nep-cmp New Economics Papers
on Computational Economics
Issue of 2015‒04‒25
seven papers chosen by
Stan Miles
Thompson Rivers University

  1. How Diverse can Spatial Measures of Cultural Diversity be? Results from Monte Carlo Simulations on an Agent-Based Model By Daniel Arribas-Bel; Peter Nijkamp; Jacques Poot
  2. Agricultural productivity and pro-poor regional growth: A computable general equilibrium analysis of India By Athula Naranpanawa
  3. Targeted carbon tariffs. Carbon leakage and welfare effects By Christoph Böhringer; Brita Bye; Taran Fæhn; Knut Einar Rosendahl
  4. Quality- and profit-oriented scheduling of flexible resource-constrained projects By Kellenbrink, Carolin; Helber, Stefan
  5. Forecasting the term structure of crude oil futures prices with neural networks By Jozef Barunik; Barbora Malinska
  6. Transitions in the Stock Markets of the US, UK, and Germany By Matthias Raddant; Friedrich Wagner
  7. Agent-based mapping of credit risk for sustainable microfinance By Joung-Hun Lee; Marko Jusup; Boris Podobnik; Yoh Iwasa

  1. By: Daniel Arribas-Bel (VU University Amsterdam); Peter Nijkamp (VU University Amsterdam); Jacques Poot (The University of Waikato, New Zealand)
    Abstract: Cultural diversity is a complex and multi-faceted concept. Commonly used quantitative measures of the spatial distribution of culturally-defined groups 'such as segregation, isolation or concentration indexes' are often only capable of identifying just one aspect of this distribution. The strengths or weaknesses of any measure can only be comprehensively assessed empirically. This paper provides evidence on the empirical properties of various spatial measures of cultural diversity by using Monte Carlo replications of agent-based modeling (MC-ABM) simulations with synthetic data assigned to a realistic and detailed geographical context of the city of Amsterdam. Schelling's classical segregation model is used as the theoretical engine to generate patterns of spatial clustering. The data inputs include the initial population, the number and shares of various cultural groups, and their preferences with respect to co-location. Our MC-ABM data generating process generates output maps that enable us to assess the performance of various spatial measures of cultural diversity under a range of demographic compositions and preferences. We find that, as our simulated city becomes more diverse, stable residential location equilibria are only possible when particularly minorities become more tolerant. We test whether observed measures can be interpreted as revealing unobserved preferences for co-location of individuals with their own group and find that the segregation and isolation measures of spatial diversity are shown to be non-decreasing in increasing preference for within-group co-location, but the Gini coefficient and concentration measures are not.
    Keywords: cultural diversity, spatial segregation, agent-based model, Monte Carlo simulation
    JEL: C63 J15 R23 Z13
    Date: 2014–07–03
  2. By: Athula Naranpanawa
    Keywords: Agricultural productivity, Regional economic growth, Pro-poor growth, Computable general equilibrium model, South Asia, India
    JEL: C68 Q16 R11
    Date: 2015–03
  3. By: Christoph Böhringer; Brita Bye; Taran Fæhn; Knut Einar Rosendahl (Statistics Norway)
    Abstract: Climate effects of unilateral carbon policies are undermined by carbon leakage. To counteract leakage and increase global cost-effectiveness carbon tariffs can be imposed on the emissions embodied in imports from non-regulating regions. We present a theoretical analysis on the economic incentives for emission abatement of producers subjected to carbon tariffs. We quantify the impacts of different carbon tariff designs by an empirically based multi-sector, multi-region CGE model of the global economy. We find that firm-targeted tariffs can deliver much stronger leakage reduction and higher efficiency gains than tariff designs operated at the industry level. In particular, because the exporters are able to reduce their carbon tariffs by adjusting emissions, their competitiveness and the overall welfare of their economies will be less randomly and less adversely affected than in previously studied carbon tariff regimes. This beneficial distributional impact could facilitate a higher degree of legitimacy and legality of carbon tariffs.
    Keywords: carbon leakage; border carbon adjustment; carbon tariffs; computable general equilibrium (CGE)
    JEL: Q43 Q54 H2 D61
    Date: 2015–03
  4. By: Kellenbrink, Carolin; Helber, Stefan
    Abstract: We study the problem of determining both the structure and the schedule of projects subject to capacity constraints. We assume that those projects are flexible in the sense that the activities to be implemented are not entirely known in advance. In such a setting, decisions must be made with respect to the implementation of the optional activities. Such decisions affect the duration, cost, quality and eventual revenue of the project. Examples of this type of problem can often be found when complex capital goods such as aircraft engines are overhauled, when buildings are renovated to meet higher environmental and efficiency standards, or in productdevelopment processes. We describe the problem, develop a mixed-integer optimisation model, explain specific features of a genetic algorithm to solve the problem and report the results of a numerical study.
    Keywords: Quality, project scheduling, genetic algorithm, RCPSP, flexible projects
    Date: 2014–12
  5. By: Jozef Barunik; Barbora Malinska
    Abstract: The paper contributes to the rare literature modeling term structure of crude oil markets. We explain term structure of crude oil prices using dynamic Nelson-Siegel model, and propose to forecast them with the generalized regression framework based on neural networks. The newly proposed framework is empirically tested on 24 years of crude oil futures prices covering several important recessions and crisis periods. We find 1-month, 3-month, 6-month and 12-month-ahead forecasts obtained from focused time-delay neural network to be significantly more accurate than forecasts from other benchmark models. The proposed forecasting strategy produces the lowest errors across all times to maturity.
    Date: 2015–04
  6. By: Matthias Raddant; Friedrich Wagner
    Abstract: In an analysis of the US, the UK, and the German stock market we find a change in the behavior based on the stock's beta values. Before 2006 risky trades were concentrated on stocks in the IT and technology sector. Afterwards risky trading takes place for stocks from the financial sector. We show that an agent-based model can reproduce these changes. We further show that the initial impulse for the transition might stem from the increase of high frequency trading at that time.
    Date: 2015–04
  7. By: Joung-Hun Lee; Marko Jusup; Boris Podobnik; Yoh Iwasa
    Abstract: Inspired by recent ideas on how the analysis of complex financial risks can benefit from analogies with independent research areas, we propose an unorthodox framework for mapping microfinance credit risk---a major obstacle to the sustainability of lenders outreaching to the poor. Specifically, using the elements of network theory, we constructed an agent-based model that obeys the stylised rules of microfinance industry. We found that in a deteriorating economic environment confounded with adverse selection, a form of latent moral hazard may cause a regime shift from a high to a low loan repayment probability. An after-the-fact recovery, when possible, required the economic environment to improve beyond that which led to the shift in the first place. These findings suggest a small set of measurable quantities for mapping microfinance credit risk and, consequently, for balancing the requirements to reasonably price loans and to operate on a fully self-financed basis. We illustrate how the proposed mapping works using a 10-year monthly data set from one of the best-known microfinance representatives, Grameen Bank in Bangladesh. Finally, we discuss an entirely new perspective for managing microfinance credit risk based on enticing spontaneous cooperation by building social capital.
    Date: 2015–04

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