nep-cmp New Economics Papers
on Computational Economics
Issue of 2014‒04‒29
eight papers chosen by
Stan Miles
Thompson Rivers University

  1. The Trade-off between Innovation and Defence Industrial Policy: A Simulation Model Analysis of the Norwegian Defence Industry By Blom, Martin; Castellacci, Fulvio; Fevolden, Arne
  2. Sand in the Wheels or Wheels in the Sand? Tobin Taxes and Market Crashes By Hynek Lavicka; Tomas Lichard; Jan Novotny
  3. National Soft Landing CO2 trajectories under global carbon budgets By Patrick Criqui; Constantin Ilasca; Emmanuel Prados
  4. Common Mistakes in Computing the Nucleolus By Guajardo, Mario; Jörnsten, Kurt
  5. Impatient in Experiments, but Patient in Simulations: A Challenge to a Neoclassical Model. By Emin Gahramanov; Xueli Tang
  6. TA Big Data Approach to Optimal Sales Taxation By Christian Baker; Jeremy Bejarano; Richard W. Evans; Kenneth L. Judd; Kerk L. Phillips
  7. Cluster analysis of weighted bipartite networks: a new copula-based approach By Alessandro Chessa; Irene Crimaldi; Massimo Riccaboni; Luca Trapin
  8. Longevity, Working Lives and Public Finances By Lassila, Jukka; Valkonen, Tarmo

  1. By: Blom, Martin; Castellacci, Fulvio; Fevolden, Arne
    Abstract: The paper investigates the trade-off between innovation and defence industrial policy. It presents an agent-based simulation model calibrated for the Norwegian defence industry that compares different policy scenarios and examines the effects of a pending EU market liberalization process. The paper points to two main results. (1) It finds that a pure scenario where national authorities focus on, and provide support exclusively for, either a) international competitiveness or b) national defence and security objectives, is more Pareto efficient than a corresponding mixed strategy where policy makers simultaneously pursue both international competitiveness and defence and security objectives. (2) Under the conditions of the new EU liberalization regime, a stronger and more visible trade-off will emerge between international competitiveness and national defence and security objectives. Policy makers will have to choose which to prioritise, and set a clear agenda focusing on one of the two objectives.
    Keywords: Innovation policy; industrial policy; defense industry; EU liberalization; agent-based simulation model
    JEL: C6 H0 L1 O3
    Date: 2014
  2. By: Hynek Lavicka; Tomas Lichard; Jan Novotny
    Abstract: The recent crisis revived interest in financial transaction taxes (FTTs) as a means to offset negative risk externalities. However, up-to-date academic research does not provide sufficient insights into the effects of transaction taxes on financial markets as the literature has here-to-fore been focused too narrowly on Gaussian variance as a measure of volatility. In this paper, we argue that it is imperative to understand the relationship between price jumps, Gaussian variance, and FTTs. While Gaussian variance is not necessarily a problem in itself, the non-normality of return distribution caused by price jumps affects not only the performance of many risk-hedging algorithms but directly influences the frequency of catastrophic market events. To study the aforementioned relationship, we use an agent-based model of financial markets. Its results show that FTTs may increase the variance while decreasing the impact of price jumps. This result implies that regulators may face a trade-off between overall variance and price jumps when designing optimal tax. However, the results are not robust to the size of the artificial market as non-linearities emerge when the size of the market is increased.
    Keywords: price jumps; financial transaction taxes; agent-based modeling; Monte Carlo; volatility;
    JEL: C15 C16 C61 G17 G18 H23
    Date: 2014–03
  3. By: Patrick Criqui (PACTE - Politiques publiques, ACtion politique, TErritoires - Institut d'Études Politiques [IEP] - Grenoble - CNRS : UMR5194 - Université Pierre-Mendès-France - Grenoble II - Université Joseph Fourier - Grenoble I); Constantin Ilasca (PACTE - Politiques publiques, ACtion politique, TErritoires - Institut d'Études Politiques [IEP] - Grenoble - CNRS : UMR5194 - Université Pierre-Mendès-France - Grenoble II - Université Joseph Fourier - Grenoble I); Emmanuel Prados (INRIA Grenoble Rhône-Alpes / LJK Laboratoire Jean Kuntzmann - STEEP - INRIA - Université Joseph Fourier - Grenoble I - Laboratoire Jean Kuntzmann - CNRS : UMR5224 - Institut polytechnique de Grenoble (Grenoble INP))
    Abstract: One of the most important outcomes during the last Conferences of the Parties was the Durban Platform for Enhanced Action, which can be seen not only as a window of opportunity, but as a necessity to act. Our concern in the present paper is with the identification of an appropriate international climate-policy architecture in order to foster climate governance. The paper attempts to raise awareness towards the Soft landing commitment scheme which is proposed as an element of answer to the climate-policy dilemma. The scheme (REDEM for REDuction of Emissions) proposes a pathway to stabilize the emissions with a timing and a level of commitment, which are differentiated on the basis of capability (per capita income levels) and responsibility (per capita emissions). We present a couple of simulation examples which show different ways to conceive the shapes of the emissions and their rates of variation. The REDEM algorithm is designed as a tool for the benchmarking of supposed national emission reduction trajectories. The tool shows a practical way to guide the potential national trajectories, through a convergence mechanism into a comprehensible framework.
    Keywords: national emission reduction ; climate policy ; REDEM ; simulation
    Date: 2014–03
  4. By: Guajardo, Mario (Dept. of Business and Management Science, Norwegian School of Economics); Jörnsten, Kurt (Dept. of Business and Management Science, Norwegian School of Economics)
    Abstract: Despite linear programming and duality have correctly been incorporated in algorithms to compute the nucleolus, we have found mistakes in how these have been used in a broad range of applications. Overlooking the fact that a linear program can have multiple optimal solutions and neglecting the relevance of duality appear to be crucial sources of mistakes in computing the nucleolus. We discuss these issues and illustrate them in mistaken examples collected from a variety of literature sources. The purpose of this note is to prevent these mistakes propagate longer by clarifying how linear programming and duality can be correctly used for computing the nucleolus.
    Keywords: Game theory; Nucleolus; Cost allocation; Linear programming; Duality
    JEL: C60 C61 C70
    Date: 2014–04–14
  5. By: Emin Gahramanov; Xueli Tang
    Abstract: Despite ample empirical evidence on the prevalence of high discount rates among people, applied, quantitative-theoretical macro studies with exponential discounting often assume low positive, or even negative discount rate values. Relying on recent advances from the numerical optimal control branch of mathematics, we solve a neoclassical, continuous time model of endogenous consumption/saving and labor supply, and show that even if an agent has a moderately high discount rate, his labour supply and consumption behavior will be highly counterfactual. We provide a remedy to such counterfactual findings by augmenting a standard utility function based on recent evidences from the leisure sciences, while maintaining a rational choice approach of neoclassical economics.
    Keywords: Bounded control; Numerical Optimal Control; Life-cycle Consumption and Labor-Leisure
    JEL: D91 C02 C61 J22 J26
    Date: 2014–03–31
  6. By: Christian Baker (Department of Economics, Brigham Young University); Jeremy Bejarano (Department of Economics, University of Chicago); Richard W. Evans (Department of Economics, Brigham Young University); Kenneth L. Judd (Hoover Institution, Stanford University); Kerk L. Phillips (Department of Economics, Brigham Young University)
    Abstract: We characterize and demonstrate a solution method for an optimal commodity (sales) tax problem consisting of multiple goods, heterogeneous agents, and a nonconvex policy maker optimization problem. Our approach allows for more dimensions of heterogeneity than has been previously possible, incorporates potential model uncertainty and policy objective uncertainty, and relaxes some of the assumptions in the previous literature that were necessary to generate a convex optimization problem for the policy maker. Our solution technique involves creating a large database of optimal responses by different individuals for different policy parameters and using ``big data'' techniques to compute policy maker objective values over these individuals. We calibrate our model to the United States and test the effects of a differentiated optimal commodity tax versus a flat tax and the effect of exempting a broad class of goods (services) from commodity taxation. We find that only a potentially small amount of tax revenue is lost for a given societal welfare level by departing from an optimal differentiated sales tax schedule to a uniform flat tax and that there is only a small loss in revenue from exempting a class of goods such as services in the United States.
    Keywords: lOptimal tax, sales tax, commodity tax, big data, robustness
    JEL: C61 C63 D31 E62 H21
    Date: 2014–03
  7. By: Alessandro Chessa (IMT Lucca Institute for Advanced Studies); Irene Crimaldi (IMT Lucca Institute for Advanced Studies); Massimo Riccaboni (IMT Lucca Institute for Advanced Studies); Luca Trapin (IMT Lucca Institute for Advanced Studies)
    Abstract: In this work we are interested in identifying clusters of "positional equivalent" actors, i.e. actors who play a similar role in a system. In particular, we analyze weighted bipartite networks that describes the relationships between actors on one side and features or traits on the other, together with the intensity level to which actors show their features. The main contribution of our work is twofold. First, we develop a methodological approach that takes into account the underlying multivariate dependence among groups of actors. The idea is that positions in a network could be defined on the basis of the similar intensity levels that the actors exhibit in expressing some features, instead of just considering relationships that actors hold with each others. Second, we propose a new clustering procedure that exploits the potentiality of copula functions, a mathematical instrument for the modelization of the stochastic dependence structure. Our clustering algorithm can be applied both to binary and real-valued matrices. We validate it with simulations and applications to real-world data.
    Keywords: Clustering, complex network, copula function, positional analysis, weighted bipartite network
    JEL: F1 C6
    Date: 2014–04
  8. By: Lassila, Jukka; Valkonen, Tarmo
    Abstract: Can longer working lives bring sufficient tax revenues to pay for the growing public health and care expenditure that longer lifetimes cause? We review studies concerning retirement decisions and pension policies, the role of mortality in health and long-term care costs, and errors in mortality projections. We combine key results into a numerical OLG model where changes in mortality have direct effects both on working careers and on per capita use of health and long-term care services. The model has been calibrated to the Finnish economy and demographics. Although there are huge uncertainties concerning future health and long-term care expenditure when people live longer, our simulations show that without policies directed to disability admission rules and old-age pension eligibility ages, working lives are unlikely to extend sufficiently. But, importantly, with such policies it seems quite possible that generations enjoying longer lifetimes can also pay for the full costs by working longer.
    Keywords: life expectancy, working careers, health and long-term care expenditure, fiscal sustainability
    JEL: H30 H63 H68 J11
    Date: 2014–04–09

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