nep-cmp New Economics Papers
on Computational Economics
Issue of 2014‒12‒08
eleven papers chosen by
Stan Miles
Thompson Rivers University

  1. Micro and Macro Policies in Keynes+Schumpeter Evolutionary Models By Giovanni Dosi; Mauro Napoletano; Andrea Roventini; Tania Treibich
  2. Endogenous grids in higher dimensions: Delaunay interpolation and hybrid methods By Ludwig, Alexander; Schön, Matthias
  3. The Impact of the 2014 Platinum Mining Strike in South Africa: An Economy-Wide Analysis By Bohlmann, H.R., Dixon, P.B., Rimmer, M.T. and Van Heerden, J.H.
  4. Optimal Portfolio Choice under Decision-Based Model Combinations By Davide Pettenuzzo; Francesco Ravazzolo
  5. Coupling high-frequency data with nonlinear models in multiple-step-ahead forecasting of energy markets' volatility By Jozef Baruník; Tomáš Køehlík
  6. A hybridised tabu search heuristic to increase security in a utility network By JANSSENS, Jochen; TALARICO, Luca; SÖRENSEN, Kenneth
  7. Stochastic technical analysis for decision making on the financial market By Höchstötter, Markus; Safarian, Mher
  8. Using A Spreadsheet SAM for GAMS CGE Modeling By Amir Borges Ferreira Neto
  9. Carbon Tax and Revenue Recycling: Impacts on Households in British Columbia. By Marisa Beck, Nicholas Rivers, Randall Wigle, Hidemichi Yonezawa
  10. Floating-point numbers: A visit to the looking glass world By William Gould
  11. A Neural Network Demand System By Julien Boelaert

  1. By: Giovanni Dosi; Mauro Napoletano; Andrea Roventini; Tania Treibich
    Abstract: This paper presents the family of the Keynes+Schumpeter (K+S, cf. Dosi et al, 2010, 2013, 2014) evolutionary agent-based models, which study the effects of a rich ensemble of innovation, industrial dynamics and macroeconomic policies on the long-term growth and short-run fluctuations of the economy. The K+S models embed the Schumpeterian growth paradigm into a complex system of imperfect coordination among heterogeneous interacting firms and banks, where Keynesian (demand-related) and Minskian (credit cycle) elements feed back into the meso and macro dynamics. The model is able to endogenously generate long-run growth together with business cycles and major crises. Moreover, it reproduces a long list of macroeconomic and microeconomic stylized facts. Here, we discuss a series of experiments on the role of policies affecting i) innovation, ii) industry dynamics, iii) demand and iv) income distribution. Our results suggest the presence of strong complementarities between Schumpeterian (technological) and Keynesian (demand-related) policies in ensuring that the economic system follows a path of sustained stable growth and employment.
    Keywords: agent-based model, fiscal policy, economic crises, austerity policies, disequilibrium dynamics
    Date: 2014–11–15
  2. By: Ludwig, Alexander; Schön, Matthias
    Abstract: This paper investigates extensions of the method of endogenous gridpoints (ENDGM) introduced by Carroll (2006) to higher dimensions with more than one continuous endogenous state variable. We compare three different categories of algorithms: (i) the conventional method with exogenous grids (EXOGM), (ii) the pure method of endogenous gridpoints (ENDGM) and (iii) a hybrid method (HYBGM). ENDGM comes along with Delaunay interpolation on irregular grids. Comparison of methods is done by evaluating speed and accuracy. We find that HYBGM and ENDGM both dominate EXOGM. In an infinite horizon model, ENDGM also always dominates HYBGM. In a finite horizon model, the choice between HYBGM and ENDGM depends on the number of gridpoints in each dimension. With less than 150 gridpoints in each dimension ENDGM is faster than HYBGM, and vice versa. For a standard choice of 25 to 50 gridpoints in each dimension, ENDGM is 1.4 to 1.7 times faster than HYBGM in the finite horizon version and 2.4 to 2.5 times faster in the infinite horizon version of the model.
    Keywords: Dynamic Models,Numerical Solution,Endogenous gridpoints Method,Delaunay Interpolation
    JEL: C63 E21
    Date: 2014
  3. By: Bohlmann, H.R., Dixon, P.B., Rimmer, M.T. and Van Heerden, J.H.
    Abstract: In this paper we measure the economy-wide impact of the 2014 labour strike in South Africa’s platinum industry. The strike lasted five months, ending in June 2014 when producers reached an agreement with the main labour unions. The immediate impacts on local mining towns were particularly severe, but our research shows that the strike could also have long lasting negative impacts on the South African economy as a whole. We find that it is not the higher nominal wages itself that caused the most damage, but the possible reaction by investors in the mining industry towards South Africa. Investor confidence is likely to be, at least, temporarily harmed, in which case it would take many years for the effects of the strike to disappear. We conduct our analysis using a dynamic CGE model of South Africa.
    Keywords: Platinum mining strike, computable general equilibrium, UPGEM
    JEL: C68 J52
    Date: 2014
  4. By: Davide Pettenuzzo (Brandeis University); Francesco Ravazzolo (Norges Bank, and BI Norwegian Business School)
    Abstract: We propose a novel Bayesian model combination approach where the combination weights depend on the past forecasting performance of the individual models entering the combina- tion through a utility-based objective function. We use this approach in the context of stock return predictability and optimal portfolio decisions, and investigate its forecasting perfor- mance relative to a host of existing combination schemes. We find that our method produces markedly more accurate predictions than the existing model combinations, both in terms of statistical and economic measures of out-of-sample predictability. We also investigate the incremental role of our model combination method in the presence of model instabilities, by considering predictive regressions that feature time-varying regression coefficients and volatil- ity. We find that the gains from using our model combination method increase significantly when we allow for instabilities in the individual models entering the combination.
    Keywords: Bayesian econometrics; Time-varying parameters; Model combinations; Port- folio choice.
    JEL: C11 C22 G11 G12
    Date: 2014–10
  5. By: Jozef Baruník (Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague, Smetanovo nábreží 6, 111 01 Prague 1, Czech Republic; Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Pod Vodarenskou Vezi 4, 182 00, Prague, Czech Republic); Tomáš Køehlík (Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague, Smetanovo nábreží 6, 111 01 Prague 1, Czech Republic; Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Pod Vodarenskou Vezi 4, 182 00, Prague, Czech Republic)
    Abstract: In the past decade, the popularity of realized measures and various linear models for volatility forecasting has attracted attention in the literature on the price variability of energy markets. However, results that would guide practitioners to a specic estimator and model when aiming for the best forecasting accuracy are missing. This paper contributes to the ongoing debate with a comprehensive evaluation of multiple-step-ahead volatility forecasts of energy markets using several popular high-frequency measures and forecasting models. To capture the complex patterns hidden to linear models commonly used to forecast realized volatility, this paper also contributes to the literature by coupling realized measures with articial neural networks as a forecasting tool. Forecasting performance is compared across models as well as realized measures of crude oil, heating oil, and natural gas volatility during three qualitatively distinct periods covering the precrisis period, recent global turmoil of markets in 2008, and the most recent post-crisis period. We conclude that coupling realized measures with articial neural networks results in both statistical and economic gains, reducing the tendency to over-predict volatility uniformly during all tested periods. Our analysis favors the median realized volatility, as it delivers the best performance and is a computationally simple alternative for practitioners.
    Keywords: artificial neural networks, realized volatility, multiple-step-ahead forecasts, energy markets
    JEL: C14 C53 G17
    Date: 2014–09
  6. By: JANSSENS, Jochen; TALARICO, Luca; SÖRENSEN, Kenneth
    Abstract: In this paper we propose a decision model aimed at increasing security in a utility network (e.g., smart grid, water network). The network consists of edges that might be a viable target for terrorists depending on several factors such as geographical location, accessibility of the network, the political stability of a region. Based on this we assume that all edges (e.g., pipes, cables) have a certain, not necessary equal, probability of failure, which can be reduced by selecting appropriate edge-specic security strategies. The decision model proposed in this paper is based on a metaheuristic approach, that uses tabu search hybridised with iterated local search and a large scale neighbourhood decent heuristic. The main goal is to reduce the risk of service failure between a couple of network nodes by selecting the right combination of security measures for each network edge given a limited security budget. A generator for realistic instances is proposed and used to create a set of test instances. Experiments on these instances are conducted to tune the parameters and evaluate the proposed metaheuristic algorithm.
    Keywords: Network security, Metaheuristics, Knapsack problem
    Date: 2014–10
  7. By: Höchstötter, Markus; Safarian, Mher
    Abstract: We apply the well-known CUSUM and the Girshick-Rubin algorithm as trading strategies involving only mutually exclusive long positions in cash and the DAX at Frankfurt mid-day auction prices. We select optimal pairs of fixed thresholds for up- and down-movements from a pre-defined two-dimensional grid, hence, admitting asymmetric intervals. We show that under three different scenarios for transaction costs, the CUSUM technique not only outperforms the passive investment in the DAX but also the alternative Girshick-Rubin algorithm.
    Keywords: CUSUM,Girshick-Rubin,trading algorithm,DAX
    JEL: R48 L92 Q55
    Date: 2014
  8. By: Amir Borges Ferreira Neto (Regional Research Institute, West Virginia University)
    Abstract: This technical document provides in a single document a template to follow when using spreadsheet Social Accounting Matrix data to drive a GAMS-based Computable General Equilibrium model.
    Keywords: CGE, SAM, spreadsheet, Excel
    JEL: C68 R13
    Date: 2014–10
  9. By: Marisa Beck, Nicholas Rivers, Randall Wigle, Hidemichi Yonezawa (Wilfrid Laurier University)
    Abstract: This study investigates the distributional implications of the revenue-neutral carbon tax policy in British Columbia. We use a computable general equilibrium (CGE) model of the Canadian economy and disaggregate households into deciles by annual income using data from a large household expenditure survey. Using the model, we find that the existing BC carbon tax is highly progressive even prior to consideration of the revenue recycling scheme, such that the negative impact of the carbon tax on households with below-median income are smaller than that on households with above-median income. We show that our finding is a result of welfare effects of a carbon tax being determined primarily by the source of a households' income rather than by the destination of its expenditures. Finally, we show that the existing revenue recycling scheme is also progressive. Overall, the tax appears to be highly progressive.
    Keywords: carbon taxes, distributional effects, British Columbia, computable general equilibrium analysis
    JEL: Q48 Q54 D63
    Date: 2014–09–07
  10. By: William Gould (StataCorp LP)
    Abstract: Researchers do not adequately appreciate that floating-point numbers are a simulation of real numbers and, as with all simulations, some features are preserved while others are not. When writing code, or even do-files, treating the computer's floating-point numbers as if they were real numbers can lead to substantive problems and to numerical inaccuracy. In this, the relationship between computers and real numbers is not entirely unlike the relationship between tea and Douglas Adams' Nutri-Matic drink dispenser. The Nutri-Matic produces a concoction that is "almost, but not quite, entirely unlike tea." Gould shows what the universe would be like if it was implemented in floating-point rather than in real numbers. The floating-point universe turns out to be nothing like the real universe and probably could not be made to function. Without jargon and without resort to binary, Gould shows how floating-point numbers are implemented on an imaginary base-10 computer and quantifies the kinds of errors that can arise. In this, floating-point subtraction stands out as really being almost, but not quite, entirely unlike subtraction. Gould shows out how to work around such problems. The point of the talk is to build your intuition about the floating-point world so that you as a researcher can predict when calculations might go awry, know how to think about the problem, and determine how to fix it.
    Date: 2014–09–28
  11. By: Julien Boelaert (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne)
    Abstract: We introduce a new type of demand system using a feedforward artificial neural network. The neural network demand system is a flexible system that requires few hypotheses, has no roots in consumer theory but may be used to test it. We use the system to estimate demand elasticities on micro data of household consumption in Canada between 2004 and 2008, and compare the results to those of the quadratic almost ideal demand system.
    Keywords: Estimating demand systems; neural networks; flexible forms; Quadratic Almost Ideal Demand System (QUAIDS)
    Date: 2013–12

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