nep-cmp New Economics Papers
on Computational Economics
Issue of 2016‒09‒25
thirteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Asymmetry Helps: Dynamic Half-Way Points for Solving Shortest Path Problems with Resource Constraints Faster By Christian Tilk; Ann-Kathrin Rothenbächer; Timo Gschwind; Stefan Irnich
  2. Predicting Future Shanghai Stock Market Price using ANN in the Period 21-Sep-2016 to 11-Oct-2016 By Barack Wamkaya Wanjawa
  3. A Conceptual Framework for Integrated Economic-Environmental Modelling By Onil Banerjee; Martin Cicowiez; Mark Horridge; Renato Vargas
  4. Bayesian Estimation of Agent-Based Models By Jakob Grazzini; Matteo Richiardi; Mike Tsionas
  5. Improving the Validity of Microsimulation Results: Lessons from Slovakia By Zuzana Siebertová; Norbert Švarda; Jana Valachyová
  6. The Impact of the COMESA-EAC-SADC Tripartite Free Trade Agreement on the South African Economy By Leone Walters; Heinrich R. Bohlmann; Matthew W. Clance
  7. A novel branch-and-bound algorithm for the chance-constrained RCPSP By Morteza Davari; Erik Demeulemeester
  8. Agent-based Macroeconomics and Dynamic Stochastic General Equilibrium Models: Where do we go from here? By Özge Dilaver; Robert Jump; Paul Levine
  9. The effects of Labour Market Reforms upon Unemployment and Income Inequalities : an agent based model By G. Dosi; M.C. Pereira; A. Roventini; M.E. Virgillito Author-Workplace-Name Scuola Superiore Sant'Anna
  10. Economic growth and individual satisfaction in an agent-based economy By J. Silvestre,; T. Araújo; M. St. Aubyn
  11. Economic growth and individual satisfaction in an agent-based economy By António Afonso; Jorge Silva
  13. Spatial firm competition in two dimensions with linear transportation costs: simulations and analytical results By Alan Roncoroni; Matus Medo

  1. By: Christian Tilk (Johannes Gutenberg-University Mainz, Germany); Ann-Kathrin Rothenbächer (Johannes Gutenberg-University Mainz, Germany); Timo Gschwind (Johannes Gutenberg-University Mainz, Germany); Stefan Irnich (Johannes Gutenberg-University Mainz, Germany)
    Abstract: With their paper “Symmetry helps: Bounded bi-directional dynamic programming for the elementary shortest path problem with resource constraints” [Discrete Optimization 3, 2006, pp. 255–273] Righini and Salani introduced bounded bidirectional dynamic programming (DP) as an acceleration technique for solving variants of the shortest path problem with resource constraints (SPPRC). SPPRCs must be solved iteratively when vehicle routing and scheduling problems are tackled via Lagrangian relaxation or column-generation techniques. Righini and Salani and several subsequent works have shown that bounded bidirectional DP algorithms are often superior to their monodirectional counterparts, since the former can mitigate the effect that the number of labels increases strongly with the path length. Bidirectional DP has become a quasi-standard for solving SPPRCs. In computational experiments, however, one can still observe that the number of forward and backward label extensions is very unbalanced despite a symmetric bounding of a critical resource in the middle of its feasible domain. We exploit this asymmetry in forward and backward label extensions and introduce a so-called dynamic half-way point, which is a dynamic bounding criterion based on the current state of the simultaneously solved forward and backward DPs. Experiments with the standard and the electric vehicle routing problem with time windows as well as the vehicle routing and truck driver scheduling problem con?rm that dynamic half-way points better balance forward and backward workload.
    Keywords: Shortest path problem with resource constraints (SPPRC), bidirectional labeling algorithms
    Date: 2016–08–04
  2. By: Barack Wamkaya Wanjawa
    Abstract: Predicting the prices of stocks at any stock market remains a quest for many investors and researchers. Those who trade at the stock market tend to use technical, fundamental or time series analysis in their predictions. These methods usually guide on trends and not the exact likely prices. It is for this reason that Artificial Intelligence systems, such as Artificial Neural Network, that is feedforward multi-layer perceptron with error backpropagation, can be used for such predictions. A difficulty in neural network application is the determination of suitable network parameters. A previous research by the author already determined the network parameters as 5:21:21:1 with 80% training data or 4-year of training data as a good enough model for stock prediction. This model has been put to the test in predicting selected Shanghai Stock Exchange stocks in the future period of 21-Sep-2016 to 11-Oct-2016, about one week after the publication of these predictions. The research aims at confirming that simple neural network systems can be quite powerful in typical stock market predictions.
    Date: 2016–09
  3. By: Onil Banerjee (Inter-American Development Bank); Martin Cicowiez (UNLP - FCE); Mark Horridge (Victoria University); Renato Vargas (World Bank)
    Abstract: Economy-wide models such as Computable General Equilibrium (CGE) Models are powerful tools that provide insights on policy impacts on standard economic indicators. With the recent publication of the System of Environmental-Economic Accounts (SEEA), the power of this approach is amplified. This paper addresses an important gap in economy-wide policy modelling applications and literature by developing a conceptual framework for the integration of the SEEA in the CGE framework, enabling for the first time the analysis of policy impacts on the economy and the environment in a quantitative, comprehensive and consistent framework. Previous integrated modelling efforts have generally focused on the interaction between the economy and one environmental resource in isolation, requiring significant data reconciliation. Integration of SEEA into a CGE circumvents this resource intense process, enhancing analytical power, obviating the need for strong assumptions in reconciling economic-environmental data, reducing start-up costs, and increasing the timeliness of evidence-based policy advice.
    Date: 2016–09
  4. By: Jakob Grazzini (Catholic University of Milan, Italy); Matteo Richiardi (Institute for New Economic Thinking, Nuffield College and University of Torino); Mike Tsionas (Lancaster Univesity Mangament School)
    Abstract: We consider Bayesian inference techniques for Agent-Based (AB) models, as an alternative to simulated minimum distance (SMD). We discuss the specificities of AB models with respect to models with exact aggregation results (as DSGE models), and how this impact estimation. Three computationally heavy steps are involved: (i) simulating the model, (ii) estimating the likelihood and (iii) sampling from the posterior distribution of the parameters. Computational complexity of AB models implies that efficient techniques have to be used with respect to points (ii) and (iii), possibly involving approximations. We first discuss non-parametric (kernel density) estimation of the likelihood, coupled with Markov chain Monte Carlo sampling schemes. We then turn to parametric approximations of the likelihood, which can be derived by observing the distribution of the simulation outcomes around the statistical equilibria, or by assuming a specific form for the distribution of external deviations in the data. Finally, we introduce Approximate Bayesian Computation techniques for likelihood-free estimation. These allow embedding SMD methods in a Bayesian framework, and are particularly suited when robust estimation is needed. These techniques are tested, for the sake of comparison, in the same price discovery model used by Grazzini and Richiardi (2015) to illustrate SMD techniques.
    Date: 2015–11–27
  5. By: Zuzana Siebertová; Norbert Švarda; Jana Valachyová
    Abstract: This paper summarizes the lessons learned in the process of building a microsimulation tool tailored to country-specific conditions and involving a maximum degree of user control. The objective to construct a model useful in the process of budgeting and fiscal forecasting has been achieved by paying attention to policy simulation details as well as to the representativeness of the underlying micro-dataset. The validity of simulated results improved significantly after the input database sample has been reweighted in such a way that the new weights replicate, among other factors, the earned income distribution and selected age cohorts directly.Innovative approaches in bringing the model closer to legislation as well as data highlight the benefits of having more user control compared with standardized microsimulation tools.
    Date: 2016–09–12
  6. By: Leone Walters (Department of Economics, University of Pretoria, South Africa); Heinrich R. Bohlmann (Department of Economics, University of Pretoria, South Africa); Matthew W. Clance (Department of Economics, University of Pretoria, South Africa)
    Abstract: This paper analyses the e¤ects of the COMESA-EAC-SADC Tripartite Free Trade Agreement (TFTA) on the South African economy using a global Computable General Equilibrium (CGE) model. Simulation results show that South Africa’s economy gains from the implementation of the trade agreement with GDP rising by more than 1 per cent relative to the baseline. This win in overall economic activity occurs on the back of a term of trade increase and a surge in regional trade, which allows for higher levels of both exports and imports. The boost to exports stimulates local industries, whilst relatively cheaper imports lead to welfare gains for local consumers. Increased trade and industry activity causes higher demand for endowments, including skilled and unskilled labour, capital and land, pushing up wages and capital rentals.
    Keywords: Computable General Equilibrium (CGE) Modelling, Free Trade Agreement, South Africa
    JEL: C68 F13 O55
    Date: 2016–09
  7. By: Morteza Davari; Erik Demeulemeester
    Abstract: The resource-constrained project scheduling problem (RCPSP) has been widely studied during the last few decades. In real-world projects, however, not all information is known in advance and uncertainty is an inevitable part of these projects. The chance-constrained resource-constrained project scheduling problem (CC-RCPSP) has been recently introduced to deal with uncertainty in the RCPSP. In this paper, we propose a branch-and-bound (B&B) algorithm and a MILP formulation that solve the CC-RCPSP. We introduce two different branching schemes and eight different priority rules for the proposed B&B algorithm. Since solving CC-RCPSP is computationally intractable, its sample average approximation counterpart is considered to be solved. The computational results suggest that the proposed branch-and-bound procedure clearly outperforms both a proposed MILP formulation and a branch-and-cut algorithm from the literature.
    Keywords: Chance-constrained problem, Branch-and-bound, CC-RCPSP
    Date: 2016–09
  8. By: Özge Dilaver (University of Surrey); Robert Jump (Kingston University London); Paul Levine (University of Surrey)
    Abstract: Agent-based computational economics (ACE) has been used for tackling major research questions in macroeconomics for at least two decades. This growing field positions itself as an alternative to dynamic stochastic general equilibrium (DSGE) models. In this paper we first review the arguments raised against DSGE in the ACE literature. We then review existing ACE models, and their empirical performance. We then turn to a literature on behavioural New Keynesian models that attempts to synthesise these two approaches to macroeconomic modelling by incorporating some of the insights of ACE into DSGE modelling. We highlight the individually rational New Keynesian model following Deak et al. (2015) and discuss how this line of research can progress.
    JEL: E03 E12 E32
    Date: 2016–01
  9. By: G. Dosi (Scuola Superiore Sant'Anna); M.C. Pereira (University of Campinas); A. Roventini (Scuola Superiore Sant'Anna OFCE Sciences PO); M.E. Virgillito Author-Workplace-Name Scuola Superiore Sant'Anna
    Abstract: This paper is meant to analyse the e ects of labour market structural reforms by means of an agent-based model. Building on Dosi et al. (2016b) we introduce a policy regime change characterized by a set of structural reforms on the labour market, keeping constant the structure of the capital- and consumption-good markets. Con rming a recent IMF report (Jaumotte and Buitron, 2015), the model shows how labour market structural reforms reducing workers' bargaining power and compressing wages tend to increase (i) unemployment, (ii) functional income inequality, and (iii) personal income inequality. We further undertake a global sensitivity analysis on key variables and parameters which confirms the robustness of our findings.
    Keywords: Labor market structural reforms, Income distribution, Inequality, Unemployment, Long Run Growth
    JEL: C63 E02 E12 E24 O11
    Date: 2016–07
  10. By: J. Silvestre,; T. Araújo; M. St. Aubyn
    Abstract: Macro and micro-economic perspectives are combined in an economic growth model. An agent-based modeling approach is used to develop an overlapping generation framework where endogenous growth is supported by workers that decide to study depending on their relative (skilled and unskilled) indi- vidual satisfaction. The micro perspective is based on individual satisfaction: an utility function computed from the variation of the relative income in both space and time. The macro perspective emerges from micro decisions, and, as in other growth models of this type, concerns an important allocative social decision the share of the working population that is engaged in producing ideas (skilled workers). Simulations show that production and satisfaction levels are higher when the evolution of income measured in both space and time are equally weighted. Key Words : agent modeling, education, heterogeneous human capital, economic growth, individual satisfaction.
    Date: 2016–09
  11. By: António Afonso; Jorge Silva
    Abstract: We assess the cyclicality of current account balances for the period 2001Q1-2014Q4, focussing on Portugal and in Germany, as a benchmark. We find that the cyclical component of the current account was positively explained by 3-months Euribor, but negatively by the financial crisis, systemic stress in Europe, employment and compensation of employees. Moreover, the non-cyclical current account was positively affected by the period of the Economic and Financial Adjustment Program and the terms of trade, but negatively influenced by financial integration. Key Words : current account cyclicality, financial markets, Portugal, Germany.
    JEL: C23 F32 G01
    Date: 2016–09
  12. By: Laura Roa Castro (IRT SystemX, LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec); Julie Stal-Le Cardinal (LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec); Laurent Gasser (IRT SystemX)
    Abstract: The research presented in this paper is part of a larger effort on collaborative design modelling, and is focused in the modelling of three main characteristics in collaborative design using simulation models: actors, activities and objects. To represent these three features, an added value process proposition for a collaborative design in early development phases using simulation models was suggested. The proposed process contributes to an added value solution at three different levels in the organization: the operational level, the tactic level and the strategic level, and was implemented during a project at the Research Institute of Technology SystemX having Renault and Airbus industries as partners of the project. After the project ends, dynamic interviews were done with the project team members in order to get a feedback regarding the process and to understand the collaborative interactions in a real use case. Afterwards, implementation and evaluation of the process conclude that collaboration in Modelling and simulation context is not a linear problem at all, but the proposed representation is highly adapted to improve global comprehension of the objectives and the context understanding in a first time. The results point out the actors as the key element on the collaborative design and raise a new research question.
    Keywords: concurrent engineer,collaborative simulation,CAE-CAE collaboration,collaborative process
    Date: 2016–05–16
  13. By: Alan Roncoroni; Matus Medo
    Abstract: Models of spatial firm competition assume that customers are distributed in space and transportation costs are associated with their purchases of products from a small number of firms that are also placed at definite locations. It has been long known that the competition equilibrium is not guaranteed to exist if the most straightforward linear transportation costs are assumed. We show by simulations and also analytically that if periodic boundary conditions in two dimensions are assumed, the equilibrium exists for a pair of firms at any distance. When a larger number of firms is considered, we find that their total equilibrium profit is inversely proportional to the square root of the number of firms. We end with a numerical investigation of the system's behavior for a general transportation cost exponent.
    Date: 2016–09

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