documents the structure the applied simulation tool and its parameterization for the group of coffee farmers, and reporting the results of model validation. The main strength of this assessment is that it considers certification-related costs of the farmers, which are ignored in the analyses available so far. The obtained simulation results constitute quantitative evidence of UTZ certification being able to create considerable positive impacts on the participating farmers. The results outline the importance of external financing and supportive measures complementing certification in groups. |
| Keywords: | commercialization, rural producer organizations, multi-agent systems, sustainability standards, Uganda, Agricultural and Food Policy, Environmental Economics and Policy, C61, C63, D12, Q12, Q13, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:iaae15:229069&r=cmp |
| By: | Yves-Laurent Kom Samo; Alexander Vervuurt |
| Abstract: | In this paper we propose a novel application of Gaussian processes (GPs) to financial asset allocation. Our approach is deeply rooted in Stochastic Portfolio Theory (SPT), a stochastic analysis framework introduced by Robert Fernholz that aims at flexibly analysing the performance of certain investment strategies in stock markets relative to benchmark indices. In particular, SPT has exhibited some investment strategies based on company sizes that, under realistic assumptions, outperform benchmark indices with probability 1 over certain time horizons. Galvanised by this result, we consider the inverse problem that consists of learning (from historical data) an optimal investment strategy based on any given set of trading characteristics, and using a user-specified optimality criterion that may go beyond outperforming a benchmark index. Although this inverse problem is of the utmost interest to investment management practitioners, it can hardly be tackled using the SPT framework. We show that our machine learning approach learns investment strategies that considerably outperform existing SPT strategies in the US stock market. |
| Date: | 2016–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1605.02654&r=cmp |
| By: | Sebastian Herrmann (Johannes Gutenberg University Mainz); Gabriela Ochoa (University of Stirling); Franz Rothlauf (Johannes Gutenberg University Mainz) |
| Abstract: | We conduct an analysis of local optima networks extracted from ?tness landscapes of the Kauffman NK model under iterated local search. Applying the Markov Cluster Algorithm for community detection to the local optima networks, we ?nd that the landscapes consist of multiple clusters. This result complements recent ?ndings in the literature that landscapes often decompose into multiple funnels, which increases their difficulty for iterated local search. Our results suggest that the number of clusters as well as the size of the cluster in which the global optimum is located are correlated to the search difficulty of landscapes. We conclude that clusters found by community detection in local optima networks offer a new way to characterize the multi-funnel structure of ?tness landscapes. |
| Keywords: | Fitness landscape analysis; search difficulty; local optima networks; NK-landscapes. |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:jgu:wpaper:1609&r=cmp |