从CATS到CAOS:基于宏观经济主体模型中的财政乘数与主体预期

Severin Reissl
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引用次数: 2

摘要

本文以Delli Gatti et al.(2011)为基础,构建基于宏观经济主体的模型,研究主体预期和消费选择对政府支出乘数的影响。在对先前的基线模型中乘数的大小进行彻底调查之后,引入了一种修改,允许代理人在基于未来收入估计的预算约束下从事消费的跨期优化。与基线相比,财政乘数受到这种替代消费行为的强烈影响,变得明显变小。进一步,明确地引入了代理人对政府支出冲击影响的信念。在外源性强加信念与个体信念的适应或不同类型信念之间的转换行为相结合的情况下,研究表明乐观和悲观预期都可以暂时自我实现,并增加或减少乘数的值。这两种形式的信念动态也考虑到了财政政策的公告效应。在最后的实验中,为了估计政府支出冲击对未来收入的影响,代理人被允许进行最小二乘学习。研究表明,在最小二乘学习下,信念是“理性的”,因为它们平均会导致大致正确的预测。因此,本文有助于解决卢卡斯批评在宏观资产管理模型中的应用问题,因为经济主体对财政政策变化的公告做出了系统(且合理)的反应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
From CATS to CAOS: Fiscal Multipliers and Agents’ Expectations in a Macroeconomic Agent-Based Model
This paper uses a macroeconomic agent-based model building on Delli Gatti et al. (2011) to investigate the influence of agents’ expectations and consumption choices on government expenditure multipliers. Following a thorough investigation of the size of the multiplier in the pre-existing baseline model, a modification is introduced, allowing agents to engage in inter-temporal optimization of consumption subject to a budget constraint which is based on estimates of future income. Compared to the baseline, the fiscal multiplier is strongly affected by this alternative consumption behavior, becoming significantly smaller. In a further step, agents’ beliefs about the effects of government expenditure shocks are explicitly introduced. In the case of exogenously imposed beliefs coupled either with adaptation of individual beliefs or switching behavior between different types of beliefs, it is shown that both optimistic and pessimistic expectations can be temporarily self-fulfilling and either increase or decrease the value of the multiplier. Both forms of belief dynamics also allow for the incorporation of announcement effects of fiscal policy. In a final experiment, agents are allowed to engage in least-squares learning in order to gain an estimate of the effect of government expenditure shocks on future income. It is shown that under least squares learning, beliefs are ‘rational’ insofar as they lead to broadly correct predictions on average. The paper hence contributes to addressing aspects of the Lucas critique as applied to macro-ABMs, since agents react systematically (and reasonably) to announcements of changes in fiscal policy.
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