New Economics Papers
on Computational Economics
Issue of 2007‒06‒11
seven papers chosen by

  1. The economic impacts of a construction project, using SinoTERM, a multi-regional CGE model of China By Mark Horridge; Glyn Wittwer
  2. Globe: A SAM Based Global CGE Model using GTAP Data By Karen Thierfelder; Scott McDonald; Sherman Robinson
  3. Testing the Martingale Difference Hypothesis Using Neural Network Approximations By George Kapetanios; Andrew P. Blake
  4. A Monte Carlo approach to value exchange options using a single stochastic factor By Giovanni Villani
  5. Level Scheduling of Mixed-Model Assembly Lines under Storage Constraints By Nils Boysen; Malte Fliedner; Armin Scholl
  6. Yxilon – A Client/Server Based Statistical Environment By Wolfgang Härdle; Sigbert Klinke; Uwe Ziegenhagen
  7. Estimating Probabilities of Default With Support Vector Machines By Wolfgang Härdle; Rouslan Moro; Dorothea Schäfer

  1. By: Mark Horridge; Glyn Wittwer
    Abstract: The paper outlines the theory and database preparation of SinoTERM, a "bottom-up" computable general equilibrium model of the Chinese economy. The methodology by which we construct the multi-regional model allows us to present the economy of China in an unprecedented amount of detail. SinoTERM covers all 31 provinces and municipalities. The database of the model extends the published national input-output table for 2002 to 137 sectors. The single crops sector in the published national input-output table is split into 11 and the single livestock sector into 3. The multi-regional CGE model provides a framework that we could modify to apply to many different policy applications. We can use SinoTERM to analyse the regional economic impacts of region-specific shocks. Such shocks could major construction projects or investments in health and education sectors, in an effort to accelerate economic growth in the lagging inland provinces. We use a 63 sector, 10 region aggregation of the SinoTERM master database to model the regional economic impacts of the proposed Chongqing-Lichuan rail link construction project.
    Keywords: CGE modelling, regional modelling, construction projects
    JEL: C68 R13 L74
    Date: 2007–06
  2. By: Karen Thierfelder (United States Naval Academy); Scott McDonald (The University of Sheffield); Sherman Robinson (University of Sussex)
    Abstract: This paper provides a technical description of a global computable general equilibrium (CGE) model that is calibrated from a Social Accounting Matrix (SAM) representation of the Global Trade Analysis Project (GTAP) database. An important feature of the model is the treatment of nominal and real exchange rates and hence the specification of multiple numéraire. Another distinctive feature of the model is the use of a ‘dummy’ region, known as globe, that allows for the recording of inter regional transactions where either the source or destination are not identified.
    Date: 2007–06
  3. By: George Kapetanios (Queen Mary, University of London); Andrew P. Blake (Bank of England)
    Abstract: The martingale difference restriction is an outcome of many theoretical analyses in economics and finance. A large body of econometric literature deals with tests of that restriction. We provide new tests based on radial basis function neural networks. Our work is based on the test design of Blake and Kapetanios (2000, 2003a,b). However, unlike that work we can provide a formal theoretical justification for the validity of these tests using approximation results from Kapetanios and Blake (2007). These results take advantage of the link between the algorithms of Blake and Kapetanios (2000, 2003a,b) and boosting. We carry out a Monte Carlo study of the properties of the new tests and find that they have superior power performance to all existing tests of the martingale difference hypothesis we consider. An empirical application to the S&P500 constituents illustrates the usefulness of our new test.
    Keywords: Martingale difference hypothesis, Neural networks, Boosting
    JEL: C14
    Date: 2007–06
  4. By: Giovanni Villani
    Abstract: Exchange options give the holder the right to exchange one risky asset V for another risky asset D. The asset V is referred to as the optioned (underlying) asset, while D is the delivery asset. So, when an exchange option is valued, we generally are exposed to two sources of uncertainity, namely we have two stochastic variables. Exchange options arise quite naturally in a number of signi¯cant ¯nancial arrangements including bond futures contracts, investment performance, options whose strike price is an average of the experienced underlying asset price during the life ot the option and so on. In this paper we propose some algorithms to estimate exchange options by Monte Carlo simulation reducing the bi-dimensionality of valuation problem to single stochastic factor.
    Keywords: Exchange Options; Monte Carlo Simulations.
    JEL: G13 C15
    Date: 2007–05
  5. By: Nils Boysen (Universität Hamburg, Institut für Industrielles Management); Malte Fliedner (Universität Hamburg, Institut für Industrielles Management); Armin Scholl (University of Jena, Faculty of Economics)
    Abstract: In a mixed-model assembly line dierent models of a common base product can be manufactured in intermixed production sequences. A famous solution approach for the resulting short-term sequencing problem is the so called level scheduling problem, which aims at evenly smoothing the material requirements over time in order to facilitate a just-in-time supply. However, if materials are delivered in discrete quantities, the resulting spreading of material usages implies that issued cargo carriers of a respective material remain at a station for a longer period of time. In practical applications with plenty materials required per station, this procedure might lead to bottlenecks with respect to the scarce storage space at stations. This paper investigates level scheduling under the constraint that the induced part usage patterns may not violate given storage constraints. The resulting sequencing problem is formalized and solved by suited exact and heuristic solution approaches.
    Keywords: Mixed-Model Assembly Lines, Sequencing, Dynamic Programming, Simulated Annealing
    Date: 2007–05–29
  6. By: Wolfgang Härdle; Sigbert Klinke; Uwe Ziegenhagen
    Abstract: Along with many others, we agree that a modern education in statistics needs to incorporate the practical analysis of real datasets, which are usually more complex than the common examples found in standard textbooks. The software used in the teaching of statistics includes standard spreadsheet environments such as OpenOffice and Excel and dedicated commercial and non-commercial packages such as R, Minitab or SPSS. With the freely available Yxilon environment we add another package and proliferate the statistical programming language XploRe, using a modern client/server based architecture. This architecture has the capabilities of serving statistical results in a variety of flavors for different groups of users. In this paper we describe the general setup of the Yxilon environment and present selected technical details.
    Keywords: E-learning, Statistical Software.
    JEL: C88
    Date: 2007–06
  7. By: Wolfgang Härdle; Rouslan Moro; Dorothea Schäfer
    Abstract: This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of testing our approach on German Bundesbank data. In particular we discuss the selection of variables and give a comparison with more traditional approaches such as discriminant analysis and the logit regression. The results demonstrate that the SVM has clear advantages over these methods for all variables tested.
    Keywords: Bankruptcy, Company rating, Default probability, Support vector machines.
    JEL: C14 G33 C45
    Date: 2007–06

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