Econometrics for the Firm (FIRMMETRIX)

这项提议描述的研究将通过对公司生产过程和相互作用的实证评估来应对现有的挑战。公司的决策和互动存在于当前关于不平等、市场力量、生产率和宏观经济波动根源等重要主题的辩论的背景下。对企业行为主要驱动力的量化是影响这些辩论的许多衡量标准的关键因素。因此，识别企业投入和产出与其市场行为之间的因果联系是根本的，因为这里的不准确将引导对这些重大社会主题的结论。然而，(A)从传统数据估计生产可能性的现代程序依赖于关于公司如何以及何时选择可能不可靠地推动估计的投入的关键假设；(B)重要的多公司谈判模型缺乏关于其经验有效性的数据要求的明确指导方针；以及(C)系统的市场定义协议--研究和竞争政策的关键--仍然是一项挑战。该提案提供了解决这些问题的开创性研究。该提案纳入了新的和越来越多的可用数据来解决上述问题；开发了必要的工具来应对这些新数据带来的计量经济学挑战；并通过实际应用表明这种方法是如何帮助的。该提案涵盖了在四个相互补充和建立的工作流程中分析企业互动模型的方法论考虑和经验应用。这些工作流程将：(1)纳入关于公司预期和业务网络的数据，以解决(A)中的问题；(2)在两个单独的工作流程中；(2)正式探索数据需求，以便准确评估(B)中提到的公司对公司关系模型；(3)将机器学习方法和经济学结合起来，以解决市场细分问题。

The research this proposal describes will tackle existing challenges with the empirical assessment of firms' production processes and interactions. Firms' decisions and interactions lie in the background of the current debate on important themes such as inequality, market power, productivity, and the origins of macroeconomic fluctuations. The quantification of the main drivers of firms' behaviour is a key ingredient to many metrics colouring those debates. The identification of the causal links between firms' inputs and outputs and their market behaviour is thus fundamental as imprecisions here will steer conclusions on those big societal themes. Yet, (a) modern procedures to estimate production possibilities from conventional data rest on critical assumptions on how and when firms choose inputs that may unreliably drive estimates; (b) important multi-firm negotiation models lack clear guidelines on the data requirements for their empirical validity; and (c) systematic market definition protocols - key for research and competition policy - remain a challenge. This proposal offers ground-breaking research addressing these issues.The proposal incorporates new and increasingly available data to address the issues above; develops the necessary tools to take on the econometric challenges that these new data bring; and shows through substantive applications how this approach helps. The proposal covers methodological considerations and empirical applications on the analysis of firm interaction models in four workstreams that complement and build on one another. The workstreams will: (i) incorporate data on firm expectations and business networks to address the issues in (a) in two separate workstreams; (ii) formally explore the data demands for the accurate assessment of firm-to-firm relationship models noted in (b); (iii) and bring together machine learning methods and economics for market segmentation to address (c).