Data and Code

Data: Updated and Improved Staggered Board Classification

•  Contains the staggered board status for over 15,000 firms (over 149,000 firm-year observations) from 1991 to 2023. For EDGAR filings, we scrape DEF 14A filings and apply the Random Forests Classifier algorithm to determine the staggered board status of firms. In this version of the data, we manually inspect all instances when a firm changes to or from having a staggered board as well as check for any other errors. We also hand collect classified board information from DEF 14A microfiche filings for pre-EDGAR data and from S-1 filings for IPOs.

• Here is the link to the Python code and textual data to implement the RF Classifier and a Read Me file describing the variables in the dataset.

• Citation: Guernsey, Scott, Feng Guo, Tingting Liu, and Matthew Serfling, 2024, Thirty years of change: The evolution of classified boards, Journal of Finance, Forthcoming.

  • The process to collect this data was built on a prior paper: Guernsey, Scott, Simone M. Sepe, and Matthew Serfling, 2022, Blood in the water: The value of antitakeover provisions during market shocks, Journal of Financial Economics 143, 1070-1096.

Data: Staggered Board Classification

• We scrape DEF 14A filings and apply machine learning techniques to determine the staggered board status for over 14,000 firms (over 120,000 firm-year observations) beginning in 1994. Here is the link to the Stata code and textual data used to create the final dataset.

• Citation: Guernsey, Scott, Simone M. Sepe, and Matthew Serfling, 2022, Blood in the water: The value of antitakeover provisions during market shocks, Journal of Financial Economics 143, 1070-1096.

Data: Historical Headquarters Locations

• Contains hand-collected historical headquarters data going back to 1969 for the near universe of CRSP-Compustat firms (over 100,000 firm-year observations).

• Citation: Bai, John (Jianqiu), Douglas Fairhurst, and Matthew Serfling, 2020, Employment protection, investment, and firm growth, Review of Financial Studies 33: 644-688.

Data: State-Level Covenants-not-to-Compete Enforcement Index

• This dataset extends the state-level CNC enforcement index from Garmaise (JLEO, 2011) and Ertimur, Rawson, Rogers, and Warren (JAR, 2018) through 2018.

• Citation: Bai, John (Jianqiu), Ashleigh Eldemire, and Matthew Serfling, 2024, The effect of labor mobility on corporate investment and performance over the business cycle, Journal of Banking and Finance 166, 107258.