Reflections on Learning from Observational Data

Q2 Economics, Econometrics and Finance
Caleb Piche-Larocque, Joseph Findlay, Akhter Faroque
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引用次数: 0

Abstract

The social sciences study various aspects of human behaviour – social, economic and political – based on observational data. Observational data are inaccurate and subject to simultaneity, seasonality, structural breaks, random variation and too many interlocking variables masking the underlying causal patterns. During the past two decades or so, the use experimental data (RCTs) has become widely popular across the social sciences, creating a tension between the supporters and critics of the new and the old methodologies. In this paper, we first review these methodologies, both observational and experimental, focusing on how economists and other social scientists try to learn about the underlying causal relationships from the correlations contained in the data. We then reflect on whether the new or the old methodologies should be the way forward from a purely statistical and a broader policy and development perspectives.
关于从观测数据中学习的思考
社会科学基于观测数据研究人类行为的各个方面——社会、经济和政治。观测数据是不准确的,并受到同时性、季节性、结构断裂、随机变化和太多连锁变量的影响,这些变量掩盖了潜在的因果模式。在过去二十年左右的时间里,使用实验数据(rct)在社会科学领域广泛流行,在新旧方法的支持者和批评者之间产生了紧张关系。在本文中,我们首先回顾了这些方法,包括观察和实验,重点关注经济学家和其他社会科学家如何试图从数据中包含的相关性中了解潜在的因果关系。然后,我们从纯粹的统计和更广泛的政策和发展的角度考虑新的或旧的方法是否应该是前进的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Economics and Finance Studies
International Journal of Economics and Finance Studies Economics, Econometrics and Finance-Economics, Econometrics and Finance (miscellaneous)
CiteScore
3.40
自引率
0.00%
发文量
0
审稿时长
12 weeks
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