标题： 通过进化实现效率，基于代理的经济预测建模的达尔文方法 显示英文标题

标题： Efficiency through Evolution, A Darwinian Approach to Agent-Based Economic Forecast Modeling

摘要： 本文提出了一种新颖的达尔文代理模型（ABM）方法，用于宏观经济预测，该方法利用进化原则实现了显著的计算效率和涌现的真实性。 与依赖于从大型企业分析中得出的复杂行为规则的传统动态随机一般均衡（DSGE）和ABM方法不同，我们的框架采用了代表直接服务于最终消费者的中小企业的简单“常识”规则。 该方法将家庭视为经济动态的主要驱动因素，企业则通过有限互动邻域内的基于市场的自然选择进行适应。 我们证明，当受到投入产出表结构约束时，这种方法能够生成现实的经济模式，包括财富分布、企业规模分布和行业就业模式，而无需广泛的参数校准。 使用FIGARO投入产出表对46个国家进行分析，并以奥地利为例进行研究，我们表明该模型能够再现经验规律，同时在普通笔记本电脑上保持计算效率，而不是需要超级计算机集群。 主要发现包括：(1) 从最小的行为假设中涌现出现实的企业和就业分布，(2) 通过进化动力学准确再现初始社会核算矩阵值，(3) 仅使用5-6个国家特定参数即可成功校准以补充FIGARO数据，(4) 计算性能使得在消费级硬件上进行全面模拟成为可能。 这些结果表明，进化ABM方法可以通过捕捉分散的市场适应性提供稳健的政策见解，同时避免传统DSGE和全面ABM模型的计算复杂性。 显示英文摘要

摘要： This paper presents a novel Darwinian Agent-Based Modeling (ABM) methodology formacroeconomic forecasting that leverages evolutionary principles to achieve remarkablecomputational efficiency and emergent realism. Unlike conventional DSGE and ABM approachesthat rely on complex behavioral rules derived from large firm analysis, our framework employssimple "common sense" rules representative of small firms directly serving final consumers. Themethodology treats households as the primary drivers of economic dynamics, with firms adaptingthrough market-based natural selection within limited interaction neighborhoods. We demonstrate that this approach, when constrained by Input-Output table structures,generates realistic economic patterns including wealth distributions, firm size distributions, andsectoral employment patterns without extensive parameter calibration. Using FIGARO Input-Output tables for 46 countries and focusing on Austria as a case study, we show that the modelreproduces empirical regularities while maintaining computational efficiency on standard laptopsrather than requiring supercomputing clusters. Key findings include: (1) emergence of realistic firm and employment distributions fromminimal behavioral assumptions, (2) accurate reproduction of the initial Social Accounting Matrixvalues through evolutionary dynamics, (3) successful calibration using only 5-6 country-specificparameters to complement the FIGARO data, and (4) computational performance enabling fullsimulations on consumer hardware. These results suggest that evolutionary ABM approaches canprovide robust policy insights by capturing decentralized market adaptations while avoiding thecomputational complexity of traditional DSGE and comprehensive ABM models.