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on Computational Economics |
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Issue of 2016‒06‒04
fourteen papers chosen by |
| By: | Joachim Merz; Lars Rusch (LEUPHANA University Lüneburg,Department of Economic, Behaviour and Law Sciences, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB))) |
| Abstract: | Microsimulation models allow targeted simulations to analyze the impacts of alternative policies, measures, scenarios based on microunits like persons, families, households, firms etc. Meanwhile it is out of question that microsimulation models are a helpful, successful and an imperative instrument for a wide range of policy analyses in the political administration, business area, private and university institutes and consulting groups in general. Though there is a multitude of microsimulation models nowadays developed and in use, however, in most cases they still need skilled handling and experience or another program system when applied. A general, generic stand-alone and platform independent microsimulation model which provides all necessary simulation tools under a common shield, and which is easy to use for non-expert scholars, is still required. The overall objective of this paper and of the new MICSIM-4J is to describe and offer such a userfriendly, non-technical and powerful general microsimulation model, to support impact microanalyses for applied research, teaching and consulting. Though the stand-alone MICSIM-4J as a general tool also allows dynamic model building, its focus is on static microsimulation with a powerful module for the adjustment of microdata. |
| Keywords: | Stand-alone general microsimulation model, impact analysis of economic and social policies, simulation of microdata, static and dynamic aging, microdata adjustment, information theory |
| JEL: | C80 C81 D10 D30 D31 J20 |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:leu:wpaper:100&r=cmp |
| By: | Mahaffey, Harry; Taheripour, Farzad; Tyner, Wallace E. |
| Abstract: | The objective of this research is to assess the global economic and greenhouse gas emission impacts of GMO crops. This is done by modeling two counterfactual scenarios and evaluating them apart and in combination. The first scenario models the impact of a global GMO ban. The second scenario models the impact of increased GMO penetration. The focus is on the price and welfare impacts, and land use change greenhouse gas (GHG) emissions associated with GMO technologies. Much of the prior work on the economic impacts of GMO technology has relied on a combination of partial equilibrium analysis and econometric techniques. However, Computable General Equilibrium (CGE) modelling is a way of analyzing economy-wide impacts that takes into account the linkages in the global economy. Though it has been used in the context of GMO crops, the focus has been on the effects of various trade policies and regulatory regimes. Here the goal is to contribute to the literature on the benefits of GMO technology by estimating the impacts on price, supply and welfare. Food price impacts range from an increase of 0.27% to 2.2%, depending on the region. Total welfare losses associated with loss of GMO technology total up to $9.75 billion. The loss of GMO traits as an intensification technology has not only economic impacts, but also environmental ones. The full environmental analysis of GMO is not undertaken here. Rather we model the land use change owing to the loss of GMO traits and calculate the associated increase in GHG emissions. We predict a substantial increase in GHG emissions if GMO technology is banned. |
| Keywords: | GMO Crops, Productivity, Computable General Equilibrium, Economic Impacts, Land Use Change, Land Use Emissions, Agricultural and Food Policy, |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:235591&r=cmp |
| By: | Giorgio Fagiolo (Laboratory of Economics and Management (LEM)); Andrea Roventini (Laboratory of Economics and Management (Pisa) (LEM)) |
| Abstract: | The Great Recession seems to be a natural experiment for economic analysis, in that it has shown the inadequacy of the predominant theoretical framework | the New Neoclassical Synthesis (NNS) | grounded on the DSGE model. In this paper, we present a critical discussion of the theoretical, empirical and political-economy pitfalls of the DSGE-based approach to policy analysis. We suggest that a more fruitful research avenue should escape the strong theoretical requirements of NNS models (e.g., equilibrium, rationality, representative agent, etc.) and consider the economy as a complex evolving system, i.e. as an ecology populated by heterogeneous agents, whose far-from-equilibrium interactions continuously change the structure of the system. This is indeed the methodological core of agent-based computational economics (ACE), which is presented in this paper. We also discuss how ACE has been applied to policy analysis issues, and we provide a survey of macroeconomic policy applications ( fiscal and monetary policy, bank regulation, labor market structural reforms and climate change interventions). Finally, we conclude by discussing the methodological status of ACE, as well as the problems it raises. |
| Keywords: | Economic policy; New neoclassical synthesis; New keynesian models; Agent based computational economics; Agent based models; Complexity theory; Great recession; Crisis |
| JEL: | B41 B50 E32 E52 |
| Date: | 2016–04 |
| URL: | http://d.repec.org/n?u=RePEc:spo:wpmain:info:hdl:2441/dcditnq6282sbu1u151qe5p7f&r=cmp |
| By: | Holderieath, Jason |
| Abstract: | Species are often viewed as either beneficial or detrimental. The determination of beneficial or detrimental depends on the evaluator, often with disagreement within disciplines such as agriculture or wildlife biology. One common argument against a species revolves around its status as native or non-native, with the latter as a negative characteristic. Defining native and non-native is highly subjective, with a common North American delineation as an introduction before and after Columbus, respectively (Nelson 2010). However, in the past, native species such as the American buffalo (Bison bison) have been targets of eradication campaigns and even today white-tailed deer (Odocoileus virginianus) and Canadian geese (Branta Canadensis) populations are managed to limit the damage they inflict on agriculture. It is also acknowledged that these example species have intrinsic value in the ecosystem and value as a recreationally hunted species in the case of white-tailed deer and Canadian geese. Non-native species can be viewed beneficially, as most agricultural species are introduced, for recreational use, and even as a replacement for extirpated native species (Schlaepfer, Sax and Olden 2011; Zivin, Hueth and Zilberman 2000). In the US, one contentious species is feral swine (Sus scrofa). Federal removal and control efforts are underway as some private landowners encourage their growth on their property (Bevins et al. 2014; Bannerman and Cole 2014). Feral swine are a vector for diseases, cause ecosystem damage, and inflict physical losses to agriculture (Pimentel, Zuniga and Morrison 2005; Cozzens 2010; Seward et al. 2004). However, feral swine are a valuable recreational species. With benefits and costs often accruing to different people, conflict over management is inevitable. As in most externality problems, property lines do not inhibit damage. Unique to most externality problems is the way the damage causing agent can multiply and spread unaided once introduced. Stakeholders include agricultural landowners, recreational landowners, private conservationists, and government entities. Agriculturalists may be sensitive to crop damage and unwilling to sell hunting licenses on their property to offset the damage. Recreational users may enjoy the opportunity to hunt feral swine or may be sensitive to habitat damage and predation of other game species. Private individuals may also own land with the expressed purpose of native habitat conservation. This division between agriculturalist, recreationists, and conservationists is in reality too strong. Landowners are often a mix of the three. Landowners may also exhibit inconsistent preferences or a lack of information, implying a need to relax rationality assumptions. Rational choice theory, or the rationality assumptions, require that a consumer's actions exhibit completeness, transitivity, and perfect information. Finally, government entities are responsible for many goals including preservation of native species, maintenance of protective structures such as levees, and preventing outbreaks of dangerous diseases. These varying objectives can result in inconsistent policymaker actions (Karp et al. 2015). Management decisions by one stakeholder will affect the outcomes of all stakeholders. The variety of opinions and the interaction between landowners, government agencies, and the swine themselves make an optimal policy solution, here defined as the policy solution with the highest total welfare gain, hard to determine. Previous work has ignored interaction between people and swine, spatial issues, temporal characteristics of feral swine spread, or the variety of values held among stakeholders. To address these shortcomings, an agent-based modeling approach is used to determine the optimal management solution, as well as how varying stakeholder opinions and rationality can change the optimal solution. Agent-based modeling promises to be able to model a rich diversity in objectives across time and space (Heckbert, Baynes and Reeson 2010). Applications of agent-based modeling demonstrate its capabilities with interactive heterogeneous agents and spatiotemporally explicit modeling (Evans and Kelley 2004; Schreinemachers et al. 2009; Berger and Troost 2014). Agents can be modeled maintaining traditional compatibility with economic theory (e.g. utility maximizing rational agents), with varying degrees of rationality and awareness of their surroundings, and established tools such as linear programming can be used to help agents make decisions (Berger 2001; Schreinemachers et al. 2009). ABMs have been shown to be suited for analysis of policy intended to address previously unseen events such as the effects of climate change or a new trade agreement (Berger 2001; Berger and Troost 2014). This paper will demonstrate the importance of the interaction between individuals across time and space over management decisions in a way that has not previously been published. Management paths have been established for heterogeneous groups of agriculturalists, recreational land users, private conservationists and governmental entities with varying motivations. The setting for the simulations is a hypothetical rural environment with the potential for feral swine and damage to crops, livestock, and habitat. Results from these simulations are being compared to situations with individuals of heterogeneous preferences. Preliminary results indicate that both locality and individual characteristics matter in determining the optimal outcome. The code for the ABM is being written in a program that provides striking visuals in addition to the quantitative data needed for analysis. These visualizations, the research goals, and the subject matter of feral swine have not failed to generate substantial discussion when presented. The model, properly calibrated, can be used to simulate a potential management area to determine the best path forward. Results of the analysis are expected to inform policymakers to help guide hunting license protocol and public management efforts to manage feral swine in a humane, environmentally sustainable, and socially responsible manner. |
| Keywords: | feral swine, wild pigs, ABM, agent-based modeling, wildlife, Agricultural and Food Policy, Environmental Economics and Policy, Institutional and Behavioral Economics, Land Economics/Use, Q15, Q18, Q59, |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:235850&r=cmp |
| By: | Rafael A. Barrio; Tzipe Govezensky; \'Elfego Ruiz-Guti\'errez; Kimmo K. Kaski |
| Abstract: | We present a simple dynamical model for describing trading interactions between agents in a social network by considering only two dynamical variables, namely money and goods or services, that are assumed conserved over the whole time span of the agents' trading transactions. A key feature of the model is that agent-to-agent transactions are governed by the price in units of money per goods, which is dynamically changing, and by a trust variable, which is related to the trading history of each agent. All agents are able to sell or buy, and the decision to do either has to do with the level of trust the buyer has in the seller, the price of the goods and the amount of money and goods at the disposal of the buyer. Here we show the results of extensive numerical calculations under various initial conditions in a random network of agents and compare the results with the available related data. In most cases the agreement between the model results and real data turns out to be fairly good, which allow us to draw some general conclusions as how different trading strategies could affect the distribution of wealth in different kinds of societies. |
| Date: | 2016–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1605.08899&r=cmp |
| By: | Marquez Alcala, German A. |
| Abstract: | The undocumented migration of Mexican nationals to the U.S. is largely influenced by the availability of labor demand in unskilled sectors in the U.S., making it more efficient than the legal channels of migration available to unskilled Mexican nationals. Labor demand in unskilled industries is larger than the available unskilled labor in the U.S., but Mexican migrants, who constitute the majority share of foreign-born individuals in the U.S., are immigrating at the lowest rates in modern times, with net Mexican migration at approximately zero. This paper simulates a market-based immigration system for Mexican nationals, with a focus on the partial equilibrium effects in long run supply and demand for undocumented Mexican migrant labor in the U.S. agriculture sector. Reducing the additive tax on Mexican wages in the model effectively simulates an immigration policy shift. I estimate the net-of-tax long run labor supply and demand curves for U.S. agriculture, simulating an open-border policy with Mexico. Eliminating the additive tax on Mexican wages (which represents immigration policy reform) increases the quantity of labor used in U.S. agriculture, decreases U.S. agriculture wages for Mexican migrants, and raises Mexican agriculture wages. Since the labor supply curve for Mexican nationals is extremely elastic, the largest benefits of an immigration policy shift go to the U.S. producers, who can use higher labor inputs in production to lower the price of production. The results of the experiments are very similar, even with large differences in the visa pricing scheme chosen; this represents an exciting finding: the demand for access to the U.S. unskilled labor market for Mexican nationals is inelastic, which explains the fact that migrant smuggler costs have increased from approximately $50 in 1990 to upwards of $5,000 in the mid-2010s. |
| Keywords: | Immigration, Migrant Labor, Agricultural Migrant Labor, Mexican Immigration, Undocumented Immigration, Immigration Reform, Low Skill Labor, Agricultural and Food Policy, International Relations/Trade, Labor and Human Capital, Political Economy, |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:236275&r=cmp |
| By: | Krzysztof Domino |
| Abstract: | The cumulant analysis plays an important role in non Gaussian distributed data analysis. The shares' prices returns are good example of such data. The purpose of this research is to develop the cumulant based algorithm and use it to determine eigenvectors that represent "respectively safe" investment portfolios with low variability. Such algorithm is based on the Alternating Least Square method and involves the simultaneous minimisation 2'nd -- 6'th cumulants of the multidimensional random variable (percentage shares' returns of many companies). Then the algorithm was examined for daily shares' returns of companies traded on the Warsaw Stock Exchange. It was shown that the algorithm gives the investment portfolios that are on average better than portfolios achieved by other methods, as well as than the proposed benchmark. Remark that the algorithm of is based on cumulant tensors up to the 6'th order, what is the novel idea. It can be expected that the algorithm would be useful in the financial data analysis on the world wide scale as well as in the analysis of other types of non Gaussian distributed data. |
| Date: | 2016–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1605.09181&r=cmp |
| By: | Bulut, Harun |
| Abstract: | Towards explaining regional differences in U.S. farmers’ crop insurance choices, we propose a budget heuristic effect within the standard Expected Utility Theory (EUT) framework and conduct theoretical and simulation analyses. We also disentangle the effects of various aspects the cumulative prospect theory (CPT) framework in a separate simulation analysis. |
| Keywords: | agricultural (crop and livestock) insurance, cumulative prospect theory, budget heuristics, mental accounting, Agricultural and Food Policy, Agricultural Finance, Crop Production/Industries, Demand and Price Analysis, Farm Management, Institutional and Behavioral Economics, Marketing, Production Economics, Public Economics, Research Methods/ Statistical Methods, Risk and Uncertainty, D81, D82, G22, G28, Q12, Q18, |
| Date: | 2016–05–25 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:236019&r=cmp |
| By: | Luckstead, Jeff; Devadoss, Stephen |
| Abstract: | We develop a model to comprehensively analyze the effects of 2014 Farm Bill wheat policies---loan deficiency payments (LDP), price loss coverage (PLC), agriculture risk coverage-county (ARC-CO), individual revenue protection crop insurance (RP), and supplemental coverage option (SCO)---on input use, yield, certainty equivalent, optimal RP insurance coverage level, expected payments, and premiums. The comparative static results show the directional impact of the coupling, wealth, and insurance effects for each policy. We calibrate the model to a representative dryland wheat farm in Kansas. The simulation results show that the expected LDP payment is zero for 2014, RP causes input use and yield to decline, and ARC-CO, PLC, and SCO result in higher input use and yield. Thus, both the theoretical and empirical results provide evidence of moral hazard associated with RP and SCO insurance. If the farmer selects only RP insurance, then the optimal coverage level is 85%, but drop to 50% if SCO is added. Based on certainty equivalent analysis, the optimal policy combination is RP with ARC-CO. The results also provide evidence that farmers would opt for crop insurance programs even without premium subsidies. |
| Keywords: | Coupling, Wealth, and Insurance Effects, Farm Bill, Moral Hazard, Wheat, Agricultural and Food Policy, Q18, Q12, D24, |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:235362&r=cmp |
| By: | MARCELO DE OLIVEIRA PASSOS; JEAN RODRIGUES VENECIAN |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:anp:en2014:044&r=cmp |
| By: | OBARA, Takuya |
| Abstract: | This paper examines optimal nonlinear income taxes under the provision of a public good when individuals differ in public goods preferences and earning abilities. We suppose two groups whose benefits from public goods are different, and we consider that the government implement the group-specific income tax schedules. Our main argument is that the government redistributive tastes and the correlation of public goods preferences and earning abilities are especially crucial in differentiating marginal income tax rates. In numerical simulations, we present how these factors affect the shape of the optimal differentiated marginal income tax rates in terms of some social welfare functions. |
| Keywords: | Extensive margin, Optimal nonlinear income taxation, Public goods, Tagging |
| JEL: | H20 H41 |
| Date: | 2016–05–17 |
| URL: | http://d.repec.org/n?u=RePEc:hit:ccesdp:64&r=cmp |
| By: | Zhao, Xin; Guolin, Yao; Wallace, Tyner |
| Abstract: | Techno-economic analysis (TEA) is a well-established modeling process in which benefit-cost analysis (BCA) is used to evaluate the economic feasibility of emerging technologies. Most previous TEA studies focused on creating reliable cost estimates but returned deterministic net present values (NPV) and deterministic breakeven prices. Nevertheless, the deterministic results cannot convey the considerable uncertainties embedded in techno-economic variables such as capital investment, conversion technology yield, and output prices. We obtain distributions of NPV, IRR, and breakeven price. The breakeven price is the most important indicator in TEA because it is independent of scale and communicates results effectively. The deterministic breakeven price is the price for which there is a 50 percent probability of earning more or less than the stipulated rate of return. For an investment under relatively high uncertainty, it is unlikely that investors would provide financing to a project with a 50 percent probability of loss. The point estimate breakeven price, therefore, does not represent the threshold under which investment would occur. In this study, we introduce the stochastic techno-economic analysis in which we incorporate Monte Carlo simulation into traditional TEA. A case of cellulosic biofuel production from fast pyrolysis and hydroprocessing pathway is used to illustrate the method of modeling stochastic TEA and quantifying the breakeven price distribution. The input uncertainties are translated to outputs so that the probability density distribution of both NPV and breakeven price are derived. Two methods, a mathematical method and a programming method, are developed to quantify breakeven price distribution in a way that can consider future price trend and uncertainty. We analyze two scenarios, one assuming constant real future output prices, and the other assuming that future prices follow an increasing trend with stochastic disturbances. We demonstrate that the breakeven price distributions derived using our methods are consistent with the corresponding NPV distributions regarding the percentile value and the probability of gain/loss. |
| Keywords: | breakeven price, techno-economic analysis, cellulosic biofuel, Monte-Carlo simulation, Environmental Economics and Policy, Research Methods/ Statistical Methods, Risk and Uncertainty, Q16, D6, D81, C15, |
| Date: | 2016–05–12 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:235215&r=cmp |
| By: | Dennis, Elliott; Schroeder, Ted; Renter, David |
| Abstract: | Bovine respiratory disease complex (BRDC) is one of the costliest ailments in cattle feeding. Often cattle do not manifest symptoms until 15 to 20 days on feed. BRDC causes reduced feeding efficiency, lower average daily gain, and sub packing plant characteristics. A preventative intervention for high risk cattle is metaphylaxis, otherwise known as mass medication. While mass treatment of high risk cattle lowers death loss, net return and return risk impacts of alternative animal health treatment strategies have not been adequately quantified. This studies estimates the net feeding returns under different health strategies and risk category for cattle fed from 1989 to 2008 and 2014 – 2015 comprising over 42,000 observations. Monte Carlo simulations and net return feeding equations were used to develop net return distributions under baseline scenarios. Results suggest that removal of mass medication greatly increases the variation in feeding returns between risk categories. There are clear trade-offs between cattle risk category and health management practice. As public scrutiny of antibiotic use in feedlots continues to grow, a body of research needs to be developed assessing the economic and societal welfare impacts of eliminating arrival metaphylaxis in US feedlots. |
| Keywords: | cattle, Monte Carlo, antibiotic, Bovine Respiratory Disease, net returns, simulation, Demand and Price Analysis, Livestock Production/Industries, Marketing, Risk and Uncertainty, C15, C34, G11, Q11, Q13, |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:236201&r=cmp |
| By: | Singh,Raju; Bodea,Cristina; Higashijima,Masaaki |
| Abstract: | Haiti's economic development has been held back by a history of civil conflict and violence. With donor assistance declining from its exceptional levels following the 2010 earthquake, and concessional financing growing scarce, Haiti must learn to live with tighter budget constraints. At the same time, the United Nations forces that have provided security in the past decade are scaling down. Against this backdrop, this paper explores the conditions under which public spending can minimize violent conflict, and draws possible lessons for Haiti. Drawing on an empirical analysis of 148 countries over the period 1960-2009, simulations for Haiti suggest that increases in military spending would be associated with a higher risk of conflict, an observation in line with Haiti's own history. Greater welfare expenditure (education, health, and social assistance), by contrast, would be associated with lower risk of conflict. |
| Keywords: | Post Conflict Reintegration,Peace&Peacekeeping,Social Conflict and Violence,Post Conflict Reconstruction,Population Policies |
| Date: | 2016–05–23 |
| URL: | http://d.repec.org/n?u=RePEc:wbk:wbrwps:7681&r=cmp |