New Economics Papers
on Computational Economics
Issue of 2007‒06‒02
nine papers chosen by

  1. The Chinese Economy from 1997:2015: Developing a Baseline for the MC-HUGE Model By Yin Hua Mai
  2. Credit Risk Monte Carlos Simulation Using Simplified Creditmetrics' Model: the joint use of importance sampling and descriptive sampling By Jaqueline Terra Moura Marins; Eduardo Saliby
  3. Potential for car use reduction through a simulation approach: Paris and Lyon case studies By Marie-Hélène Massot; Jimmy Armoogun; Patrick Bonnel; David Caubel
  4. Which market protocols facilitate fair trading? By Marco LiCalzi; Paolo Pellizzari
  5. Global Ageing and Macroeconomic Consequences of Demographic Uncertainty in a Multi-Regional Model By Juha Alho; Vladimir Borgy
  6. Learning-by-doing in the Renewable Energy Equipment Industry or in Renewable Electricity Production : Why Does It Matter to Differentiate? By Katja Schumacher; Michael Kohlhaas
  7. Interactive Problem Structuring with ICZM Stakeholders By Frank van Kouwen; Carel Dieperink; Paul P. Schot; Martin J. Wassen
  8. An Analysis of Off-Site Supervision of Banks' Profitability, Risk and Capital Adequacy: a portfolio simulation approach applied to brazilian banks By Theodore M. Barnhill; Marcos R. Souto; Benjamin M. Tabak
  9. AD-DICE: An Implementation of Adaptation in the DICE Mode By Kelly C. de Bruin; Rob B. Dellink; Richard S.J. Tol

  1. By: Yin Hua Mai
    Abstract: MC-HUGE is a dynamic Computable General Equilibrium model of the Chinese economy. The core CGE part of the MC-HUGE model is based on that of the ORANI model. The dynamic mechanism of MC-HUGE is based on that of the MONASH model. This paper documents how the MC-HUGE model is calibrated to China's economic growth data from 1997 to 2005. It also reports how the model is used to forecast a growth path for the Chinese economy from 2005 to 2015. The historical and the forecast simulation produce a baseline or a business-as-usual scenario with which to compare the effects of any changes in economic policies or environment.
    Keywords: China, CGE modelling, economic growth, oil
    JEL: C68 F14 O10
    Date: 2006–09
  2. By: Jaqueline Terra Moura Marins; Eduardo Saliby
    Abstract: Monte Carlo simulation is implemented in some of the main models for estimating portfolio credit risk, such as CreditMetrics, developed by Gupton, Finger and Bhatia (1997). As in any Monte Carlo application, credit risk simulation according to this model produces imprecise estimates. In order to improve precision, simulation sampling techniques other than traditional Simple Random Sampling become indispensable. Importance Sampling (IS) has already been successfully implemented by Glasserman and Li (2005) on a simplified version of CreditMetrics, in which only default risk is considered. This paper tries to improve even more the precision gains obtained by IS over the same simplified CreditMetrics' model. For this purpose, IS is here combined with Descriptive Sampling (DS), another simulation technique which has proved to be a powerful variance reduction procedure. IS combined with DS was successful in obtaining more precise results for credit risk estimates than its standard form.
    Date: 2007–03
  3. By: Marie-Hélène Massot (LVMT - Laboratoire Ville, Mobilité, Transports - [INRETS] - [Université de Marne la Vallée] - [Ecole Nationale des Ponts et Chaussées]); Jimmy Armoogun (DEST - Département Economie et Sociologie des Transports - [INRETS]); Patrick Bonnel (LET - Laboratoire d'économie des transports - [CNRS : UMR5593] - [Université Lumière - Lyon II] - [Ecole Nationale des Travaux Publics de l'Etat]); David Caubel (LET - Laboratoire d'économie des transports - [CNRS : UMR5593] - [Université Lumière - Lyon II] - [Ecole Nationale des Travaux Publics de l'Etat])
    Abstract: The aim of the present study is to evaluate the possible extent of modal shifts from car use to 'alternative modes' (public transport, cycling, walking) without any change in individual patterns of activity. Its approach is based on a transfer procedure that allows the simulation of the maximal potential market for transport modes other than the private car. The method is based on repeated iterations of a simulation model that assigns journeys to transport modes other than the automobile based on a number of improved public transport scenarios. Demand is channelled towards individual modes (walking, cycling), public transport, and a combination of individual and public modes, based on their relative time and distance performance. The modal transfer procedure is applied to several transport supply scenarios, which provide a picture of what is possible in the sphere of modal split. Each simulation entails a potential transfer of private vehicle-km to each of the other modes. Even where different public transport scenarios are simulated, the transfer is evaluated for round trips in both the Paris and Lyon surveys. There is therefore no modification in the activity pattern of the people surveyed nor trips induced by improvements in transport supply. The aim is not to predict what would be the modal split in other circumstances, but the upper limit of the shifts. This paper presents our methodology and the principal results obtained through numerical simulations based on figures for the Paris and Lyon conurbations. This approach demonstrates that a policy focused on modal shifts has the potential to reduce car use, but that this potential is limited. Any aspiration to reduce car use further would mean changes in the patterns and location of activity.
    Keywords: Urban transport ; Modal split ; modal split simulation method ; Transportation policy ; Car use reduction ; Public transport ; Individual daily mobility ; modal transfer ; Paris (France) ; Lyon (France)
    Date: 2007–05–18
  4. By: Marco LiCalzi (Department of Applied Mathematics, University of Venice); Paolo Pellizzari (Department of Applied Mathematics, University of Venice)
    Abstract: We study the performance of four market protocols with regard to their ability to equitably distribute the gains from trade among two groups of participants in an exchange economy. We test the protocols by running (computerized) experiments. Assuming Walrasian tatonemment as benchmark, there is a clear-cut ranking from best to worst: batch auction, nondiscretionary dealership, the hybridization of a dealership and a continuous double auction, and finally the pure continuous double auction.
    Keywords: allocative efficiency, allocative fairness, allocative neutrality, comparison of market institutions, market microstructure, performance criteria.
    JEL: D61 D63 D69 G19
    Date: 2007–05
  5. By: Juha Alho; Vladimir Borgy
    Abstract: While demographics have long been identified as a key variable in long term macroeconomic analysis, most previous analyses have relied on deterministic population forecasts. But, as several recent papers testify, demographic developments are uncertain, and attempts at describing this via scenario-based variants have serious shortcomings. Macroeconomic consequences of demographic uncertainty have not been explored in a multi-regional setting of the world economy so far, but they can be of considerable interest. The asynchronous nature of the ageing process is expected to influence macroeconomic trends, but it is also of interest that the uncertainty of population forecasts differs across world regions. In this paper, we investigate the impact of demographic uncertainty in a multi-regional general equilibrium, overlapping generations model (INGENUE 2). Specifically, we consider the level of uncertainty in each of the ten major regions of the world, and their correlation across regions. In order to address these issues, we produce stochastic simulations of the world population for the ten regions until 2050. Then, we analyse the economic consequences on a path by path basis over the period 2000-2050.
    Keywords: Computable General Equilibrium Models; international capital flows; life cycle models and saving; demographic trends and forecasts
    JEL: C68 F21 D91 J11
    Date: 2007–05
  6. By: Katja Schumacher; Michael Kohlhaas
    Abstract: In economic models of energy and climate policy, endogenous technological change is generally introduced as the result of either investment in research-and-development or of learning-by-doing. In this paper, we analyze alternative ways of modeling learning-by-doing in the renewable energy sector in a top-down CGE model. Conventionally, learning-by-doing effects in the renewable energy sector are allocated to the production of renewable based electricity. We build on the observation that learning-by-doing also takes place in sectors that deliver capital goods to the renewable electricity sector, in particular in the production of machinery and equipment for renewable energy technologies. We therefore implement learning-by-doing alternatively in the renewable energy equipment industry and in renewable electricity production and show why it matters to differentiate between these two approaches. The main differences originate from effects on international trade, since the output of the machinery and equipment sector is intensively traded on international markets unlike renewable electricity.
    Keywords: Learning-by-doing, wind energy, general equilibrium modeling, international trade
    JEL: Q43 C68 O30 F10
    Date: 2007
  7. By: Frank van Kouwen (Utrecht University); Carel Dieperink (Utrecht University); Paul P. Schot (Utrecht University); Martin J. Wassen (Utrecht University)
    Abstract: Integrated Coastal Zone Management (ICZM) is struggling with a lack of science-management integration. Many computer systems, usually known as “decision support systems”, have been developed with the intention to make scientific knowledge about complex systems more accessible for coastal managers. These tools, allowing a multi-disciplinary approach with multi-criteria analyses, are designed for well-defined, structured problems. However, in practice stakeholder consensus on the problem structure is usually lacking. Aim of this paper is to explore the practical opportunities for the new so-called Quasta approach to structure complex problems in a group setting. This approach is based on a combination of Cognitive Mapping and Qualitative Probabilistic Networks. It comprehends a new type of computer system which is quite simple and flexible as well. The tool is tested in two workshops in which various coastal management issues were discussed. Evaluations of these workshops show that (1) this system helps stakeholders to make them aware of causal relationships, (2) it is useful for a qualitative exploration of scenarios, (3) it identifies the quantitative knowledge gaps of the problem being discussed and (4) the threshold for non technicians to use this tool is quite low.
    Keywords: Integrated Coastal Zone Management, Problem Structuring, Stakeholder Participation, Cognitive Mapping, Interactive Policy Making
    JEL: Q5
    Date: 2007–05
  8. By: Theodore M. Barnhill; Marcos R. Souto; Benjamin M. Tabak
    Abstract: In most countries, the role of off-site bank supervision involves continuous monitoring of profitability, risk and capital adequacy. The objective of this article is to demonstrate the value of bringing together advanced modeling techniques with data on banks' assets and liabilities and credit worthiness. More specifically, we apply an integrated market and credit risk simulation methodology to a group of six hypothetical banks. We show the capacity of the methodology: (i) to simulate credit transition probabilities of default close to the historical values estimated by the Central Bank of Brazil; and (ii) to simulate asset and equity returns that are unbiased estimators of average historical returns and standard deviations. Our results also indicate that: (i) a sharp reduction in the interest rate spreads of Brazilian banks reduces bank profitability and increases the probability of default; and (ii) most banks have low probability of bankruptcy. Our position is that utilization of forward looking risk evaluation methodologies in databases, such as those developed by the Central Bank of Brazil, has significant potential as an instrument of indirect supervision to identify potential risks before they materialize.
    Date: 2006–09
  9. By: Kelly C. de Bruin (Wageningen University); Rob B. Dellink (Wageningen University); Richard S.J. Tol (Institute for Environmental Studies)
    Abstract: Integrated Assessment Models (IAMS) have helped us over the past decade to understand the interactions between the environment and the economy in the context of climate change. Although it has also long been recognized that adaptation is a powerful and necessary tool to combat the adverse effects of climate change, most IAMs have not explicitly included the option of adaptation in combating climate change. This paper adds to the IAM and climate change literature by explicitly including adaptation in an IAM, thereby making the trade-offs between adaptation and mitigation visible. Specifically, a theoretical framework is created and used to implement adaptation as a decision variable into the DICE model. We use our new AD-DICE model to derive the adaptation cost functions implicit in the DICE model. In our set-up, adaptation and mitigation decisions are separable and AD-DICE can mimic DICE when adaptation is optimal. We find that our specification of the adaptation costs is robust with respect to the mitigation policy scenarios. Our numerical results show that adaptation is a powerful option to combat climate change, as it reduces most of the potential costs of climate change in earlier periods, while mitigation does so in later periods.
    Keywords: Integrated Assessment Modelling, Adaptation, Climate Change
    JEL: Q25 Q28
    Date: 2007–05

General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.