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on Computational Economics |
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Issue of 2006‒05‒06
three papers chosen by |
| By: | Carceles-Poveda, Eva; Giannitsarou, Chryssi |
| Abstract: | We analyse some practical aspects of implementing adaptive learning in the context of forward-looking linear models. In particular, we focus on how to set initial conditions for three popular algorithms, namely recursive least squares, stochastic gradient and constant gain learning. We propose three ways of initializing, one that uses randomly generated data, a second that is ad-hoc and a third that uses an appropriate distribution. We illustrate, via standard examples, that the behaviour and evolution of macroeconomic variables not only depend on the learning algorithm, but on the initial conditions as well. Furthermore, we provide a computing toolbox for analysing the quantitative properties of dynamic stochastic macroeconomic models under adaptive learning. |
| Keywords: | adaptive learning; computational methods; least square estimations; short-run dynamics |
| JEL: | C63 D83 E10 |
| Date: | 2006–04 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:5627&r=cmp |
| By: | Mark Neal (Risk and Sustainable Management Group, University of Queensland) |
| Abstract: | Introducing a stocking rate restriction is one possible course of action for regulators to improve water quality where it is affected by nitrate pollution. To determine the impact of a stocking rate restriction on a range of New Zealand dairy farms, a whole-farm model was optimised with and without a maximum stocking rate of 2.5 cows per hectare. Three farm systems, which differ by their level of feed-related capital, were examined for the changes to the optimal stocking rate and optimal level of animal milk production genetics when utility was maximised. The whole-farm model was optimised through the use of an evolutionary algorithm called differential evolution. The introduction of a stocking rate restriction would have a very large impact on the optimally organised high feed-related capital farm systems, reducing their certainty equivalent by almost half. However, there was no impact on the certainty equivalent of low feed-related capital systems. |
| Keywords: | environmental regulation, dairy farms, whole-farm model, evolutionary algorithm |
| JEL: | Q12 Q52 C61 |
| Date: | 2005–12 |
| URL: | http://d.repec.org/n?u=RePEc:rsm:murray:m05_8&r=cmp |
| By: | Leonardo Gasparini; Mariana Marchionni (Centro de Estudios Distributivos, Laborales y Sociales (CEDLAS) - Universidad Nacional de La Plata; Centro de Estudios Distributivos, Laborales y Sociales (CEDLAS) - Universidad Nacional de La Plata); Federico H. Gutierrez (Centro de Estudios Distributivos, Laborales y Sociales (CEDLAS) - Universidad Nacional de La Plata) |
| Abstract: | This paper uses microeconometric simulations to characterize the distributional changes occurred in the Bolivian economy in the period 1993-2002, and to assess the potential distributional impact of various alternative economic scenarios for the next decade. Wage equations for urban and rural areas estimated by both OLS and quantile regression are the main inputs for the microsimulations. A sizeable increase in the dispersion in worker unobserved wage determinants is the main factor behind the significant increase in household income inequality in the 90s. The results of the microsimulations suggest a small poverty-reducing effect of several potential scenarios, including education upgrading, sectoral transformations, labor informality reduction, gender and race wage gap closing, and changes in the structure of the returns to education. Sustainable and vigorous productivity growth seems to be a necessary condition for Bolivia to meet the poverty Millennium Development Goal by 2015. |
| Keywords: | distribution, Bolivia, wages, decompositions, quantile, education, MDG |
| JEL: | C15 D31 I21 J23 J31 |
| Date: | 2004–08 |
| URL: | http://d.repec.org/n?u=RePEc:dls:wpaper:0012&r=cmp |