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Agent-Based Modelling in Economics by Lynne Hamill, Nigel Gilbert

By Lynne Hamill, Nigel Gilbert

Agent-based modelling in economics

 

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

 

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

 

Key features:

  • Introduces the idea 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, in addition to sensible recommendation on tips to layout and create the models.
  • Each bankruptcy starts off with a brief precis of the appropriate monetary concept after which exhibits the way to follow ABM.
  • Explores either issues lined in easy economics textbooks and present vital coverage topics; unemployment, trade premiums, banking and environmental issues.
  • Describes the versions in pseudocode, allowing the reader to enhance courses of their selected language.
  • Supported through an internet site that includes the NetLogo versions defined within the book.

 

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

 

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Extra info for Agent-Based Modelling in Economics

Sample text

Furthermore, agents were endowed with some rationality that allowed them to attempt to optimise but within constraints imposed by limited information and limited resources of time and effort. Starting agent‐based modelling 27 At the end of each of the following chapters, there are appendices that summarise the models introduced in the chapter using a standard structure and a listing in ‘pseudocode’, a version of the program code that is closer to natural language. This chapter does the same to show for the example that we have described in detail what the pseudocode version looks like.

It does this the number of times selected. Visiting the selected stalls: Ensuring that no stall is visited twice Recording what is bought Adding up how much is spent. When the shopping list is empty, the shopper goes home. Report the results and plot the graph. References Gilbert, N. (2007) Agent‐Based Models. London: Sage. F. & Grimm, V. (2011) Agent‐Based and Individual‐Based Modeling: A Practical Introduction. Princeton: Princeton University Press. Wilensky, U. (1999) NetLogo. Center for Connected Learning and Computer‐Based Modeling, Northwestern University, Evanston, IL [Online].

1 Budget shares by household income: United Kingdom, 2010. Source: ONS (2011). Thus, households have different incomes, different tastes and different spending patterns. While the spending pattern of the average household may be useful for certain purposes, such as constructing a consumer price index, it is very likely that no household actually spent their budget in that way. Consumers are heterogeneous. One of the key benefits of agent‐based modelling is its ability to deal with heterogeneity, and this chapter demonstrates how this can be done.

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