nep-cmp New Economics Papers
on Computational Economics
Issue of 2017‒08‒06
six papers chosen by

  1. How to relate models to reality? An epistemological framework for the validation and verification of computational models By Claudius Graebner
  2. Simulating the Mutual Sequential Mate Search Model under Non-homogenous Preferences By Saglam, Ismail
  3. Mutation Clusters from Cancer Exome By Zura Kakushadze; Willie Yu
  4. Capital Misallocation and Secular Stagnation By Ander Perez-Orive; Andrea Caggese
  5. A ternary-state early warning system for the European Union By Savas Papadopoulos; Pantelis Stavroulias; Thomas Sager; Etti Baranoff
  6. Trust and Social Control. Sources of cooperation, performance, and stability in informal value transfer systems By Claudius Graebner; Wolfram Elsner; Alexander Lascaux

  1. By: Claudius Graebner (Institute for Institutional and Innovation Economics (iino), University of Bremen, Germany)
    Abstract: Agent-based simulations have become increasingly prominent in various disciplines. This trend is to be appreciated, but it comes with challenges: while there are more and more standards for design, verification, validation, and presentation of the models, the various meta-theoretical strategies of how the models should be related to reality often remain implicit. Differences in the epistemological foundations of models makes it, however, difficult to relate distinct models to each other. This paper suggests an epistemological framework that helps to make explicit how one wishes to generate knowledge about reality by the means of one's model and that helps to relate models to each other. Because the interpretation of a model is strongly connected to the activities of model verification and validation, I embed these two activities into the framework and clarify their respective epistemological roles. Finally, I show how this meta-theoretical framework aligns well with recently proposed framework for model presentation and evaluation.
    Keywords: Agent-based modelling, epistemology, models, validation, verification
    Date: 2017–06
  2. By: Saglam, Ismail
    Abstract: This paper extends the Todd and Miller's (1999) mutual sequential mate search model with homogenous preferences to the case of non-homogenous preferences. Our simulations show that the size of heterogeneity in the preferences affects the performance rankings -as well as the absolute success levels- of the mate search heuristics in the model with respect to both mating likelihood and mating stability.
    Keywords: Mate Choice; Mate Search; Simple Heuristics; Agent-Based Simulation; Correlated Preferences
    JEL: C6 C63 Z00
    Date: 2017–08–01
  3. By: Zura Kakushadze; Willie Yu
    Abstract: We apply our statistically deterministic machine learning/clustering algorithm *K-means (recently developed in to 10,656 published exome samples for 32 cancer types. A majority of cancer types exhibit mutation clustering structure. Our results are in-sample stable. They are also out-of-sample stable when applied to 1,389 published genome samples across 14 cancer types. In contrast, we find in- and out-of-sample instabilities in cancer signatures extracted from exome samples via nonnegative matrix factorization (NMF), a computationally costly and non-deterministic method. Extracting stable mutation structures from exome data could have important implications for speed and cost, which are critical for early-stage cancer diagnostics such as novel blood-test methods currently in development.
    Date: 2017–07
  4. By: Ander Perez-Orive (Federal Reserve Board); Andrea Caggese (Pompeu Fabra University)
    Abstract: The widespread emergence of intangible technologies in recent decades may have significantly hurt output growth--even when these technologies replaced considerably less productive tangible technologies--because of low interest rates. After a shift toward intangible capital in production, the corporate sector becomes a net saver because intangible capital has a low collateral value. Firms' ability to purchase intangible capital is impaired by low interest rates because low rates slow down the accumulation of savings and increase the price of capital, worsening capital misallocation. Our model simulations reproduce key trends in the U.S. in the period from 1980 to 2015.
    Date: 2017
  5. By: Savas Papadopoulos (Bank of Greece); Pantelis Stavroulias (Democritus University of Thrace); Thomas Sager (University of Texas); Etti Baranoff (Virginia Commonwealth University)
    Abstract: The global financial crisis of 2007-2008 focused the attention of financial authorities on developing methods to forecast and avoid future financial crises of similar magnitude. We contribute to the literature on crisis prediction in several important ways. First, we develop an early warning system (EWS) that provides 7-12 quarters advance warning with high accuracy in out-of-sample testing. Second, the EWS applies region-wide to the leading economies in the European Union. Third, the methodology is transparent – utilizing only publicly available macro-level data and standard statistical classification methodology (multinomial logistic regression, discriminant analysis, and neural networks). Fourth, we employ two relatively novel methodological innovations in EWS modeling: ternary state classification to guarantee a minimum advance warning period, and a fitting and evaluation criterion (the total harmonic mean) that prioritizes avoiding classification errors for the relatively infrequent events of most interest. As a consequence, a policymaker who uses these methods will enjoy a high probability that future crises will be signaled well in advance and that warnings of crisis will not be false alarms.
    Keywords: Banking crisis; financial stability; macroprudential policy; classification methods; goodness-of-fit measures
    JEL: C53 E58 G28
    Date: 2017–04
  6. By: Claudius Graebner (Institute for Institutional and Innovation Economics (iino), University of Bremen, Germany); Wolfram Elsner (Institute for Institutional and Innovation Economics, University of Bremen, Germany); Alexander Lascaux (Russian Presidential Academy of National Economy and Public Administration, Moscow, Russia)
    Abstract: We study the functioning of informal value transfer systems (IVTS) with the example of Hawala. More precisely, we use computational experiments to study the roles of generalized trust and social control for the stability and efficiency of IVTS. Previous literature was ambiguous with regard to: (i) how trust and control should be operationalized formally, (ii) which, if any of the two, carries a larger relevance for the functioning of IVTS, (iii) whether (and when) they relate to each other as substitutes or complements, and (iv) how they interact with a number of other environmental conditions. Our experiments suggest answers to all these questions. We show that both trust and control are necessary, but not sufficient to guarantee the functioning of Hawala, and that other relevant conditions, such as population size, interaction density, and forgiveness of the agents, provide important contexts. Aside from clarifying these questions, we provide a theoretically grounded operationalization of generalized trust and social control that is applicable to informal exchange systems in general.
    Keywords: Hawala, Computational experiment, Informal Value Transfer Systems, Institution, Social Control, Trust
    Date: 2017–06

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