Forecasting Earnings from Home

• 成果类型: Article; Early Access
• 署名作者: Durney, Michael; Kyung, Hoyoun; Markov, Stanimir; Park, Jihwon
• 署名单位: University of Iowa; University of Missouri System; University of Missouri Columbia; University of Texas System; University of Texas Dallas; City University of New York (CUNY) System; Baruch College (CUNY)
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2024.04637
• 发表日期: 2026
• 关键词: accounting; forecasting; capital markets; analysts; Working from home

摘要

We examine the impact of working from home (WFH) practices on the financial services industry, focusing on sell-side equity analysts. We find that analysts who previously benefited from access to in-person interactions with other informed parties experience a greater decline in earnings forecast accuracy following the COVID lockdown and the shift to WFH. Notably, the informational advantage associated with the in-person access disappears during the lockdown and returns once restrictions are lifted. Our results are stronger for all-star analysts and analysts with shorter coverage periods, suggesting that all-star analysts rely relatively more on access to in-person interactions prelockdown and that accumulated firm-specific knowledge mitigates the loss of in-person interactions. Our results remain robust across alternative analyst performance measures. We conclude that, despite recent advances in communications technology, AI, and machine learning, in-person interactions remain a unique and difficult to substitute information channel sell-side research providers and that WFH impedes information flows between market participants in capital markets.