nep-cmp New Economics Papers
on Computational Economics
Issue of 2017‒03‒05
fourteen papers chosen by
Stan Miles
Thompson Rivers University

  1. A Branch-and-Cut Algorithm for the Multi Compartment vehicle Routing Problem with Flexbile Compartment Sizes By Tino Henke; Grazia Speranza; Gerhard Wäscher
  2. Fiscal Policy, Inequality and Poverty in Iran: Assessing the Impact and Effectiveness of Taxes and Transfer By Ali Enami; Nora Lustig; Alireza Taqdiri
  3. Whose Balance Sheet is this? Neural Networks for Banks' Pattern Recognition By Leon Rincon, Carlos; Moreno, José Fernando; Cely, Jorge
  4. Testing the Assumptions of Sequential Bifurcation for Factor Screening (revision of CentER DP 2015-034) By Shi, Wen; Kleijnen, J.P.C.
  5. The development of a linked modelling framework for analysing the socioeconomic impacts of energy and climate policies in South Africa By Bruno Merven; Channing Arndt; Harald Winkler
  6. Value Added in Motion: Modelling World Trade Patterns at the 2035 Horizon By Lionel Fontagné; Jean Fouré
  7. Robust and Consistent Estimation of Generators in Credit Risk By Greig Smith; Goncalo dos Reis
  8. Opinion dynamics via search engines (and other algorithmic gatekeepers) By Fabrizio Germano; Francesco Sobbrio
  9. An Agent Based Macroeconomic Model with Social Classes and Endogenous Crises By Russo, Alberto
  10. The impact of constrained monetary policy on fiscal multipliers on output and inflation By Bletzinger, Tilman; Lalik, Magdalena
  11. Considering the use of random fields in the Modifiable Areal Unit Problem By Michal Bernard Pietrzak; Bartosz Ziemkiewicz
  12. Incremental computation of block triangular matrix exponentials with application to option pricing By Daniel Kressner; Robert Luce; Francesco Statti
  13. Introducing an IP License Box in Switzerland: Quantifying the Effects By Florian Chatagny; Marko Köthenbürger; Michael Stimmelmayr
  14. Microeconomic Simulator of Firm Behavior under Monopolistic Competition By Angelov, Aleks; Vasilev, Aleksandar

  1. By: Tino Henke (Department of Management Science, Otto-von-Guericke-University Magdeburg); Grazia Speranza (Department of Quantitative Methods, Otto-von-Guericke University Magdeburg); Gerhard Wäscher (Faculty of Management Science, University of Brescia)
    Abstract: Multi-compartment vehicle routing problems arise in a variety of problem settings in which different product types have to be transported separated from each other. In this paper, a problem variant which occurs in the context of glass waste recycling is considered. In this problem, a set of locations exists, each of which offering a number of containers for the collection of different types of glass waste (e.g. colorless, green, brown glass). In order to pick up the contents from the containers, a fleet of homogeneous disposal vehicles is available. Individually for each disposal vehicle, the capacity can be discretely separated into a limited number of compartments to which different glass waste types are assigned. The objective of the problem is to minimize the total distance to be travelled by the disposal vehicles. For solving this problem to optimality, a branch-and-cut algorithm has been developed and implemented. Extensive numerical experiments have been conducted in order to evaluate the algorithm and to gain insights into the problem structure. The corresponding results show that the algorithm is able to solve instances with up to 50 locations to optimality and that it reduces the computing time by 87% compared to instances from the literature. Additional experiments give managerial insights into the use of different variants of compartments with flexible sizes.
    Keywords: vehicle routing, multiple compartments, branch-and-cut algorithm, waste collection
    Date: 2017–04
  2. By: Ali Enami (Stone Center for Latin American Studies, Department of Economics, Tulane University. Commitment to Equity Institute (CEQI).); Nora Lustig (Stone Center for Latin American Studies, Department of Economics, Tulane University. Commitment to Equity Institute (CEQI).); Alireza Taqdiri (University of Akron, OH, USA)
    Abstract: Using the Iranian Household Expenditure and Income Survey (HEIS) for 2011/12, we apply the marginal contribution approach to determine the impact and effectiveness of each fiscal intervention, and the fiscal system as a whole, on inequality and poverty. Net direct and indirect taxes combined reduce the Gini coefficient by 0.0644 points and the headcount ratio by 61 percent. When the monetized value of in-kind benefits in education and health are included, the reduction in inequality is 0.0919 Gini points. Based on the magnitudes of the marginal contributions, we find that the main driver of these reduction is the Targeted Subsidy Program, a universal cash transfer program implemented in 2010 to compensate individuals for the elimination of energy subsidies. The main reduction in poverty occurs in rural areas, where the headcount ratio declines from 44 to 23 percent. In urban areas, fiscally-induced poverty reduction is more modest: the headcount ratio declines from 13 to 5 percent. Taxes and transfers are similar in their effectiveness in achieving their inequality-reducing potential. By achieving 40 percent of its inequality-reducing potential, the income tax is the most effective intervention on the revenue side. On the spending side, Social Assistance transfers are the most effective and they achieve 45 percent of their potential. Taxes are especially effective in raising revenue without causing poverty to rise, indicating that the poor are largely spared from being taxed. In contrast, since the bulk of transfers are not targeted to the poor, they are not very effective: the most effective ones achieve 20 percent of their poverty reduction potential. The effectiveness of the Targeted Subsidy Program could be improved by eliminating the transfer to top deciles and re-allocating the freed funds to the poor.
    Keywords: Inequality, poverty, marginal contribution, CEQ framework, policy simulation
    JEL: D31 H22 I38
    Date: 2016–07
  3. By: Leon Rincon, Carlos (Tilburg University, Center For Economic Research); Moreno, José Fernando; Cely, Jorge
    Abstract: The balance sheet is a snapshot that portraits the financial position of a firm at a specific point of time. Under the reasonable assumption that the financial position of a firm is unique and representative, we use a basic artificial neural network pattern recognition method on Colombian banks’ 2000-2014 monthly 25-account balance sheet data to test whether it is possible to classify them with fair accuracy. Results demonstrate that the chosen method is able to classify out-of-sample banks by learning the main features of their balance sheets, and with great accuracy. Results confirm that balance sheets are unique and representative for each bank, and that an artificial neural network is capable of recognizing a bank by its financial accounts. Further developments fostered by our findings may contribute to enhancing financial authorities’ supervision and oversight duties, especially in designing early-warning systems.
    Keywords: supervised learning; machine learning; artificial neural networks; classification
    JEL: C45 C53 G21 M41
    Date: 2017
  4. By: Shi, Wen; Kleijnen, J.P.C. (Tilburg University, Center For Economic Research)
    Abstract: Sequential bifurcation (or SB) is an efficient and effective factor-screening method; i.e., SB quickly identifies the important factors (inputs) in experiments with simulation models that have very many factors—provided the SB assumptions are valid. The specific SB assumptions are: (i) a secondorder polynomial is an adequate approximation (a valid metamodel) of the implicit input/output function of the underlying simulation model; (ii) the directions (signs) of the first-order effects are known (so the first-order polynomial approximation is monotonic); (iii) so-called “heredity” applies; i.e., if an input has no important first-order effect, then this input has no important second-order effects. Moreover—like many other statistical methods—SB assumes Gaussian simulation outputs if the simulation model is stochastic (random). A generalization of SB called “multiresponse SB” (or MSB) uses the same assumptions, but allows for simulation models with multiple types of responses (outputs). To test whether these assumptions hold, we develop new methods. We evaluate these methods through Monte Carlo experiments and a case study.
    Keywords: sensitivity analysis; experimental desgin; meta-modeling; validation; regression; simulation
    JEL: C0 C1 C9 C15 C44
    Date: 2017
  5. By: Bruno Merven; Channing Arndt; Harald Winkler
    Abstract: This paper presents some methodological improvements made to the linked SATIM–eSAGE energy-economy-environment modelling framework for analysing energy and climate policy in South Africa. The improvements include the linking of the households and the other economic sectors of the eSAGE economy-wide model to the SATIM energy model. Two scenarios are used to illustrate the benefits of having the new links, which include an energy efficiency scenario and an ambitious climate mitigation scenario. The results show that there are significant socio-economic benefits in having a more energy-efficient economy. The work presented in the paper provides some solid foundations for further work on the energy-economy-environment policy arena for South Africa.
    Date: 2017
  6. By: Lionel Fontagné (PSE (Paris 1) and CEPII); Jean Fouré (CEPII)
    Abstract: We address in this paper the future geography of production, migration and energy at the world level, and the consequences for the largest European countries. We take scant account of the wide range of possible evolutions of the world economy in terms of technological progress and diffusion, education, demography including migrations and finally energy price and efficiency. Taking a 2035 horizon, we examine how world trade patterns will be shaped by the changing comparative advantages, demand, and capabilities of different regions, and what will be the implications in terms of location of value added at the sector and country level. We combine a convergence model fitting three production factors (capital, labour and energy) and two factor-specific productivities, alongside a dynamic CGE model of the world economy calibrated to reproduce observed elasticity of trade to income. Each scenario involves three steps. First, we project growth at country level based on factor accumulation, demography and migration, educational attainment and efficiency gains, and discuss uncertainties related to our main drivers. Second, we impose this framework on the CGE baseline. Third, we implement trade policy scenarios (tariffs as well as non-tariff measures in goods and services), in order to get factor allocation across sectors from the model as well as demand and trade patterns.
    Keywords: Growth, Macroeconomic Projections, Dynamic Baselines
    JEL: E23 E27 F02 F17 F47
    Date: 2017–02–24
  7. By: Greig Smith; Goncalo dos Reis
    Abstract: Bond rating Transition Probability Matrices (TPMs) are built over a one-year time-frame and for many practical purposes, like the assessment of risk in portfolios, one needs to compute the TPM for a smaller time interval. In the context of continuous time Markov chains (CTMC) several deterministic and statistical algorithms have been proposed to estimate the generator matrix. We focus on the Expectation-Maximization (EM) algorithm by \cite{BladtSorensen2005} for a CTMC with an absorbing state for such estimation. This work's contribution is fourfold. Firstly, we provide directly computable closed form expressions for quantities appearing in the EM algorithm. Previously, these quantities had to be estimated numerically and considerable computational speedups have been gained. Secondly, we prove convergence to a single set of parameters under reasonable conditions. Thirdly, we derive a closed-form expression for the error estimate in the EM algorithm allowing to approximate confidence intervals for the estimation. Finally, we provide a numerical benchmark of our results against other known algorithms, in particular, on several problems related to credit risk. The EM algorithm we propose, padded with the new formulas (and error criteria), is very competitive and outperforms other known algorithms in several metrics.
    Date: 2017–02
  8. By: Fabrizio Germano; Francesco Sobbrio
    Abstract: This paper presents a stylized model to evaluate the effects of a search engine’s ranking algorithm on opinion dynamics and asymptotic learning. We focus on three key components of the ranking algorithm, namely, the initial ranking of websites, the updating of the ranking as a function of the popularity of the different websites, and the possibility to personalize search results according to users’ characteristics. At the same time, we consider two empirically grounded assumptions on individuals’ online search behavior, namely, the presence of a search cost and of a preference for like-minded websites. We then study how the ranking algorithm interacts with the individuals’ search behavior to determine the ranking of websites and the evolution of individuals’ opinions. We first show how several empirical regularities concerning the pattern of website traffic can be explained by the interaction of the search engine’s algorithm with the individuals’ search cost (rich get richer dynamic, concentration at the top) and with the preference for like-minded websites (long-tail in the distribution of website traffic). At the same time, fewer websites reporting a minority opinion might increase the ranking of those websites and consequently the overall probability of individuals accessing any one of them than if there were more (advantage of the fewer). As a consequence, a lower ex-ante accuracy of websites’ content might actually enhance asymptotic learning. Finally, when considering personalization of search results we see that it may lead to belief polarization and inhibit asymptotic learning.
    Keywords: Search Engines, Ranking Algorithm, Search Behavior, Opinion Dynamics, Information Aggregation, Asymptotic Learning, Misinformation, Polarization, Websites Traffic.
    JEL: D83 L86
    Date: 2016–12
  9. By: Russo, Alberto
    Abstract: This paper proposes an agent based macroeconomic model in which income distribution and wealth accumulation depend on the role that agents play in productive activities, that is capitalists or workers. In this framework, social class dynamics underlie the endogenous process of firm formation. The focus is on the interplay between the evolution of social structure and macroeconomic dynamics and on how business cycles and crises may endogenously emerge as the result of the interaction between financial and real factors underlying the process of capitalist production.
    Keywords: heterogeneous interacting agents; social structure, macroeconomic dynamics, inequality, crisis.
    JEL: C63 D31 P10
    Date: 2016–12–31
  10. By: Bletzinger, Tilman; Lalik, Magdalena
    Abstract: This paper uses two established DSGE models (QUEST III and Smets-Wouters) to assess the impact of fiscal spending cuts on output and, in particular, also on inflation in the euro area under alternative settings for monetary policy. We compare four different settings of constrained monetary policy, taking into account alternative agents’ expectations about future monetary policy. We illustrate that those expectations are even more important for the size of the fiscal multipliers than the difference between exogenously versus endogenously modelled constraints. We confirm the well-known finding that fiscal multipliers exhibit an over-proportional reaction when monetary policy is constrained. The novelty of our results is that this over-proportionality is stronger for the fiscal multiplier on inflation than on output. We relate this finding to the structural parameters of the models by means of a Global Sensitivity Analysis. JEL Classification: E31, E43, E52, E62, E63
    Keywords: constrained monetary policy, fiscal multipliers, zero lower bound
    Date: 2017–02
  11. By: Michal Bernard Pietrzak (Nicolaus Copernicus University, Poland); Bartosz Ziemkiewicz (Nicolaus Copernicus University, Poland)
    Abstract: The focus of the research will be on the modifiable areal unit problem (MAUP) within which two aspects will be considered: the scale problem and the aggregation problem. In the article we consider the use of random fields theory for the needs of the “Scale Problem” issue. The Scale Problem is defined as a volatility of the results of analysis as a result of a change in the aggregation scale. In the case of the scale problem empirical studies should be conducted with application of simulations. Within the simulation analysis the realisations of random fields referred to irregular regions will be generated. First, the internal structure of spatial processes will be analysed. Next, we consider the theoretical foundations for random fields relative to irregular regions. The accepted properties of random fields will be based on the characteristics established for economic phenomena. The outcome of the task will be the development of a procedure for generating the vector of random fields with specified properties. Procedure for generating random fields will be used to simulations within the scale problem too. The research is funded by National Science Centre, Poland under the research project no. 2015/17/B/HS4/01004.
    Keywords: spatial econometrics, Scale Problem, random fields, Modifiable Areal Unit Problem, simulations
    JEL: C10 C15 C21
    Date: 2016–12
  12. By: Daniel Kressner; Robert Luce; Francesco Statti
    Abstract: We study the problem of computing the matrix exponential of a block triangular matrix in a peculiar way: Block column by block column, from left to right. The need for such an evaluation scheme arises naturally in the context of option pricing in polynomial diffusion models. In this setting a discretization process produces a sequence of nested block triangular matrices, and their exponentials are to be computed at each stage, until a dynamically evaluated criterion allows to stop. Our algorithm is based on scaling and squaring. By carefully reusing certain intermediate quantities from one step to the next, we can efficiently compute such a sequence of matrix exponentials.
    Date: 2017–03
  13. By: Florian Chatagny (KOF Swiss Economic Institute, ETH Zurich, Switzerland); Marko Köthenbürger (KOF Swiss Economic Institute, ETH Zurich, Switzerland); Michael Stimmelmayr (KOF Swiss Economic Institute, ETH Zurich, Switzerland)
    Abstract: In response to mounting international pressure to reform the ring-fenced elements profits tax system, the Swiss government has put forward a comprehensive tax reform package. The proposal comprises the introduction of a license box, a substantial reduction in cantonal profit tax rates, and an allowance for excess corporate equity. We apply a computable general equilibrium model to quantify the economic effects of this reform. Our results reveal that the license box, combined with the reduction in the cantonal profit taxes, limits the outflow of the tax base of those companies that benefit from the current preferential tax treatment. The reduction in cantonal profit taxes and the fact that regularly taxed companies additionally benefit from the license box render the reform package costly, such that tax revenues might well decline after the reform.
    Keywords: Tax Competition, License Box, Mobile Firm Prots, Corporate Tax Reform, Dynamic General Equilibrium Model
    Date: 2016–11
  14. By: Angelov, Aleks; Vasilev, Aleksandar
    Abstract: Computer simulators are proving to be indispensable education tools as they enable their users to readily apply theoretical knowledge and to automatically receive immediate feedback, which is invaluable both to learners and to their instructors. Yet at present, there is virtually no publically available software for teaching economics to people who are new to this discipline. The Microeconomic Simulator of Firm Behavior under Monopolistic Competition is an interdisciplinary project which tries to fill this niche by providing an interactive means of strengthening and assessing a person’s grasp of fundamental economic concepts. It simulates the dynamic conditions of real-world markets that exhibit characteristics both of monopoly and of perfect competition, and demonstrates how choices made by a company’s executives affect its profitability. This is done in an intuitive manner through a user-friendly web application, which can be accessed from any device with an HTML5-compliant browser. The application is based on a proprietary algorithm which transforms the abstract economic model of monopolistic competition into a series of easy-to-follow steps and supplies diagrams and pop-ups, which help users comprehend the consequences of their actions. The parameters of the model are fully customizable so that different economic environments can be explored. After the end of a simulation, users are presented with a summary of their performance, which they can use to measure their progress over time, or to see how they rank among their peers.
    Keywords: monopolistic competition,computer simulators
    JEL: A1
    Date: 2017

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