nep-cmp New Economics Papers
on Computational Economics
Issue of 2006‒02‒19
six papers chosen by
Stan Miles
York University

  1. Smart Business Networks Design and Business Genetics By Pau, L-F.
  2. SOLVING NONLINEAR DYNAMIC STOCHASTIC MODELS: AN ALGORITHM COMPUTING VALUE FUNCTIONS BY SIMULATIONS By Lilia Maliar; Serguei Maliar
  3. PARAMETERIZED EXPECTATIONS ALGORITHM: HOW TO SOLVE FOR LABOR EASILY By Lilia Maliar; Serguei Maliar
  4. Introducing Imperfect Competition in CGE Models: Technical Aspects and Implications By Roberto Roson
  5. Designing Efficient Policies in a Regional Economy. A MCDM-CGE Approach By Francisco J. André; M. Alejandro Cardenete Flores
  6. A SIMULATION APPROACH TO THE VALUATION OF CAPITAL BUDGETING PROJECTS INCORPORATING A DEFER OPTION By Jorge Guardiola; Antonio Falcó

  1. By: Pau, L-F. (Erasmus Research Institute of Management (ERIM), RSM Erasmus University)
    Abstract: With the emergence of smart business networks, agile networks, etc. as important research areas in management, for all the attractiveness of these concepts, a major issue remains around their design and the selection rules. While smart business networks should provide advantages due to the quick connect of business partners for selected functions in a process common to several parties, literature does not provide constructive methods whereby the selection of temporary partners and functions can be done. Most discussions only rely solely on human judgment. This paper introduces both computational geometry, and genetic programming, as systematic methods whereby to display possible partnerships, and also whereby to plan for their effect on the organizations or functions of those involved. The two techniques are also been put in the context of emergence theory. Business maps address the first challenge with the use of Vorono? diagrams. Cellular automata, with genetic algorithms mimicking living bodies, address the second challenge. This paper does not include experimental results, which have been derived in the high tech area to determine especially the adequateness of systems integrators to set up joint ventures with smaller technology suppliers.
    Keywords: Smart Business Networks;Design of Smart business Network;Genetics;Cellular Automata;Emergence Theory;Computational Geometry;Vorono?;Smart Business Maps;Business Genetics;Technology Management;
    Date: 2006–02–01
    URL: http://d.repec.org/n?u=RePEc:dgr:eureri:30007959&r=cmp
  2. By: Lilia Maliar (Universidad de Alicante); Serguei Maliar (Universidad de Alicante)
    Abstract: This paper presents an algorithm for solving nonlinear dynamic stochastic models that computes value function by simulations. We argue that the proposed algorithm can be a useful alternative to the existing methods in some applications.
    Keywords: Nonlinear stochastic models; Value function; Parameterized expectations; Monte Carlo simulations; Numerical solutions
    JEL: C6 C63 C68
    Date: 2004–10
    URL: http://d.repec.org/n?u=RePEc:ivi:wpasad:2004-37&r=cmp
  3. By: Lilia Maliar (Universidad de Alicante); Serguei Maliar (Universidad de Alicante)
    Abstract: Euler-equation methods for solving nonlinear dynamic models involve parameterizing some policy functions. We argue that in the typical macroeconomic model with valuable leisure, labor function is particularly convenient for parameterizing. This is because under the labor-function parameterization, the intratemporal first-order condition admits a closed-form solution, while under other parameterizations, there should be a numerical solution. In the context of a simulation-based parameterized expectations algorithm, we find that using the labor-function parameterization instead of the standard consumption-function parameterization reduces computational time by more than a factor of ten.
    Keywords: Nonlinear models, Parameterized expectations, PEA, Monte Carlo simulation, Numerical solution
    JEL: C6 C63 C68
    Date: 2004–10
    URL: http://d.repec.org/n?u=RePEc:ivi:wpasad:2004-40&r=cmp
  4. By: Roberto Roson (Università Ca’ Foscari di Venezia)
    Abstract: This paper considers the technical aspects and the consequences, in terms of simulation results and policy assessment, of introducing imperfect competition in a CGE model. The modifications to the standard CGE framework needed to model imperfect competition in some industries are briefly discussed. Next, the paper discusses whether, how much and why, those changes may affect the qualitative output of a typical simulation experiment. It is argued that technical choices made in designing the model structure may have a significant impact on the model behavior. This is especially evident when the output of the model, under an imperfect competition closure, is compared with that obtained under a standard closure, assuming perfect competition. As an illustration, a scenario of agricultural trade liberalization under alternative market structures is analyzed.
    Keywords: Computable general equilibrium models, Imperfect competition, Oligopolistic models, Economies of scale, Empirical industrial organization, Agriculture, Trade liberalization, Trade policy
    JEL: D58 F12 L16
    Date: 2006–01
    URL: http://d.repec.org/n?u=RePEc:fem:femwpa:2006.3&r=cmp
  5. By: Francisco J. André (Universidad Pablo de Olavide de Sevilla); M. Alejandro Cardenete Flores (Universidad Pablo de Olavide de Sevilla)
    Abstract: Since policy makers usually pursue several conflicting objectives, policy making can be understood as a multicriteria decision problem. Following the methodological proposal in André and Cardenete (2005), we use multiobjective programming in connection with a computable general equilibrium model to represent optimal policy making and to get so-called efficient policies in an application to a regional economy (Andalusia, Spain). We illustrate the solution of two bicriteria problems (unemployment vs. inflation and growth vs. unemployment) from which we get a new reading of two classical results: the Phillips curve and the Okun law. Finally, we enlarge the scope of the exercise by solving a problem with five objectives and discuss the efficient solutions that can be obtained in this context.
    Keywords: Public Policy, Multicriteria Decision Making, Computable General Equilibrium Model, Efficient Policy.
    JEL: C61 C68 D78
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:cea:doctra:e2006_03&r=cmp
  6. By: Jorge Guardiola (Universidad Cardenal Herrera); Antonio Falcó (Universidad Cardenal Herrera)
    Abstract: Techniques applied to determine the value of derivatives have been recently exported in the field of investment valuation. This paper aims to provide some light to the use of a new technique in the investment valuation literature, aiming to take into account the value of flexibility. This technique, designed by Longstaff and Schwartz, combines Monte Carlo simulation and the Ordinary Least Squares in order to value American-style derivatives with different specifications. We show that this method can easily be incorporated to value capital budgeting projects in the framework of the real options theory and provides coherent results from an economic point of view. We do this by estimating the value of several cases of an investment project that incorporates an option to defer the initial investment or layout through time. We estimate these values by using the Ox programming language. Algunas técnicas aplicadas para determinar el valor de derivados han sidorecientemente exportadas en el campo de la valoración de inversiones. Este trabajo tienecomo objetivo clarificar el uso de una nueva técnica dentro de la literatura de valoraciónde inversiones, teniendo en cuenta el valor de flexibilidad. Esta técnica, diseñada porLongstaff y Schwartz, combina la simulación de Monte Carlo y los Mínimos CuadradosOrdinarios con el objetivo de valorar derivados de tipo americano con distintasespecificaciones. En este trabajo demostramos que este método puede ser fácilmenteincorporado para valorar proyectos de inversión en el marco de la teoría de opcionesreales y muestra resultados coherentes desde el punto de vista económico. Lo hacemosestimando el valor de distintos casos de un proyecto de inversión que incorpora unaopción de posponer la inversión inicial en el tiempo. Estimamos estos valores usando ellenguaje de programación Ox.
    Keywords: Least Squares Monte Carlo, opción de espera, movimiento geométrico Browniano, proyecto de inversión. Least Squares Monte Carlo, defer option, geometric Brownian motion, investment project.
    Date: 2004–11
    URL: http://d.repec.org/n?u=RePEc:ivi:wpasec:2004-22&r=cmp

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