报告题目：Quantitative Macroeconomics: Lessons Learned from Fourteen Replications
报 告 人：Robert Kirkby
报告地点：腾讯会议（会议ID：842 810 204）
Robert Kirkby，惠灵顿维多利亚大学经济与金融学院高级讲师，本科生项目负责人。2014年获马德里卡洛斯三世大学经济学博士学位。他主要通过开发理论和计算工具进行宏观经济政策分析。其论文发表在Computional Economics、Journal of Real Estate Finance and Economics、Macroeconomic Dynamics、Journal of Macroeconomics等期刊。
I replicate all tables and figures from fourteen papers in Quantitative Macroeconomics, with an emphasis on incomplete market heterogeneous agent models. I report three main findings: (i) all (non-welfare related) major findings of the papers replicate, (ii) welfare findings based on linear approximation methods — 1st-order perturbation, linear and log-linearization around steady-state, and linear-quadratic methods — should be treated as quantitatively suspect, (iii) decisions around methods for discretizing exogenous shocks have a large and unappreciated influence on results and should be prominently discussed in papers. While some smaller aspects of the papers do not replicate exactly, rather than nitpick in the body of this paper I instead describe some lessons learnt that may be useful for practitioners working with Quantitative Macroeconomic models. The replications use global methods allowing for non-linearities and I argue that these are important and need to be more widely used. I provide a checklist that researchers can use when trying to check that their work will be more easily reproducible. Matlab codes implementing the replications using the VFI Toolkit are provided, and full results of all replications are given in the online appendix. I conclude with three core points for best practice: (i) codes be made directly available (e.g., on github, not only ‘on request’, and not just inside a zip file), (ii) report not just baseline parameters but also hyperparameters, equilibrium values, non-baseline parameters and initial conditions, and (iii) replication means rewriting codes from scratch, not just re-running available codes.
腾讯会议ID：842 810 204
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撰稿：王杰 审核：齐鹰飞 单位：高等经济研究院