nep-cmp New Economics Papers
on Computational Economics
Issue of 2008‒04‒21
five papers chosen by
Stan Miles
Thompson Rivers University

  1. WATER SCARCITY AND THE IMPACT OF IMPROVED IRRIGATION MANAGEMENT: A CGE ANALYSIS By Alvaro Calzadilla; Katrin Rehdanz; Richard S.J. Tol
  2. Learning by Doing vs. Learning from Others in a Principal-Agent Model By Jasmina Arifovic; Alexander Karaivanov
  3. "A Hybrid Asymptotic Expansion Scheme:an Application to Long-term Currency Options" By Akihiko Takahashi; Kohta Takehara
  4. Optimally solving the Alternative Subgraphs Assembly Line Balancing Problem By Armin Scholl; Malte Fliedner; Nils Boysen; Malte Fliedner
  5. Balancing assembly lines with variable parallel workplaces: Problem definition, model and exact solution procedure By Christian Becker; Armin Scholl

  1. By: Alvaro Calzadilla; Katrin Rehdanz; Richard S.J. Tol (Economic and Social Research Institute)
    Abstract: We use the new version of the GTAP-W model to analyze the economy-wide impacts of enhanced irrigation efficiency. The new production structure of the model, which introduces a differentiation between rainfed and irrigated crops, allows a better understanding of the use of water resources in agricultural sectors. The results indicate that a water policy directed to improvements in irrigation efficiency in water-stressed regions is not beneficial for all. For water-stressed regions the effects on welfare and demand for water are mostly positive. For non-water scarce regions the results are more mixed and mostly negative. Global water savings are achieved. Not only regions where irrigation efficiency changes are able to save water, but also other regions are pushed to conserve water.
    Keywords: Computable General Equilibrium, Irrigation, Water Policy, Water Scarcity, Irrigation efficiency
    JEL: D58 Q17 Q25
    Date: 2008–04
    URL: http://d.repec.org/n?u=RePEc:sgc:wpaper:160&r=cmp
  2. By: Jasmina Arifovic (Simon Fraser University); Alexander Karaivanov (Simon Fraser University)
    Abstract: We introduce learning in a principal-agent model of stochastic output sharing under moral hazard. Without knowing the agents' preferences and technology the principal tries to learn the optimal agency contract. We implement two learning paradigms - social (learning from others) and individual (learning by doing). We use a social evolutionary learning algorithm (SEL) to represent social learning. Within the individual learning paradigm, we investigate the performance of reinforcement learning (RL), experience-weighted attraction learning (EWA), and individual evolutionary learning (IEL). Overall, our results show that learning in the principal-agent environment is very difficult. This is due to three main reasons: (1) the stochastic environment, (2) a discontinuity in the payoff space in a neighborhood of the optimal contract due to the participation constraint and (3) incorrect evaluation of foregone payoffs in the sequential game principal-agent setting. The first two factors apply to all learning algorithms we study while the third is the main contributor for the failure of the EWA and IEL models. Social learning (SEL), especially combined with selective replication, is much more successful in achieving convergence to the optimal contract than the canonical versions of individual learning from the literature. A modified version of the IEL algorithm using realized payoff evaluation performs better than the other individual learning models; however, it still falls short of the social learning's ability to converge to the optimal contract.
    Keywords: learning, principal-agent model, moral hazard
    JEL: D83 D86 C63
    Date: 2007–11
    URL: http://d.repec.org/n?u=RePEc:sfu:sfudps:dp07-24&r=cmp
  3. By: Akihiko Takahashi (Faculty of Economics, University of Tokyo); Kohta Takehara (Graduate School of Economics, University of Tokyo)
    Abstract: This paper develops a general approximation scheme, henceforth called a hybrid asymptotic expansion scheme for the valuation of multi-factor European path-independent derivatives. Specifically, we apply it to pricing long-term currency options under a market model of interest rates and a general diffusion stochastic volatility model with jumps of spot exchange rates. Our scheme is very effective for a type of models in which there exist correlations among all the factors whose dynamics are not necessarily affine nor even Markovian so long as the randomness is generated by Brownian motions. It can also handle models that include jump components under an assumption of their independence of the other random variables when the characteristic functions for the jump parts can be analytically obtained. An asymptotic expansion approach provides a closed-form approximation formula for their values, which can be calculated in a moment and thus can be used for calibration or for an explicit approximation of Greeks of options. Moreover, this scheme develops Fourier transform method with an asymptotic expansion as well as with closed-form characteristic functions obtainable in parts of a model. It also introduces a characteristic-function-based Monte Carlo simulation method with the asymptotic expansion as a control variable in order to make full use of analytical approximations by the asymptotic expansion and of the closed-form characteristic functions. Finally, a series of numerical examples shows the validity of our scheme. This paper develops a general approximation scheme, henceforth called a hybrid asymptotic expansion scheme for valuation of European derivatives. Specifically, we apply it to pricing longterm currency options under a market model of interest rates and a general stochastic volatility model with jumps of spot exchange rates. Our scheme is very effective for models which admits correlations among all factors whose dynamics are not necessarily affine nor even Markovian so long as the randomness is generated by Brownian motions. It can also handle jump components under an assumption of their independence of the other random variables when the characteristic functions for the jump parts can be analytically obtained. An asymptotic expansion approach provides a closed-form approximation formula calculated instantly and thus can be used for calibration or explicit approximations of Greeks. Moreover, this scheme develops Fourier transform method with an asymptotic expansion as well as with closed-form characteristic functions obtainable in parts of a model. It also introduces a characteristic-function-based Monte Carlo simulation method with the asymptotic expansion as a control variable to make full use of analytical approximations by the asymptotic expansion and the closed-form characteristic functions. Finally, a series of numerical examples shows the validity of our scheme.
    Date: 2008–04
    URL: http://d.repec.org/n?u=RePEc:tky:fseres:2008cf536&r=cmp
  4. By: Armin Scholl (Chair of Decision Analysis and Management Science, Friedrich-Schiller-University Jena); Malte Fliedner; Nils Boysen (Chair of Operations Management, Friedrich-Schiller-University Jena); Malte Fliedner (Institute of Industrial Management, University of Hamburg)
    Abstract: Assembly line balancing problems (ALBP) consist of distributing the total workload for manufacturing any unit of the products to be assembled among the work stations along a manufacturing line as used in the automotive or the electronics industries. Usually, it is assumed that the production process is fixed, i.e., has been determined in a preceding planning step. However, this sequential planning approach is often suboptimal because the efficiency of the production process can not be evaluated definitely with- out knowing the distribution of work. Instead, both decisions should be taken simultaneously. This has led to the Alternative Subgraphs ALBP.<BR> We give an alternative representation of the problem, formulate an improved mixed-integer program and propose a solution approach based on SALOME, an effective branch + bound procedure for the well-known Simple ALBP. Computational experiments indicate that the proposed procedure is success- ful in finding optimal solutions for small- and medium-sized problem instances and rather good heuris- tic solutions for large-scaled instances.
    Keywords: Assembly line balancing, Production process, Mass-production, Combinatorial optimization, Sequencing
    Date: 2008–04–08
    URL: http://d.repec.org/n?u=RePEc:jen:jenjbe:2008-05&r=cmp
  5. By: Christian Becker (Railion Deutschland AG); Armin Scholl (Chair of Decision Analysis and Management Science, Friedrich-Schiller-University Jena)
    Abstract: Assembly line balancing problems (ALBP) arise whenever an assembly line is con- figured, redesigned or adjusted. An ALBP consists of distributing the total workload for manu- facturing any unit of the products to be assembled among the work stations along the line sub- ject to a strict or average cycle time. Traditionally, stations are considered to be manned by one operator, respectively, or duplicated in form of identical parallel stations, each also manned by a single operator. In practice, this assumption is usually too restrictive. This is particularly true for large products like cars, trucks, busses and machines, which can be handled by several op- erators performing different tasks at the same time. Only restricted research has been done on such parallel workplaces within the same station though they have significant relevance in real- world assembly line settings.<BR> In this paper, we consider an extension of the basic ALBP to the case of flexible parallel work- places (VWALBP) as they typically occur in the automobile and other industries assembling large products. The problem is defined and modelled as an integer linear program. As a solution approach a branch-and-bound procedure is proposed which also can be applied as a heuristic. Finally, computational experiments documenting the solution capabilities of the procedure are reported.
    Keywords: Assembly line balancing, Mass-production, Combinatorial optimization, Sequencing
    Date: 2008–04–08
    URL: http://d.repec.org/n?u=RePEc:jen:jenjbe:2008-06&r=cmp

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