nep-cmp New Economics Papers
on Computational Economics
Issue of 2015‒01‒31
nineteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Modelling the Common Agricultural Policy. General equilibrium effects of the 2014-2020 budget agreement By Boulanger, Pierre ; Philippidis, George
  2. Stochastic simulation framework for the Limit Order Book using liquidity motivated agents By Efstathios Panayi ; Gareth Peters
  3. Modelling regional labour market dynamics. Participation, employment and migration decisions in a spatial CGE model for the EU By Damiaan Persyn ; d'Artis Kancs ; Wouter Torfs
  4. Ponzi schemes: computer simulation By Mário Cunha ; Hélder Valente ; Paulo B. Vasconcelos
  5. Bank's strategies during the financial crisis By Recchioni, Maria Cristina ; Tedeschi, Gabriele ; Berardi, Simone
  6. A calibration procedure for analyzing stock price dynamics in an agent-based framework By Recchioni, Maria Cristina ; Tedeschi, Gabriele ; Gallegati, Mauro
  7. Economy-wide Impacts of Food Waste Reduction: A General Equilibrium Approach By Britz, Wolfgang ; Dudu, Hasan ; Ferrari, Emanuele
  8. Efficient multi-product multi-BOM batch scheduling for a petrochemical blending plant with a shared pipeline network By HILL, Alessandro ; CORNELISSENS, Trijntje ; SÖRENSEN, Kenneth
  9. Classic Kriging versus Kriging with Bootstrapping or Conditional Simulation : Classic Kriging's Robust Confidence Intervals and Optimization (Revised version of CentER DP 2013-038) By Mehdad, E. ; Kleijnen, Jack P.C.
  10. Formal Approaches to Socio Economic Policy Analysis - Past and Perspectives By Gräbner, Claudius
  11. Simulating world trade in the decades ahead: Driving forces and policy implications By Fontagné, Lionel ; Fouré, Jean ; Keck, Alexander
  12. A two-level variable neighbourhood search for the Euclidean clustered vehicle routing problem By DEFRYN, Christof ; SÖRENSEN, Kenneth
  13. “Multiple-input multiple-output vs. single-input single-output neural network forecasting” By Oscar Claveria ; Enric Monte ; Salvador Torra
  14. “Effects of removing the trend and the seasonal component on the forecasting performance of artificial neural network techniques” By Oscar Claveria ; Enric Monte ; Salvador Torra
  15. Security Assessment and Optimization of Energy Supply By Tomasz Jasinski ; Agnieszka Scianowska
  16. dynamics of assets liquidity and inequality in economies with decentralized markets By Maurizio Iacopetta
  17. SIMULATING FARM LEVEL RESPONSE TO CROP DIVERSIFICATION POLICY By Mahy, Louis ; Dupeux, Bérénice ; Van Huylenbroeck, Guido ; Buysse, Jeroen
  18. Farmers’ willingness to vaccinate against endemic animal diseases: A theoretical approach By Rault, Arnaud ; Krebs, Stephane
  19. Willingness to purchase Genetically Modified food: an analysis applying artificial Neural Networks By Salazar-Ordóñez, M. ; Rodríguez-Entrena, M. ; Becerra-Alonso, D.

  1. By: Boulanger, Pierre ; Philippidis, George
    Abstract: This paper presents methodological development of MAGNET, a sophisticated agricultural variant of the well-known GTAP computable general equilibrium (CGE) model for representing the Common Agricultural Policy (CAP). Using original data on EU domestic support, it examines some likely macroeconomic effects in the European Union (EU) of the expected budget over the period 2014-2020. Results suggest that agreed budget cuts, in constant price, have limited impacts on EU and world markets, given the broadly non-distortive representation of present CAP policy.
    Keywords: CGE, CAP, domestic support, EU28, Agricultural and Food Policy,
    Date: 2014–08
  2. By: Efstathios Panayi ; Gareth Peters
    Abstract: In this paper we develop a new form of agent-based model for limit order books based on heterogeneous trading agents, whose motivations are liquidity driven. These agents are abstractions of real market participants, expressed in a stochastic model framework. We develop an efficient way to perform statistical calibration of the model parameters on Level 2 limit order book data from Chi-X, based on a combination of indirect inference and multi-objective optimisation. We then demonstrate how such an agent-based modelling framework can be of use in testing exchange regulations, as well as informing brokerage decisions and other trading based scenarios.
    Date: 2015–01
  3. By: Damiaan Persyn (European Commission – JRC - IPTS ); d'Artis Kancs (European Commission – JRC - IPTS ); Wouter Torfs (European Commission – JRC - IPTS )
    Abstract: This paper outlines how regional labour market adjustments to macro-economic and policy shocks are modelled in RHOMOLO through participation, employment and migration decisions of workers. RHOMOLO, being a multi-sectoral, inter-regional general equilibrium model, is complex both in terms of its dimensionality and the modelling of spatial interactions through trade flows and factor mobility. The modelling of the labour market is therefore constrained by the tractability and computational solvability of the model. The labour market module consists of individual labour participation decisions, including the extensive margin (to participate or not) and the intensive margin (hours of work). Unemployment is determined through a wage curve and inter-regional labour migration decisions are modelled in a discrete-choice framework, with backward-looking expectations.
    Keywords: Participation, unemployment, labour migration, wage curve, CGE, new economic geography
    JEL: C68 D58 F22 J20 J61 J64 O15
    Date: 2014–12
  4. By: Mário Cunha (Economy master program student at FEP ); Hélder Valente (CEF.UP, Center for Economics and Finance at UP ); Paulo B. Vasconcelos (CMUP, Mathematics Center at UP )
    Abstract: Ponzi and Madoff names, as well as the Portuguese D. Branca, are so-called investment schemes that have become well-known. These scams are widespread and continue to exist, with more or less modifications, depicting serious damage to many people and society in general. Being a phenomenon of easy explanation after the implosion, its perception is not easy in a timely manner. There are some interesting studies on this subject, although in reduced numbers. In this paper we present a computational approach to the mathematical model developed by Artzrouni (2009), to study Ponzi schemes. The model describes the dynamics of an investment fund that promises higher incomes than those it can effectively offer. In the genesis there are a promised return rate, the actual nominal rate, unrealistic market capture rate of new investment and the rate of removal of accumulated deposits. Simulations resulting from shocks on the parameters of the model will be presented, in order to illustrate the impact on the success or the collapse of the investment fund. For the model calibration, data available for one of the most famous fraudulent financial schemes was used: Charles Ponzi, 1920. A philanthropic version of the model is also presented for discussion, bearing in mind social security models. The aptitude of simulation in the detection of unsustainable patterns may be of interest to financial regulators and investors when confronted with situations where funds show unrealistic performances vis-à-vis the economic and financial constraints.
    Keywords: Ponzi schemes; investment; rate of return; ordinary differential equations; numerical methods for odes; simulation
    Date: 2013–02
  5. By: Recchioni, Maria Cristina ; Tedeschi, Gabriele ; Berardi, Simone
    Abstract: In this paper we introduce a calibration procedure suitable for the validation of agent based models. Starting from the well-known financial model of Brock and Hommes 1998, we show how an appro- priate calibration technique makes the model able to describe price time series.The calibration results show that the simplest version of the Brock and Hommes model, with two trader types, fundamentalists and trend-followers, well replicates the price series of four sub-sectoral banking indexes, representing different geographical areas. Moreover, we show how the parameter values of the calibrated model are important to analyse the trader behavior on the different investigated markets.
    Keywords: Validation,Agent-based models,Asset pricing,Heterogeneous beliefs
    JEL: C52 C63 G15
    Date: 2014
  6. By: Recchioni, Maria Cristina ; Tedeschi, Gabriele ; Gallegati, Mauro
    Abstract: In this paper we introduce a calibration procedure for validating of agent based models. Starting from the well-known financial model of Brock and Hommes 1998, we show how an appropriate calibration enables the model to describe price time series. We formulate the calibration problem as a nonlinear constrained optimization that can be solved numerically via a gradient-based method. The calibration results show that the simplest version of the Brock and Hommes model, with two trader types, fundamentalists and trend-followers, replicates nicely the price series of four different markets indices: the S&P 500, the Euro Stoxx 50, the Nikkei 225 and the CSI 300. We show how the parameter values of the calibrated model are important in interpret- ing the trader behavior in the different markets investigated. These parameters are then used for price forecasting. To further improve the forecasting, we modify our calibration approach by increasing the trader information set. Finally, we show how this new approach improves the model's ability to predict market prices.
    Keywords: Calibration,Validation,Forecasting,Agent-based models,Asset pricing,Heterogeneous beliefs
    JEL: C53 C63 G17
    Date: 2014
  7. By: Britz, Wolfgang ; Dudu, Hasan ; Ferrari, Emanuele
    Abstract: Food waste has been started to be recognized as an important factor threatening a sustainable food system. However most of the studies in the literature ignore the costs of reducing food waste. In this study we develop a framework to analyse the effects of food waste reduction on the whole economy when associated costs are taken into account in a regional CGE model. Our results suggest that the level of cost is quite important on determining the final impact. Food waste reduction may cause severe loss of competitiveness for agriculture and food production if costs are not taken into account.
    Keywords: Food waste, Regional Modelling, CGE Modelling, Leisure – Labour trade-off, Agricultural and Food Policy, Consumer/Household Economics, Crop Production/Industries, Food Consumption/Nutrition/Food Safety, Resource /Energy Economics and Policy,
    Date: 2014–10
  8. By: HILL, Alessandro ; CORNELISSENS, Trijntje ; SÖRENSEN, Kenneth
    Abstract: We present an e?ffective scheduling heuristic for realistic production planning in a petrochemical blending plant. ?The considered model takes into account orders spanning a multi-product portfolio with multiple bills of materials per product, that need to be scheduled on shared production facilities including a complex pipeline network. Capacity constraints, intermediate storage restrictions, due dates, and the dedication of resources to speci?fic product families have to be respected. Th?e primary objective of the heuristic is to minimize the total order tardiness. Secondary objectives include the minimization of pipeline cleaning operations, the minimization of lead times, and the balanced utilization of fi?lling units. Th?e developed algorithm is based on a dynamic prioritization-based greedy search that schedules the orders sequentially. ?The proposed method can schedule short to mid-term operations and evaluate diff?erent plant con?gurations or production policies for tactical planning. We demonstrate its performance on various real-world inspired scenarios for diff?erent scheduling strategies. Key words: batch scheduling, chemical blending plant, heuristic.
    Date: 2014–12
  9. By: Mehdad, E. (Tilburg University, Center For Economic Research ); Kleijnen, Jack P.C. (Tilburg University, Center For Economic Research )
    Abstract: Kriging is a popular method for estimating the global optimum of a simulated system. Kriging approximates the input/output function of the simulation model. Kriging also estimates the variances of the predictions of outputs for input combinations not yet simulated. These predictions and their variances are used by efficient global optimization"(EGO), to balance local and global search. This article focuses on two related questions: (1) How to select the next combination to be simulated when searching for the global optimum? (2) How to derive confidence intervals for outputs of input combinations not yet simulated? Classic Kriging simply plugs the estimated Kriging parameters into the formula for the predictor variance, so theoretically this variance is biased. This article concludes that practitioners may ignore this bias, because classic Kriging gives acceptable confidence intervals and estimates of the optimal input combination. This conclusion is based on bootstrapping and conditional simulation.
    Keywords: simulaiton; Optimization; Kriging; Bootstrap; Conditional simulation
    JEL: C0 C1 C15 C44
    Date: 2014
  10. By: Gräbner, Claudius
    Abstract: This paper is motivated by the observation that (1) socio economic analysis uses significantly less formalisms than mainstream economics, and (2) that there exist numerous situations in which socio economics could benefit from a more formal analysis. This is particularly the case if institutions play an important role in the system to be investigated. Starting with a broad conception of a formalism, this paper introduces and discusses five different formal approaches regarding their adequateness for socio economic analysis: The Social Fabric Matrix Approach, the Institutional Analysis and Development Framework, System Dynamics, (Evolutionary) Game Theory, and Agent Based Computational Modeling. As a formal analysis always comes up with implicit ontological and epistemological tendencies, that have to be reflected if the formalism should contribute to a better understanding of the system under investigation, this paper pays particular attention to these tendencies of the considered formalisms. In the end, antagonisms and possible convergences among the formalisms are discussed.
    Keywords: Social Economics, Institutional Economics, Methodology, Epistemology, Ontology, System Dynamics, Social Fabric Matrix, (Evolutionary) Game Theory, Agent-Based Computational Economics, Econometrics.
    JEL: B41 B52 C63 C70
    Date: 2015–01–15
  11. By: Fontagné, Lionel ; Fouré, Jean ; Keck, Alexander
    Abstract: Constructing fully traceable scenarios based on assumptions grounded in the literature, we are also able to isolate the relative impact of key economic drivers. We find that the stakes for developing countries are particularly high: The emergence of new players in the world economy, intensification of South-South trade and diversification into skill-intensive activities may continue only in a dynamic economic and open trade environment. Current trends towards increased regionalization may be reversed, with multilateral trade relationships gaining in importance. Hypothetical mega-regionals could slow down, but not frustrate the prevalence of multilateralism. Continuing technological progress is likely to have the biggest impact on future economic developments around the globe. Population dynamics are influential as well: For some countries, up-skilling will be crucial, for others labour shortages may be addressed through migration. Several developing countries would benefit from increased capital mobility; others will only diversify into dynamic sectors, when trade costs are further reduced.
    Keywords: international trade,macroeconomic projections,CGE simulations
    JEL: E27 F02 F17 F47
    Date: 2014
  12. By: DEFRYN, Christof ; SÖRENSEN, Kenneth
    Abstract: In this paper, a metaheuristic approach is presented to solve the Clustered Vehicle Routing Problem (CluVRP). The CluVRP, in which customers are grouped into predefi?ned clusters, can be seen as a generalisation of the classical Capacitated Vehicle Routing Problem (CVRP). When serving all these customers with a given fl?eet of vehicles it should be ensured that clients belonging to the same cluster are served by one vehicle, sequentially in the same path (CluVRP with hard cluster constraints). In a second phase, these constraints will be relaxed as we will de?ne the CluVRP with so? cluster constraints. Th?e proposed metaheuristic approach tries to fi?nd the optimal solution for both problems by combining two variable neighbourhood search algorithms, exploring the distribution area at two different levels. ?The algorithm is tested on di?erent benchmark instances from the literature with up to 484 nodes, obtaining high quality solutions.
    Keywords: Clustered Vehicle Routing Problem (CVRP), Variable neighbourhood search, Metaheuristics
    Date: 2015–01
  13. By: Oscar Claveria (Department of Econometrics. University of Barcelona ); Enric Monte (Department of Signal Theory and Communications. Polytechnic University of Catalunya. ); Salvador Torra (Department of Econometrics & Riskcenter-IREA. Universitat de Barcelona )
    Abstract: This study attempts to improve the forecasting accuracy of tourism demand by using the existing common trends in tourist arrivals form all visitor markets to a specific destination in a multiple-input multiple-output (MIMO) structure. While most tourism forecasting research focuses on univariate methods, we compare the performance of three different Artificial Neural Networks in a multivariate setting that takes into account the correlations in the evolution of inbound international tourism demand to Catalonia (Spain). We find that the MIMO approach does not outperform the forecasting accuracy of the networks when applied country by country, but it significantly improves the forecasting performance for total tourist arrivals. When comparing the forecast accuracy of the different models, we find that radial basis function networks outperform multilayer-perceptron and Elman networks.
    Keywords: Tourism demand, forecasting, multivariate, multiple-output, artificial neural networks JEL classification: C22, C45, C63, L83, R11
    Date: 2015–01
  14. By: Oscar Claveria (Department of Econometrics. University of Barcelona ); Enric Monte (Department of Signal Theory and Communications. Polytechnic University of Catalunya. ); Salvador Torra (Department of Econometrics & Riskcenter-IREA. Universitat de Barcelona )
    Abstract: This study aims to analyze the effects of data pre-processing on the performance of forecasting based on neural network models. We use three different Artificial Neural Networks techniques to forecast tourist demand: a multi-layer perceptron, a radial basis function and an Elman neural network. The structure of the networks is based on a multiple-input multiple-output setting (i.e. all countries are forecasted simultaneously). We use official statistical data of inbound international tourism demand to Catalonia (Spain) and compare the forecasting accuracy of four processing methods for the input vector of the networks: levels, growth rates, seasonally adjusted levels and seasonally adjusted growth rates. When comparing the forecasting accuracy of the different inputs for each visitor market and for different forecasting horizons, we obtain significantly better forecasts with levels than with growth rates. We also find that seasonally adjusted series significantly improve the forecasting performance of the networks, which hints at the significance of deseasonalizing the time series when using neural networks with forecasting purposes. These results reveal that, when using seasonal data, neural networks performance can be significantly improved by working directly with seasonally adjusted levels.
    Keywords: Artificial neural networks, forecasting, multiple-input multiple-output (MIMO), seasonality, detrending, tourism demand, multilayer perceptron, radial basis function, Elman JEL classification: L83, C53, C45, R11
    Date: 2015–01
  15. By: Tomasz Jasinski (Lodz University of Technology, Poland ); Agnieszka Scianowska (Lodz University of Technology, Poland )
    Abstract: The question of energy supply continuity is essential from the perspective of the functioning of society and the economy today. The study describes modern methods of forecasting emergency situations using Artificial Intelligence (AI) tools, especially neural networks. It examines the structure of a properly functioning model in the areas of input data selection, network topology and learning algorithms, analyzes the functioning of an energy market built on the basis of a reserve market, and discusses the possibilities of economic optimization of such a model, including the question of safety.
    Keywords: energy supply, security, neural networks, operating reserve
    JEL: Q40 Q47 C45 C53
    Date: 2014–12
  16. By: Maurizio Iacopetta (OFCE )
    Abstract: An algorithm for computing Dynamic Nash Equilibria (DNE) in an extended ver- sion of Kiyotaki and Wright (1989) (hereafter KW) is proposed. The algorithm com- putes the equilibrium pro.le of (pure) strategies and the evolution of the distribution of three types of assets across three types of individuals. It has two features that together make it applicable in a wide range of macroeco- nomic experiments: (i) it works for any feasible initial distribution of assets; (ii) it allows for multiple switches of trading strategies along the transitional dynamics. The algorithm is used to study the relationship between liquidity, production, and inequality in income and in welfare, in economies where assets fetch di¤erent returns and agents have heterogeneous skills and preferences. One experiment shows a case of reversal of fortune. An economy endowed with a low-return asset takes over a similar economy endowed with a high-return asset because, in the former economy, a group of agents abandon a rent-seeking trading behavior and increase their income by trading and producing more intensively. A second experiment shows that a reduction of market frictions leads both to higher income and lower inequality. Other experiments evaluate the propagation mechanism of shocks that hit the assets.returns. A key result is that trade and liquidity tend to squeeze income inequality.
    Keywords: Trading strategies; Liquidity; Matching; Decentralized markets
    JEL: C61 C63 E41 E27 D63
    Date: 2014–12
  17. By: Mahy, Louis ; Dupeux, Bérénice ; Van Huylenbroeck, Guido ; Buysse, Jeroen
    Abstract: One of the new political instruments of the European Common Agricultural Policy-reform is the crop diversification measure. To comply with this measure, arable farmers will have to grow a minimum number of crops on their land, in given proportions. In this paper a non-parametric simulation model is developed to predict land cover changes while tackling the self-selection problem. Farmers’ behaviour is based on their closest peer‘s behaviour. A comparison between the results on diversity, measured through the Shannon Diversity Index, and the policy impact on farms, shows a clear trade-of and a potential for targeting.
    Keywords: Crop diversification, policy, impact analysis, model, Shannon diversity index, Agricultural and Food Policy, Farm Management,
    Date: 2014–08
  18. By: Rault, Arnaud ; Krebs, Stephane
    Abstract: The aim of this paper is to propose an analytical framework to explore farmers’ vaccination decisions against endemic animal diseases. First, a theoretical model is developed to highlight how the characteristics of the vaccine influence the farmer’s vaccination decisions over time and the resulting disease dynamics. Numerical simulations are then performed to illustrate the impacts of the different vaccine effectiveness parameters on these dynamics.
    Keywords: Animal health economics, disease control, risk management, vaccination, model simulation, Health Economics and Policy,
    Date: 2014–08
  19. By: Salazar-Ordóñez, M. ; Rodríguez-Entrena, M. ; Becerra-Alonso, D.
    Abstract: Findings about consumer decision-making process regarding GM food purchase remain mixed and are inconclusive. This paper offers a model which classifies willingness to purchase GM food, using data from 399 surveys in Southern Spain. Willingness to purchase has been measured using three dichotomous questions and classification, based on attitudinal, cognitive and socio-demographic factors, has been made by an artificial neural network model. The results show 74% accuracy to forecast the willingness to purchase. The highest relative contributions lie in the variables related to beliefs, especially those link to perceived risks; while the variables with the least relative contribution are age and knowledge on GMO.
    Keywords: Genetically Modified Food, Willingness to purchase, Artificial Neural Network, Food Consumption/Nutrition/Food Safety,
    Date: 2014–08

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