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on Computational Economics |
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Issue of 2012‒03‒21
twelve papers chosen by |
| By: | Omar Feraboli (Chemnitz University of Technology, Germany) |
| Abstract: | This paper deals with the economic effects and the policy implications of trade liberalisation on the Jordanian economy, with emphasis on welfare, income distribution and real wages of heterogeneous households, by using a neoclassical dynamic computable general equilibrium (CGE) model. Specifically the paper assesses the impacts of preferential trade liberalisation with the European Union (EU) and compare them with those brought about by broad and non-discriminatory trade liberalisation. |
| Keywords: | Dynamic CGE Models, Heterogeneous households, Trade liberalisation, Jordan |
| JEL: | C68 F11 I32 D31 |
| Date: | 2012–03 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:08_12&r=cmp |
| By: | Pierre Henry-Labordere (SOCIETE GENERALE - Equity Derivatives Research Societe Generale - Société Générale) |
| Abstract: | The purpose of this paper is to design an algorithm for the computation of the counterparty risk which is competitive in regards of a brute force ''Monte-Carlo of Monte-Carlo" method (with nested simulations). This is achieved using marked branching diffusions describing a Galton-Watson random tree. Such an algorithm leads at the same time to a computation of the (bilateral) counterparty risk when we use the default-risky or counterparty-riskless option values as mark-to-market. Our method is illustrated by various numerical examples. |
| Keywords: | Counterparty risk valuation; BSDE; branching diffusions; semi-linear PDE; Galton-Watson tree |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-00677348&r=cmp |
| By: | D. Blueschke (University of Klagenfurt, Austria); V. Blueschke-Nikolaeva (University of Klagenfurt, Austria); Ivan Savin (DFG Research Training Program "The Economics of Innovative Change", Friedrich Schiller University Jena and the Max Planck Institute of Economics, Jena) |
| Abstract: | Optimal control of dynamic econometric models has a wide variety of applications including economic policy relevant issues. There are several algorithms extending the basic case of a linear-quadratic optimization and taking nonlinearity and stochastics into account, but being still limited in a variety of ways, e.g., symmetry of the objective function and identical data frequencies of control variables. To overcome these problems, an alternative approach based on heuristics is suggested. To this end, we apply a 'classical' algorithm (OPTCON) and a heuristic approach (Differential Evolution) to three different econometric models and compare their performance. In this paper we consider scenarios of symmetric and asymmetric quadratic objective functions. Results provide a strong support for the heuristic approach encouraging its further application to optimum control problems. |
| Keywords: | Differential evolution, dynamic programming, nonlinear optimization, optimal control |
| JEL: | C54 C61 E27 E61 E62 |
| Date: | 2012–03–07 |
| URL: | http://d.repec.org/n?u=RePEc:jrp:jrpwrp:2012-008&r=cmp |
| By: | Sebastian Henn (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg) |
| Abstract: | Order picking deals with the retrieval of articles from their storage locations in order to satisfy customer requests. The transformation and consolidation of customer orders into picking orders (batches) is pivotal for the performance of order picking systems. Typically, customer orders have to be completed by certain due dates in order to avoid delays in production or in the shipment to customers. The composition of the batches, their processing times, their assignment to order pickers and the sequence according to which they are scheduled determine whether and the extent to which the due dates are missed. This article shows how Variable Neighborhood Descent and Variable Neighborhood Search can be applied in order to minimize the total tardiness of a given set of customer orders. In a series of extensive numerical experiments, the performance of the two approaches is analyzed for different problem classes. It is shown that the proposed methods provide solutions which may allow order picking systems to operate more efficiently. |
| Keywords: | Warehouse Management; Order Batching; Batch Sequencing; Due Dates; Variable Neighborhood Descent; Variable Neighborhood Search |
| Date: | 2012–02 |
| URL: | http://d.repec.org/n?u=RePEc:mag:wpaper:120004&r=cmp |
| By: | Jos\'e E. Figueroa-L\'opez; Peter Tankov |
| Abstract: | We characterize the small-time asymptotic behavior of the exit probability of a L\'evy process out of a two-sided interval and of the law of its overshoot, conditionally on the terminal value of the process. The asymptotic expansions are given in the form of a first order term and a precise computable error bound. As an important application of these formulas, we develop a novel adaptive discretization scheme for the Monte Carlo computation of functionals of killed L\'evy processes with controlled bias. The considered functionals appear in several domains of mathematical finance (e.g. structural credit risk models, pricing of barrier options, and contingent convertible bonds) as well as in natural sciences. The proposed algorithm works by adding discretization points sampled from the L\'evy bridge density to the skeleton of the process until the overall error for a given trajectory becomes smaller than the maximum tolerance given by the user. As another contribution of particular interest on its own, we also propose two simple methods to simulate from the L\'evy bridge distribution based on the classical rejection method. |
| Date: | 2012–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1203.2355&r=cmp |
| By: | Viktor Steiner; Katharina Wrohlich; Peter Haan; Johannes Geyer |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:diw:diwddc:dd63&r=cmp |
| By: | Bhanumurthy, N. R. (National Institute of Public Finance and Policy); Das, Surajit (National Institute of Public Finance and Policy); Bose, Sukanya (National Institute of Public Finance and Policy) |
| Abstract: | This paper analyses the impact of transmission of international oil prices and domestic oil price pass-through policy on major macroeconomic variables in India with the help of a macroeconomic policy simulation model. Three major channels of transmission viz. import channel, price channel and fiscal channel are explored with the help of a comparative static macroeconomic general equilibrium framework. The policy option of deregulation of domestic oil prices in the scenario of occurrence of a one-time shock in international oil prices as well as no oil price shock situation analysed through its impact on growth, inflation, fiscal balances and external balances during the 12th Plan period of 2012-13 to 2016-17. The simulation results indicate that the deregulation policy as such would have adverse impact on the growth as well as on the inflation. But if this policy is complemented with the policy of switching of subsidy bill to capital expenditure might result in positive growth effects only in the medium term. Given, the current pass-through policy, one-time oil shock has more intense adverse impact on growth and inflation in the year of shock while it mitigates slowly over time. The model shows that with the oil shock and with current partial pass-through regime, a 10 per cent rise in oil prices result in a 0.6 per cent fall in growth while in the full pass-through situation, it can reduce the growth by 0.9 per cent. Overall, the paper argues that the pass-through has diferential impact on growth and inflation over the 12th Plan period. Hence, the policy of oil price deregulation must be carefully weighed and prioritized. |
| Keywords: | Policy simulation ; International price shock ; Transmission channels ; Macroeconomic modelling ; Growth ; Inflation ; Current account deficit ; Subsidies ; Fiscal deficit ; India |
| JEL: | C32 E10 E17 E30 E60 H60 |
| Date: | 2012–03 |
| URL: | http://d.repec.org/n?u=RePEc:npf:wpaper:12/99&r=cmp |
| By: | Laurence JACQUET (THEMA - University of Cergy-Pontoise, UCL-IRES, UCL-Hoover Chair and CESifo); Etienne LEHMANN (CREST-INSEE, UCL-IRES, IDEP, IZA and CESifo); Bruno VAN DER LINDEN (UNIVERSITE CATHOLIQUE DE LOUVAIN, Institut de Recherches Economiques et Sociales (IRES), IZA and ERMES Université Paris 2) |
| Abstract: | We develop a methodology to sign output distortions in the random participation framework. We apply our method to monopoly nonlinear pricing problem, to the regulatory monopoly problem and mainly to the optimal income tax problem. In the latter framework, individuals are heterogeneous across two unobserved dimensions: their skill and their disutility of participation to the labor market. We derive a fairly mild condition for optimal marginal tax rates to be non negative everywhere, implying that in-work effort is distorted downwards. Numerical simulations for the U.S. confirm this property. Moreover, it is typically optimal to provide a distinct level of transfer to the non-employed and to workers with zero or negligible earnings. |
| Keywords: | Adverse selection, Optimal taxation, Random participation |
| JEL: | H21 H23 |
| Date: | 2012–03–13 |
| URL: | http://d.repec.org/n?u=RePEc:ctl:louvir:2012003&r=cmp |
| By: | John Geanakoplos (Cowles Foundation, Yale University); Robert Axtell (George Mason University); Doyne J. Farmer (Santa Fe Institute); Peter Howitt (Brown University); Benjamin Conlee (Ellington Management Group); Jonathan Goldstein (George Mason University); Matthew Hendrey (George Mason University); Nathan M. Palmer (George Mason University); Chun-Yi Yang (George Mason University) |
| Abstract: | Systemic risk must include the housing market, though economists have not generally focused on it. We begin construction of an agent-based model of the housing market with individual data from Washington, DC. Twenty years of success with agent-based models of mortgage prepayments give us hope that such a model could be useful. Preliminary analysis suggests that the housing boom and bust of 1997-2007 was due in large part to changes in leverage rather than interest rates. |
| Keywords: | Agent based models, Housing prices, Boom and bust, Leverage, Interest rates, Foreclosures, Systemic risk |
| JEL: | E3 E31 E32 E37 E44 E63 R2 R20 R21 R23 R28 R3 R30 R31 R38 |
| Date: | 2012–03 |
| URL: | http://d.repec.org/n?u=RePEc:cwl:cwldpp:1852&r=cmp |
| By: | Joachim Merz; Dominik Hanglberger; Rafael Rucha (LEUPHANA University Lüneburg,Department of Economic, Behaviour and Law Sciences, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB))) |
| Abstract: | Knowledge about the timing of consumption opens new insights into consumption behaviour for consumer, economic, social as well as for communal and societal policies. It not only allows sound information for a better match of timely supply and demand but also about everyday living arrangements. This study contributes to the timing aspect of daily consumption by posing the question: how is the timing of daily demand for goods and services affected by major changes in German society? We concentrate on important and currently discussed developments and policies: the huge shift in Germany’s demographic structure with an aging society (with a population forecast for 2020 by the German Federal Statistical Office), the deregulation and the further expansion in flexibility of the labour market and the current policy of extending public childcare support. For each aspect and policy we first describe the actual timing of daily demand for goods and services. With the microsimulation approach and different scenarios we then quantify the respective societal and policy impacts based on more than 37,000 time use diaries of the current German Time Budget Survey of 2001/2002. |
| Keywords: | timing of daily demand for goods and services, consumer policy analysis by microsimulation: aging society, deregulation of the labour market, flexible working hours, public childcare support, German Time Budget Survey 2001/2002 |
| JEL: | D12 J12 |
| Date: | 2011–05 |
| URL: | http://d.repec.org/n?u=RePEc:leu:wpaper:90&r=cmp |
| By: | Sven Banischa, Ricardo Lima and Tanya Araújo |
| Abstract: | This paper introduces a Markov chain approach that allows a rigorous analysis of agent based opinion dynamics as well as other related agent based models (ABM). By viewing the ABM dynamics as a micro description of the process, we show how the corresponding macro description is obtained by a projection construction. Then, well known conditions for lumpability make it possible to establish the cases where the macro model is stillMarkov. In this case we obtain a complete picture of the dynamics including the transient stage, the most interesting phase in applications. For such a purpose a crucial role is played by the type of probability distribution used to implement the stochastic part of the model which defines the updating rule and governs the dynamics. In addition, we show how restrictions in communication leading to the co–existence of different opinions follow from the emergence of new absorbing states. We describe our analysis in detail with some specific models of opinion dynamics. Generalizations concerning different opinion representations as well as opinion models with other interaction mechanisms are also discussed. We find that our method may be an attractive alternative to mean–field approaches and that this approach provides new perspectives on the modeling of opinion exchange dynamics, and more generally of other ABM. |
| Keywords: | Agent Based Models, Opinion Dynamics, Markov chains, MicroMacro, Lumpability, Transient Dynamics. |
| Date: | 2012–03 |
| URL: | http://d.repec.org/n?u=RePEc:ise:isegwp:wp102012&r=cmp |
| By: | Rhema Vaithianathan (Department of Economics, University of Auckland, Auckland, New Zealand.); Nan Jiang (Department of Economics, Auckland University of Technology, Auckland, New Zealand.); Toni Ashton (School of Population Health, University of Auckland, Auckland, New Zealand.) |
| Abstract: | Predictive Risk Models which utilize routinely collected data to develop algorithms are used in England to stratify patients according to their hospital admission risk. An individual’s risk score can be used as a basis to select patients for hospital avoidance programmes. This paper presents a brief empirical analysis of New Zealand hospital data to create a prediction algorithm and illustrates how a hospital avoidance business case can be developed using the model. A sample of 134,262 patients was analyzed in a Multivariate logistic regression, various socioeconomic factors and indictors of previous admissions were used to predict the probability that a patient is readmitted to hospital within the 12 months following discharge. The key factors for readmission prediction were age, sex, diagnosis of last admission, length of stay and cost-weight of previous admission. The prognostic strength of the algorithm was good, with a randomly selected patient with a future re-admission being 71.2% more likely to receive a higher risk score than one who will not have a future admission. |
| Keywords: | Hospital readmission; Risk prediction; Prognostic strength. |
| JEL: | I10 C13 O22 |
| Date: | 2012–02 |
| URL: | http://d.repec.org/n?u=RePEc:aut:wpaper:201202&r=cmp |