New Economics Papers
on Computational Economics
Issue of 2013‒06‒24
fifteen papers chosen by

  1. A Spatially Explicit Watershed Scale Optimization of Cellulosic Biofuels Production By Song, Jingyu; Gramig, Benjamin M.
  2. Housing market bubbles and business cycles in an agent-based credit economy By Erlingsson, Einar Jon; Cincotti, Silvano; Stefansson, Hlynur; Sturlusson, Jon Thor; Teglio, Andrea; Raberto, Marco
  3. Modeling the Diffusion of Residential Photovoltaic Systems in Italy: An Agent-based Simulation By Palmer, Johannes; Sorda, Giovanni; Madlener, Reinhard
  4. Modeling a Dynamic Forest Sector in a General Equilibrium Framework By Tian, Xiaohui; Sohngen, Brent; Sands, Ronald
  5. Sequential Monte Carlo Sampling for DSGE Models By Edward P. Herbst; Frank Schorfheide
  6. Optimizing Distance-Based Methods for Big Data Analysis By Tobias Scholl; Thomas Brenner
  7. Household and Intersectoral Effects of Reduced SNAP Expenditures: A Computable General Equilibrium Analysis By West, Tyler T.; Reimer, Jeffrey J.
  8. A cutting surface algorithm for semi-infinite convex programming with an application to moment robust optimization By Sanjay Mehrotra; David Papp
  9. High Food Prices and their Implications for Poverty in Uganda From Demand System Estimation to Simulation By Boysen, Ole
  10. Applying the Wiener-Hopf Monte Carlo simulation technique for Levy processes to path functionals such as first passage times, undershoots and overshoots By Albert Ferreiro-Castilla; Kees van Schaik
  11. Time-Varying Parameters and Endogenous Learning Algorithms By Eric Gaus
  12. Water Scarcity and International Agricultural Trade By Liu, Jing; Hertel, Thomas W.; Taheripour, Farzad; Zhu, Tingju; Ringler, Claudia
  13. Assessing the Efficiency of Alternative Best Management Practices to Reduce Nonpoint Source Pollution in the Broiler Production Region of Louisiana By Gottshall, Bryan; Paudel, Krishna
  14. Emergence of a New Biofuels Market: A Computable General Equilibrium Analysis By Zheng, Xiaojuan; Reimer, Jeff
  15. "Heterodox Shocks" By Greg Hannsgen

  1. By: Song, Jingyu; Gramig, Benjamin M.
    Abstract: As environmental deterioration and global warming arouses more and more attention, identifying cleaner and more environmentally friendly energy sources is of interest to society. In addition to environmental concerns, both the high price of gasoline and the fact that the United States has heavy reliance on imports of energy have driven policymakers to find alternative energy sources. Producing biofuels from energy crops is one such alternative with relatively lower greenhouse gas emissions compared to traditional energy sources. Cellulosic feedstocks such as corn stover, perennial grasses and fast growing trees are regarded as promising energy crops and are expected to help with the energy supply. This study takes a spatially explicit approach to examine fields within a watershed and explores the conditions under which the agricultural land in the watershed can meet the demand of a biorefinery. Costs of two dedicated energy crops, switchgrass and miscanthus, are compared with corn stover. A Matlab program is developed based on a genetic algorithm to minimize production cost subject to biomass production and pollution constraints in the Wildcat Creek Watershed in Indiana, USA. The process of using a genetic algorithm to solve high dimensionality mixed integer optimization problems is discussed. Results indicate that to achieve the required amount of biomass production for a minimum feasible scale thermochemical biorefinery within the watershed, miscanthus must be planted. Miscanthus also helps reduce pollutant levels (total sediment, N and P loadings) when compared to stover removal from continuous corn and corn-soybean rotations. Switchgrass is found to have similar environmental advantages, but is not economically competitive based on preliminary results that require further validation. Corn stover is the lowest cost feedstock considered, however, it results in relatively higher sediment, nitrogen and phosphorus loading than the perennial grasses considered. Relative to the baseline without stover removal, no-till in combination with stover removal results in decreased sediment loading, an increased loading of nitrogen under continuous corn and an increase in phosphorus (except at the 50% removal rate from continuous corn). There is clear tradeoff among cost, production and environmental improvement.
    Keywords: cellulosic biofuels, spatially explicit optimization, genetic algorithm, watershed, water pollution, SWAT, Research and Development/Tech Change/Emerging Technologies, Research Methods/ Statistical Methods, Resource /Energy Economics and Policy,
    Date: 2013
  2. By: Erlingsson, Einar Jon; Cincotti, Silvano; Stefansson, Hlynur; Sturlusson, Jon Thor; Teglio, Andrea; Raberto, Marco
    Abstract: In this paper the authors present an agent-based model of a credit network economy. The artificial economy includes different economic agents that interact using simple behavioral rules through various markets, i.e., the consumption goods market, the labor market, the credit market and the housing market. A set of computational experiments, based on numerical simulations of the model, have been carried out in order to explore the effects of different households' creditworthiness conditions required by the banking system to grant a mortgage. The authors find that easier access to credit inflates housing prices, triggering a short run output expansion, mainly due to the wealth effect. Also, with a more permissive policy towards household mortgages, and thus higher levels of credit, the artificial economy becomes more unstable and prone to recessions usually caused by falling housing prices. Often the authors find that an initial crisis can leave firms in a fragile state. If the situation is not cured, a subsequent crisis can lead to mass bankruptcies of firms with catastrophic effects on the credit sector and on the real economy. With stricter conditions on household mortgages the economy is more stable and does not fall into serious recessions, although a too severe regulation can slow down economic growth. --
    Keywords: Credit cycles,housing market,agent-based model,subprime lending
    JEL: E20 E25 G21 R31 R38
    Date: 2013
  3. By: Palmer, Johannes (RWTH Aachen University); Sorda, Giovanni (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN)); Madlener, Reinhard (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN))
    Abstract: We propose an agent-based model to simulate the diffusion of small PV systems among single- or two-family homes in Italy over the 2006-2026 period. To this end,we explicitly model the geographical distribution of the agents in order to account for regional differences across the country. The adoption decision is assumed to be influenced predominantly by (1) the payback period of the investment, (2) its environmental benefit, (3) the household’s income, and (4) the influence of communication with other agents. For the estimation of the payback period, the model considers investment costs, local irradiation levels, governmental support, earnings from using self-produced electricity vs. buying electricity from the grid, as well as various administrative fees and maintenance costs. The environmental benefit is estimated by a proxy for the CO2 emissions saved. The level of the household income is associated with the specific economic conditions of the region where the agent is located, as well as the agent’s socio-economic group (age group, level of education, household type). Finally, the influence of communication is measured by the number of links with other households that have already adopted a PV system. In each simulation step, the program dynamically updates the social system and the communication network, while the evolution of the PV system’s investment costs depend on a one-factor experience curve model that is based on the exogeneous development of the global installed PV capacity. Our results show that Italy’s domestic PV installations are already beyond an initial stage of rapid growth and, though likely to spread further, they will do so at a significantly slower rate of diffusion.
    Keywords: PV; Technological diffusion; Agent-based modeling; Italy
    Date: 2013–05
  4. By: Tian, Xiaohui; Sohngen, Brent; Sands, Ronald
    Abstract: We develop a dynamic forest sector in a Computable General Equilibrium model. There has been an increasing demand in using general equilibrium models to examine forests' role in climate change mitigation, global land competition and the energy sector. But modeling forestry sector in a general equilibrium context remains an extremely difficult task due to the complex dynamics in forestry management and timer markets. The innovation of this study lies in introducing a land-based and dynamic forest sector and incorporating rational expectations in all the sectors.
    Keywords: CGE, dynamic forest sector, carbon policy, Environmental Economics and Policy, Land Economics/Use,
    Date: 2013–05–31
  5. By: Edward P. Herbst; Frank Schorfheide
    Abstract: We develop a sequential Monte Carlo (SMC) algorithm for estimating Bayesian dynamic stochastic general equilibrium (DSGE) models, wherein a particle approximation to the posterior is built iteratively through tempering the likelihood. Using three examples consisting of an artificial state-space model, the Smets and Wouters (2007) model, and Schmitt-Grohé and Uribe’s (2012) news shock model we show that the SMC algorithm is better suited for multimodal and irregular posterior distributions than the widely-used random walk Metropolis- Hastings algorithm. We find that a more diffuse prior for the Smets and Wouters (2007) model improves its marginal data density and that a slight modification of the prior for the news shock model leads to drastic changes in the posterior inference about the importance of news shocks for fluctuations in hours worked. Unlike standard Markov chain Monte Carlo (MCMC) techniques, the SMC algorithm is well suited for parallel computing.
    JEL: C11 C15 E10
    Date: 2013–06
  6. By: Tobias Scholl (House of Logistics and Mobility (HOLM), Frankfurt and Economic Geography and Location Research, Philipps-University, Marburg); Thomas Brenner (Philipps-Universität Marburg)
    Abstract: Distance-based methods for measuring spatial concentration such as the Duranton-Overman index undergo an increasing popularity in the spatial econometrics community. However, a limiting factor for their usage is their computational complexity since both their memory requirements and running-time are in O(n2). In this paper, we present an algorithm with constant memory requirements and an improved running time, enabling the Duranton-Overman index and related distance-based methods to run big data analysis. Furthermore, we discuss the index by Scholl and Brenner (2012) whose mathematical concept allows an even faster computation for large datasets than the improved algorithm does.
    Keywords: Spatial concentration, Duranton-Overman index, big-data analysis, MAUP, distance-based measures.
    JEL: C40 M13 R12
    Date: 2013–10–06
  7. By: West, Tyler T.; Reimer, Jeffrey J.
    Keywords: Consumer/Household Economics, Food Consumption/Nutrition/Food Safety, Public Economics,
    Date: 2013
  8. By: Sanjay Mehrotra; David Papp
    Abstract: We first present and analyze a central cutting surface algorithm for general semi-infinite convex optimization problems, and use it to develop an algorithm for distributionally robust optimization problems in which the uncertainty set consists of probability distributions with given bounds on their moments. The cutting surface algorithm is also applicable to problems with non-differentiable semi-infinite constraints indexed by an infinite-dimensional index set. Examples comparing the cutting surface algorithm to the central cutting plane algorithm of Kortanek and No demonstrate the potential of the central cutting surface algorithm even in the solution of traditional semi-infinite convex programming problems, whose constraints are differentiable, and are indexed by an index set of low dimension. Our primary motivation for the higher level of generality is to solve distributionally robust optimization problems with moment uncertainty. After the analysis of the cutting surface algorithm, we extend the authors' moment matching scenario generation algorithm to a probabilistic algorithm that finds optimal probability distributions subject to moment constraints. The combination of this distribution optimization method and the cutting surface algorithm yields a solution to a family of distributionally robust optimization problems that are considerably more general than the ones proposed to date.
    Date: 2013–06
  9. By: Boysen, Ole
    Abstract: This paper represents an initial attempt at assessing the importance of estimated demand systems for the simulation of large price shocks with respect to poverty analysis. Using a Ugandan household survey data set and an estimated flexible demand system, three different approaches to simulating the compensated expenditure budget due to large food price shocks are compared: a non-behavioral microaccounting, and three behavioral demand systems (LES, CDE, and QUAIDS). The aim of this study is twofold. First, to provide an indication whether it is worthwhile to invest in the estimation of a demand system for similar consumption side poverty impact analyses. Second, to provide a sense of the magnitude in the loss of fidelity from using a less flexible instead of a more flexible demand system within computable general equilibrium analyses of poverty impacts. The results show that using no demand system overestimates poverty impacts to quite some extent. The differences between using either of the three demand systems are rather small but may be more substantial in the extremes.
    Keywords: Demand system, simulation, Uganda, food price inflation, poverty, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, International Relations/Trade,
    Date: 2013
  10. By: Albert Ferreiro-Castilla; Kees van Schaik
    Abstract: In this note we apply the recently established Wiener-Hopf Monte Carlo (WHMC) simulation technique for Levy processes from Kuznetsov et al. [17] to path functionals, in particular first passage times, overshoots, undershoots and the last maximum before the passage time. Such functionals have many applications, for instance in finance (the pricing of exotic options in a Levy model) and insurance (ruin time, debt at ruin and related quantities for a Levy insurance risk process). The technique works for any Levy process whose running infimum and supremum evaluated at an independent exponential time allows sampling from. This includes classic examples such as stable processes, subclasses of spectrally one sided Levy processes and large new families such as meromorphic Levy processes. Finally we present some examples. A particular aspect that is illustrated is that the WHMC simulation technique performs much better at approximating first passage times than a `plain' Monte Carlo simulation technique based on sampling increments of the Levy process.
    Date: 2013–06
  11. By: Eric Gaus (Ursinus College)
    Abstract: The adaptive learning has primarily focused on decreasing gain learning and constant gain learning. As pointed out theoretically by Marcet and Nicolini (2003) and empirically by Milani (2007) an endogenous learning mechanism may explain key economic behaviors, such as recurrent hyperinflation or time varying volatility. This paper evaluates the mechanism used in those papers in addition to proposing an alternative endogenous learning algorithm. The proposed algorithm outperforms the Marcet and Nicolini's algorithm in simulations and may result in exotic dynamics.
    Keywords: Learning, Rational Expectations, Endogenous Learning
    JEL: E52 D83
    Date: 2013–03–01
  12. By: Liu, Jing; Hertel, Thomas W.; Taheripour, Farzad; Zhu, Tingju; Ringler, Claudia
    Abstract: Agriculture’s reliance on irrigation and concerns over water scarcity raise the question of how global food output and trade could be affected if the issue of water shortfall needs to be resolved on the back of agriculture. To understand changes in food production and international agricultural trade as the responses to local water shortage, we construct a computable general equilibrium model in which irrigation water supply reliability is perturbed. The results suggest that regions under water stress cut back food production and turn into net food importers, although domestic water productivity improves. The regions’ welfare falls, primarily due to less endowment available for agriculture and decline in the terms of trade.
    Keywords: CGE modeling, water scarcity, irrigated and rainfed agriculture, food security, international agricultural trade, Food Security and Poverty, International Relations/Trade, Resource /Energy Economics and Policy, Q25, Q17,
    Date: 2013
  13. By: Gottshall, Bryan; Paudel, Krishna
    Abstract: We demonstrate the impact of choosing suites of best management practices (BMPs) to reduce nitrogen, phosphorus and sediment load in Chenier Creek water segment located within the Baouf watershed, Louisiana. Simulation outputs generated from MAPSHED are used to generate regression coefficients and marginal effects which are then used in the optimization model. Results indicated that agricultural land retirement can meet up to 35% goal in phosphorus reduction with $840132. With restriction on ag land conversion to 10% available row crop area, it was found three different BMPs can reduce up to 20% phosphorus compared to no BMP adoption scenario. This goal in reduction of phosphorus can also bring down the nitrogen and sediment pollution by 5 and 33 percents, respectively. Careful modeling of different BMPs and development of optimization model can help to meet the water quality goal in Louisiana.
    Keywords: Best management practices, cost, optimization, water quality, Farm Management, Research and Development/Tech Change/Emerging Technologies, Resource /Energy Economics and Policy,
    Date: 2013
  14. By: Zheng, Xiaojuan; Reimer, Jeff
    Keywords: Demand and Price Analysis, Research and Development/Tech Change/Emerging Technologies, Resource /Energy Economics and Policy,
    Date: 2013
  15. By: Greg Hannsgen
    Abstract: Should shocks be part of our macro-modeling tool kit—for example, as a way of modeling discontinuities in fiscal policy or big moves in the financial markets? What are shocks, and how can we best put them to use? In heterodox macroeconomics, shocks tend to come in two broad types, with some exceptions for hybrid cases. What I call Type 1 shocks are one-time exogenous changes in parameters or variables. They are used, for example, to set computer simulations in motion or to pose an analytical question about dynamic behavior outside of equilibrium. On the other hand, Type 2 shocks, by construction, occur at regular time intervals, and are usually drawn at random from a probability distribution of some kind. This paper is an appreciation and a survey of shocks and their admittedly scattered uses in the heterodox macro literature, along with some proposals and thoughts about using shocks to improve models. Since shocks of both types might appear at times to be ad hoc when used in macro models, this paper examines possible justifications for using them.
    Keywords: Shocks; Discontinuity; Dynamic Macro Models; Heterodox Macroeconomics; Growth and Fluctuations; Simulation Methodology
    JEL: B40 E12 E17 E30 E60
    Date: 2013–06

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