Technological Innovation , Resource Allocation and Growth ∗

We explore the role of technological innovation as a source of economic growth by constructing direct measures of innovation at the firm level. We combine patent data for US firms from 1926 to 2010 with the stock market response to news about patents to assess the economic importance of each innovation. We use our innovation measure to directly test the predictions of a Schumpeterian growth model, where innovation takes the form of quality improvements in existing product lines. Consistent with the model, innovation is associated with significant patterns of capital and labor reallocation, increases in productivity and output growth. JEL classifications: G14, E32, O3, O4 ∗We thank Hal Varian for helping us in extracting information on Patents from Google Patents database. We are grateful to Frederico Belo, Nick Bloom, John Cochrane, Iain Cockburn, Carola Frydman, Yuriy Gorodnichenko, John Heaton, Adam Jaffe, Pete Klenow, Josh Lerner, Gustavo Manso, Petra Moser, Tom Nicholas, Stavros Panageas, Jonathan Parker, Monika Piazzesi and Heidi Williams for detailed comments. We also thank seminar participants at AEA, Boston University, Columbia Business School, Duke/UNC Asset Pricing Conference, FRB Chicago, NBER Asset Pricing, NBER Economic Fluctuations and Growth, NBER Entrepreneurship, NBER Productivity, Northwestern, NYU, and SITE for helpful discussions. We are grateful to Tom Nicholas for sharing his patent citations data. The authors thank the Fama-Miller Center at University of Chicago, the Zell Center and the Jerome Kenney Fund for financial assistance. †MIT Sloan and NBER ‡Kellogg School of Management and NBER §Booth School of Business and NBER ¶Kelly School of Business Since Schumpeter, economists have argued that technological innovation is a key driver of economic growth. Models of endogenous growth have rich testable predictions about both aggregate quantities and the cross-section of firms, linking improvements in the technology frontier to resource reallocation and subsequent economic growth. However, the predictions of these models are difficult to test directly, mainly due to the scarcity of directly observable measures of technological innovation. For instance, to study the relation between firm decisions and innovation, an ideal measure of innovation should capture the ex-ante private economic value of new inventions, and be comparable both across industries and across time. This paper aims to fill this gap by constructing an economic measure of innovation that can be used to study the predictions of Schumpeterian growth models. We propose a new measure of innovation, combining a novel dataset of patent grants over the period 1926 to 2010 with stock market data. Patents provide useful direct information about technological innovation going as far back as the eighteenth century. However, patents tend to be heterogenous in economic value, hence a simple patent count is unlikely to be informative. Our central idea is to use the stock market reaction around the day each patent is granted to appropriately weigh its information content. Indeed, asset prices offer a promising path, since they are forward looking and are therefore sensitive to the determinants of economic growth. Consistent with this view, we find that trading activity in the stock of the firm that issued a patent increases after the patent issuance date. We interpret the stock price reaction to patent grants using a model along the lines of Grossman and Helpman (1991). Even though our empirical analysis is motivated by this model, the insights obtained are common in a variety of models of endogenous growth. In our model, technological innovation manifests as quality improvements in existing product lines. Our model retains the key features of the framework of Grossman and Helpman (1991) – growth through creative destruction – but we allow both the aggregate rate of technological progress, as well as the quality improvement each innovation represents, to be stochastic. Patents are valuable to their owners because they restrict competition among producers of the leading product vintages. Following a successful patent application, the prior uncertainty about the applying firm’s ability to extract monopoly rents going forward is resolved, resulting in the firm’s stock price appreciation. The magnitude of this stock price appreciation is increasing in the market value of the patent, which is a function of the quality of the latest vintage as well as the quality improvement embodied in the good covered by the patent. We construct an estimate of the private value of the patent by filtering the firm’s stock market reaction around the days that patents are issued to the firm. The distribution of the estimated patent values is fat-tailed, consistent with past research describing the Several new studies exploit the same source of patent data (Google Patents) as we do in our paper. For instance, see Moser and Voena (2012), Moser, Voena, and Waldinger (2012) and Lampe and Moser (2011). Not all innovation is patentable. However, innovation that is embodied in new products is more easily patentable (see for example Comin, 2008, for a discussion on patentable innovation). Hence, when we are measuring innovation through patents we are capturing technological change embodied in new products.