nep-cmp New Economics Papers
on Computational Economics
Issue of 2011‒07‒02
twelve papers chosen by
Stan Miles
Thompson Rivers University

  1. Returns to scale, productivity and efficiency in US banking (1989-2000): the neural distance function revisited By Panayotis G. Michaelides; Angelos T. Vouldis; Efthymios G. Tsionas
  2. Exploring the polycentric city with an agent-based model By Rémi Lemoy; Charles Raux; Pablo Jensen
  3. Multilevel Monte Carlo method for jump-diffusion SDEs By Yuan Xia
  4. Impact of tax rate cut cum base broadening reforms on heterogeneous firms: Learning from the German tax reform 2008 By Finke, Katharina; Heckemeyer, Jost H.; Reister, Timo; Spengel, Christoph
  5. A stochastic programming model of the sowing plan with crop succession restrictions By Jitka Janová
  6. How do ex ante simulations compare with ex post evaluations ? evidence from the impact of conditional cash transfer programs By Leite, Phillippe; Narayan, Ambar; Skoufias, Emmanuel
  7. Studio di un indicatore per la valutazione del rischio delprogetto nella metodologia dell’analisi costi benefici - Proposed risk indicators in the cost-benefit analisys methodology By Mario Genco
  8. Credit Market Imperfection and Sectoral Asymmetry of Chinese Business Cycle By Yuanyan Sophia Zhang
  9. Machine Learning Markets By Amos Storkey
  10. Chaos structures. Multicurrency adviser on the basis of NSW model and social-financial nets By A. M. Avdeenko
  11. Geometric Allocation Approach for Transition Kernel of Markov Chain By Hidemaro Suwa; Synge Todo
  12. Decision Support Systems and the Economics of Seeding Rate in Crop Yield By Mohamed, Issam A.W.

  1. By: Panayotis G. Michaelides (National Technical University of Athens); Angelos T. Vouldis (Bank of Greece); Efthymios G. Tsionas (Athens University of Economics and Business)
    Abstract: Productivity and efficiency analyses have been indispensable tools for evaluating firms’ performance in the banking sector. In this context, the use of Artificial Neural Networks (ANNs) has been recently proposed in order to obtain a globally flexible functional form which is capable of approximating any existing output distance function while enabling the a priori imposition of the theoretical properties dictated by production theory, globally. Previous work has proposed and estimated the so-called Neural Distance Function (NDF) which has numerous advantages when compared to widely adopted specifications. In this paper, we carefully refine some of the most critical characteristics of the NDF. First, we relax the simplistic assumption that each equation has the same number of nodes because it is not expected to approximate reality with any reasonable accuracy and different numbers of nodes are allowed for each equation of the system. Second, we use an activation function which is known to achieve faster convergence compared to the conventional NDF model. Third, we use a relevant approach for technical efficiency estimation based on the widely adopted literature. Fitting the model to a large panel data we illustrate our proposed approach and estimate the Returns to Scale, the Total Factor Productivity and the Technical Efficiency in US commercial banking (1989-2000). Our approach provides very satisfactory results compared to the conventional model, a fact which implies that the refined NDF model successfully expands and improves the conventional NDF approach.
    Keywords: Output distance function; Neural networks; Technical efficiency; US banks
    JEL: C50 C45 C30
    Date: 2011–03
  2. By: Rémi Lemoy (LET - Laboratoire d'économie des transports - CNRS : UMR5593 - Université Lumière - Lyon II - Ecole Nationale des Travaux Publics de l'Etat, IXXI - Institut Rhône-Alpin des systèmes complexes - INRIA - École Normale Supérieure de Lyon - Institut National des Sciences Appliquées de Lyon - Université Claude Bernard - Lyon I - Université Joseph Fourier - Grenoble I - CNRS - IRD - École Normale Supérieure de Lyon); Charles Raux (LET - Laboratoire d'économie des transports - CNRS : UMR5593 - Université Lumière - Lyon II - Ecole Nationale des Travaux Publics de l'Etat, IXXI - Institut Rhône-Alpin des systèmes complexes - INRIA - École Normale Supérieure de Lyon - Institut National des Sciences Appliquées de Lyon - Université Claude Bernard - Lyon I - Université Joseph Fourier - Grenoble I - CNRS - IRD - École Normale Supérieure de Lyon); Pablo Jensen (LET - Laboratoire d'économie des transports - CNRS : UMR5593 - Université Lumière - Lyon II - Ecole Nationale des Travaux Publics de l'Etat, IXXI - Institut Rhône-Alpin des systèmes complexes - INRIA - École Normale Supérieure de Lyon - Institut National des Sciences Appliquées de Lyon - Université Claude Bernard - Lyon I - Université Joseph Fourier - Grenoble I - CNRS - IRD - École Normale Supérieure de Lyon, Phys-ENS - Laboratoire de Physique de l'ENS Lyon - CNRS : UMR5672 - École Normale Supérieure de Lyon)
    Abstract: The standard urban economics model of Alonso, Muth, Mills, describes analytically an equilibrium location of households in urban areas. We present an agent-based model, using simple interactions between agents, and able to reach this equilibrium in a dynamic way. The agent-based model allows us to simulate the development of a city by combination of heterogeneous agents and the introduction of several work centers. This tool allows the addition of a wide variety of features to the standard urban economics model to study their effects. We focus here on the study of the polycentric city.
    Keywords: agent-based model ; urban economics ; location choice ; polycentric city
    Date: 2011–05–30
  3. By: Yuan Xia
    Abstract: We investigate the extension of the multilevel Monte Carlo path simulation method to jump-diffusion SDEs. We consider models with finite rate activity, using a jump-adapted discretisation in which the jump times are computed and added to the standard uniform dis- cretisation times. The key component in multilevel analysis is the calculation of an expected payoff difference between a coarse path simulation and a fine path simulation with twice as many timesteps. If the Poisson jump rate is constant, the jump times are the same on both paths and the multilevel extension is relatively straightforward, but the implementation is more complex in the case of state-dependent jump rates for which the jump times naturally differ.
    Date: 2011–06
  4. By: Finke, Katharina; Heckemeyer, Jost H.; Reister, Timo; Spengel, Christoph
    Abstract: The German corporate tax reform of 2008 has brought about important cuts in corporate tax rates, which were at the same time accompanied by significant changes in the determination of the tax base for both major German corporate taxes - corporate income tax and trade tax. The reform followed the distinct and internationally prevalent pattern of tax rate cut cum base broadening. Its implications are thus not unique to Germany. Especially in view of the current economic crisis, questions on the distribution of the tax burden among firms of different characteristics have arisen and still remain at the heart of the academic and political debate in Germany and other countries. In this paper we present a new corporate microsimulation model, ZEW TaxCoMM, which allows for the coherent micro-based analysis of revenue implications of tax reforms and the distribution of tax consequences among heterogeneous firms. The model processes firm-level financial accounting input data and derives the firm specific tax base and tax due endogenously in accordance with the tax code. To smooth out distortions between the sample and the population of German corporations, the sample is extrapolated on the basis of the corporate income tax statistic. The simulation results show inter alia that the average annual relief as measured by the average decline in the effective tax burden on cash flow amounts to 2.8 percentage points for large corporations and to 6 percentage points for small corporations. Furthermore, the results illustrate that firms with low profitability, high debt ratio and high capital intensity benefit least from the reform. As to tax revenues, the reform induced decrease amounts to 9.8 billion and the trade tax gains fiscally in importance. --
    Keywords: Tax reform,microsimulation,tax policy evaluation
    JEL: H25 H32 K34 C8
    Date: 2011
  5. By: Jitka Janová (Department of Statistics and Operational Research, FBE MENDELU in Brno)
    Abstract: A user-friendly decision support model for agricultural production planning in the Czech Republic is developed covering both the randomness of harvest parameters entering the decision problem and the complex crop succession requirements. The methods of stochastic programming are applied and the linear re-sowing constraints are developed, described in detail and incorporated in such a way that the model can be approached by software tools commonly available at farms. The model abilities are demonstrated in the particular case of production planning decision making in the South Moravian farm. The re-sowing constraints themselves are verified with respect to covering the local crop succession requirements and the validation of the model as a whole is performed using a Monte Carlo simulation.
    Keywords: stochastic programming, crop rotation, crop plan, agriculture optimization
    JEL: C44 C61 Q15
    Date: 2011–06
  6. By: Leite, Phillippe; Narayan, Ambar; Skoufias, Emmanuel
    Abstract: This paper compares the ex ante simulation of the impacts of conditional cash transfer programs against the ex post estimates of impacts obtained from experimental evaluations. Using data on program-eligible households in treatment areas from the same baseline surveys that are used for experimental evaluations of conditional cash transfer programs in Mexico and Ecuador, the authors use a micro-simulation model to derive ex ante estimates of the impact of the programs on enrollment rates and poverty. The estimates reveal that ex ante predictions of certain impacts of conditional cash transfer programs match up well against the benchmark estimates of ex post experimental studies. The findings seem to support the use of this model to assess the potential impact and cost efficiency of a conditional cash transfer program ex ante, in order to inform decisions about how the program would be designed.
    Keywords: Poverty Monitoring&Analysis,Scientific Research&Science Parks,Science Education,Youth and Governance,Primary Education
    Date: 2011–06–01
  7. By: Mario Genco (Centre for Industrial Studies (CSIL))
    Abstract: Cost-benefit analysis allows to assess in advance the performance of investment projects through the calculation of appropriate indices, such as the NPV, the IRR, the B/C ratio. Performance indicators are, however, affected by the uncertainty inherent in the exercise of forecasting the future values of the physical and economic parameters generated by the project. Probability distribution of the expected values of each performance indicator can be determined, e.g., through Montecarlo simulations of the CBA model. Derived from the simulated probability distribution, the paper, starting from the definition of the loss function in the statistical decision theory, proposes a set of risk indicators (Index of absolute risk, Index of internal relative risk, Index of generalized relative risk), which include a "weight" function that models the level of aversion against the expected loss of the performance indices by the person who will bear the project risk.
    Keywords: risk analysis, risk adversion, Montecarlo simulation, cost benefit analysis - rischio, avversione al rischio, simulazione Montecarlo, analisi costi benefici
    JEL: D81
    Date: 2011–04–01
  8. By: Yuanyan Sophia Zhang
    Abstract: This paper analyzes the role of credit market imperfection and sectoral asymmetry as a means through which shocks to the real economy are propagated and amplified. Drawing on firm-level data to calibrate the model, our simulations capture two key stylized facts of the Chinese economy: that credit constraints are more binding in nontradable sectors than in tradable industries and that output volatility is much greater in China than in industrial economies. We find that the driving force behind our simulation results is strongly related to the non-uniform nature of credit market imperfections in China and their implications for resource allocation and the way in which the economy reacts to shocks. Correctly capturing these macro-financial interactions are essential to understand the dynamic behavior of the Chinese economy.
    Keywords: Business cycles , China , Credit , Economic models ,
    Date: 2011–05–23
  9. By: Amos Storkey
    Abstract: Prediction markets show considerable promise for developing flexible mechanisms for machine learning. Here, machine learning markets for multivariate systems are defined, and a utility-based framework is established for their analysis. This differs from the usual approach of defining static betting functions. It is shown that such markets can implement model combination methods used in machine learning, such as product of expert and mixture of expert approaches as equilibrium pricing models, by varying agent utility functions. They can also implement models composed of local potentials, and message passing methods. Prediction markets also allow for more flexible combinations, by combining multiple different utility functions. Conversely, the market mechanisms implement inference in the relevant probabilistic models. This means that market mechanism can be utilized for implementing parallelized model building and inference for probabilistic modelling.
    Date: 2011–06
  10. By: A. M. Avdeenko
    Abstract: Algorithm of multicurrency trading at the market of Forex is realized on the basis of nonlinear stochastic wavelets. The distinctive feature of the algorithm is the possibility of weakly- and strongly connected horizontal self-assemblies, as well as use of nested structures. On-line trading with eight currency couples has shown high effectiveness and stability of the algorithm. It is discussed the problem of possibility of excess profit earning in electronic markets via development of social-financial nets based on synchronization of work of individual traders by means of proposed algorithm.
    Date: 2011–06
  11. By: Hidemaro Suwa; Synge Todo
    Abstract: We introduce a new geometric approach that constructs a transition kernel of Markov chain. Our method always minimizes the average rejection rate and even reduce it to zero in many relevant cases, which cannot be achieved by conventional methods, such as the Metropolis-Hastings algorithm or the heat bath algorithm (Gibbs sampler). Moreover, the geometric approach makes it possible to find not only a reversible but also an irreversible solution of rejection-free transition probabilities. This is the first versatile method that can construct an irreversible transition kernel in general cases. We demonstrate that the autocorrelation time (asymptotic variance) of the Potts model becomes more than 6 times as short as that by the conventional Metropolis-Hastings algorithm. Our algorithms are applicable to almost all kinds of Markov chain Monte Carlo methods and will improve the efficiency.
    Date: 2011–06
  12. By: Mohamed, Issam A.W.
    Abstract: The present study constructs a decision support system to determine the best seeding rate out of a group of seeding rates applied in the field. The DSS has been built receives the field data as inputs, and then apply split plot algorithms of (Gomez & Gomez, 1984) to find the results. These results showed in stepwise manner and specifically similar to that of the manual processing, hence it is so easy to understand. The DSS specific is four folds seeding rates with two cultivars of the crop.
    Keywords: Informatics; Decision Support System;Seeding Rate; Productivity
    JEL: D2 D81 A1 A10 C4 O1 C44 N5 D8 D83 L15
    Date: 2011

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