***************************************************** TOP LEVEL NOTE: See 2014 JF paper referenced below for full detail and for a complete understanding of product market fluidity. The fluidity measure is a measure of how intensively the product market around a firm is changing in each year. Measures of fluidity are customized to each firm based on each firm's unique product market vocabulary. Like all TNIC-derived variables, they are also updated in each year. ****** FYI on most recent 2022 update: In this update, in addition to forward extending the database to 2021 fiscal year endings, we also improved the linking to Compustat gvkeys resulting in 1% more observations in each year relative to older versions. We also used better parsing technology to improve the quality of the item 1 extracted from some 10-Ks (we thank Christopher Ball at metaHeuristica.com). We tested these improvements using standard tests from HP2016 referenced below and find a modest improvement in signal power indicating that this version is improved relative to prior versions. ****** NOTE: Please read the technical descriptions below before using the data. ****************************** The data is at the firm-year level, and can be merged with Compustat data using the gvkey and year fields, where year corresponds to the year of a given Compustat record's datadate year. The variable "prodmktfluid" is the local product market fluidity variable described in the "Product Market Threats, payouts and Financial Flexibility" paper described below. ********************************************************************************************************************************** ********************************************************************************************************************************** ********************************** General Background on Fluidity data and TNIC industries *************************************** ********************************** General Background on Fluidity data and TNIC industries *************************************** ********************************** General Background on Fluidity data and TNIC industries *************************************** ********************************************************************************************************************************** ********************************************************************************************************************************** Please read the following study and its data section when using this data: Product Market Threats, Payouts, and Financial Flexibility Gerard Hoberg, Gordon Phillips, and Nagpuranand Prabhala, Journal of Finance (February 2014) 69 (1), 293-324. **** Please cite this above study when using fluidity data. * This study's data section is particularly important to read and understand before using fluidity data. ************ This next study forms the foundation for the TNIC industry classification, which is used as a foundation for constructing product market fluidity data. This is very relevant background reading regarding text based industry classification and its benefits. Text-Based Network Industries and Endogenous Product Differentiation Gerard Hoberg and Gordon Phillips, Journal of Political Economy (October 2016), 124 (5) 1423-1465. ************ This next study is the first research examination that drew heavily form the same data foundation underlying the TNIC industry data. This study assesses the decision to merge, and the existence of asset complementarities and product market synergies in mergers. Product Market Synergies and Competition in Mergers and Acquisitions: A Text-Based Analysis Gerard Hoberg and Gordon Phillips, Review of Financial Studies (October 2010) 23 (10), 3773-3811. ************************************************************************************************************** ************************************************************************************************************** ********************************************** Citations ***************************************************** ********************************************** Citations ***************************************************** ********************************************** Citations ***************************************************** ************************************************************************************************************** ************************************************************************************************************** As stated above, please cite this study when using fluidity data Product Market Threats, Payouts, and Financial Flexibility Gerard Hoberg, Gordon Phillips, and Nagpuranand Prabhala, Forthcoming, Journal of Finance ********************************************************************************************************************** ********************************************************************************************************************** ********************************************** Technical Details ***************************************************** ********************************************** Technical Details ***************************************************** ********************************************** Technical Details ***************************************************** ********************************************************************************************************************** ********************************************************************************************************************** Please read the following carefully to ensure proper usage of this data. Technical Note 1) Each file contains a gvkey and year firm identifier. The TNIC3HHI variable is a concentration measure and TNIC3TSIMM is a total similarity measure. Each observation should be mapped to COMPUSTAT using fiscal year endings that match the year field in this data. It is important to note that were already did the merge to COMPUSTAT, so you do not have to repeat this, which is why we provide data with gvkey as the identifier. The data contained here is not lagged. Researchers needing lagged data must lag the data on their own. On date conventions, for convenience, the year field in this database is based on Compustat calendar years obtained as the first four digits of the YYYYMMDD datadate variable. Consider a COMPUSTAT firm with a fiscal year ending on Sept 30th, 1997, for example. The corresponding record for this firm's gvkey in 1997 in this database ia based on the product description of the 10-K report that was associated with this firm's 9/30/1997 fiscal year end. Technical Note 2) The database in this database is larger than the one used in the above mentioned article. The reason is that the dividend and cash literatures have a convention of applying various screens. For the purposes of the data distribution here, we intentionally apply no screens and simply distribute as much data as we can regarding observations for which fluidity can be computed. This is because various research projects may wish to apply different screens, and this gives the researcher the ability to apply their own screens as needed.