Read e-book online Agent-based modelling in economics PDF

By Lynne Hamill, Nigel Gilbert

ISBN-10: 1118945506

ISBN-13: 9781118945506

ISBN-10: 1118945514

ISBN-13: 9781118945513

ISBN-10: 1118945522

ISBN-13: 9781118945520

Agent-based modelling in economics


Lynne Hamill and Nigel Gilbert, Centre for study in Social Simulation (CRESS), college of Surrey, UK


New equipment of monetary modelling were sought due to the international monetary downturn in 2008.This distinct booklet highlights some great benefits of an agent-based modelling (ABM) method. It demonstrates how ABM can simply deal with complexity: heterogeneous humans, families and corporations interacting dynamically. in contrast to conventional tools, ABM doesn't require humans or organisations to optimise or financial structures to arrive equilibrium. ABM bargains the way to hyperlink micro foundations on to the macro situation. 


Key features:

  • Introduces the concept that of agent-based modelling and exhibits the way it differs from current approaches.
  • Provides a theoretical and methodological intent for utilizing ABM in economics, besides sensible suggestion on find out how to layout and create the models.
  • Each bankruptcy begins with a brief precis of the suitable financial idea after which indicates the right way to practice ABM.
  • Explores either subject matters coated in simple economics textbooks and present very important coverage topics; unemployment, alternate premiums, banking and environmental issues.
  • Describes the types in pseudocode, allowing the reader to boost courses of their selected language.
  • Supported by way of an internet site that includes the NetLogo types defined within the book.


Agent-based Modelling in Economics provides scholars and researchers with the talents to layout, enforce, and research agent-based types. 3rd yr undergraduate, grasp and doctoral scholars, school economists will locate this publication a useful resource.


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Extra resources for Agent-based modelling in economics

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39 ; go to that stall 40 face stall The rest of the code is the same as before (although we can if we wish use the produce‐ price and buy‐from‐stall reporters to make the code more readable). 7 Running experiments The amount of scanning that agents do to find the cheapest stalls should be correlated with a reduction in the average price that they pay: the more they search, the more likely that they will find the optimum set of prices. However, it is not easy to see this by running the model once for each of several values of the n‐scans slider.

For further discussion, see Blundell et al. (1993). We noted at the beginning of this chapter that households have different budgets and different preferences and different consumption patterns and that the average household in this sense does not exist. Why, then, should analysis be based on averages? 1 Results: estimated effect of the imposition of a 10% ad valorem tax on food. Bottom quintile Lower quintile Middle quintile Upper quintile Top quintile Overall/total Based on 30 runs with 1000 agents.

8 Discussion This chapter has aimed to provide an idea of what the internals of an agent‐based model looks like, as well as providing an introduction to some of the most common constructs and commands in NetLogo. Although the example we have dissected is rather simple (as it had to be in order that it could be explained within the confines of one chapter), it does illustrate the characteristics of agent‐based models that were mentioned in Chapter 1. The agents were heterogeneous: the range of fruits and vegetables stocked differed between market traders, and every shopper had a different shopping list.

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Agent-based modelling in economics by Lynne Hamill, Nigel Gilbert

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