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We describe a multiproduct barter trading experiment in which students exchange real goods in an open market based on their own preferences. The experiment is designed for simulating a pure exchange market in order to demonstrate the role of money and its functions in real economies by showing the limitations and inefficiencies of the traditional barter economy. In addition, the simulation is very effective in highlighting some of the key feature that an object that serves as money needs to possess in order to function as an efficient medium of exchange, unit of account, and store of value.
This volume provides a practical guide to building and using simulation models for international trade theory and policy. Through a sequence of carefully constructed and fully documented programs, the volume illustrates how numerical simulation can be used to analyze a wide array of problems. Modern computable general equilibrium (CGE) models for trade policy are challenging in their complexity, but can be thought of as constructions of much simpler building blocks. By developing the building blocks in a consistent manner, and gradually putting them together in more complex and interesting ways, the volume makes CGE accessible to anyone with a background in microeconomics/trade theory. The volume will be useful to graduate students and researchers in international trade looking for a detailed guide to building simulation models and to developing the skill set necessary to enter into the world of CGE modeling.
This volume comprises select proceedings of the 7th International and 28th All India Manufacturing Technology, Design and Research conference 2018 (AIMTDR 2018). The papers in this volume discuss simulations based on techniques such as finite element method (FEM) as well as soft computing based techniques such as artificial neural network (ANN), their optimization and the development and design of mechanical products. This volume will be of interest to researchers, policy makers, and practicing engineers alike.
Understanding how the Papua New Guinea (PNG) agricultural economy and associated household consumption is affected by climate, market and other shocks requires attention to linkages and substitution effects across various products and the markets in which they are traded. In this study, we use a multi-market simulation model of the PNG food economy that explicitly includes production, consumption, external trade and prices of key agricultural commodities to quantify the likely impacts of a set of potential shocks on household welfare and food security in PNG. In this study, we use a multi-market simulation model of the PNG food economy that explicitly includes production, consumption, external trade and prices of key agricultural commodities to quantify the likely impacts of a set of potential shocks on household welfare and food security in PNG. We have built the model to be flexible in order to explore different potential scenarios and then identify where and how households are most affected by an unexpected shock. The model is designed using region and country-level data sources that inform the structure of the PNG food economy, allowing for a data-driven evaluation of potential impacts on agricultural production, food prices, and food consumption. Thus, as PNG confronts different unexpected challenges within its agricultural economy, the model presented in this paper can be adapted to evaluate the potential impact and necessary response by geographic region of an unexpected economic shock on the food economy of the country. We present ten simulations modeling the effects of various shocks on PNG’s economy. The first group of scenarios consider the effects of shocks to production of specific agricultural commodities including: 1) a decrease on maize and sorghum output due to Fall Armyworm; 2) reduction in pig production due to a potential outbreak of African Swine Fever; 3) decline in sweet potato production similar to the 2015/16 El Niño Southern Oscillation (ENSO) climate shock; and 4) a decline in poultry production due to COVID-19 restrictions on domestic mobility and trade. A synopsis of this report, which focuses on the COVID-19 related shocks on the PNG economy is also available online (Diao et al., 2020).1 The second group of simulations focus on COVID-19-related changes in international prices, increased marketing costs in international and domestic trade, and reductions in urban incomes. We simulate a 1) 30 percent increase in the price of imported rice, 2) a 30 percent decrease in world prices for major PNG agricultural exports, 3) higher trade transaction costs due to restrictions on the movement of people (traders) and goods given social distancing measures of COVID-19, and 4) potential economic recession causing urban household income to fall by 10 percent. Finally, the last simulation considers the combined effect of all COVID-19 related shocks combining the above scenarios into a single simulation. A key result of the analysis is that urban households, especially the urban poor, are particularly vulnerable to shocks related to the Covid-19 pandemic. Lower economic activity in urban areas (assumed to reduce urban non-agricultural incomes by 10 percent), increases in marketing costs due to domestic trade disruptions, and 30 percent higher imported rice prices combine to lower urban incomes by almost 15 percent for both poor and non-poor urban households. Urban poor households, however, suffer the largest drop in calorie consumption - 19.8 percent, compared to a 15.8 percent decline for urban non-poor households. Rural households are much less affected by the Covid-19 related shocks modeled in these simulations. Rural household incomes, affected mainly by reduced urban demand and market disruptions, fall by only about four percent. Nonetheless, calorie consumption for the rural poor and non-poor falls by 5.5 and 4.2 percent, respectively.
This volume explores the field of artificial intelligence and features in-depth coverage of important theoretical areas including computational organization, computational economics, computational approaches in social science, and game theory. The conception of the multi-agent system is particularly attractive, as it promises autonomy based on the conceptual speciality of a rational agent as well as collective behaviour through interactions.
This book constitutes the thoroughly refereed post-conference proceedings of the 17th International Workshop on Multi-Agent-Based Simulation, MABs 2016, held in Singapore, in May 2016. The workshop was held in Conjunction with the 15th International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2016. The 10 revised full papers included in this volume were carefully selected from 15 submissions. The topic of the papers is about modeling and analyzing multi-agent systems and applying agent-based simulation techniques to real-world problems, focusing on the confluence of socio-technical- natural sciences and multi-agents systems with a strong application/empirical vein. Special emphasis is given on exploratory agent-based simulation as a principled way of undertaking scientific research in the social sciences and on using social theories as an inspiration to new frameworks and developments in multi-agent systems.