My da|ra Login

Detailed view

metadata language: English

INNOVATION a: WHAT DO STOCK PRICE INDEXES OF IP-INTENSIVE COMPANIES TELL US ABOUT INNOVATION?

Version
1
Resource Type
Dataset : other
Creator
  • Corrado, Carol (The Conference Board)
  • Martin, David (M-CAM International, LLC)
  • Wu, Qianfan (M-CAM International, LLC)
Publication Date
2020-05-15
Funding Reference
  • The Conference Board
  • M-CAM International, LLC
Free Keywords
Economics; Finance; intellectual property
Description
  • Abstract

    Abstract:
    Stock prices are a leading indicator of economic activity in the United States, e.g., they are a component of The Conference Board’s U.S. Leading Economic Index. This paper re-examines stock prices and business productivity in light of the growing importance of intangible investment in overall investment in recent decades (Corrado and Hulten, 2010; Haskel and Westlake, 2017). The new information brought to bear in this paper is the M·CAM database (Martin 2004, 2013; Luse and Martin 2014). This database includes traditional full-text patent and other IP data (such as state-granted rights) and includes both explicit citation information together with implicit conceptual association calculated using M·CAM’s proprietary linguistic genomic algorithms that provide estimates of the uniqueness, quality, and value chain associations of patents across companies. The M·CAM database is used to estimate a stock price index of companies determined to have the strongest ties between their holdings of intangible assets and the company’s future profitability. We find that (a) the intangibles-driven stock price index is 10 percent higher than the S&P 500 since its real-time inception in July 2015 and greatly outperforms the S&P 500 over its backcasted history, which extends to July 2007; (b) IP and other innovation assets are essential business assets of over 70 percent of the Standard & Poors 500 and the Russell 1000; and (c) that M·CAM’s sector-level IP data are “value added” indicators of the sector’s technological capability vis a vis “raw” indicators such as WIPO or USPTO patent counts
  • Weighting

    No specific weighting strategy is adopted when acquiring the data.
  • Technical Information

    Response Rates: We use publicly available patents and stock market performance data for companies around the globe. There is no response rate associated.
  • Technical Information

    Presence of Common Scales: quantitative and qualitative
Temporal Coverage
  • 2013-01-01 / 2019-09-30
    Time Period: Tue Jan 01 00:00:00 EST 2013--Mon Sep 30 00:00:00 EDT 2019
  • 2019-05-01 / 2019-09-30
    Collection Date(s): Wed May 01 00:00:00 EDT 2019--Mon Sep 30 00:00:00 EDT 2019
Geographic Coverage
  • Global
Sampled Universe
Patent and company stock market performance data. Smallest Geographic Unit: Developed countries
Sampling
The data is publicly available an there is no sampling issues associated.
Collection Mode
  • other;

Availability
Download
Relations
  • Is supplement to
    DOI: 10.1257/pandp.20201056 (Text)
Publications
  • Corrado, Carol, David Martin, and Qianfan Wu. “Innovation a: What Do IP-Intensive Stock Price Indexes Tell Us about Innovation?” AEA Papers and Proceedings 110 (May 2020): 31–35. https://doi.org/10.1257/pandp.20201056.
    • ID: 10.1257/pandp.20201056 (DOI)
  • Winer, David, David Martin, Jason Waston, and David Pratt. Method and system for graphical representation of multitemporal, multidimensional data relationships, issued December 16, 2003.
  • Andrews, Dan. “The Global Productivity Slowdown, Technology Divergence and Public Policy: A Firm Level Perspective.” OECD Productivity Working Papers: OECD, n.d.
  • Corrado, Carol. “How Do You Measure a ‘Technological Revolution.’” American Economic Review 100, no. 2 (n.d.).
  • Corrado, Carol. “Innovation and Intangible Investment in Europe, Japan, and the United States.” Oxford Review of Economic Policy 29, no. 2 (n.d.).
  • Deng, Houtao. “A Time Series Forest for Classification and Feature Extraction.” Information Sciences, n.d.

Update Metadata: 2020-05-18 | Issue Number: 2 | Registration Date: 2020-05-15

Corrado, Carol; Martin, David; Wu, Qianfan (2020): INNOVATION a: WHAT DO STOCK PRICE INDEXES OF IP-INTENSIVE COMPANIES TELL US ABOUT INNOVATION?. Version: 1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E117423V1