Solution for information and analytical support of staffing management in the Arctic zone of the Russian Federation

One of the main problems of Arctic zone development in the Russian Federation (AZRF) is a limited labor resources. Poly-model complex for analysis and simulation of the AZRF labor market is presented in the article. The complex allows you to forecast the formation of the labor demand of socio-economic systems in AZRF and to explore the possibilities of regional professional education systems in terms of meeting the forecasted needs. Technologies of system-dynamic and agent-based modeling are shared within the framework of the complex. The advantage of the presented software tool is the ability to operatively vary not only the quantitative characteristics of the modeled system, but also the structure of interaction between the components of the system. This is a useful opportunity to analyze the possible impact on the regional labor market of investment projects that are planned for implementation in the region. Developed tool was used to support the personnel policy management in the Murmansk region

Modeling And Economic Analysis Of A Crop-Livestock Production System Incorporating Cereal Rye As A Forage

This thesis consists of two chapters using agent-based modeling for a crop-livestock production system incorporating human labor. The first chapter examines the principles used to develop a fundamental simulation pertaining to grazing cereal rye (Secale cereal L.) with calves. Within the software guidelines, the base model has the ability to capture diverse system interactions between livestock/plants and land management with human labor efficiency. AnyLogic incorporates agent-based modeling while combining with discrete event modeling and system dynamics. The purpose of the model was to find the economic returns of grazing cover crops relative to the area of Mead, Nebraska. In our simulation model, we used data from the University of Nebraska-Lincoln Climate Center. The model was developed to create more in depth case studies to help further the understanding of crop and livestock interactions through simulation. AnyLogic is a complex tool that has the capabilities of discovering the interactions between crops, livestock, land, and humans. In the second chapter, we examined the economic returns of grazing cereal rye with calves versus mechanically removing the cover crop. This analysis evaluated production risks due to weather variability and cattle market risk to determine the theoretical best outcome using existing weather and market data. Working with the University of Nebraska-Lincoln’s agronomy and animal science departments, we modified a cereal rye growth production model first proposed by Feyereisen et al. (2006) to match recent on-farm production trial experience in Mead, Nebraska. Based on simulation results over multiple years, it was determined that mechanically harvesting cereal rye is a better option as a long term fixed strategy than grazing cereal rye. This is largely due to cattle market risk during the spring grazing period. The costs associated with mechanically removing the crop depend on farm size and equipment used. Both chapters utilize a model simulating the grazing of cover crops developed using the AnyLogic software while the analysis on mechanically removing the forage was completed with the use of a University of Nebraska-Lincoln cover crop budget. Through bridging the gap between production and economic information, this study sought to develop a financial comparison between the two cover crop strategies for eastern Nebraska farmers. Advisor: Jay Parson

Spatial interactions in agent-based modeling

Agent Based Modeling (ABM) has become a widespread approach to model complex interactions. In this chapter after briefly summarizing some features of ABM the different approaches in modeling spatial interactions are discussed. It is stressed that agents can interact either indirectly through a shared environment and/or directly with each other. In such an approach, higher-order variables such as commodity prices, population dynamics or even institutions, are not exogenously specified but instead are seen as the results of interactions. It is highlighted in the chapter that the understanding of patterns emerging from such spatial interaction between agents is a key problem as much as their description through analytical or simulation means. The chapter reviews different approaches for modeling agents' behavior, taking into account either explicit spatial (lattice based) structures or networks. Some emphasis is placed on recent ABM as applied to the description of the dynamics of the geographical distribution of economic activities, - out of equilibrium. The Eurace@Unibi Model, an agent-based macroeconomic model with spatial structure, is used to illustrate the potential of such an approach for spatial policy analysis.Comment: 26 pages, 5 figures, 105 references; a chapter prepared for the book "Complexity and Geographical Economics - Topics and Tools", P. Commendatore, S.S. Kayam and I. Kubin, Eds. (Springer, in press, 2014

Modeling economic systems as locally-constructive sequential games

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 essential properties imply real-world economies are locally-constructive sequential games. This paper discusses a modeling approach, Agent-based Computational Economics, that permits researchers to study economic systems from this point of view. ACE modeling principles and objectives are first concisely presented and explained. The remainder of the paper then highlights challenging issues and edgier explorations that ACE researchers are currently pursuing

Two monetary models with alternating markets : [Version 28 October 2013]

We present a thought-provoking study of two monetary models: the cash-in-advance and the Lagos and Wright (2005) models. We report that the different approach to modeling money — reduced-form vs. explicit role — neither induces theoretical nor quantitative differences in results. Given conformity of preferences, technologies and shocks, both models reduce to one difference equation. The equations do not coincide only if price distortions are differentially imposed across models. To illustrate, when cash prices are equally distorted in both models equally large welfare costs of inflation are obtained in each model. Our insight is that if results differ, then this is due to differential assumptions about the pricing mechanism that governs cash transactions, not the explicit microfoundation of money