nep-cmp New Economics Papers
on Computational Economics
Issue of 2015‒03‒22
seven papers chosen by

  1. Forecasting the US CPI: Does Nonlinearity Matter? By Marcos Álvarez-Díaz; Rangan Gupta
  2. Methodology Does Matter: About Implicit Assumptions in Applied Formal Modelling. The case of Dynamic Stochastic General Equilibrium Models vs Agent-Based Models By Gräbner, Claudius
  3. Numerical approximations for Heston-Hull-White type models By M. Briani; L. Caramellino; A. Zanette
  4. Some experiments on solving multistage stochastic mixed 0-1 programs with time stochastic dominance constraints By Escudero Bueno, Laureano F.; Garín Martín, María Araceli; Merino Maestre, María; Pérez Sainz de Rozas, Gloria
  5. CompDTIMe: Computing one-dimensional invariant manifolds for saddle points of discrete time dynamical systems By Anastasiia Panchuk
  6. Impacts of Cambodia's Tariff Elimination on Household Welfare and Labor Market: a CGE Approach By Heng Dyna; Senh Senghor; Ear Sothy; Kanga Em
  7. Co-firing in Coal Power Plants and its Impact on Biomass Feedstock Availability By Dumortier, Jerome

  1. By: Marcos Álvarez-Díaz (Department of Economics, University of Vigo, Galicia, Spain); Rangan Gupta (Department of Economics, University of Pretoria)
    Abstract: The objective of this paper is to predict, both in-sample and out-of-sample, the consumer price index (CPI) of the United States (US) economy based on monthly data covering the period of 1980:1-2013:12, using a variety of linear (random walk (RW), autoregressive (AR) and seasonally-adjusted autoregressive moving average (SARIMA)) and nonlinear (artificial neural network (ANN) and genetic programming (GP)) univariate models. Our results show that, while the SARIMA model is superior relative to other linear and nonlinear models, as it tends to produce smaller forecast errors; statistically, these forecasting gains are not significant relative to higher-order AR and nonlinear models, though simple benchmarks like the RW and AR(1) models are statistically outperformed. Overall, we show that in terms of forecasting the US CPI, accounting for nonlinearity does not necessarily provide us with any statistical gains.
    Keywords: Linear, Nonlinear, Forecasting, Consumer Price Index
    JEL: C22 C45 C53 E31
    Date: 2015–03
  2. By: Gräbner, Claudius
    Abstract: This article uses the functional decomposition approach to modeling Mäki (2009b) to discuss the importance of methodological considerations before choosing a modeling framework in applied research. It considers the case of agent-based models and dynamic stochastic general equilibrium models to illustrate the implicit epistemological and ontological statements related to the choice of the corresponding modeling framework and highlights the important role of the purpose and audience of a model. Special focus is put on the limited capacity for model exploration of equilibrium models and their difficulty to model mechanisms explicitly. To model mechanisms that have interaction effects with other mechanisms is identified as a particular challenge that sometimes makes the explanation of phenomena by isolating the underlying mechanisms a difficult task. Therefore I argue for a more extensive use of agent-based models as they provide a formal tool to address this challenge. The overall conclusion is that a plurality of models is required: single models are simply pushed to their limits if one wishes to identify the right degree of isolation required to understand reality.
    Keywords: Functional decomposition approach, general equilibrium, agent-based models, methodology, epistemology, ontology, formal modeling, isolation
    JEL: B41 C6 C63
    Date: 2015–03–19
  3. By: M. Briani; L. Caramellino; A. Zanette
    Abstract: We study a hybrid tree-finite difference method which permits to obtain efficient and accurate European and American option prices in the Heston Hull-White and Heston Hull-White2d models. Moreover, as a by-product, we provide a new simulation scheme to be used for Monte Carlo evaluations. Numerical results show the reliability and the efficiency of the proposed methods
    Date: 2015–03
  4. By: Escudero Bueno, Laureano F.; Garín Martín, María Araceli; Merino Maestre, María; Pérez Sainz de Rozas, Gloria
    Abstract: In this work we extend to the multistage case two recent risk averse measures for two-stage stochastic programs based on first- and second-order stochastic dominance constraints induced by mixed-integer linear recourse. Additionally, we consider Time Stochastic Dominance (TSD) along a given horizon. Given the dimensions of medium-sized problems augmented by the new variables and constraints required by those risk measures, it is unrealistic to solve the problem up to optimality by plain use of MIP solvers in a reasonable computing time, at least. Instead of it, decomposition algorithms of some type should be used. We present an extension of our Branch-and-Fix Coordination algorithm, so named BFC-TSD, where a special treatment is given to cross scenario group constraints that link variables from different scenario groups. A broad computational experience is presented by comparing the risk neutral approach and the tested risk averse strategies. The performance of the new version of the BFC algorithm versus the plain use of a state-of-the-artMIP solver is also reported.
    Keywords: scenario clustering, risk averse measures, stochastic dominance constraints, multistage stochastic mixed 0-1 optimization
    Date: 2015
  5. By: Anastasiia Panchuk (National Academic of Sciences of Ukraine)
    Abstract: This paper describes briefly main functionalities and exploited numerical methods of the package CompDTIMe which consists of several Matlab routines. This package allows one to calculate two-dimensional bifurcation diagrams, to find periodic points not depending on whether they are attracting, to compute one-dimensional stable and unstable manifolds of saddle points. Certain functions are also provided for plotting the numerical outcome by means of Matlab.
    Keywords: discrete time dynamical systems software; numerical methods; saddle periodic points; stable and unstable invariant manifolds
    JEL: C61 C62 C63
    Date: 2015–02
  6. By: Heng Dyna; Senh Senghor; Ear Sothy; Kanga Em
    Abstract: This study builds Cambodia’s social accounting matrix. Using a CGE-based simulation, it then assesses the impacts of Cambodia’s tariff elimination on household welfare and the labour market. Our results show that tariff elimination leads to an expansion in production output and an increase in export/import volumes. Government policy for indirect tax-led revenue compensation results in a structural change of output, favoring manufacturing over the agriculture and services sectors. Those manufacturing industries include textiles, raw metals, fabricated metals, machinery, and office and computing machinery. Tariff removal’s effect favours the textiles industry as it is presently less protected and consumes a large proportion of now cheaper intermediate inputs. This industry will continue to be the backbone for growth and employment over the short and medium term. In terms of effects on labor market, low-skilled labourers see relatively less benefit from tariff elimination. At the household level, the impacts on their incomes and consumption are almost the same. Phnom Penh households are less affected by the indirect tax increase. Overall, welfare gains for the whole country and most representative households are positive but small. The exceptions are households in Kratie, Preah Vihear, Rattanakiri, and Stung Treng; these remote provinces experience a negative welfare effect from the simulations of tariff removal.
    Keywords: Tariff Elimination, Welfare, CGE, Labour Market
    JEL: C63 C67 C68
    Date: 2015
  7. By: Dumortier, Jerome
    Abstract: Several states have a renewable portfolio standard (RPS) and allow for biomass co-firing to meet the RPS requirements. In addition, a federal renewable fuel standard (RFS) mandates an increase in cellulosic ethanol production over the next decade. This paper quantifies the effects on local biomass supply and demand of different co-firing policies imposed on 398 existing coal-fired power plants. Our model indicates which counties are most likely to be able to sustain cellulosic ethanol plants in addition to co-firing electric utilities. The simulation incorporates the county-level biomass market of corn stover, wheat straw, switchgrass, and forest residues as well as endogenous crop prices. Our scenarios indicate that there is sufficient feedstock availability in Southern Minnesota, Iowa, and Central Illinois. Significant supply shortages are observed in Eastern Ohio, Western Pennsylvania, and the tri-state area of Illinois, Indiana, and Kentucky which are characterized by a high density of coal-fired power plants with high energy output.
    Keywords: switchgrass, miscanthus, land-use change, Environmental Economics and Policy, Land Economics/Use, Resource /Energy Economics and Policy,
    Date: 2015

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