New Economics Papers
on Computational Economics
Issue of 2011‒04‒02
thirteen papers chosen by



  1. A method for pricing American options using semi-infinite linear programming By S\"oren Christensen
  2. A Local Search Algorithm for Clustering in Software as a Service Networks By Gaast, J.P. van der; Rietveld, C.A.; Gabor, A.F.; Zhang, Y.
  3. Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models By Siem Jan Koopman; Andre Lucas; Marcel Scharth
  4. An Equilibrium Model of Habitat Conservation under Uncertainty and Irreversibility By Luca Di Corato; Michele Moretto; Sergio Vergalli
  5. Assessing the Impact of the ASEAN Economic Community By Hiro Lee; Michael G. Plummer
  6. Learning-by-doing in Two Sectors, Production Structure, Leisure and Optimal Endogenous Growth By Matthias Göcke
  7. Multi-funds in the Chilean Pension System By Soledad Hormazabal
  8. Phased in nuclear power and electricity prices: the case of Italy By Eric Guerci; Fulvio Fontini
  9. Simulations of long-term returns and replacement rates in the Colombian pension system By Javier Alonso; Carlos Herrera; Claudia Llanes; David Tuesta
  10. Reviving the Competitive Storage Model: A Holistic Approach to Food Commodity Prices By Norbert Funke; Yanliang Miao; Weifeng Wu
  11. Sequencing Heuristics for Storing and Retrieving Unit Loads in 3D Compact Automated Warehousing Systems By Yu, Y.; Koster, M.B.M. de
  12. Stochastic evolution equations in portfolio credit modelling By Nick Bush; Ben M. Hambly; Helen Haworth; Lei Jin; Christoph Reisinger
  13. About the Impact of Model Risk on Capital Reserves: A Quantitative Analysis. By Bertram, Philip; Sibbertsen, Philipp; Stahl, Gerhard

  1. By: S\"oren Christensen
    Abstract: We introduce a new approach for the numerical pricing of American options. The main idea is to choose a finite number of suitable excessive functions (randomly) and to find the smallest majorant of the gain function in the span of these functions. The resulting problem is a linear semi-infinite programming problem, that can be solved using standard algorithms. This leads to good upper bounds for the original problem. For our algorithms no discretization of space and time and no simulation is necessary. Furthermore it is applicable even for high-dimensional problems. The algorithm provides an approximation of the value not only for one starting point, but for the complete value function on the continuation set, so that the optimal exercise region and e.g. the Greeks can be calculated. We apply the algorithm to (one- and) multidimensional diffusions and to L\'evy processes, and show it to be fast and accurate.
    Date: 2011–03
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1103.4483&r=cmp
  2. By: Gaast, J.P. van der; Rietveld, C.A.; Gabor, A.F.; Zhang, Y.
    Abstract: In this paper we present and analyze a model for clustering in networks that offer Software as a Service (SaaS). In this problem, organizations requesting a set of applications have to be assigned to clusters such that the costs of opening clusters and installing the necessary applications in clusters are minimized. We prove that this problem is NP-hard, and model it as an Integer Program with symmetry breaking constraints. We then propose a Tabu search heuristic for situations where good solutions are desired in a short computation time. Extensive computational experiments are conducted for evaluating the quality of the solutions obtained by the IP model and the Tabu Search heuristic. Experimental results indicate that the proposed Tabu Search is promising.
    Keywords: Tabu Search;integer programming;software as a service;complexity theory
    Date: 2011–03–02
    URL: http://d.repec.org/n?u=RePEc:dgr:eureri:1765022723&r=cmp
  3. By: Siem Jan Koopman (VU University Amsterdam); Andre Lucas (VU University Amsterdam); Marcel Scharth (VU University Amsterdam)
    Abstract: We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. By combining existing numerical and Monte Carlo integration methods, we obtain a general and efficient likelihood evaluation method for this class of models. Our approach is based on the idea that only a small part of the likelihood evaluation problem requires simulation, even in high dimensional settings. We refer to this method as Numerically Accelerated Importance Sampling. Computational gains of our efficient importance sampler are obtained by relying on Kalman filter and smoothing methods associated with an approximated linear Gaussian state space model. Our approach also leads to the removal of the bias-variance tradeoff in the efficient importance sampling estimator of the likelihood function. We illustrate our new methods by an elaborate simulation study which reveals high computational and numerical efficiency gains for a range of well-known models.
    Keywords: State space models; importance sampling; simulated maximum likelihood; stochastic volatility; stochastic copula; stochastic conditional duration
    JEL: C15 C22
    Date: 2011–03–22
    URL: http://d.repec.org/n?u=RePEc:dgr:uvatin:20110057&r=cmp
  4. By: Luca Di Corato (Swedish University of Agricultural Sciences); Michele Moretto (Università di Padova); Sergio Vergalli (Università di Brescia)
    Abstract: In this paper stochastic dynamic programming is used to investigate habitat conservation by a multitude of landholders under uncertainty about the value of environmental services and irreversible development. We study land conversion under competition on the market for agricultural products when voluntary and mandatory measures are combined by the Government to induce adequate participation in a conservation plan. We analytically determine the impact of uncertainty and optimal policy conversion dynamics and discuss different policy scenarios on the basis of the relative long-run expected rate of deforestation. Finally, some numerical simulations are provided to illustrate our findings.
    Keywords: optimal stopping, deforestation, payments for environmental services, Natural Resources Management.
    JEL: C61 D81 Q24 Q58
    Date: 2010–12
    URL: http://d.repec.org/n?u=RePEc:pad:wpaper:0122&r=cmp
  5. By: Hiro Lee (Osaka School of International Public Policy, Osaka University); Michael G. Plummer (OECD and Johns Hopkins University, SAIS-Bologna)
    Abstract: Consequences of the ASEAN Economic Community (AEC) are investigated using a dynamic computable general equilibrium (CGE) model. Quantitative assessments of the effects on economic welfare, trade flows and sectoral output are offered. When the removal of trade barriers are combined with reductions in administrative and technical barriers and lowering the trade and transport margins under the assumption of endogenously determined productivity, the estimated welfare gains for the year 2015 range from 1.1% in Indonesia to 9.4% in Thailand. The results suggest that streamlining customs procedures and other reductions in administrative and technical barriers, as well as increased competition and improvements in infrastructure, are significant in enlarging the benefits of the AEC.
    Keywords: ASEAN, AEC, CGE model
    JEL: F15 F17
    Date: 2011–03
    URL: http://d.repec.org/n?u=RePEc:osp:wpaper:11e002&r=cmp
  6. By: Matthias Göcke (University of Giessen)
    Abstract: A model with two different production sectors and endogenous growth based on the accumulation of sector-specific human capital due to learning-by-doing is presented. Accumulation of experience is measured by means of sectoral production output aggregated over time. Growth is controlled by a dynamic optimisation of the use of time for working in the different sectors or for leisure. Transitional dynamics of production growth, especially of structural change towards a 'new' sector (with relatively scarce experience), of the optimal sectoral distribution of working time and of leisure as well as the corresponding steady state levels are derived and a numerical simulation is performed.
    JEL: C61 D90 J22 O41
    Date: 2011
    URL: http://d.repec.org/n?u=RePEc:mar:magkse:201111&r=cmp
  7. By: Soledad Hormazabal
    Abstract: This work describes the development of the multi-fund scheme in Chile, as well as its key features and results. It includes simulation exercises designed to model the returns and volatilities of the different types of Chilean pension funds over a 50-year horizon. It shows how the trend is for increasing returns and that the average expected return of the pension funds is greater as the percentage invested in equity increases, although the volatility is also higher. The considerable risk premium associated with investment in shares would justify the adoption of a greater risk when the investment horizon is longer. This does not mean that the risk is limited over time, but rather that the volatility of the equity assets provides periods of exit opportunities with significant returns.
    Date: 2010–02
    URL: http://d.repec.org/n?u=RePEc:bbv:wpaper:1028&r=cmp
  8. By: Eric Guerci (Universite' de la Mediterranee, Marseille); Fulvio Fontini (University of Padova)
    Abstract: In this paper, we evaluate the impact of the proposed construction of new nuclear power (NP) plants on the cost of electricity in Italy. We create an agent‐based model that simulates actual Italian market generators’ behaviour in their bid offers at the Italian wholesale electricity market (IPEX), using the existing grid structure and power plant characteristics. We calculate the possible impact of the proposed installation of four nuclear power plants on zonal and average (National Single Price, PUN) electricity prices, taking into account the network grid (with its transmission constraints), the possible location of NP plants, the process of market splitting and the status of the generation side of the market, namely the capacity, production and marginal costs of generators. Both a cost‐ based scenario and a strategic scenario are considered. In the cost‐based scenario, we investigate how NP would shift the supply curve, which technology will be substituted hour by hour and zone by zone and whether the introduction of NP will reduce electricity prices. In the strategic scenario, we allow firms to strategically withhold some capacity through their bids in order to influence the system marginal price and evaluate how the introduction of nuclear base load power generation increases operators’ strategic space and impacts electricity prices.
    Keywords: Electricity market, PUN, Agent-based computational economics, Nuclear power.
    JEL: Q41 C63
    Date: 2011–03
    URL: http://d.repec.org/n?u=RePEc:pad:wpaper:0130&r=cmp
  9. By: Javier Alonso; Carlos Herrera; Claudia Llanes; David Tuesta
    Abstract: This study is a theoretical exercise for Colombia that aims to simulate a variety of scenarios under a hypothetical scheme similar to the multi-funds currently in operation in Chile, Mexico and Peru. This has been done by modeling the future movement of asset prices that are considered to be representative of equity and fixed-income using the Monte Carlo method. After making the simulations we have constructed alternative investment portfolios according to the chosen combination of equity and fixed-income, and compared and assessed them in terms of their risk-return ratio. The study emphasizes the fundamental importance of adequate contribution densities for obtaining sufficient income for old age, and the relevance of high returns, with adequate risk limitation. Another of the study’s aims is to use the new multi-fund scheme defined for Colombia as a basis for the hypotheses of different scenarios projected to 2050. These will include the composition of members’ pension fund portfolios and changes in the scheme over time, taking as a reference the life-cycle scheme operated in Mexico, as well as other compositions and profiles that participants may decide to enter into in accordance with their choice and the limits set by regulations. The results of the work confirm what has been found in other studies on the subject for the Colombian economy: that the implementation of a multi-fund system will provide pension-fund members with efficient returns in the long term, with limited volatility over time.
    Date: 2010–12
    URL: http://d.repec.org/n?u=RePEc:bbv:wpaper:1029&r=cmp
  10. By: Norbert Funke; Yanliang Miao; Weifeng Wu
    Abstract: We revive in this paper the empirical relevance of the competitive storage model by taking a holistic approach to food commodity prices. We augment the seminal Deaton and Laroque (1992, 1996) model by incorporating more comprehensive and realistic supply and demand factors: output and demand trends, shocks to the yield, and time-varying interest rates. While the computational burden increases exponentially, the augmented model succeeds in replicating all four key patterns of food commodity prices. Our simulation and comparative statics also show that (i) the long-run declining trend of food prices may come to a halt or even reverse due to the shifting balance between supply and demand; (ii) short-run price fluctuations are mainly attributable to sizeable, though low-probability, shocks to output such as inclement weather; and (iii) the impact of monetary policy, though small in normal times, is nonlinear and asymmetric, and can become large if the real rate passes a certain threshold.
    Date: 2011–03–23
    URL: http://d.repec.org/n?u=RePEc:imf:imfwpa:11/64&r=cmp
  11. By: Yu, Y.; Koster, M.B.M. de
    Abstract: Sequencing unit load retrieval requests has been studied extensively in literature for conventional single-deep automated warehousing systems. A proper sequence can greatly reduce the makespan when carrying out a group of such requests. Although the sequencing problem is NP-hard some very good heuristics exist. Surprisingly the problem has not yet been investigated for compact (multi-deep) storage systems, which have greatly increased in popularity the last decade. This paper studies how to sequence a group (or block) of storage and retrieval requests in a multi-deep automated storage system with the objective to minimize the makespan. We adapt well-known sequencing heuristics for the multi-deep system, and propose and evaluate a new heuristic: percentage priority to retrievals with shortest leg (PPR-SL). Our results show the PPR-SL heuristic consistently outperforms all the other heuristics. Generally, it can outperform the benchmark first-come first-served (FCFS) heuristic by 20-70%. The nearest neighbor (NN) heuristic that performs very well in conventional single-deep storage systems, appears to perform poorly in the multi-deep system; even worse than FCFS. In addition, based on FCFS and PPR-SL, we find robust rack dimensions yielding a short makespan, regardless of the number of storage and retrieval requests.
    Keywords: logistics;TSP;warehouse;compact storage;sequencing;AS/RS
    Date: 2011–02–17
    URL: http://d.repec.org/n?u=RePEc:dgr:eureri:1765022722&r=cmp
  12. By: Nick Bush; Ben M. Hambly; Helen Haworth; Lei Jin; Christoph Reisinger
    Abstract: We consider a structural credit model for a large portfolio of credit risky assets where the correlation is due to a market factor. By considering the large portfolio limit of this system we show the existence of a density process for the asset values. This density evolves according to a stochastic partial differential equation and we establish existence and uniqueness for the solution taking values in a suitable function space. The loss function of the portfolio is then a function of the evolution of this density at the default boundary. We develop numerical methods for pricing and calibration of the model to credit indices and consider its performance pre and post credit crunch.
    Date: 2011–03
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1103.4947&r=cmp
  13. By: Bertram, Philip; Sibbertsen, Philipp; Stahl, Gerhard
    Abstract: This paper analyzes and quantifies the idea of model risk in the environment of internal model building. We define various types of model risk including estimation risk, model risk in distribution and model risk in functional form. By the quantification of these concepts we analyze the impact of the modeling process of an econometric model on the resulting company model. Utilizing real insurance data we specify, estimate and simulate various linear and nonlinear time series models for the inflation rate and examine its impact on pension liabilities under the aspect of model risk. Under consideration of different risk measures it is shown that model risk can differ profoundly due to the specification process of the econometric model resulting in remarkable monetary differences concerning capital reserves. We furthermore propose a specification strategy for univariate time series models and demonstrate that thereby market risk and capital reserves can be reduced distinctively.
    Keywords: Model risk, Estimation risk, Misspecification risk, Basel multiplication factor, Empirical model specification, Capital reserves
    JEL: G12 G18
    Date: 2011–03
    URL: http://d.repec.org/n?u=RePEc:han:dpaper:dp-469&r=cmp

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