The Quality of Ideas: Measuring Innovation with Multiple Indicators

We model early expectations about the value and technological importance ('quality') of a patented innovation as a latent variable common to a set of four indicators: the number of patent claims, forward citations, backward citations and family size. The model is estimated for four technology areas using a sample of about 8000 U.S. patents applied for during 1960-91. We measure how much noise' each individual indicator contains and construct a more informative, composite measure of quality. The variance in quality', conditional on the four indicators, is just one-third of the unconditional variance. We show the variance reduction generated by subsets of indicators, and find forward citations to be particularly important. Our measure of quality is significantly related to subsequent decisions to renew a patent and to litigate infringements. Using patent and R&D data for 100 U.S. manufacturing firms, we find that adjusting for quality removes much of the apparent decline in research productivity (patent counts per R&D) observed at the aggregate level.

Community Detection and Growth Potential Prediction Using the Stochastic Block Model and the Long Short-term Memory from Patent Citation Networks

Scoring patent documents is very useful for technology management. However, conventional methods are based on static models and, thus, do not reflect the growth potential of the technology cluster of the patent. Because even if the cluster of a patent has no hope of growing, we recognize the patent is important if PageRank or other ranking score is high. Therefore, there arises a necessity of developing citation network clustering and prediction of future citations. In our research, clustering of patent citation networks by Stochastic Block Model was done with the aim of enabling corporate managers and investors to evaluate the scale and life cycle of technology. As a result, we confirmed nested SBM is appropriate for graph clustering of patent citation networks. Also, a high MAPE value was obtained and the direction accuracy achieved a value greater than 50% when predicting growth potential for each cluster by using LSTM.Comment: arXiv admin note: substantial text overlap with arXiv:1904.1204

Community Detection and Growth Potential Prediction from Patent Citation Networks

The scoring of patents is useful for technology management analysis. Therefore, a necessity of developing citation network clustering and prediction of future citations for practical patent scoring arises. In this paper, we propose a community detection method using the Node2vec. And in order to analyze growth potential we compare three ''time series analysis methods'', the Long Short-Term Memory (LSTM), ARIMA model, and Hawkes Process. The results of our experiments, we could find common technical points from those clusters by Node2vec. Furthermore, we found that the prediction accuracy of the ARIMA model was higher than that of other models.Comment: arXiv admin note: text overlap with arXiv:1607.00653 by other author

Strategic Patenting and Software Innovation

Strategic patenting is widely believed to raise the costs of innovating,especially in industries characterised by cumulative innovation. This paperstudies the effects of strategic patenting on R&D, patenting and marketvalue in the computer software industry. We focus on two key aspects:patent portfolio size which affects bargaining power in patent disputes, andthe fragmentation of patent rights (.patent thickets.) which increases thetransaction costs of enforcement. We develop a model that incorporates botheffects, together with R&D spillovers. Using panel data for the period 1980-99, we find evidence that both strategic patenting and R&D spilloversstrongly affect innovation and market value of software firms.patents, anti-commons, patent thickets, R&D spillovers, marketvalue

Patents, Thickets, and the Financing of Early-Stage Firms: Evidence from the Software Industry

The impact of stronger intellectual property rights in the software industry is controversial. One means by which patents can affect technical change, industry dynamics, and ultimately welfare, is through their role in stimulating or stifling entry by new ventures. Patents can block entry, or raise entrants' costs in variety of ways, while at the same time they may stimulate entry by improving the bargaining position of entrants vis-à-vis incumbents, and supporting a "market for technology" which enables new ventures to license their way into the market, or realize value through trade in their intangible assets. One important impact of patents may be their influence on capital markets, and here we find evidence that the extraordinary growth in patenting of software during the 1990s is associated with significant effects on the financing of software companies. Start-up software companies operating in markets characterized by denser patent thickets see their initial acquisition of VC funding delayed relative to firms in markets less affected by patents. The relationship between patents and the probability of IPO or acquisition is more complex, but there is some evidence that firms without patents are less likely to go public if they operate in a market characterized by patent thickets.

Measuring the impact of innovation on firm value: a new approach

Most of the existing empirical literature on the relationship of firm value and knowledge capital is based on the stock market valuation of companies. However, the assets of many firms are not publicly traded, and hence the calculation of market value is limited to a subsample of firms. We suggest to use a credit rating score instead and present an empirical analysis. It turns out that innovative firms, i.e. those with a reasonable knowledge stock, have a better credit rating and thus, as we propose, a higher value. However, too much of innovative activi-ties is seen as risky and the firm value decreases. --Firm Value,Credit Rating,Innovation,Intellectual Property Discrete Regression Models

Technology and Trade - an analysis of technology specialization and export flows

This paper examines how technology specialization, measured by citations-weighted patents, affects trade flows. The paper analyzes (i) the relationship between technology specialization and export specialization across regions and (ii) how the technology specialization of origin and destination affect the size and structure of link-specific export flows. We find that the export specialization of a region typically corresponds to the region’s technology specialization, which supports the view that comparative advantages can be created by investments in technology and knowledge. Export flows from regions to destination countries with similar technology specialization as the origin regions consist of commodities of higher quality in the specific technology, as indicated by higher prices. Highly specialized regions export more and charge higher prices. The results of the paper suggest that an understanding of trade ultimately requires an understanding of the spatial pattern of investments in (and creation of) technology and knowledge, as such investments shape export specialization patterns and the corresponding composition of export flows between locations across space.exports; technology; knowledge; specialization; quality; patents

Determinants of Renewable Energy Innovation: Environmental Policies vs. Market Regulation

This paper carries out a comprehensive analysis of renewable energy innovations considering four mechanisms suggested by innovation models: 1. policy-inducement; 2. market structure; 3. demand and social cohesion- mainly proxied by income inequality; 4. characteristics of country knowledge base. For OECD countries and years 1970-2005, we build a unique dataset containing time-varying information on quality-adjusted patent production in renewable energy, the latter being a function of environmental policies, green R&D, entry barriers, knowledge stock, knowledge diversity and income inequality. We develop count data models using the Generalized Method of Moments (GMM) to account for endogeneity of policy support. Our synthetic policy index positively affects innovations especially in countries with deregulated energy markets and low entry barriers. The effect of entry barriers and inequality is negative and of similar magnitude as that of policy. Product market liberalization positively affects green patent generation, especially so when ambitious policies are adopted, when the initial level of public R&D expenditures and when the initial share of distributed energy generation is high. Our results are robust to alternative specifications, to the inclusion of technology-specific effects and to the use of quality-adjusted patents as dependent variables. In the latter case, the estimated effect of lowering entry barriers and of knowledge diversity almost double on citation count relatively to patent count.renewable energy technology; patent; environmental policies; product market regulation; inequality

Determinants of Renewable Energy Innovation: environmental policies vs. market regulation

This paper carries out a comprehensive analysis of renewable energy innovations considering four mechanisms suggested by innovation models: 1. policy-inducement; 2. market structure; 3. demand and social cohesion- mainly proxied by income inequality; 4. characteristics of country knowledge base. For OECD countries and years 1970-2005, we build a unique dataset containing time-varying information on quality-adjusted patent production in renewable energy, the latter being a function of environmental policies, green R&D, entry barriers, knowledge stock, knowledge diversity and income inequality. We develop count data models using the Generalized Method of Moments (GMM) to account for endogeneity of policy support. Our synthetic policy index positively affects innovations especially in countries with deregulated energy markets and low entry barriers. The effect of entry barriers and inequality is negative and of similar magnitude as that of policy. Product market liberalization positively affects green patent generation, especially so when ambitious policies are adopted, when the initial level of public R&D expenditures and when the initial share of distributed energy generation is high. Our results are robust to alternative specifications, to the inclusion of technology-specific effects and to the use of quality-adjusted patents as dependent variables. In the latter case, the estimated effect of lowering entry barriers and of knowledge diversity almost double on citation count relatively to patent count.renewable energy technology, patent, environmental policies, product market regulation, inequality

Growth through Heterogeneous Innovations

We study how exploration versus exploitation innovations impact economic growth through a tractable endogenous growth framework that contains multiple innovation sizes, multi-product firms, and entry/exit. Firms invest in exploration R&D to acquire new product lines and exploitation R&D to improve their existing product lines. We model and show empirically that exploration R&D does not scale as strongly with firm size as exploitation R&D. The resulting framework conforms to many regularities regarding innovation and growth differences across the firm size distribution. We also incorporate patent citations into our theoretical framework. The framework generates a simple test using patent citations that indicates that entrants and small firms have relatively higher growth spillover effects.: Endogenous Growth, Innovation, Exploration, Exploitation, Research and Development, Patents, Citations, Scientists, Entrepreneurs.