nep-cmp New Economics Papers
on Computational Economics
Issue of 2017‒03‒19
ten papers chosen by
Stan Miles
Thompson Rivers University

  1. A Regional Trade Model with Ricardian Productivity Gains and Multi-technology Electricity Supply By Pothen, Frank; Hübler, Michael
  2. Accessibility, Transportation Cost and Regional Growth: A Case Study for Egypt By Dina N. Elshahawany; Eduardo A. Haddad; Michael L. Lahr
  3. New Perspectives on Institutionalist Pattern Modeling: Systemism, Complexity, and Agent-Based Modeling By Gräbner, Claudius; Kapeller, Jakop
  4. Case Study of the Moldovan Bank Fraud: Is Early Intervention the Best Central Bank Strategy to Avoid Financial Crises? By Alexandru Monahov; Thomas Jobert
  5. *K-means and Cluster Models for Cancer Signatures By Zura Kakushadze; Willie Yu
  6. Humans of Simulated New York (HOSNY): an exploratory comprehensive model of city life By Francis Tseng; Fei Liu; Bernardo Alves Furtado
  7. Mega-Regional Trade Agreements: Costly Distractions for Developing Countries? By Badri Narayan G.
  8. Closing the gender gap in pensions. A microsimulation analysis of the Norwegian NDC pension system By Elin Halvorsen; Axel West Pedersen
  9. Computational analysis of source receptor air pollution problems By Halkos, George; Tsilika, Kyriaki
  10. System Integration of Wind and Solar Power in Integrated Assessment Models: a Cross-model Evaluation of New Approaches By Pietzcker, Robert C.; Ueckerdt, Falko; Carrara, Samuel; de Boer, Harmen Sytze; Després, Jacques; Fujimori, Shinichiro; Johnson, Nils; Kitous, Alban; Scholz, Yvonne; Sullivan, Patrick; Luderer, Gunnar

  1. By: Pothen, Frank; Hübler, Michael
    Abstract: This article presents an applied general equilibrium model which combines the theoretical foundations of an Eaton-Kortum type model of international trade with the complexity of a global multi-region, multi-sector Computable General Equilibrium (CGE) model of production and consumption. The Eaton-Kortum model features endogenous trade-induced productivity gains via Ricardian specialization and takes non-tariff trade costs into account. Model regions and sectors can be disaggregated, e.g., representing technology-specific electricity generation. The models is tailored to explicitly study the German Federal State of Lower Saxony, a prime location for renewable electricity generation in Germany with ambitious climate policy goals. The calibration utilizes the structural estimation of a gravity model with constraints, while the disaggregation adapts methods used in regional science and energy economics. With these features the model goes beyond standard CGE models and provides new insights in the nexus between trade policy and climate policy. Simulations suggest that the removal of tariffs creates smaller welfare gains than a comparable reduction of non-tariff barriers to trade but also a slightly smaller increase in global CO2 emissions. Trade policy-induced productivity gains and renewable energy subsidies significantly reduce carbon leakage from the EU to the rest of the world by making the EU more CO2-efficient. With its large wind power potential, Lower Saxony is less susceptible to negative effects of climate policy than the rest of Germany.
    Keywords: international trade; regional model; climate policy; renewable energy; CGE
    JEL: C68 F10 F18 Q40
    Date: 2017–03
  2. By: Dina N. Elshahawany (Zagazig University); Eduardo A. Haddad; Michael L. Lahr
    Abstract: The potential ability of transport infrastructure investments to produce transport benefits depends on the travel time reductions and accessibility. In this paper, we use an interregional computable general equilibrium (CGE) model to estimate the economic impacts of transportation cost change due specifically to changes in accessibility induced by new transportation projects. The model is integrated with a stylized geo-coded transportation network model to help quantify the spatial effects of transportation cost change. The analysis is focus on a proposed development corridor in Egypt. A main component of the project is a desert-based expansion of the current highway network. The paper focuses on the likely structural economic impacts that such a large investment in transportation could enable through a series of simulations. It is clear that an integrated spatial CGE model can be useful in estimating the potential economic impacts of transportation projects in Egypt. In this vein, this or similar models should support government decisions on such projects.
    Date: 2016–01–09
  3. By: Gräbner, Claudius; Kapeller, Jakop
    Abstract: This paper focuses on the complementarity between original institutional economics, Mario Bunge’s framework of systemism, and the formal tools developed by complexity economists, especially in the context of agent-based modeling. Thereby, we assert that original institutional economics might profit from exploiting this complementarity.
    Keywords: Aggregation, Original Institutionalism, Systemism, Agent-Based Computational Economics, Complexity
    JEL: B41 B52 C63
    Date: 2015–06–19
  4. By: Alexandru Monahov (Université Côte d'Azur; GREDEG CNRS); Thomas Jobert (Université Côte d'Azur; GREDEG CNRS)
    Abstract: In this paper, we study the means by which a billion dollar fraud that was perpetuated in the Moldovan banking sector evolved into a severe financial crisis in which the Central Bank’s inaction came under scrutiny. We examine the financial operations through which money was taken out of the banking system and reconstruct the fraudulent schemes that led to the demise of three systemically important banks. We also create an agent-based simulation of the banking system which replicates the pre-crisis environment and the fraudulent schemes to determine whether Central Bank intervention could have improved the outcome of the crisis.
    Keywords: Financial Fraud, Prudential supervision, Central Bank Intervention, Agent Based Model, Multi-Agent Simulation
    JEL: C61 C63 E58 E65 G28
    Date: 2017–03
  5. By: Zura Kakushadze; Willie Yu
    Abstract: We present *K-means clustering algorithm and source code by expanding statistical clustering methods applied in to quantitative finance. *K-means is essentially deterministic without specifying initial centers, etc. We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF). *K-means' computational cots is a faction of NMF's. Using 1,389 published samples for 14 cancer types, we find that 3 cancers (liver cancer, lung cancer and renal cell carcinoma) stand out and do not have cluster-like structures. Two clusters have especially high within-cluster correlations with 11 other cancers indicating common underlying structures. Our approach opens a novel avenue for studying such structures. *K-means is universal and can be applied in other fields. We discuss some potential applications in quantitative finance.
    Date: 2017–03
  6. By: Francis Tseng; Fei Liu; Bernardo Alves Furtado
    Abstract: The model presented in this paper experiments with a comprehensive simulant agent in order to provide an exploratory platform in which simulation modelers may try alternative scenarios and participation in policy decision-making. The framework is built in a computationally distributed online format in which users can join in and visually explore the results. Modeled activity involves daily routine errands, such as shopping, visiting the doctor or engaging in the labor market. Further, agents make everyday decisions based on individual behavioral attributes and minimal requirements, according to social and contagion networks. Fully developed firms and governments are also included in the model allowing for taxes collection, production decisions, bankruptcy and change in ownership. The contributions to the literature are multifold. They include (a) a comprehensive model with detailing of the agents and firms' activities and processes and original use of simultaneously (b) reinforcement learning for firm pricing and demand allocation; (c) social contagion for disease spreading and social network for hiring opportunities; and (d) Bayesian networks for demographic-like generation of agents. All of that within a (e) visually rich environment and multiple use of databases. Hence, the model provides a comprehensive framework from where interactions among citizens, firms and governments can be easily explored allowing for learning and visualization of policies and scenarios.
    Date: 2017–03
  7. By: Badri Narayan G. (School of Environmental and Forestry Sciences, University of Washington-Seattle, USA)
    Abstract: This paper examines how new trade rules under mega-regional agreements (in the Asia Pacific and the Atlantic) aim to liberalise ‘substantially all trade and investment’ but commitments undertaken by member countries could potentially impact on the health of the public in these countries. The mechanism of impact that the paper examines is through tariff elimination and the requirements of stronger intellectual property commitments for partner countries. We analyse two interlinked policy concerns: first, how tariff reduction/elimination under mega regional agreements impact on prices of tobacco and tobacco products as well as sugar and sugary beverages. Second, how mega regional agreements with Trade-Related Aspects of Intellectual Property Rights (TRIPS) like and TRIPS-plus commitments could modify intellectual property rules among partner countries and impact on developing countries’ access to life saving drugs and access to medicines. Using dynamic-GTAP model we find that there are significant health consequences of commitments undertaken by developing countries. Simulation results reveal: first, production of sugar increases under trade agreements with potential detrimental health effects. Second, stricter intellectual property rules under mega trade agreements lead to net global gains but developing countries suffer in terms of adverse health impact and from regulatory chill effect.
    Keywords: Economic Integration; Trade Policy; Government policy
    JEL: F15 F13 I18
    Date: 2017–03
  8. By: Elin Halvorsen; Axel West Pedersen (Statistics Norway)
    Abstract: In this paper we use an advanced micro-simulation model to study the distributional effects of the reformed Norwegian pension system with a particular focus on gender equality. The reformed Norwegian system is based on the NDC-formula with fixed contribution/accrual rates over the active life-phase and with accumulated pension wealth being transformed into an annuity upon retirement. A number of redistributive components are built into the system that makes it deviate from complete actuarial fairness: a unisex annuity divisor, a ceiling on annual earnings, generous child credits, a possibility for widows/widowers to inherit pension rights from a deceased spouse, a targeted guarantee pensions with higher benefit rates to single pensioners compared to married/cohabitating pensioners, and finally the tax system that is particularly progressive in its treatment of pensioners and pension income. Taking complete actuarial fairness as the point of departure, we conduct a stepwise analysis to investigate how these different components of the National Insurance pension system impact on the gender gap in pensions and on inequality in the distribution of pension income within a cohort of pensioners.
    Keywords: Pensions; Gender gap; Inequality; Micro simulation
    JEL: D31 E47 H55
    Date: 2017–01
  9. By: Halkos, George; Tsilika, Kyriaki
    Abstract: This study introduces a method of graph computing for Environmental Economics. Different visualization modules are used to reproduce source-receptor air pollution schemes and identify their structure. Data resources are emissions-depositions tables, available online from the European Monitoring and Evaluation Program (EMEP) of the Long-Range Transmission of Air Pollutants in Europe. In network models of pollutants exchange, we quantify the responsibility of polluters by exploring graph measures and metrics. In a second step, we depict the size of the responsibility of EU countries. We create pollution schemes for ranking the blame for the change in pollutants in the extended EMEP area. Our approach considers both the activity and the amount of pollution for each polluter. To go a step further in qualitative analysis of pollution features, we cluster countries in communities, bonded with strong polluting-based relationships. The network framework and pollution pattern visualization in tabular representations is integrated in Mathematica computer software.
    Keywords: Computational data analysis; graph modeling; visual analytics; source-receptor air pollution; polluters’ responsibility.
    JEL: C63 C88 P28 Q51 Q53 Q58
    Date: 2017
  10. By: Pietzcker, Robert C.; Ueckerdt, Falko; Carrara, Samuel; de Boer, Harmen Sytze; Després, Jacques; Fujimori, Shinichiro; Johnson, Nils; Kitous, Alban; Scholz, Yvonne; Sullivan, Patrick; Luderer, Gunnar
    Abstract: Mitigation-Process Integrated Assessment Models (MP-IAMs) are used to analyze long-term transformation pathways of the energy system required to achieve stringent climate change mitigation targets. Due to their substantial temporal and spatial aggregation, IAMs cannot explicitly represent all detailed challenges of integrating the variable renewable energies (VRE) wind and solar in power systems, but rather rely on parameterized modeling approaches. In the ADVANCE project, six international modeling teams have developed new approaches to improve the representation of power sector dynamics and VRE integration in IAMs. In this study, we qualitatively and quantitatively evaluate the last years’ modeling progress and study the impact of VRE integration modeling on VRE deployment in IAM scenarios. For a comprehensive and transparent qualitative evaluation, we first develop a framework of 18 features of power sector dynamics and VRE integration. We then apply this framework to the newly-developed modeling approaches to derive a detailed map of strengths and limitations of the different approaches. For the quantitative evaluation, we compare the IAMs to the detailed hourly-resolution power sector model REMIX. We find that the new modeling approaches manage to represent a large number of features of the power sector, and the numerical results are in reasonable agreement with those derived from the detailed power sector model. Updating the power sector representation and the cost and resources of wind and solar substantially increased wind and solar shares across models: Under a carbon price of 30$/tCO2 in 2020 (increasing by 5% per year), the model-average cost-minimizing VRE share over the period 2050-2100 is 62% of electricity generation, 24%-points higher than with the old model version.
    Keywords: Integrated Assessment Models (IAM), Variable Renewable Energy (VRE), Wind and Solar Power, System Integration, Power Sector Model, Flexibility Options (Storage, Transmission Grid, Demand Response), Model Evaluation, Model Validation, Resource /Energy Economics and Policy, C6, C61, Q40, Q42, Q47, Q49,
    Date: 2017–03–03

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