nep-cmp New Economics Papers
on Computational Economics
Issue of 2018‒05‒14
nine papers chosen by
Stan Miles
Thompson Rivers University

  1. Inequality, Redistributive Policies and Multiplier Dynamics in an Agent-based Model with Credit Rationing By Elisa Palagi; Mauro Napoletano; Andrea Roventini; Jean-Luc Gaffard
  2. Innovation, Finance, and Economic Growth : an agent-based model By Giorgio Fagiolo; Daniele Giachini; Andrea Roventini
  3. Optimal inflation target: insights from an agent-based model By Jean-Philippe Bouchaud; Stanislao Gualdi; Marco Tarzia; Francesco Zamponi
  4. Interbank Contagion: An Agent-based Model Approach to Endogenously Formed Networks By Anqi Liu; Mark Paddrik; Steve Yang; Xingjia Zhang
  5. Neglected chaos in international stock markets: Bayesian analysis of the joint return–volatility dynamical system By Tsionas, Mike G.; Michaelides, Panayotis G.
  6. A Practical Guide to Parallelization in Economics By Fernández-Villaverde, Jesús; Zarruk Valencia, David
  7. DeepTriangle: A Deep Learning Approach to Loss Reserving By Kevin Kuo
  8. Counterfactual comparisons of investment options for wind power and agricultural production in the United States: Lessons from Northern Ohio By Alexandre Ribeiro Scarcioffolo; Fernanda Finotti Perobelli, Ariaster Baumgratz Chimeli
  9. Economic inequality and Islamic Charity: An exploratory agent-based modeling approach By Hossein Sabzian; Alireza Aliahmadi; Adel Azar; Madjid Mirzaee

  1. By: Elisa Palagi; Mauro Napoletano (Observatoire français des conjonctures économiques); Andrea Roventini (Laboratory of Economics and Management (LEM)); Jean-Luc Gaffard (Observatoire français des conjonctures économiques)
    Abstract: We build an agent-based model populated by households with heterogenous and timevarying financial conditions in order to study how different inequality shocks affect income dynamics and the effects of different types of fiscal policy responses. We show that inequality shocks generate persistent falls in aggregate income by increasing the fraction of credit-constrained households and by lowering aggregate consumption. Furthermore, we experiment with different types of fiscal policies to counter the effects of inequality-generated recessions, namely deficit-spending direct government consumption and redistributive subsidies financed by different types of taxes. We find that subsidies are in general associated with higher fiscal multipliers than direct government expenditure, as they appear to be better suited to sustain consumption of lower income households after the shock. In addition, we show that the effectiveness of redistributive subsidies increases if they are financed by taxing financial incomes or savings.
    Keywords: Income inequality; Fiscal multipliers; Redistributive Policies; Credit-rationing; Agent-based models
    JEL: E63 E21 C63
    Date: 2017–11
  2. By: Giorgio Fagiolo (Laboratory of Economics and Management (LEM)); Daniele Giachini (Scuola Superiore Sant'Anna); Andrea Roventini (Laboratory of Economics and Management (LEM))
    Abstract: This paper extends the endogenous-growth agent-based model in Fagiolo and Dosi (2003) to study the financegrowth nexus. We explore industries where firms produce a homogeneous good using existing technologies, perform R&D activities to introduce new techniques, and imitate the most productive practices. Unlike the original model, we assume that both exploration and imitation require resources provided by banks, which pool agent savings and finance new projects via loans. We find that banking activity has a positive impact on growth. However, excessive financialization can hamper growth. In- deed, we find a significant and robust inverted-U shaped relation between financial depth and growth. Overall, our results stress the fundamental (and still poorly understood) role played by innovation in the finance-growth nexu
    Keywords: Agent based model; Innovation; Exploration vs exploitation; Endogenous Growth; Banking sector; Finance Growth Nexus
    JEL: C63 G21 O30 O31
    Date: 2017–11
  3. By: Jean-Philippe Bouchaud (CFM - Capital Fund Management - Capital Fund Management); Stanislao Gualdi (CFM - Capital Fund Management - Capital Fund Management); Marco Tarzia (LPTMC - Laboratoire de Physique Théorique de la Matière Condensée - UPMC - Université Pierre et Marie Curie - Paris 6 - CNRS - Centre National de la Recherche Scientifique); Francesco Zamponi (LPTENS - Laboratoire de Physique Théorique de l'ENS - ENS Paris - École normale supérieure - Paris - UPMC - Université Pierre et Marie Curie - Paris 6 - CNRS - Centre National de la Recherche Scientifique)
    Abstract: Which level of inflation should Central Banks be targeting? The authors investigate this issue in the context of a simplified Agent Based Model of the economy. Depending on the value of the parameters that describe the behaviour of agents (in particular inflation anticipations), they find a rich variety of behaviour at the macro-level. Without any active monetary policy, our ABM economy can be in a high inflation/high output state, or in a low inflation/low output state. Hyper-inflation, deflation and " business cycles " between coexisting states are also found. The authors then introduce a Central Bank with a Taylor rule-based inflation target, and study the resulting aggregate variables. The main result is that too-low inflation targets are in general detrimental to a CB-monitored economy. One symptom is a persistent under-realization of inflation, perhaps similar to the current macroeconomic situation. Higher inflation targets are found to improve both unemployment and negative interest rate episodes. The results are compared with the predictions of the standard DSGE model.
    Keywords: Taylor rule,Agent based models,monetary policy,inflation target
    Date: 2018
  4. By: Anqi Liu (Stevens Institute of Technology); Mark Paddrik (Office of Financial Research); Steve Yang (Stevens Institute of Technology); Xingjia Zhang (Stevens Institute of Technology)
    Abstract: The potential impact of interconnected financial institutions on interbank financial systems is a financial stability concern for central banks and regulators. A number of algorithms/methods have been developed to extrapolate latent interbank risk exposures. However, most use highly stylized network models and reconstruction methods with global optimality lending allocation approaches such as maximizing entropy or minimizing costs. This paper argues that U.S. bank lending and borrowing decisions are largely suboptimal and performance-driven. We present an agent-based model to endogenously reconstruct interbank networks based on 6,600 banks' decision rules and behaviors reflected in quarterly balance sheets. The model formulation reproduces dynamics similar to those of the 2007-09 financial crisis and shows how bank losses and failures arise from network contagion and lending market illiquidity. When calibrated to post-crisis data from 2011-14, the model shows the banking system has reduced its likelihood of bank failures through network contagion and illiquidity, given a similar stress scenario.
    Keywords: Interbank lending market, agent-based simulation, contagion risk, network topology, financial crisis
    Date: 2016–12–20
  5. By: Tsionas, Mike G.; Michaelides, Panayotis G.
    Abstract: We use a novel Bayesian inference procedure for the Lyapunov exponent in the dynamical system of returns and their unobserved volatility. In the dynamical system, computation of largest Lyapunov exponent by traditional methods is impossible as the stochastic nature has to be taken explicitly into account due to unobserved volatility. We apply the new techniques to daily stock return data for a group of six countries, namely USA, UK, Switzerland, Netherlands, Germany and France, from 2003 to 2014, by means of Sequential Monte Carlo for Bayesian inference. The evidence points to the direction that there is indeed noisy chaos both before and after the recent financial crisis. However, when a much simpler model is examined where the interaction between returns and volatility is not taken into consideration jointly, the hypothesis of chaotic dynamics does not receive much support by the data (“neglected chaos”).
    Keywords: Neglected chaos; Lyapunov exponent; Neural networks; Bayesian analysis; Sequential Monte Carlo; Global economy;
    JEL: C1 F3 G3
    Date: 2017–09
  6. By: Fernández-Villaverde, Jesús; Zarruk Valencia, David
    Abstract: This guide provides a practical introduction to parallel computing in economics. After a brief introduction to the basic ideas of parallelization, we show how to parallelize a prototypical application in economics using, on CPUs, Julia, Matlab, R, Python, C++ - OpenMP, Rcpp - OpenMP, and C++ - MPI, and, on GPUs, CUDA and OpenACC. We provide code that the user can download and fork, present comparative results, and explain the strengths and weaknesses of each approach. We conclude with some additional remarks about alternative approaches.
    Keywords: Computational Methods; Parallel Computing; Programming Languages
    JEL: C63 C68 E37
    Date: 2018–04
  7. By: Kevin Kuo
    Abstract: We propose a novel approach for loss reserving based on deep neural networks. The approach allows for jointly modeling of paid losses and claims outstanding, and incorporation of heterogenous inputs. We validate the models on loss reserving data across lines of business, and show that they attain or exceed the predictive accuracy of existing stochastic methods. The models require minimal feature engineering and expert input, and can be automated to produce forecasts at a high frequency.
    Date: 2018–04
  8. By: Alexandre Ribeiro Scarcioffolo; Fernanda Finotti Perobelli, Ariaster Baumgratz Chimeli
    Abstract: We analyze potential efficiency gains in wind power projects by comparing counterfactual investment decisions in two different scenarios under a real options framework. The first scenario is a standard wind power investment, where the investor rents the land from local farms. In the second scenario, the wind power investor buys the land and commercializes both electricity and crop production, thus shortening the revenue risk through the diversification. Both scenarios have a waiting option, with the wholesale prices leading the installation decision. We model the electricity price as a mean reverting process with jumps and with different jumping probabilities for the different seasons of the year. Corn prices follow a mean reverting process. The waiting flexibility was modeled as a bundle of European options. The results indicate that the waiting option is exercised in 100% of our simulations in both scenarios, suggesting the still important role of government policies to stimulate wind power. More importantly, in more than 90% of the simulations, the second scenario brought value to the investment. Furthermore, net present values are more sensitive to reductions in capital costs than electricity prices. These results can form the basis for more effective policies for the wind power sector.
    Keywords: Wind Energy; Corn; Real Options Framework; Investment decision
    JEL: G23 Q42 Q48
    Date: 2018–04–11
  9. By: Hossein Sabzian; Alireza Aliahmadi; Adel Azar; Madjid Mirzaee
    Abstract: Economic inequality is one of the pivotal issues for most of economic and social policy makers across the world to insure the sustainable economic growth and justice. In the mainstream school of economics, namely neoclassical theories, economic issues are dealt with in a mechanistic manner. Such a mainstream framework is majorly focused on investigating a socio-economic system based on an axiomatic scheme where reductionism approach plays a vital role. The major limitations of such theories include unbounded rationality of economic agents, reducing the economic aggregates to a set of predictable factors and lack of attention to adaptability and the evolutionary nature of economic agents. In tackling deficiencies of conventional economic models, in the past two decades, some new approaches have been recruited. One of those novel approaches is the Complex adaptive systems (CAS) framework which has shown a very promising performance in action. In contrast to mainstream school, under this framework, the economic phenomena are studied in an organic manner where the economic agents are supposed to be both boundedly rational and adaptive. According to it, the economic aggregates emerge out of the ways agents of a system decide and interact. As a powerful way of modeling CASs, Agent-based models (ABMs) has found a growing application among academicians and practitioners. ABMs show that how simple behavioral rules of agents and local interactions among them at micro-scale can generate surprisingly complex patterns at macro-scale. In this paper, ABMs have been used to show (1) how an economic inequality emerges in a system and to explain (2) how sadaqah as an Islamic charity rule can majorly help alleviating the inequality and how resource allocation strategies taken by charity entities can accelerate this alleviation.
    Date: 2018–04

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