New Economics Papers
on Computational Economics
Issue of 2014‒05‒17
thirteen papers chosen by

  1. Climate Impacts in Europe - The JRC PESETA II Project By Ciscar, Juan-Carlos; Feyen, Luc; Soria, Antonio; Lavalle, Carlo; Raes, Frank; Perry, Miles; Nemry, Françoise; Demirel, Hande; Rozsai, Máté; Dosio, Alessandro; Donatelli, Marcello; Srivastava, Amit Kumar; Fumagalli, Davide; Niemeyer, Stefan; Shrestha, Shailesh; Ciaian, Pavel; Himics, Mihaly; Van Doorslaer, Benjamin; Barrios, Salvador; Ibáñez, Nicolás; Forzieri, Giovanni; Rojas, Rodrigo; Bianchi, Alessandra; Dowling, Paul; Camia, Andrea; Libertà, Giorgio; San-Miguel-Ayanz, Jesús; de Rigo, Daniele; Caudullo, Giovanni; Barredo, Jose-I.; Paci, Daniele; Pycroft, Jonathan; Saveyn, Bert; Van Regemorter, Denise; Revesz, Tamas; Vandyck, Toon; Vrontisi, Zoi; Baranzelli, Claudia; Vandecasteele, Ine; Batista e Silva, Filipe; Ibarreta, Dolores
  2. VRP algorithms for decision support systems to evaluate collaborative urban freight transport systems By Jesus Gonzalez-Feliu; Josep-Maria Salanova Grau
  3. The Long Term Economic Impacts of Reducing Migration: the Case of the UK Migration Policy By Dr Miguel Sanchez-Martinez; Dr Katerina Lisenkova
  4. Stochastic Volatility Estimation with GPU Computing By António Alberto Santos; João Andrade
  5. Social Learning about Consumption By Isabelle Salle; Pascal Seppecher
  6. Modelling the dynamic effects of transfer policy through the life-course: the LINDA policy analysis tool By Dr Justin van de Ven
  7. Assessing the impact of fta: a case study of pakistan- malaysia fta By mahmood, Hamid mahmood; gul, Sidra gul
  8. Overview of the NiGEM-S Model: Scottish version of the National Institute Global Econometric Model By Dr Katerina Lisenkova; Iana Liadze; Dr Ian Hurst
  9. Introducing spatial heterogeneity in forest sector modelling: insights from the French forest Sector Model By Antonello Lobianco; Philippe Delacote; Sylvain Caurla; Ahmed Barkaoui
  10. A Multi-factor Adaptive Statistical Arbitrage Model By Wenbin Zhang; Zhen Dai; Bindu Pan; Milan Djabirov
  11. A Branch-and-Price-and-Cut approach for Sustainable Crop Rotation Planning By Laurent Alfandari; Agnès Plateau; Xavier Schepler
  12. Internal versus External Growth in Industries with Scale Economies: A Computational Model of Optimal Merger Policy By Ben Mermelstein; Volker Nocke; Mark A. Satterthwaite; Michael D. Whinston
  13. Macro-prudential assessment of Colombian financial institutions’ systemic importance By Carlos León; Clara Machado; Andrés Murcia

  1. By: Ciscar, Juan-Carlos; Feyen, Luc; Soria, Antonio; Lavalle, Carlo; Raes, Frank; Perry, Miles; Nemry, Françoise; Demirel, Hande; Rozsai, Máté; Dosio, Alessandro; Donatelli, Marcello; Srivastava, Amit Kumar; Fumagalli, Davide; Niemeyer, Stefan; Shrestha, Shailesh; Ciaian, Pavel; Himics, Mihaly; Van Doorslaer, Benjamin; Barrios, Salvador; Ibáñez, Nicolás; Forzieri, Giovanni; Rojas, Rodrigo; Bianchi, Alessandra; Dowling, Paul; Camia, Andrea; Libertà, Giorgio; San-Miguel-Ayanz, Jesús; de Rigo, Daniele; Caudullo, Giovanni; Barredo, Jose-I.; Paci, Daniele; Pycroft, Jonathan; Saveyn, Bert; Van Regemorter, Denise; Revesz, Tamas; Vandyck, Toon; Vrontisi, Zoi; Baranzelli, Claudia; Vandecasteele, Ine; Batista e Silva, Filipe; Ibarreta, Dolores
    Abstract: The objective of the JRC PESETA II project is to gain insights into the sectoral and regional patterns of climate change impacts in Europe by the end of this century. The study uses a large set of climate model runs and impact categories (ten impacts: agriculture, energy, river floods, droughts, forest fires, transport infrastructure, coasts, tourism, habitat suitability of forest tree species and human health). The project integrates biophysical direct climate impacts into a macroeconomic economic model, which enables the comparison of the different impacts based on common metrics (household welfare and economic activity). Under the reference simulation the annual total damages would be around €190 billion/year, almost 2% of EU GDP. The geographical distribution of the climate damages is very asymmetric with a clear bias towards the southern European regions. More than half of the overall annual EU damages are estimated to be due to the additional premature mortality (€120 billion). Moving to a 2°C world would reduce annual climate damages by €60 billion, to €120 billion (1.2% of GDP).
    Keywords: Environmental economics; greenhouse gas emissions reduction; green tax reform; energy tax; energy-intensive sectors; competitiveness; multi-sectoral; computable general equilibrium model (CGE); scenario-building techniques; climate change impacts and adaptation assessment; data-transformation modelling; integrated modelling; Semantic Array Programming; Relative distance similarity; Europe; Agriculture; Forest; Tourism; Tipping points; Water resources; Coastline; Transport infrastructure; Forest Fires; River floods; Human health; Tree species habitat suitability; Sea level rise; Droughts;
    JEL: C15 C6 Q1 Q4 Q5 Q51 Q54 Q56 Q57
    Date: 2014
  2. By: Jesus Gonzalez-Feliu (LET - Laboratoire d'économie des transports - CNRS : UMR5593 - École Nationale des Travaux Publics de l'État [ENTPE] - Université Lumière - Lyon II); Josep-Maria Salanova Grau (Hellenic Institute or Transport - Center of Research and Technologie Hellas)
    Abstract: This paper proposes a comparison between genetic and semi-greedy algorithms for a collaborative VRP in city logistics. In order to compare the performance of both algorithms on real-size test cases, we develop a cluster-first route second algorithm. The clustering phase is made by a seep algorithm, which defines the number of used vehicles and assigns a set of customers to it. Then, for each vehicle, we build a min-cost route by two methods. The first is a semi-greedy algorithm. The second is a genetic algorithm. We test both approaches on real-size instances Computational results are presented and discussed.
    Keywords: city logistics systems; two-echelon vehicle routing; cross-docking; simulation; collaboration
    Date: 2014–02–17
  3. By: Dr Miguel Sanchez-Martinez; Dr Katerina Lisenkova
    Abstract: This paper uses an OLG-CGE model for the UK to illustrate the long-term effect of migration on the economy. We use the current Conservative Party migration target to reduce net migration “from hundreds of thousands to tens of thousands†as an illustration. Achieving this target would require reducing recent net migration numbers by a factor of about 2. In presented simulations, we compare a baseline scenario, which incorporates the principal 2010-based ONS population projections, with a lower migration scenario, which assumes that net migration is reduced by around 50%. The results show that such a significant reduction in net migration has strong negative effects on the economy. The level of both GDP and GDP per person fall during the simulation period by 11.0% and 2.7% respectively. Moreover, this policy has a significant impact on public finances. To keep the government budget balanced, the labour income tax rate has to be increased by 2.2 percentage points in the lower migration scenario.
    Date: 2013–12
  4. By: António Alberto Santos (Faculty of Economics, University of Coimbra and GEMF, Portugal); João Andrade (Instituto de Telecomunicações, Dept. Electrical and Comp. Eng., University of Coimbra, Portugal)
    Abstract: In this paper, we show how to estimate the parameters of stochastic volatility models using Bayesian estimation and Markov chain Monte Carlo (MCMC) simulations through the approximation of the a-posteriori distribution of parameters. Simulated independent draws are made possible by using Graphics Processing Units (GPUs) to compute several Markov chains in parallel. We show that the higher computational power of GPUs can be harnessed and put to good use by addressing two challenges. Bayesian estimation using MCMC simulations benefit from powerful processors since it is a complex numerical problem. Moreover, sequential approaches are characterized for drawing highly correlated samples which reduces the Effective Sample Size (ESS) associated with the simulated values obtained from the posterior distribution under a Bayesian analysis. However, under the proposed parallel expression of the algorithm, we show that a faster convergence rate is possible by running independent Markov chains, drawing lower correlations and therefore increase the ESS. The results obtained with this approach are presented for the Stochastic Volatility (SV) model, basic and with leverage.
    Keywords: Bayesian Estimation; Graphics Processing Unit; Parallel Computing; Simulation; State-Space Models; Stochastic Volatility.
    JEL: C11 C13 C15 C53 C63 C87
    Date: 2014–04
  5. By: Isabelle Salle (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - CNRS : UMR5113 - Université Montesquieu - Bordeaux IV, CeNDEF - Center for Nonlinear Dynamics in Economics and Finance - Universiteit van Amsterdam); Pascal Seppecher (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS : UMR7321 - Université Nice Sophia Antipolis (UNS))
    Abstract: This paper applies a social learning model to the optimal consumption rule of Allen & Carroll (2001), and delivers convincing convergence dynamics towards the optimal rule. These findings constitute a significant improvement regarding previous results in the literature, both in terms of speed of convergence and parsimony of the learning model. The learning model exhibits several appealing features: it is frugal, easy to apply to a range of learning objectives, requires few procedures and little information. Particular care is given to behavioural interpretation of the modelling assumptions in light of evidence from the fields of psychology and social science. Our results highlight the need to depart from the genetic metaphor, and account for intentional decision-making, based on agents' relative performances. By contrast, we show that convergence is strongly hindered by exact imitation processes, or random exploration mechanisms, which are usually assumed when modelling social learning behaviour. Our results suggest a method for modelling bounded rationality, which could be tested most interestingly within the framework of a wide range of economic models with adaptive dynamics.
    Keywords: learning; bounded rationality; evolutionary algorithms; consumption rule
    Date: 2013–09–10
  6. By: Dr Justin van de Ven
    Abstract: This paper describes a structural dynamic microsimulation model that generates individualspecific data over a range of demographic and economic characteristics at annual intervals over the life-course. The model is specifically designed to analyse the distributional implications of policy alternatives in terms of their bearing on income and consumption measured over alternative time periods, from one year up to the entire life-course. This focus on economic characteristics measured over appreciable periods of life motivates endogenous simulation of savings and labour supply decisions, taking explicit account of uncertainty regarding the evolving decision environment.In contrast to the existing literature of savings in context of uncertainty, the model described here takes an overlapping generations for which we argue is better adapted to the needs of policy makers and has distinct advantages for empirical investigations.
    Date: 2013–11
  7. By: mahmood, Hamid mahmood; gul, Sidra gul
    Abstract: The paper focuses on understanding the dynamics of pre and post Free Trade Agreement (FTA) agreement between Pakistan and Malaysia. It makes use of descriptive analysis and SMART model for simulating the impact of trade liberalization and its impact on the local and ASEAN economy. The impact is measured for top five export product of Pakistan and separate case of automobile sector of Pakistan understanding the changes in export, revenue, trade creation and diversion and welfare impact. The results from the descriptive analysis suggests trade in favor of Malaysia while simulation shows increase in export, welfare and trade diversion with automobile sector showing insignificant impact on welfare.
    Keywords: Simulation, trade creation, trade diversion, export revenue and welfare
    JEL: F10 F15 F17
    Date: 2014–05–30
  8. By: Dr Katerina Lisenkova; Iana Liadze; Dr Ian Hurst
    Abstract: The NiGEM-S model is based on the National Institute Global Econometric Model, NiGEM, a large-scale structural macro-econometric model of the world economy, which the National Institute has been developing since 1987. NiGEM is used for forecasting and policy analysis by NIESR and model subscribers, mainly in the policy community, including the ECB, the IMF, the OECD, the FSA, the Bank of England, and the central banks of France, Germany, Italy, Netherlands, Spain, Portugal and the Czech Republic. NiGEM-S has two additional countries/regions and one extra-regio sector – Scotland, the rest of the UK and North Sea oil and gas sector – which are used in conjunction with the current UK model. The simulation options are limited to those affecting Scotland, the rest of the UK or North Sea oil and gas sector. NiGEM-S will be available[1] from the National Institute in Q2 2014 with a user-friendly ‘front-end’ specifically designed to facilitate simulation analysis. [1] For details check  
    Date: 2014–01
  9. By: Antonello Lobianco (Laboratoire d'Economie Forestière, INRA - AgroParisTech); Philippe Delacote (Laboratoire d'Economie Forestière, INRA - AgroParisTech; Climate Economic Chair); Sylvain Caurla (Laboratoire d'Economie Forestière, INRA - AgroParisTech); Ahmed Barkaoui (Laboratoire d'Economie Forestière, INRA - AgroParisTech)
    Abstract: Given the importance of anthropogenic determinants in forest ecosystems within Europe, the objective of FFSM++ is to link the evidence arising from biological models with socioeconomic determinants, where the expected returns of forest investments represent the main drivers. An inventory-based forest dynamic model is hence coupled with a market module and a management one in a national level forest sector model for France (FFSM++). In this paper we show that only considering the environment heterogeneity, and hence considering the local characteristics of the forest under management, we can realistically model the micro-based management module. In particular, an application is proposed that spatialises the forest growth rate and long-term scenarios (until 2100) are run to examine the effects on the forest dynamic, and notably the interaction with forest management strategies, of a potential increase of coniferous mortality in certain areas due to climate change.
    Keywords: Forest sector modelling, Spatial model, Bio-economic model, Forest mortality.
    JEL: C63 L52 Q23 Q54
    Date: 2014–04
  10. By: Wenbin Zhang; Zhen Dai; Bindu Pan; Milan Djabirov
    Abstract: This paper examines the implementation of a statistical arbitrage trading strategy based on co-integration relationships where we discover candidate portfolios using multiple factors rather than just price data. The portfolio selection methodologies include K-means clustering, graphical lasso and a combination of the two. Our results show that clustering appears to yield better candidate portfolios on average than naively using graphical lasso over the entire equity pool. A hybrid approach of using the combination of graphical lasso and clustering yields better results still. We also examine the effects of an adaptive approach during the trading period, by re-computing potential portfolios once to account for change in relationships with passage of time. However, the adaptive approach does not produce better results than the one without re-learning. Our results managed to pass the test for the presence of statistical arbitrage test at a statistically significant level. Additionally we were able to validate our findings over a separate dataset for formation and trading periods.
    Date: 2014–05
  11. By: Laurent Alfandari (IDS - Information Systems / Decision Sciences Department - ESSEC Business School); Agnès Plateau (CEDRIC - Centre d'Etude et De Recherche en Informatique du Cnam - Conservatoire National des Arts et Métiers (CNAM)); Xavier Schepler (LMAH - Laboratoire de Mathématiques Appliquées du Havre - Université du Havre)
    Abstract: In this paper, we study a multi-periodic production planning problem in agriculture. This problem belongs to the class of crop rotation planning problems, which have received increased attention in the literature in recent years. Crop cultivation and fallow periods must be scheduled on land plots over a given time horizon so as to minimize the total surface area of land used, while satisfying crop demands every period. This problem is proven strongly NP-hard. We propose a 0-1 linear programming compact formulation based on crop-sequence graphs. An extended formulation is then provided with a polynomial-time pricing problem, and a Branch-and-Priceand- Cut (BPC) algorithm is presented with adapted branching rules and cutting planes. The numerical experiments on instances varying the number of crops, periods and plots show the effectiveness of the BPC for the extended formulation compared to solving the compact formulation, even though these two formulations have the same linear relaxation bound.
    Keywords: OR in agriculture ; crop rotations ; production planning, column generation ; branch-and-price-and-cut
    Date: 2014–04
  12. By: Ben Mermelstein; Volker Nocke; Mark A. Satterthwaite; Michael D. Whinston
    Abstract: We study optimal merger policy in a dynamic model in which the presence of scale economies implies that firms can reduce costs through either internal investment in building capital or through mergers. The model, which we solve computationally, allows firms to invest or propose mergers according to the relative profitability of these strategies. An antitrust authority is able to block mergers at some cost. We examine the optimal policy when the antitrust authority can commit to a policy rule and when it cannot commit, and consider both consumer value and aggregate value as possible objectives of the antitrust authority. We find that optimal policy can differ substantially from what would be best considering only welfare in the period the merger is proposed. We also find that the ability to commit can lead to a significant welfare improvement. In general, antitrust policy can greatly affect firms' optimal investment behavior, and firms' investment behavior can in turn greatly affect the antitrust authority's optimal policy.
    JEL: L40 L41
    Date: 2014–04
  13. By: Carlos León; Clara Machado; Andrés Murcia
    Abstract: This document presents an enhanced and condensed version of preceding proposals for identifying systemically important financial institutions in Colombia. Three systemic importance metrics are implemented: (i) money market net exposures network hub centrality; (ii) large-value payment system network hub centrality; and (iii) an adjusted assets measure. Two complementary aggregation methods for those metrics are implemented: fuzzy logic and principal component analysis. The two resulting indexes concur in several features: (i) the ranking and remoteness of the top-two most systemically important financial institutions; (ii) the preeminence of credit institutions in the indexes; (iii) the appearance of a brokerage firm in the top-six; (iv) the skewed nature of the indexes, which match the skewed (i.e. inhomogeneous) nature of the three metrics and their approximate scale-free distribution. The indexes are non-redundant and provide a comprehensive relative assessment of each financial institution’s systemic importance, in which the choice of metrics pursues the macro-prudential perspective of financial stability. The indexes may serve financial authorities as quantitative tools for focusing their attention and resources where the severity resulting from an institution failing or near-failing is estimated to be the greatest. They may also serve them for enhanced policy and decision-making.
    Keywords: Systemic Importance, Systemic Risk, Fuzzy Logic, Principal Component Analysis, Financial Stability, Macro-prudential
    JEL: D85 C63 E58 G28
    Date: 2013–12–26

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