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on Computational Economics |
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Issue of 2005‒09‒29
twelve papers chosen by |
| By: | B. MAENHOUT; M. VANHOUCKE |
| Abstract: | In this paper, we present a novel meta-heuristic technique for the nurse scheduling problem (NSP). This well-known scheduling problem assigns nurses to shifts per day taking both hard and soft constraints into account. The objective is to maximize the preferences of the nurses and to minimize the total penalty cost from violations of the soft constraints. The problem is known to be NP-hard. Due to its complexity and relevance, many algorithms have been developed to solve practical, and often case-specific versions of the NSP. The enormous amount of different constraints has led to an overwhelming amount of exact and meta-heuristic procedures, and hence comparison and stateof- the-art reporting of standard results seem to be a utopian idea. The contribution of this paper is twofold. First, we present a meta-heuristic procedure for the NSP based on the framework proposed by Birbil and Fang (2003). The Electromagnetic (EM) approach is based on the theory of physics, and simulates attraction and repulsion of sample points in order to move towards a promising solution. Second, we present computational experiments on a standard benchmark dataset, and solve problem instances under different assumptions. We show that our procedure performs consistently well under many different circumstances, and hence, can be considered as robust against case-specific constraints. |
| Keywords: | meta-heuristics; electromagnetism; nurse scheduling |
| Date: | 2005–07 |
| URL: | http://d.repec.org/n?u=RePEc:rug:rugwps:05/316&r=cmp |
| By: | Boer-Sorban, K.; Kaymak, U.; Bruin, A. de (Erasmus Research Institute of Management (ERIM), RSM Erasmus University) |
| Abstract: | Artificial stock markets are built with diffuse priors in mind regarding trading strategies and price formation mechanisms. Diffuse priors are a natural consequence of the unknown relation between the various elements that drive market dynamics and the large variety of market organizations, findings, however, might hold only within the specific market settings. In this paper we propose a framework for building agent-based artificial stock markets. We present the mechanism of the framework based on a previously identified list of organizational and behavioural aspects. Within the framework experiments with arbitrary many trading strategies, acting in various market organizations can be conducted in a flexible way, without changing its architecture. In this way experiments of other artificial stock markets, as well as theoretical models can be replicated and their findings compared. Comparisons of the different experimental results might indicate whether findings are due to traders’ behaviour or to the chosen market structure and could suggest how to improve market quality. |
| Keywords: | Computational economics;agent-based modelling;artificial stock markets;behavioural finance; |
| Date: | 2005–04–03 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:eureri:30002104&r=cmp |
| By: | K. Vela Velupillai |
| Keywords: | general equilibrium theory,CGE models,mathematical economics,computability,constructivity |
| JEL: | C62 C63 D50 D58 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:trn:utwpde:0513&r=cmp |
| By: | Koijen,Ralph S.J.; Nijman,Theo E.; Werker,Bas J.M. (Tilburg University, Center for Economic Research) |
| Abstract: | The riskless nature in real terms of inflation-linked bonds has led to the conclusion that inflation-linked bonds should constitute a substantial part of the optimal investment portfolio of long-term investors. This conclusion is reached in models where investors do not receive labor income during the investment period. Since such an income stream is often indexed with inflation, labor income in itself constitutes an implicit holding of real bonds. As such, the optimal investment in inflation-linked bonds is substantially reduced. By extending recently developed simulation-based techniques, we are able to determine the optimal portfolio choice among inflation-linked bonds, nominal bonds, and stocks for investors endowed with an indexed stream of income. We find that the fraction invested in inflation-linked bonds is much smaller than reported in the literature, the duration of the optimal nominal bond portfolio is lengthened, and the utility gains of having access to inflation-linked bonds are substantially reduced. We investigate as well the robustness of our results to time-variation in bond risk premia, the riskiness of labor income, and correlation between labor income risk and financial risks. We find that especially accounting for time-variation in bond risk premia and correlation between labor income risk and financial risks is important for both optimal portfolios and the utility gains of having access to inflation-linked bonds. |
| Keywords: | inflation linked bonds;optimal lifetime investment;simulation-based portfolio choice |
| JEL: | C15 C63 E43 G11 G12 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:kubcen:200595&r=cmp |
| By: | M. VANHOUCKE; S. VANDEVOORDE |
| Abstract: | It is well-known that well managed and controlled projects are more likely to be delivered on time and within budget. The construction of a (resource-feasible) baseline schedule and the follow-up during execution are primary contributors to the success or failure of a project. Earned value management systems have been set up to deal with the complex task of controlling and adjusting the baseline project schedule during execution. Although earned value systems have been proven to provide reliable estimates for the follow-up of cost performance, it often fails to predict the total duration of the project. In this paper, we extensively review the existing methods to forecast the total project duration. Moreover, we investigate the potential of a newly developed method, the earned schedule method, which makes the connection between earned value metrics and the project schedule. We present an extensive simulation study where we carefully control the level of uncertainty in the project, the influence of the project network structure on the accuracy of the forecasts, and the time horizon where the newly developed measures provide accurate and reliable results. |
| Keywords: | Earned value; earned duration; earned schedule; CPM |
| Date: | 2005–07 |
| URL: | http://d.repec.org/n?u=RePEc:rug:rugwps:05/317&r=cmp |
| By: | Lence, Sergio H.; Hayes, Dermot J. |
| Abstract: | A two-country extension of an ex ante simulation model of research and development (R&D) in agriculture developed by Lence, Hayes, McCunn, Smith, and Niebur (2005) is used to analyze issues regarding intellectual property (IP) protection, spillovers, and genetic use restriction technologies (GURTs) in the context of the United States and South America soybean sectors. The model is used to examine how various IP protection levels in the United States and South America might have impacted on the level of innovation, market equilibrium and the welfare of market participants had they been in place prior to the introduction of Roundup Ready technologies. The results indicate that technology fees that are charged in the United States but not in South America are harmful to US producers. Neither producers in the United States nor US-based R&D firms have incentives to support or develop technologies such as Roundup Ready that can be easily adopted in countries with low IP protection. However, total world welfare is higher when this type of transferable R&D is conducted. Equalizing IP protection across countries gives R&D firms a strong incentive to conduct R&D of relevance to both countries. Surprisingly, the introduction of a low level of IP protection in South America does not necessarily improve expected welfare of US producers. To the extent that GURTs contribute toward IP protection harmonization, they can be world-welfare enhancing. However, the positive impact of GURTs could be greatly reduced if they increase IP protection beyond a certain level. The use of GURTs to impose IP protection in South America generally increases the expected welfare of US producers. |
| Keywords: | GURT, Roundup Ready soybeans, spillover, technology fee, welfare. |
| Date: | 2005–09–22 |
| URL: | http://d.repec.org/n?u=RePEc:isu:genres:12417&r=cmp |
| By: | Post, G.T. (Erasmus Research Institute of Management (ERIM), RSM Erasmus University) |
| Abstract: | FIRST-ORDER STOCHASTIC DOMINANCE (FSD) is one of the fundamental concepts of decision making under uncertainty, relying only on the assumption of nonsatiation, or decision makers preferring more to less. There exist well-known, simple algorithms for establishing FSD relationships between a pair of choice alternatives. Unfortunately, these algorithms have limited use in applications with more than two choice alternatives. The analysis of investment portfolios is one such application; investors generally can form a large number of portfolios by diversifying across individual assets. For such applications, there is a need to develop an algorithm for establishing if a given portfolio represents the optimal solution for at least some nonsatiable investor, i.e., is in the FSD optimal set. |
| Keywords: | Stochastic Dominance;Portfolio Diversification;Optimality;Admissibility; |
| Date: | 2005–06–28 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:eureri:30007068&r=cmp |
| By: | W. BUCKINX; G. VERSTRAETEN; D. VAN DEN POEL |
| Abstract: | Loyalty and targeting are central topics in Customer Relationship Management. Yet, the information that resides in customer databases only records transactions at a single company, whereby customer loyalty is generally unavailable. In this study, we enrich the customer database with a prediction of a customer's behavioral loyalty such that it can be deployed for targeted marketing actions without the necessity to measure the loyalty of every single customer. To this end, we compare multiple linear regression with two state-of-the-art machine learning techniques (random forests and automatic relevance determination neural networks), and we show that (i) a customer’s behavioral loyalty can be predicted to a reasonable degree using the transactional database, (ii) given that overfitting is controlled for by the variable-selection procedure we propose in this study, a multiple linear regression model significantly outperforms the other models, (iii) the proposed variable-selection procedure has a beneficial impact on the reduction of multicollinearity, and (iv) the most important indicator of behavioral loyalty consists of the variety of products previously purchased. |
| Keywords: | Predictive modeling; customer relationship management; behavioral loyalty; overfitting; multicollinearity; data enrichment |
| Date: | 2005–08 |
| URL: | http://d.repec.org/n?u=RePEc:rug:rugwps:05/324&r=cmp |
| By: | Zsuzsanna Fluck; Kedran Garrison; Stewart C. Myers |
| Abstract: | This paper develops a model to study how entrepreneurs and venture-capital investors deal with moral hazard, effort provision, asymmetric information and hold-up problems. We explore several financing scenarios, including first-best, monopolistic, syndicated and fully competitive financing. We solve numerically for the entrepreneur's effort, the terms of financing, the venture capitalist's investment decision and NPV. We find significant value losses due to holdup problems and under-provision of effort that can outweigh the benefits of staged financing and investment. We show that a commitment to later-stage syndicate financing increases effort and NPV and preserves the option value of staged investment. This commitment benefits initial venture capital investors as well as the entrepreneur. |
| JEL: | G24 G32 |
| Date: | 2005–09 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:11624&r=cmp |
| By: | Pastine, Tuvana; Pastine, Ivan |
| Abstract: | In an observational learning environment, rational agents with incomplete information may mimic the actions of their predecessors even when their own signal suggests the opposite. This herding behaviour may lead the society to an inefficient outcome if the signals of the early movers happen to be incorrect. This paper analyses the effect of signal accuracy on the probability of an inefficient informational cascade. The literature so far has suggested that an increase in signal accuracy leads to a decline in the probability of inefficient herding, because the first movers are more likely to make the correct choice. Indeed, the simulation results in Bikhchandani, Hirshleifer and Welch (1992) support this proposition. This paper however shows this not to be the case in general. We present simulations that demonstrate that even a small departure from symmetry in signal accuracy may lead to non-monotonic results. An increase in signal accuracy may result in a higher likelihood of an inefficient cascade. |
| Keywords: | herding; social learning |
| JEL: | D80 D82 |
| Date: | 2005–09 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:5219&r=cmp |
| By: | Bigsten, Arne (Department of Economics, School of Economics and Commercial Law, Göteborg University); Shimeles, Abebe (Department of Economics, School of Economics and Commercial Law, Göteborg University) |
| Abstract: | This study uses simulations to explore the possibility of halving the percentage of people living in extreme poverty in Africa by 2015. A pro-poor growth-scenario and a constant-inequality scenario are compared. It is shown that initial levels of inequality and mean per capita income determine the cumulative growth and inequalityreduction required to achieve the target. The trade-off between growth and inequality varies greatly among countries and their policy-choices are thus quite different. In some cases small changes in income-distribution can have a large effect on poverty, while in others a strong focus on growth is the only viable option. <p> |
| Keywords: | Poverty; pro-poor growth; millennium development goals; Africa |
| JEL: | I32 O15 |
| Date: | 2005–08–23 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:gunwpe:0177&r=cmp |
| By: | Laurence Seidman (Department of Economics,University of Delaware); Kenneth Lewis (Department of Economics,University of Delaware) |
| Abstract: | This paper simulates the use of transfers to households plus central-bank open-market purchases to generate a recovery of a low-interest-rate economy from a negative demand shock. Transfers to households are automatically triggered in recession; the prescribed anti-recession transfer ratio is proportional to the unemployment gap. Three alternative complementary monetary policies that the Federal Reserve might decide to implement are considered: standard, moderate, and aggressive. The simulations suggest that transfers plus open market purchases are likely to be an effective remedy for such a recession while limiting potential adverse impacts on inflation and government debt held by the non-central-bank public. |
| Keywords: | Macroecomics; Recession |
| Date: | 2004 |
| URL: | http://d.repec.org/n?u=RePEc:dlw:wpaper:04-02&r=cmp |