آکادمی و موسسه علمی پژوهشی ابن سینا

بخشی از رساله دکتری به زبان انگلیسی

The second approach is based on micro theoretical relationships and has become influential in central banks in recent years. The approach posits that the economy can be understood by reference to a single so-called ‘representative agent’, who makes decisions in order to maximize his/her utility over an infinite time horizon.  I refer you to Woodford’s paper (Woodford, 2009) in case you are interested to have more information about this approach. These models do not use statistical techniques to estimate their parameters.  Instead, the macro-behavior, which emerges from the micro-foundations of the model, is calibrated against macro-relationships. These models explain emergent features of the macro-economy from micro-level behavioral principles. For following this approach we need to connect the micro-behavioral model to the macro model. 
In the developed micro-simulation model, individual agents within the Lugano housing market (e.g. dissatisfied households in the housing market) have been modeled. The weakness of the developed agent-based micro-simulation model is that it operates in a closed system without taking account of the economic environment in which the agents are living. Another weakness of the agent-based simulation models in general is that they just model the first round effects without taking account of the responses of the agents to the changes that occur in the system. On the other hand, the strength of macro-economic models is that they are capable of modeling the changes that occur within the entire economy. However, the macro-models are not able to provide us with information about how aggregate changes in the economy affect individuals. Therefore in order to exploit the complementary nature of micro and macro models' strengths and weaknesses these two models, which are taking, place in two different scales should be linked.
In this chapter, we are seeking a way to connect the designed behavioral agent-based model to macroeconomic indicators.  Connecting the micro-level behavior of each agent to macro-economic indicators provides us with a new approach to trace the behavior of the agents in the housing market and consequently helps us to figure out the effects of agents’ decisions on macro-economic indicators and vice-versa. The research work that has been done on micro-macro economic modeling is still rare and the techniques and approaches are in their infancy. Considering advances in econometric and computational methods, researchers are showing a growing interest in micro-macro economic modeling (Davies, Microsimulation, CGE and Macro Modelling for Transition and Developing Economics, 2004). Connecting the developed agent-based simulation model and the macro-economic indicators will improve the model and provide us with the following benefits:
•    This will help us to improve the housing market model within the overall economy by providing a detailed description of the individual agents behavior (providing a microeconomic basis for aggregate behavior).
•    This will help us to integrate the agent-based simulation model with multiple types of agents and the explicit spatial model with the macro-economic indicators. 
•    This will help us to align the predictions of the micro and macro model through importing the outputs of the macro-model into the micro-simulation model and vice versa.

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