nep-cmp New Economics Papers
on Computational Economics
Issue of 2013‒11‒22
thirteen papers chosen by
Stan Miles
Thompson Rivers University

  1. “Forecasting Business surveys indicators: neural networks vs. time series models” By Oscar Claveria; Salvador Torra
  2. Revealed preference tests of collectively rational consumption behavior: formulations and algorithms*. By Talla Nobibon, Fabrice; Cherchye, L.; Crama, Yves; Demuynck, T.; De Rock, B.; Spieksma, Frits
  3. “Tourism demand forecasting with different neural networks models” By Oscar Claveria; Enric Monte; Salvador Torra
  4. Pr\'evision du risque de cr\'edit : Une \'etude comparative entre l'Analyse Discriminante et l'Approche Neuronale By Younes Boujelb\`ene; Sihem Khemakhem
  5. General Equilibrium Assessment of the COMESA-EAC-SADC Tripartite FTA By Willenbockel, Dirk
  6. Increasing Inequality and Financial Fragility in an An Agent Based Macroeconomic Model By Russo, Alberto; Riccetti, Luca; Gallegati, Mauro
  7. A Fast Algorithm for Computing High-dimensional Risk Parity Portfolios By Th\'eophile Griveau-Billion; Jean-Charles Richard; Thierry Roncalli
  8. An Equilibrium Analysis of a Collective Farm-Household Model: Policy and Welfare Simulations By Eleonora Matteazzi; Martina Menon; Federico Perali
  9. The impact of an increase in the legal retirement age on the effective retirement age. By Bernal, Noelia; Vermeulen, Frederic
  10. A combination of flow shop scheduling and the shortest path problem. By Nip, Kameng; Wang, Zhenbo; Talla Nobibon, Fabrice; Leus, Roel
  11. Sequential diagnosis of k-out-of-n systems with imperfect tests. By Wei, Wenchao; Talla Nobibon, Fabrice; Leus, Roel
  12. Advances in rule-based process mining: applications for enterprise risk management and auditing. By Caron, Filip; Vanthienen, Jan; Baesens, Bart
  13. RSVP summary refresh extension in OPNET modeler: implementation and evaluation. By Pana, Flavius-Alexandru; Put, Ferdi

  1. By: Oscar Claveria (Faculty of Economics, University of Barcelona); Salvador Torra (Faculty of Economics, University of Barcelona)
    Abstract: The objective of this paper is to compare different forecasting methods for the short run forecasting of Business Survey Indicators. We compare the forecasting accuracy of Artificial Neural Networks (ANN) vs. three different time series models: autoregressions (AR), autoregressive integrated moving average (ARIMA) and self-exciting threshold autoregressions (SETAR). We consider all the indicators of the question related to a country’s general situation regarding overall economy, capital expenditures and private consumption (present judgement, compared to same time last year, expected situation by the end of the next six months) of the World Economic Survey (WES) carried out by the Ifo Institute for Economic Research in co-operation with the International Chamber of Commerce. The forecast competition is undertaken for fourteen countries of the European Union. The main results of the forecast competition are offered for raw data for the period ranging from 1989 to 2008, using the last eight quarters for comparing the forecasting accuracy of the different techniques. ANN and ARIMA models outperform SETAR and AR models. Enlarging the observed time series of Business Survey Indicators is of upmost importance in order of assessing the implications of the current situation and its use as input in quantitative forecast models.
    Keywords: Business surveys; Forecasting; Time series models; Nonlinear models; Neural networks.
    Date: 2013–11
  2. By: Talla Nobibon, Fabrice; Cherchye, L.; Crama, Yves; Demuynck, T.; De Rock, B.; Spieksma, Frits
    Abstract: This paper focuses on revealed preference tests of the collective model of household consumption. We start by showing that the decision problems corresponding to testing collective rationality are np-complete. This makes the application of these tests problematic for (increasingly available) large(r) scale data sets. We then present two approaches to overcome this negative result. First, we introduce exact algorithms based on mixed-integer programming (mip) formulations of the collective rationality tests, which can be usefully applied to medium sized data sets. Next, we propose simulated annealing heuristics, which allow for ecient testing of the collective model in the case of large data sets. We illustrate our methods by a number of computational experiments based on Dutch labor supply data.
    Keywords: Revealed preference axioms; Rationality; Mixed-integer programming; Global optimization; Simulated annealing;
    Date: 2013–09
  3. By: Oscar Claveria (Faculty of Economics, University of Barcelona); Enric Monte (Department of Signal Theory and Communications, Polytechnic University of Catalunya (UPC)); Salvador Torra (Faculty of Economics, University of Barcelona)
    Abstract: This paper aims to compare the performance of different Artificial Neural Networks techniques for tourist demand forecasting. We test the forecasting accuracy of three different types of architectures: a multi-layer perceptron, a radial basis function and an Elman network. We also evaluate the effect of the memory by repeating the experiment assuming different topologies regarding the number of lags introduced. We used tourist arrivals from all the different countries of origin to Catalonia from 2001 to 2012. We find that multi-layer perceptron and radial basis function models outperform Elman networks, being the radial basis function architecture the one providing the best forecasts when no additional lags are incorporated. These results indicate the potential existence of instabilities when using dynamic networks for forecasting purposes. We also find that for higher memories, the forecasting performance obtained for longer horizons improves, suggesting the importance of increasing the dimensionality for long term forecasting.
    Keywords: tourism demand; forecasting; artificial neural networks; multi-layer perceptron; radial basis function; Elman networks; Catalonia. JEL classification: L83; C53; C45; R11
    Date: 2013–11
  4. By: Younes Boujelb\`ene; Sihem Khemakhem
    Abstract: Banks are interested in evaluating the risk of the financial distress before giving out a loan. Many researchers proposed the use of models based on the Neural Networks in order to help the banker better make a decision. The objective of this paper is to explore a new practical way based on the Neural Networks that would help improve the capacity of the banker to predict the risk class of the companies asking for a loan. This work is motivated by the insufficiency of traditional prevision models. The sample consists of 86 Tunisian firms and 15 financial ratios are calculated, over the period from 2005 to 2007. The results are compared with those of discriminant analysis. They show that the neural networks technique is the best in term of predictability.
    Date: 2013–11
  5. By: Willenbockel, Dirk
    Abstract: This study provides an ex-ante computable general equilibrium (CGE) assessment of the Tripartite Free Trade Agreement between the member states of the Common Market for Eastern and Southern Africa, the East African Community and the Southern African Development Community. The CGE approach enables a consistent integrated predictive evaluation of sectoral production and employment impacts, aggregate income and welfare effects of changes in trade barriers while taking full account of the macroeconomic repercussion arising e.g. from terms-of trade effects, tariff revenue changes and intersectoral input-output linkages. The simulation analysis considers eight distinct trade integration scenarios that differ in their level of ambition.
    Keywords: Free trade agreement, South-south trade, regional economic integration, computable general equilibrium
    JEL: D58 F13 F15 F17
    Date: 2013–09
  6. By: Russo, Alberto; Riccetti, Luca; Gallegati, Mauro
    Abstract: The aim of this paper is to investigate the relationship between increasing inequality and financial fragility in an agent based macroeconomic model. We analyse the effects of a non-linear relationship between wealth and consumption on the evolution of the economic system. Preliminary results show that more inequality rises macroeconomic volatility, increasing the likelihood of observing large unemployment crises.
    Keywords: agent-based model, business cycle, inequality, crisis
    JEL: C63 D31 E21 E32
    Date: 2013–06
  7. By: Th\'eophile Griveau-Billion; Jean-Charles Richard; Thierry Roncalli
    Abstract: In this paper we propose a cyclical coordinate descent (CCD) algorithm for solving high dimensional risk parity problems. We show that this algorithm converges and is very fast even with large covariance matrices (n > 500). Comparison with existing algorithms also shows that it is one of the most efficient algorithms.
    Date: 2013–11
  8. By: Eleonora Matteazzi (Department of Economics (University of Verona)); Martina Menon (Department of Economics (University of Verona)); Federico Perali (Department of Economics (University of Verona))
    Abstract: This study develops a household enterprise model extended to encompass recent advances in collective theory. We use a simulation model, in which production and consumption-leisure choices are represented along with the rule governing intra-household resource allocation, to analyze the income and wage responses of each family member. The household is treated as an equilibrium model whose accounts are based on a household social accounting matrix, and the social classes are the wife/husband classes. The simulation analysis illustrates the policy relevance of the collective approach to household behavior for inferring the impact of economic policies on individual welfare levels.
    Keywords: Collective household enterprise model, sharing rule, household production, household social accounting matrix, simulation analysis
    JEL: D11 D12 D13 C61
    Date: 2013–11
  9. By: Bernal, Noelia; Vermeulen, Frederic
    Abstract: We analyze the impact of an increase in the legal retirement age on the effective retirement age in the Netherlands. We do this by means of a dynamic programming model for the retirement behavior of singles. The model is applied to new administrative data that contain very accurate and detailed information on individual incomes and occupational pension entitlements. Our model is able to capture the main patterns observed in the data. We observe that as individuals get older their labor supply declines considerably and this varies by health status. We simulate a soon to be implemented pension reform which aims at gradually increasing the legal retirement age from 65 to 67. The simulation results show a rather small impact on the effective retirement age. Individuals postpone their retirement by only 3 months on average, while differences across individuals mainly depend on their health status.
    Date: 2013–02
  10. By: Nip, Kameng; Wang, Zhenbo; Talla Nobibon, Fabrice; Leus, Roel
    Abstract: This paper studies a combinatorial optimization problem which is obtained by combining the flow shop scheduling problem and the shortest path problem. The objective of the obtained problem is to select a subset of jobs that constitutes a feasible solution to the shortest path problem, and to execute the selected jobs on the flow shop machines to minimize the makespan. We argue that this problem is NP-hard even if the number of machines is two, and is NP-hard in the strong sense for the general case. We propose an intuitive approximation algorithm for the case where the number of machines is an input, and an improved approximation algorithm for fixed number of machines.
    Keywords: Approximation algorithm; Combination of optimization problems; Flow shop scheduling; Shortest path;
    Date: 2013–08
  11. By: Wei, Wenchao; Talla Nobibon, Fabrice; Leus, Roel
    Abstract: A k-out-of-n system configuration requires that, for the overall system to be functional, at least k out of the total of n components must be working. This paper addresses the search for a least-cost diagnosis strategy for k-out-of-n systems when the individual component tests are imperfect, which means that a test can identify a component as working when in reality it is down, and vice versa. The inspection procedure stops when the output accuracy exceeds a given threshold. We underline the importance of the possibility of fixing positive and negative predictive values, we examine different classes of diagnosis policies, we discuss global optimality of each of the classes, and we present a polynomial-time algorithm to find a globally optimal policy.
    Keywords: System diagnosis; k-out-of-n systems; Imperfect tests; Sequencing and scheduling;
    Date: 2013–08
  12. By: Caron, Filip; Vanthienen, Jan; Baesens, Bart
    Abstract: Process mining research has mainly focused on the development of process mining techniques, with process discovery algorithms in the center of attention. However, far less research attention has been paid to the actual applicability of these process mining techniques in common business settings. Consequently, there only exists a partial fit between the existing process mining techniques and the compliance checking & risk management applications. This research report contributes to the process mining and compliance checking research by proposing an effective and efficient rule-based approach for analyzing organizational information and processes. Additionally, a general content-based business rule taxonomy has been developed as a source of business rules for the compliance checking approach. Furthermore, we also provide formal grounding for and an evaluation of the rule-based approach.
    Keywords: Business Rules; Compliance Checking; Risk Management; Process Mining; Process-Aware Information Systems;
    Date: 2013–03
  13. By: Pana, Flavius-Alexandru; Put, Ferdi
    Abstract: The Summary Refresh extension represents the most notable scalability extensions of the Resource Reservation Protocol (RSVP). This extension was introduced by the Internet Engineering Task Force (IETF) in RFC 2961. Most important network simulation tools do not have an implementation of the RSVP Summary Refresh extension, thus making it impossible to analyze the scalability of RSVP and the behavior of the protocol in complex scenarios that might use the aforementioned extension. This paper presents the implementation and evaluation of the RSVP Summary Refresh in OPNET Modeler. Technical aspects that can help researchers implement or modify different RSVP extensions in OPNET Modeler are presented.
    Keywords: Implementation; RSVP; Summary Refresh; OPNET; Simulation;
    Date: 2013

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