Technological Innovation, Resource Allocation, and Growth

By Leonid Kogan, Dimitris Papanikolaou, Amit Seru, Noah Stoffman. 2012

879 citations recorded by the source corpus.

We propose a new measure of the economic importance of each innovation. Our measure uses newly collected data on patents issued to US firms in the 1926 to 2010 period, combined with the stock market response to news about patents. Our patent- level estimates of private economic value are positively related to the scientific value of these patents, as measured by the number of citations that the patent receives in the future. Our new measure is associated with substantial growth, reallocation and creative destruction, consistent with the predictions of Schumpeterian growth models. Aggregating our measure suggests that technological innovation accounts for significant medium-run fluctuations in aggregate economic growth and TFP. Our measure contains additional information relative to citation-weighted patent counts; the relation between our measure and firm growth is considerably stronger. Importantly, the degree of creative destruction that is associated with our measure is higher than previous estimates, confirming that it is a useful proxy for the private valuation of patents.

Subfields: Economics and Econometrics, Management of Technology and Innovation

View Paper: https://www.semanticscholar.org/paper/911dd5447a62a236e2f4e4c69c0e91d31892c380

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Citations in the corpus

New Frontiers: The Origins and Content of New Work, 1940–2018 (2022, methodology): “This is illustrated in Figure 5, which plots the occupational 25As an alternative we have followed Kogan et al. (2017) by assigning patents to industries directly, using patent awarded to firms in Center for Research in Security Prices records linked to Compustat data on the industry of these…”
Does Going Public Affect Innovation (2015, positive): “Indeed, Kogan et al. (2012) show that the stock market strongly, and positively, reacts to the approval of patents that are eventually highly cited, and that such patents predict both firm productivity and capital and labor flows from noninnovative to innovative firms within the industry.”
Corporate Venture Capital, Value Creation, and Innovation (2014, methodology): “As has now become standard in the innovation literature (e.g., Aghion et al, 2005; Seru, 2012; and Kogan et al, 2012), we use the National Bureau of Economics Research (NBER) Patent Citation database to construct two measures of innovation output: the number of patents generated by a firm as our…”
Is this time different? How digitalization influences job creation and destruction (2019, background): “After all, consistent with Schumpeter’s concept of creative destruction, the net impact on jobs seems to be positive (Mastrostefano and Pianta, 2009; Kogan et al., 2017).”
The Life Cycle of Corporate Venture Capital (2019, background): “Moreover, it is important to point out that citations are generally considered to be relevant to patent value (Kogan et al., 2017), so this “fewer citations-better profits” concern is further mitigated.”
The Real Effects of Real Earnings Management: Evidence from Innovation (2018, methodology): “14 We first combine the updated NBER patent data set developed by Hall et al. (2005b) and the patent data set of Kogan et al. (2017).”
Does Political Corruption Impede Firm Innovation? Evidence from the United States (2019, background): “Kogan et al. (2017) argue that patent citations may not fully capture the economic importance of each innovation and propose a quality measure using the stock market responses to news about patents.”