Visual Representation of Hoberg/Phillips Product Space


The Hoberg and Phillips Text Based Industry Classifications have a spatial representation. All firms have a location in a product market space shaped as a unit sphere. Competitive product markets are areas of the sphere where many firms are located. Concentrated areas are sparsely populated.

Some regions of the product space have no firms residing there, as some text descriptions of products would describe products with no demand, such as the word combination: "eggs", "paint" and "gardening".

The best way to tap the full research power of this product market grid is to use the Text-based Network Industry Classifications (TNIC), which is a network way of identifying competitors to each firm. Competitors are firms residing in close proximity in product space to each firm based on a continuous measure of similarity. Another key benefit of TNIC industries is that industry composition is updated annually, and our own research indicates that the product market space itself thus dynamically changes over time. As a result, static fixed-location FIC classifications miss out on much of the picture.

Picture Van Munching Hall

Hoberg and Phillips
Data Library


Robert H. Smith School of Business
University of Maryland
Van Munching Hall
University of Maryland
College Park, MD 20742-1815


Welcome to the Hoberg-Phillips Industry Classification Data Library


Data provided by Gerard Hoberg and Gordon Phillips

10-K Text-based Network Industry Classifications (TNIC) data

  • Readme File Describing Data

  • Download Data (about 26MB zipped, 179MB unzipped)

    • * This data offers more research flexibility, and is also more informative, than FIC classifications such as SIC, NAICS, and the 10-K based FIC classifications below. These benefits are outlined in the readme file above, and in the Hoberg and Phillips (2010a,b) papers cited therein.

    ** Please cite the following two studies that provided key innovations when referring to this data:

    Product Market Synergies and Competition in Mergers and Acquisitions: A Text-Based Analysis. [Download Paper]
    Gerard Hoberg and Gordon Phillips, 2010, Review of Financial Studies 23 (10), 3773-3811.

    Text-Based Network Industries and Endogenous Product Differentiation. [Download Paper]
    Gerard Hoberg and Gordon Phillips, 2010, University of Maryland Working Paper.

    *** The following paper also uses the above data:

    Product Market Threats, Payouts, and Financial Flexibility [Download Paper]
    Gerard Hoberg, Gordon Phillips and Nagpurnanand Prabhala, 2012, Forthcoming, Journal of Finance.

10-K Text-based Fixed Industry Classifications (FIC-100,200,300,400,500) data

  • Readme File Describing Data

  • Download Data (about 300KB zipped, 2MB unzipped)

    • * This data can be used in the same way SIC or NAICS industry controls are used. We include this analog for convenience, as it can be highly useful in robustness analysis, or in analysis for which 10-K based industry controls might be helpful. See readme file above for more.

    ** Please cite the following two studies that provided key innovations when referring to this data:

    Product Market Synergies and Competition in Mergers and Acquisitions: A Text-Based Analysis. [Download Paper]
    Gerard Hoberg and Gordon Phillips, 2010, Review of Financial Studies 23 (10), 3773-3811.

    Text-Based Network Industries and Endogenous Product Differentiation. [Download Paper]
    Gerard Hoberg and Gordon Phillips, 2010, University of Maryland Working Paper.

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Last updated 07/15/10