nep-cmp New Economics Papers
on Computational Economics
Issue of 2017‒03‒26
nineteen papers chosen by
Stan Miles
Thompson Rivers University

  1. New approaches in agent-based modeling of complex financial systems By T. T. Chen; B. Zheng; Y. Li; X. F. Jiang
  2. Long-run expectations in a Learning-to-Forecast Experiment: A Simulation Approach By Annarita Colasante; Simone Alfarano; Eva Camacho-Cuena; Mauro Gallegati
  3. PSO-based tuning of MURAME parameters for creditworthiness evaluation of Italian SMEs By Marco Corazza; Giovanni Fasano; Stefania Funari; Riccardo Gusso
  4. Can International Migration Accelerate Development? A Global Dynamic General Equilibrium Analysis By Dirk Willenbockel; S. Amer Ahmed - The World Bank; Delfin S. Go - The World Bank (Emeritus)
  5. Sovereign default contagion: an agent-based model approach By João Silvestre
  6. Portfolio choice decision making with NBP-effSAMWMIX: A Stochastic Multi-Armed Bandit Algorithm using Naïve Bandit Portfolio Approach By Boby Chaitanya Villari; Mohammed Shahid Abdulla
  7. Modeling Economic Systems as Locally-Constructive Sequential Games By Tesfatsion, Leigh
  8. R&Dsimulab: a micro-policy simulator for an ex-ante assessment of the effect of public R&D policies By Giovanni Cerulli; Federico Cecconi; Maria Augusta Miceli; Pierpaolo Angelini; Bianca Potì
  9. Ctx-effSAMWMIX: A Contextual Multi-Armed Bandit Algorithm for personalized recommendations By Boby Chaitanya Villari; Mohammed Shahid Abdulla
  10. An Agent-based Model of Contagion in Financial Networks By Leonardo dos Santos Pinheiro; Flavio Codeco COelho
  11. Hybridized Ant Colony Algorithm for Convoy Movement Problem By Alan John Maniamkot; P N Ram Kumar; R Sridharan
  12. An Agent-Based Simulation of Urban Passenger Mobility and Related Policies. The Case Study of an Italian Small City By Maggi,Elena; Vallino,Elena
  13. The economy wide impact of HIV/AIDS and the funding dilemma in Africa: Evidence from a dynamic life cycle horizon By Judith Kabajulizi; Judith Kabajulizi; Mthuli Ncube
  14. A plausible Decision Heuristics Model: Fallibility of human judgment as an endogenous problem By Carlos Sáenz-Royo
  15. Agent Based modeling of Housing Asset Bubble: A Simple Utility Function Based Investigation By Kausik Gangopadhyay; Kousik Guhathakurta
  16. What drives markups? Evolutionary pricing in an agent-based stock-flow consistent macroeconomic model By Pascal Seppecher; Isabelle Salle; Marc Lavoie
  17. Thematic and Spatial Concentration of CGE Models’ Application to Policy Research: Evidences from Palestine, Israel, the Sudan and Nigeria By Khalid Siddig
  18. A Simple Framework for Climate-Change Policy under Model Uncertainty By Stergios Athanasoglou; Valentina Bosetti; Laurent Drouet
  19. Drivers of private grain storage. A computational-economics and empirical approach By Jan Brockhaus; Jan Brockhaus; Matthias Kalkuhl

  1. By: T. T. Chen; B. Zheng; Y. Li; X. F. Jiang
    Abstract: Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of the agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogenous personal preferences and interactions, these models are successful to explain the microscopic origination of the temporal and spatial correlations of the financial markets. We then present a novel paradigm combining the big-data analysis with the agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces, and develop an agent-based model to simulate the dynamic behaviors of the complex financial systems.
    Date: 2017–03
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1703.06840&r=cmp
  2. By: Annarita Colasante (LEE and Department of Economics, Universitat Jaume I, Castellón, Spain); Simone Alfarano (LEE and Department of Economics, Universitat Jaume I, Castellón, Spain); Eva Camacho-Cuena (LEE and Department of Economics, Universitat Jaume I, Castellón, Spain); Mauro Gallegati (Department of Economics, Università Politecnica delle Marche, Ancona, Italy)
    Abstract: In this paper, we elicit both short and long-run expectations about the evolution of the price of a financial asset by conducting a Learning-to-Forecast Experiment (LtFE) in which subjects, in each period, forecast the asset price for each one of the remaining periods. The aim of this paper is twofold: on the one hand, we try to fill the gap in the experimental literature of LtFEs where great effort has been made in investigating short-run expectations, i.e. one step-ahead predictions,while there are no contributions that elicit long-run expectations. On the other hand, we propose an alternative computational approach with respect to the Heuristic Switching Model (HSM), to replicate the main experimental results. The alternative learning algorithm, called Exploration-Exploitation Algorithm (EEA), is based on the idea that agents anchor their expectations around the last market price, rather than on the fundamental value, with a range proportional to the recent past observed price volatility. Both algorithms perform well in describing the dynamics of short-run expectations and the market price. EEA, additionally, provides a fairly good description of long-run expectations.
    Keywords: Expectations, Experiment, Evolutionary Learning
    JEL: D03 G12 C91
    Date: 2017
    URL: http://d.repec.org/n?u=RePEc:jau:wpaper:2017/03&r=cmp
  3. By: Marco Corazza (Dept. of Economics, Università Ca' Foscari Venice); Giovanni Fasano (Dept. of Management, Università Ca' Foscari Venice); Stefania Funari (Dept. of Management, Università Ca' Foscari Venice); Riccardo Gusso (Dept. of Management, Università Ca' Foscari Venice)
    Abstract: In this work we use a MultiCriteria Decision Analysis (MCDA) model to evalu- ate the creditworthiness of a sample of Italian Small and Medium-sized Enterprises (SMEs), on the basis of their balance sheet data provided by the AIDA database. Our methodology is able to consider simultaneously different factors affecting the firmsÕ solvency level, and can produce results in terms of scoring, classification into homogeneous rating classes and migration probabilities. In this contribution we compare the results obtained considering two scenarios. On one hand, we experience an exogenous specification of the parameters that describe the preference structure implicit in the used MCDA model. On the other hand, we consider the results obtained using a preference disaggregation method to endogenously determine some of the model parameters. Because of the complexity of the obtained math- ematical programming problem, we use an heuristic methodology, namely Particle Swarm Optimization (PSO), which provides a reasonable compromise between the quality of the solution and the computational burden.
    Keywords: MultiCriteria Decision Analysis, Small and Medium-sized Enterprises, Credit Risk, Particle Swarm Optimization.
    JEL: C38 C61 C63
    Date: 2017–04
    URL: http://d.repec.org/n?u=RePEc:vnm:wpdman:137&r=cmp
  4. By: Dirk Willenbockel; S. Amer Ahmed - The World Bank; Delfin S. Go - The World Bank (Emeritus)
    Abstract: Policies to facilitate international migration and targets for reductions in remittance costs faced by migrant workers are set to be part of the emerging post-2015 development agenda. This is a recognition of significant linkages between international migration and the achievement of the post-2015 development goals, and is a response to the fact that total remittance flows to developing countries are already a multiple of international development assistance flows. Global demographic shifts over the coming decades are bound to magnify the economic incentives for South-North migration and reinforce the economic case for a reduction of existing barriers to international labor mobility. The domestic labor supply has already peaked in high-income countries as a whole. It is set to decline steadily over coming decades while hundreds of millions of new workers are projected to enter the labor force by 2030 in developing countries as a group. Moreover, given the considerable variety in demographic dynamics and labor productivity levels across developing regions, there is potentially also considerable scope for mutual gains from further South-South migration. Correspondingly, forward-looking assessments of the prospective economic impacts of future changes in policies toward cross-border migration flows deserve a high priority on the global development research agenda. Aims This study adopts a global dynamic computable general equilibrium simulation approach to provide a regionally differentiated quantitative assessment of the incremental economic benefits resulting from a marginal relaxation of existing restrictions on international migration flows. The simulation analysis will also assess the welfare impacts of a gradual reduction in remittance transaction costs to the target levels envisaged in the current draft proposal for the post-2015 sustainable development goals. This latter simulation scenario will take account of recent empirical estimates of the elasticity of remittances with respect to remittance costs reviewed in McKenzie and Yang (2014). The existing previous global CGE-model-based studies of gains from further international labor migration (e.g. Walmsley and Winters, 2005; World Bank, 2006; Walmsley et al., 2007) focus predominantly on South-North migration impacts. However, in terms of absolute headcount figures, the present observed extent of South-South migration is nearly as large as that of South-North migration (UNESA, 2012; Ratha and Shaw, 2007; Bakewell, 2009). Heterogeneity in demographic trends, as well as wage differentials across regions within the “Global South,” suggests non-trivial potential gains from further South-South migration. Thus, the present study includes a quantification of the potential gains from an incremental increase in South-South migration flows, starting from observed South-South migration patterns. The analytical framework is a modified version of the recursive dynamic global CGE model LINKAGE. An earlier version of this model has been used in an assessment of potential gains from further international migration reported in the World Bank Global Economic Prospects Report 2006. The new extended version of the model will be calibrated to the recent GMig2 extension of the GTAP 8.1 database, which contains the latest available model-consistent estimates of bilateral migration stocks, labor earnings and remittance flows at GTAP 8.1 regional aggregation level as described in Walmsley et al (2013). The construction of a dynamic baseline up to 2030 under the assumption of no changes in the stance of international migration policies will be based on the latest World Bank global economic projections including UNDESA population and labour force growth projections. As the latter already contain assumptions about the evolution of migration flows over the simulation horizon, it is important to back out these assumptions at the dynamic model calibration stage to arrive at a methodologically clean separation of changes in migration implicitly built into the baseline and changes in migration due to deviations from the baseline migration policy path. Attention to this important detail appears to have been neglected in respective previous modelling work. The existing CGE studies capture remittance effects and direct wage effects on origin countries, but largely ignore other sending country impact channels identified in the literature. These channels include in particular potential productivity impacts associated with return migration and potential brain gain effects arising from incentives to invest in human capital formation in the presence of expected future migration opportunities. As Kerr and Kerr (2011) emphasize, proper accounting for return migration is essential for determining the economic impacts for both origin and host countries, given the available evidence on the extent of return migration from the main host regions and existing empirical estimates of possible associated benefits for the home country (e.g. Mayr and Peri, 2008; Dustmann and Weiss, 2007, De Vreyer, Gubert and Robilliard, 2010). With respect to brain gain effects, recent econometric evidence seems to point to a “robust, positive and sizeable effect of skilled migration prospects on human capital formation in developing countries” (Beine, Docquier and Rapoport, 2010; see Docquier and Rapoport, 2012 for qualifications). The present study aims to incorporate these additional impact channels in a stylized form. In each case, the calibration of the respective new model parameters that govern the size orders of these effects will be based on a review of the pertinent recent empirical literature, so that the model-based simulation results can credibly inform ongoing controversial debates about the relative importance of these impact channels. Back-of-the-envelope calculations as well as previous model-based simulation studies suggest that the potential net benefits from reducing barriers to international labor mobility are large. As Clemens (2011) has put it, “(r)esearch on this question has been distinguished by its rarity and obscurity, but the few estimates we have should make economists’ jaws hit their desks”., as these benefits “may be much larger than those available through any other shift in a single class of global economic policy”. We do not expect that our new results - which will be based on more recent and better data and incorporates a wider range of impact channels – will overturn this broad conclusion. However, the attention to factors that could qualify the development impact of migration, such as the cost of remittances, will help marry the literature on the overall gains of migration to specific interventions.
    Keywords: Global, Developing countries, General equilibrium modeling
    Date: 2015–07–01
    URL: http://d.repec.org/n?u=RePEc:ekd:008007:8503&r=cmp
  5. By: João Silvestre
    Abstract: Sovereign default contagion in Eurozone has been under attention since the first problems in Greece at the end of 2009. Despite the improvements in the situation, in particular after several European Central Bank non- conventional monetary policy measures, the roots of the problem and policy prescriptions are still fiercely debated today. Using an agent-based model adapted from Tirole (2015), we simulate sovereign default contagion in a world where countries have random incomes, heterogeneous borrowing behaviors and risk aversion levels and where governments have the possibility to enter in ex-ante agreements to protect against default. We conclude that default contagion can be a very fast and ‘destructive’ process, higher spending countries tend to have lower disposable incomes and higher risk aversion levels are associated with lower default rates.
    JEL: C63 E62 G01
    Date: 2017–03
    URL: http://d.repec.org/n?u=RePEc:ise:isegwp:wp082017&r=cmp
  6. By: Boby Chaitanya Villari (Indian Institute of Management Kozhikode); Mohammed Shahid Abdulla (Indian Institute of Management Kozhikode)
    Abstract: Portfolio Selection Problem (PSP) is actively discussed in financial research. The choice of available assets poses the need for exploration and the objective to maximize the portfolio payoffs makes the PCP an explore-exploit decision-making problem. Multi-armed bandit algorithms (MAB) suit well for such problems when applied as the decision engines in Naïve Bandit Portfolio algorithms (NBP). An NBP’s performance varies by varying the MAB inside the algorithm. In this work we test a Stochastic Multi-Armed Bandit (SMAB) named effSAMWMIX, which we proposed in a previous work of ours, to solve the PSP. We compare the performance of effSAMWMIX vis-à-vis KL-UCB,Thompson Sampling algorithm and the benchmark Market Buy & Hold strategy. We tested the algorithms on simulated and real-world market datasets. We report our results where effSAMWMIX, applied as the decision-making engine of NBP, has achieved better cumulative wealth for all portfolios when compared to the competing SMAB algorithms.
    Keywords: Portfolio Selection Problem, Multi-Armed Bandit, Geometric Brownian Motion.
    Date: 2017–01
    URL: http://d.repec.org/n?u=RePEc:iik:wpaper:219&r=cmp
  7. By: Tesfatsion, Leigh
    Abstract: Real-world economies are open-ended dynamic systems consisting of heterogeneous interacting participants. Human participants are decision-makers who strategically take into account the past actions and potential future actions of other participants. All participants are forced to be locally constructive, meaning their actions at any given time must be based on their local states; and participant actions at any given time affect future local states. Taken together, these properties imply real-world economies are locally-constructive sequential games. This study discusses a modeling approach, agent-based computational economics (ACE), that permits researchers to study economic systems from this point of view. ACE modeling principles and objectives are first concisely presented. The remainder of the study then highlights challenging issues and edgier explorations that ACE researchers are currently pursuing.
    Date: 2017–03–08
    URL: http://d.repec.org/n?u=RePEc:isu:genstf:201703080800001022&r=cmp
  8. By: Giovanni Cerulli; Federico Cecconi; Maria Augusta Miceli; Pierpaolo Angelini; Bianca Potì
    Abstract: R&Dsimulab is a micro-policy simulator for an ex-ante assessment of public Research & Development (R&D) policy effect on companies’ R&D activity. It is an agent-based computational model based on the interaction between a public agency, entitled to manage a direct (or grant-based) R&D policy, and a given set of companies eligible for receiving a monetary support to increase their actual level of R&D activity. On the part of policymakers, such model can be used to build and compare ex-ante evaluation scenarios related to alternative policies aimed at fostering the R&D activity of companies undergoing a given public R&D support. R&Dsimulab can be run either using a pre-defined set of parameters, thus exploring outcomes’ sensitivity to parameters’ changes, or by a calibration based on empirical evidence. R&Dsimulab assumes that agents (the public agency and the companies) maximize an objective function under reasonable constraints, and assumes that companies doing R&D are placed within a network of firms where possible positive or negative externality effects can arise. To our knowledge, no previous models of this type have been proposed so far in the literature. Therefore, R&Dsimulab constitutes a first attempt to build a policy simulator for an ex-ante assessment of R&D policy effects, whose scientific and policy-oriented scope can be worth exploring. R&Dsimulab is an agent-based simulative model. The agents constituting the model are: one public agency, which provides public funds to support private R&D companies, and a set of eligible-for-fund private companies. Both types of agents take decisions by maximizing an objective function under reasonable constraints. In particular, the model run under these assumptions: a.Agency behaviour It is assumed that the direct objective of the public agency is that of maximizing the total level of R&D (i.e., the sum of all companies’ R&D spending, that we indicate by R) using a given amount of monetary support S which has to be optimally allocated within firms. The agency knows the company ability to do R&D and its centrality within the network, but it has only an imperfect knowledge of all firms’ R&D network relationships. As objective, the agency wants to determine two things: (i) which companies are worth to support and which are not (i.e., selection-process); (ii) which share of S has the agency to provide to each firm selected for support. Thus, the agency comes up with two optimal solutions: (i) the N1 (out of N) selected companies; the optimal allocation of the subsidy S within the N1 selected companies. b. Companies’ behaviour Companies choose the level of R that maximizes the profit. Thus, the optimal R is the one equalizing the marginal rate of return and the marginal capital cost of doing R&D. The optimal level of R&D is in turn a function of the R&D support that a firm might potentially receive. We assume that each company owns an optimal level of the subsidy, thus making the R&D optimal equation as a concave function of the public support (a parabola, for instance). Finally, we also assume that R&D spillovers among firms may take place, due to companies’ relationships within an R&D Network, where the R&D flows from one company to another according to the strength of the relationship between firms. Therefore, each company R&D includes both an idiosyncratic component and an “additional” component due to the presence of R&D externalities. c. Externality or network effect As companies are located within an R&D network, different network topologies can produce different policy effects. The network impacts on R in two ways: (i) on the one hand, the more a company is central in the network, the more a lower barrier to do R&D is assumed (thus reducing the fixed costs of doing R&D); (ii) on the other hand, different network topologies could provide different R&D performance. Therefore, running a series of simulations under different policy scenarios can provide some guidance to detect the emerging properties in the R&D effect’s pattern, especially when one considers specific model’s parameterizations. R&Dsimulab uses Monte Carlo methods to provide sound conclusions about simulation results. Are specific configurations of the network more likely to produce larger R&D effect than other types of settings? In order to answer questions like this, we run a number of R&Dsimulab simulation exercises. For example, one could be interested in identifying whether, ceteris paribus, a quasi-random network is or is not more conducive to higher levels of R&D than, for instance, networks characterized by the emergence of specific nodes playing as hubs. It may thus be interesting to assess whether the policy effect on R will show an increasing or decreasing pattern as a function of the network’s “hubness”. Other experiments could also include the assessment of policy effect when other significant network parameters are changed or when one considers different network topologies, such as “scale-free” or “small-world” networks. Moreover, once a measure of the actual companies’ network is available and an empirical calibration of the model’s parameters achieved, one may also provide an assessment of the impact of the R&D support policy on a real study context, thus using R&Dsimulab as a tool for an effective ex-ante evaluation of the R&D policy considered.
    Keywords: Italy, Agent-based modeling, Agent-based modeling
    Date: 2015–07–01
    URL: http://d.repec.org/n?u=RePEc:ekd:008007:8631&r=cmp
  9. By: Boby Chaitanya Villari (Indian Institute of Management Kozhikode); Mohammed Shahid Abdulla (Indian Institute of Management Kozhikode)
    Abstract: Machine Learning algorithms play an active role in modern day business activities and have been put to an extensive use in the marketing domain as well. In Ecommerce domain, these algorithms play an important role in suggesting recommendations to users, be it a merchandise of interest to the user or a news article for a website visitor. Due to the larger variety of available information and multiplicity in the merchandise based data, these personalized recommendations play a major role in the successful business activity that could be a sale in the case of an Ecommerce website or a click on a news article in case of a news website. The personalized recommendation problem, where the challenge is to choose from a set of available choices to cater to a target user group, can be modelled as a Contextual Multi-Armed Bandit problem. In this work we propose Ctx-effSAMWMIX which is based on LinUCB and effSAMWMIX algorithms. We empirically test the proposed algorithm on Yahoo! Frontpage R6B dataset by using an unbiased offline evaluation technique proposed in literature. The performance is measured on Click Through Rate (CTR) which effectively reports the ratio of Clicks the recommended articles obtained to that of total recommendations. We compare the performance of Ctx-effSAMWMIX with LinUCB and a random selection algorithm and also report the results of t tests performed on the mean CTRs.
    Keywords: Contextual Multi-Armed Bandit, Unbiased offline evaluation, personalized recommendations
    Date: 2017
    URL: http://d.repec.org/n?u=RePEc:iik:wpaper:224&r=cmp
  10. By: Leonardo dos Santos Pinheiro; Flavio Codeco COelho
    Abstract: This work develops an agent-based model for the study of how the leverage through the use of repurchase agreements can function as a mechanism for the propagation and amplification of financial shocks in a financial system. Based on the analysis of financial intermediaries in the repo and interbank lending markets during the 2007-08 financial crisis we develop a model that can be used to simulate the dynamics of financial contagion.
    Date: 2017–03
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1703.07513&r=cmp
  11. By: Alan John Maniamkot (Indian Institute of Technology Bombay); P N Ram Kumar (Indian Institute of Management Kozhikode); R Sridharan (National Institute of Technology Calicut)
    Abstract: Convoy movement problem is the problem of routing and scheduling military convoys across a limited route network while satisfying some strategic constraints. The problem bears lot of similarities with other real-life applications such as scheduling passenger and freight trains along a single line network, scheduling aircraft landings on runways, routing of automated guided vehicles in a FMS environment, handling baggage along a common automated conveyer belt system, to name a few. Being a proven NP–complete problem, this problem warrants the usage of meta-heuristics to obtain quick solutions. This work focuses on the development of a hybridized ant colony algorithm that combines local search with ant colony optimization to solve the problem. By testing the methodology on a wide range of hypothetical problem instances, we establish the efficacy and practical relevance of the proposed approach. The importance of using a good seed solution for initializing the trail intensities is analyzed and found that it leads to quicker convergence of the algorithm. The need to hybridize the ant colony algorithm with a local search procedure for obtaining superior results is also demonstrated.
    Keywords: Military convoys; Ant colony; local search; hybridization; conflicts; metaheuristics.
    Date: 2016–10
    URL: http://d.repec.org/n?u=RePEc:iik:wpaper:207&r=cmp
  12. By: Maggi,Elena; Vallino,Elena (University of Turin)
    Abstract: In this paper we present an agent-based model which reproduces transport choices of a sample of 5,000 citizens of the city of Varese (Northern Italy) and the corresponding PM emissions of their daily commutes. The aim of the model is testing the impact of public policies willing to foster commuting choices with lower PM emissions. Our model, taking inspiration from other existing works, considers the commuters‘ decisions on the transport mode to be used. A set of preferences, one for each transport mode - private car, bicycle, public transport - is assigned to every agent. Throughout the process, agents decide about the means for commuting on the basis of the relative price of the different means of transport, of the social influence and of the intensity of the policies applied. The initial distribution of preferences for each transport mode are inspired to empirical data on Varese commuters. Results suggest that preference-based policies are more effective if compared to price-based ones. However, the application of a mix of different policies seems to give the best outputs: the same amount of resources in terms of policy intensity produce much better results if they are allocated at the same time to two policies, then to one only.
    Date: 2017–03
    URL: http://d.repec.org/n?u=RePEc:uto:dipeco:201708&r=cmp
  13. By: Judith Kabajulizi; Judith Kabajulizi; Mthuli Ncube
    Abstract: The HIV pandemic, even though it is still a major killer in Africa, seems to have been tamed medically into a chronic disease through advances in treatment drugs (ARTs). However, the full economic costs, over a lifecycle horizon, of keeping people on treatment and implementing prevention measures, are still not fully quantified and are unfolding. Indeed, the economic effects of the HIV/AIDS disease, and also the economic effects of various interventions, also need to be better understood. Sub-Saharan Africa (SSA) disproportionately bears the burden of HIV/AIDS compared to the rest of the word. Over 70% of the people living with HIV (PLWHIV) are resident in SSA, of which 82% are adults. It is evident that the productive segment of the population is afflicted by the devastating health effects of the pandemic. The economic impact of AIDS is felt at all levels of economic analysis: micro, meso and macro. At the micro level, the household experiences increased costs of healthcare expenditure. Additionally the household faces indirect costs of reduced earnings and income when the productive household members are infected. At the meso level, sectors that are labour intensive are faced with low labour productivity. The increased demand for healthcare implies that health sector incurs higher budget allocations, which may necessitate a reduction of the budgets of other government functions. At the macro level, there is loss in economy-wide productivity due to increased absenteeism of sufferers and carers of sick people. Increased mortality from AIDS leads to a reduction in total labour force supply. There is a change in the skill composition of the labour force if AIDS affects one category of skilled labour relatively more. And finally, aggregate savings decline as a result of households resorting to assets and savings for immediate health expenditures, and the reduced capacity to earn income. The advances made in treatment of HIV/AIDS since the advent of anti-retroviral therapies (ART) in 1996 have meant that people can live longer while on treatment. Ultimately HIV/AIDS has become a chronic ailment that continuously draws resources from the health system. The commitment by governments to avail ART to those who need it constitutes a long-term financial liability which can be conceptualised as a debt liability. The dilemma for SSA countries is that they continue to grapple with the challenge of finding adequate resources to finance their health systems and yet also have to increase expenditure for HIV interventions. In exploring the “moral duty of rescue” for PLWHIV, Collier, Sterck and Manning (2015) conclude that funding HIV interventions spans beyond the infected person and the governments of the affected countries, especially for resource poor countries. On the other hand, it is also evident that donor funding for HIV has been gradually dwindling and its sustainability is not certain. The purpose of this paper is to model the economy-wide impact of HIV/AIDS taking into account various modes of funding HIV/AIDS interventions for selected SSA countries. This study extends the previous CGE methodologies by incorporating updating equations that emphasize the cost impact channel of HIV/AIDS interventions. Specifically, given the long term debt liability feature of HIV interventions, the impact on the countries’ debt burden is explicitly modelled, in addition to the impact on growth rate in GDP, investment, private consumption and the trade account. The study countries are purposefully selected to fulfil one of three criteria. A country with high prevalence rates of HIV and (i) resource rich – Botswana, currently resource poor but with prospects of future natural resource exploitation - Uganda, and (iii) currently resource poor and no prospects of future natural resources exploitation -Malawi. We explore different ways of funding the HIV interventions including government capital expenditure, foreign grants, tax financing, domestic borrowing, and foreign borrowing including financial innovations such as diaspora bonds and future-flows securitisation, among others. We use a recursive dynamic model in order to capture the lagged effects of HIV/AIDS-related health effects and the HIV intervention investments over time. It is an adaption of the “core” version of the Maquette for MDG Simulations (MAMS) model developed by the Word Bank group and documented in (Lofgren, Cicowiez, & Diaz-Bonilla, 2013). Technically the model is comprised of a static (within-period) equilibrium solution where producers maximise profit and consumers maximise utility in a given set of institutional constraints, and a dynamic (between-period) equilibrium solution. For the dynamic component, exogenous variables are updated to reflect changes in HIV/AIDS induced population and labour supply growth rates, capital accumulation and total factor productivity growth changes. Additionally, the HIV related government expenditure patterns and sources of funding are updated over the model period. The dynamic module captures the tracking of assets and liabilities of the households and the government, a feature that makes it suitable to predict the impact of HIV intervention cost on debt sustainability. Model solutions are analysed and presented as comparative growth rates over the model horizon. The impact of HIV/AIDS –with no intervention is contrasted with the baseline results. Similarly the impact of HIV/ AIDS-with intervention and different sources of financing the cost of intervention is contrasted with the baseline. Results present the baseline growth path and deviations from the baseline caused by changes in exogenous variables, holding other factors constant. Specifically each country results will show the impact on growth rates in GDP, and as a share of GDP, growth in consumption (private and government), investment (private and government), exports and imports, domestic and foreign debt. At the intermediate level, sectoral growth rates and sector shares are reported. The mechanisms of adjustment: exchange rate dynamics, interest rate payments (domestic and foreign), and factor income changes are explicitly captured and reported.
    Keywords: Malawi, Uganda, Botswana, General equilibrium modeling, Developing countries
    Date: 2015–07–01
    URL: http://d.repec.org/n?u=RePEc:ekd:008007:8563&r=cmp
  14. By: Carlos Sáenz-Royo (LEE and Department of Economics, Universitat Jaume I, Castellón, Spain)
    Abstract: This study meditates about mental heuristic rules as a representation of bounded rationality in individual decision making. The heuristic process presented here represents simultaneously limited computational capacity, the capacity to determine relevant information in complex contexts around beliefs, and time as an endogenous part of decision. The mathematical model of this heuristic rule correlates to the fallibility of the agent depending on the relative outcome of the alternatives in exogenous terms; the availability of only part of the information regarding the alternatives concert by beliefs; and the amount of time the decision maker is willing to spend on a decision based on previous experience and knowing that there is a tradeoff between time and fallibility. The resulting mathematical model can be applied to many disciplines like such as opinion models, game theory, the comparison of systems of distribution of authority, and fields that utilize the technique of agent-based models (ABM) that use individual behavior to study the macroscopic results of interactions.
    Keywords: Bounded rationality, individual decisions making, heuristic, fallibility, modelling decisions, ABM.
    JEL: A14 C00 D03 Z13
    Date: 2017
    URL: http://d.repec.org/n?u=RePEc:jau:wpaper:2017/04&r=cmp
  15. By: Kausik Gangopadhyay (Indian Institute of Management, Kozhikode); Kousik Guhathakurta (Indian Institute of Management, Kozhikode)
    Abstract: The housing asset bubble and mortgage crisis of 2007-08 in the US market poses a challenge to understanding of market and hypotheses related to market efficiency. The contribution of our paper is bifold. First, we present a survey of the existing literature which explains the housing asset bubble. We have emphasized on agent based modeling approaches in this context. The second part of the paper frames an economic model to demonstrate the power of irrational “exuberance hypothesis”, a term coined by Robert J Shiller. Using a felicity function based framework, this shows that the power of irrational expectation in bringing about an artificial and unintended boost in demand for investment of housing asset.
    URL: http://d.repec.org/n?u=RePEc:iik:wpaper:129&r=cmp
  16. By: Pascal Seppecher (CEPN - Centre d'Economie de l'Université Paris Nord - Université Paris 13 - USPC - Université Sorbonne Paris Cité - CNRS - Centre National de la Recherche Scientifique); Isabelle Salle (Utrecht School of Economics - Utrecht University [Utrecht]); Marc Lavoie (CEPN - Centre d'Economie de l'Université Paris Nord - Université Paris 13 - USPC - Université Sorbonne Paris Cité - CNRS - Centre National de la Recherche Scientifique)
    Abstract: This paper studies coordination between firms in a multi-sectoral macroeconomic model with endogenous business cycles. Firms are both in competition and interdependent, and set their prices with a markup over unit costs. Markups are heterogeneous and evolve under market pressure. We observe a systematic coordination within firms in each sector, and between each sector. The resulting pattern of relative prices are consistent with the labor theory of value. Those emerging features are robust to technology shocks.
    Keywords: General interdependence, Pricing, Agent-based modeling
    Date: 2017–03–10
    URL: http://d.repec.org/n?u=RePEc:hal:cepnwp:hal-01486597&r=cmp
  17. By: Khalid Siddig
    Abstract: Many countries in the developing world lack the required capacities and data to provide evidence-based policymaking. As a consequence, they apply a trial-and-error approach to their exchange rate, trade and domestic tax policies, among others. Some countries base their policies on the experiences of other countries that are not necessarily similar in terms of economic structure, sectoral linkages and trade openness. This could be partially justified as well by the difficulty of basing economic policies on researched evidence due to the forward and backward linkages that prevail in any economy, which necessitates ex post and ex ante policy impact analysis on the entirety of economic actors. This reality was recognized during the 1960s by researchers and Johansen (1960) was the first to envisage a solution for it in the form of what is currently known as Computable General Equilibrium (CGE) models. A CGE model is a mathematical representation of the economic actors (production activities, commodities and institutions, including foreign countries) that depict the entire economic structure of a regional entity (country, state, village etc.) in a specific period, usually one year, and using a dataset with the entire body of economic transactions among them. The data set includes a Social Accounting Matrix (SAM) in addition to various parameter values. Johansen’s CGE model was developed to assess the impact of economic policies in Norway and since then this method has developed rapidly and contributing significantly to the policy making process not only in the developed world, but also in developing countries. The importance of CGE models rests on their ability to provide economy-wide impact assessments with huge flexibility in capturing a detailed representation of the economy depending on the availability of data. Despite its reliance on the detailed dataset, CGE models are applied to many countries, including those with relatively poor records of economic data. Due to their complex mathematical representation and their detailed data requirement, CGE models have made significant use of recent advancements in processor speed and storage capacity, and are now not only static but also dynamic and part of integrated systems in which they source inputs from and deliver output to various types of models such as crop, biophysical and climate models. The possibility of linking them to other models means their use is not only confined to economics, but can also be applied to various economic aspects of physics, environmental sciences, engineering and medicine, among other disciplines. Despite the widespread use of CGE models, no comprehensive review of their applications to the different geographical regions of the world, the different types of problems they contributed to and the different disciplines they addressed is available. This kind of review is expected to show their usefulness and identify the regions, themes and disciplines that lack their applications and, hence, to direct future research. These are the main objectives of this current study. This study starts by exploring the history of CGE models, including the intensity of their applications worldwide and the areas of research in which they have been applied through the time, with a special focus on the period between 1980 and 2014. The study also explores classifying CGE applications by the kind of services they have provided to advice policymaking, especially in developing countries. A comprehensive review of the CGE literature based on research included in the Scopus database (Scopus is a bibliographic database that contains abstracts and citations for academic journal articles, books, chapters and other research work. It comprises 53 million records, 21,915 titles from 5000 publishers and it belongs to Elsevier. For more details, visit: http://www.elsevier.com/online-tools/scopus) showed more than a thousand (The results of the search showed 1027 studies of which 854 are published as journal articles, 65 as conference proceedings, 15 as book chapters, 14 as review articles and 4 as books.) of CGE-based studies were conducted during the period between 1980 and 2014. Although this search does not reflect the entirety of CGE publication in the last three decades and a half, it provides rough indications about the importance of such a method and its contribution to policy analysis and the policymaking process globally. CGE applications began, and flourished, in the developed world, led by the United States (USA) and Europe. Early CGE models applied to the USA were designed to address policy issues such as public finance, international trade and environmental policy (Devarajan and Robinson, 2013a). Their applications to developing countries, although not as numerous as those of the developed world three decades ago, also started to appear during the eighties, and various applications have followed during the last three decades. The study reviewed the entire Scopus CGE literature and classified it according to geography, disciplines and model types. Due the research focus of the author in his own empirical work, the study chose to select four countries to provide deep assessments of CGE applications and identify areas for future research using CGE models. The selected countries are Palestine, Israel, the Sudan and Nigeria. All the CGE applications to these countries are reviewed, and their areas of applications and the type of problems they addressed have been identified. Major conclusions are that CGE applications to any of these countries are mostly concentrated on specific areas of research and specific types of problems. CGE applications to Palestine, for instance, are mainly focused on assessing the impact of Intifada and exploring policy options for Palestine away from the settings provided by the Paris protocol. CGE applications to Nigeria mainly address issues related to oil prices and government spending. This concentration is not a negative aspect in general, because research is usually motivated by the prevailing policy problems in the particular country. However, in some countries it seems that CGE applications are determined by the area of research given in the first study applied to the country. Researchers may recognize the usefulness of CGE models in addressing certain type of problems in their country and continue pursuing similar research without exploring other areas in which CGE models could be useful, such as addressing labor movement in Palestine or the environmental problems caused by the continuous sabotaging of oil pipelines in Nigeria.
    Keywords: Global + Palestine, Israel, the Sudan and Nigeria, General equilibrium modeling, Impact and scenario analysis
    Date: 2015–07–01
    URL: http://d.repec.org/n?u=RePEc:ekd:008007:8528&r=cmp
  18. By: Stergios Athanasoglou (University of Milan - Bicocca and CMCC); Valentina Bosetti (Bocconi University and FEEM); Laurent Drouet (FEEM and CMCC)
    Abstract: We propose a novel framework for the economic assessment of climate-change policy. Our main point of departure from existing work is the adoption of a "satisficing", as opposed to optimizing, modeling approach. Along these lines, we place primary emphasis on the extent to which different policies meet a set of goals at a specific future date instead of their performance vis-à-vis some intertemporal objective function. Consistent to the nature of climate-change policy making, our model takes explicit account of model uncertainty. To this end, the value function we propose is an analogue of the well-known success-probability criterion adapted to settings characterized by model uncertainty. We apply this decision criterion to probability distributions constructed by Drouet et al. (2015) linking carbon budgets to future consumption. The main result that emerges is the superiority of "medium" carbon budgets in line with a 3°C target (i.e., 2000-3000 GtCO2) in preventing large future consumption losses with high probability. Insights from computational geometry facilitate computations considerably, and allow for the efficient application of the model in high-dimensional settings.
    Keywords: Satisficing, Model Uncertainty, Climate Change, Computational Geometry
    JEL: C60 D81 Q42 Q48
    Date: 2017–03
    URL: http://d.repec.org/n?u=RePEc:fem:femwpa:2017.13&r=cmp
  19. By: Jan Brockhaus; Jan Brockhaus; Matthias Kalkuhl
    Abstract: This study develops a new method to empirically verify the competitive storage model and investigate the determinants of private carry-over grain stocks within a reduced-form approach. Storage is an important instrument for stabilizing food supply. Yet, analysis of carry-over grain stocks is usually done by two methodological approaches: Equilibrium modeling and comparison of price characteristics or econometric analysis. This paper develops a new way to analyze private grain storage combining both approaches. Based on the canonical competitive storage model we derive a reduced-form storage equation for grain stocks in an open economy based on domestic and global supply and income. This approximation allows characterizing grain stocking by a piece-wise linear function for a broad set of parameters and model assumptions. The results provide for the first time a direct confirmation of the competitive storage model based on observed stock data. Furthermore, the results may be used to analyze private-public storage interactions as well as to offer a more simple reduced-form storage modelling approach which is theoretically well-founded and based on rational expectations.The competitive storage model is used to analyze the dependency of carry-over stocks on the different input parameters. The model specification follows Gouel (2011) and Gouel and Jean (2012) but differs in explicitly including the rest of the world (RoW) as a second country, in including income shocks and excluding public stocks. Stockholders and producers are risk-neutral and profit maximizing, act competitively and have rational expectations. Competitive trade occurs until there are no more possibilities for spatial arbitrage; consumption is isoelastic. The model is calibrated for a broad set of parameters, namely the interest rate, the relative country size, the standard deviation of supply shocks, the demand and the supply elasticities. For all these variables, three different values have been used and the model is solved on a 9x9x9 grid of the state variables, namely the supply and the income shock in the country as well as the supply in RoW. This gives 3^5⋅9^3=177,147 observations in total. The simulations are conducted in Matlab and to solve the model, the CompEcon toolbox (Fackler and Miranda, 2011) and the RECS solver (Gouel, 2013b) are used. Then, a reduced form storage equation is derived, first for a simplified and then for the full model specification. After providing a qualitative explanation of this non-linear reduced form storage rule approximation, this rule is verified with the help of the simulation results. A two-step procedure is applied here. In the first step, it is shown that for each set of parameters individually, the reduced-form model is able to approximate simulated stock levels dependent on the state variables. In the second step it is tested whether the dependence on the different parameters (interest rate, elasticities …) can be captured by linear combinations of structural parameters. The model is found to be well-specified and the reduced form storage equation to be a good approximation of the stocks which results from solving the partial equilibrium model. While almost all parameters are both highly significant and relevant in terms of effect size, the interest rate is the only parameter which is consistently insignificant (considering that all parameters appear a few times in the reduced form storage equation). Finally, the reduced-form model is applied to empirical stock data for 63 countries using a non-linear least-square panel regression. USDA and FAO GIEWS data for stocks, production and demand from 1990 to 2013 for maize, rice, wheat, soy, and sorghum are used. GDP per capita is obtained from the World Bank and used to approximate income shocks. The Hodrick-Prescott filter is used for de-trending as well as for calculating supply shocks. Dividing stock and production data by the consumption trends gives stationary data. Two regression models are used for the empirical estimation. Both include country- and crop-specific mean stocks to account for unobserved heterogeneity resulting in a fixed-effect-like non-linear panel regression. One regression model controls for country-specific characteristics and heterogeneous response to state variables, the other assumes a homogenous response to state variables and uses therefore less parameters and interaction terms. Both models support the hypothesis that real-world stock data can be well explained by the competitive storage model and the considered reduced-form approximation. The aim of this study was to reconcile the complexity of the competitive storage model which lacks a closed-form solution with econometric modeling of agricultural fundamentals that is often used in applied and policy-related research. The resulting non-linear reduced-form model turned out to be both precise and flexible when applied to data generated by the competitive storage model. The basic qualitative behavior is as follows: Ending stocks are zero if domestic and global supplies are below a threshold which depends on GDP shocks and production in RoW. Above this threshold, stocks are piece-wise linear and increase with supply levels. The slope depends on the structural model parameters. The coefficients from the empirical estimation are largely in line with the expectations from the theoretical model. Structural characteristics of countries and crops, however, seem to have only a small impact on threshold levels and slopes. Three results are of direct policy relevance: First, operational stocks are on average roughly 11 percent of domestic consumption, implying that stock-to-use ratios have to be subtracted by 11 percentage points to yield the amount of stocks that are actually available for consumption smoothing. Second, domestic stocks respond strongly to the international supply situation which indicates a high degree of market integration. This underlines the need for multinational agreements and regulations about how to deal with supply shocks in individual countries as well as on the global level. Third, GDP shocks are important in the theoretical model but insignificant in the empirical validation. This might indicate that stockholders do not perform well in anticipating future demand. As a result, private storage levels might not be optimal providing a rational for interventions and information system might need to focus also on demand side factors rather than only on the supply side.
    Keywords: 63 countries in total, including US, India, China and others., Agricultural issues, Microsimulation models
    Date: 2015–07–01
    URL: http://d.repec.org/n?u=RePEc:ekd:008007:8430&r=cmp

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