State-Dependent Intellectual Property Rights Policy

What form of intellectual property rights (IPR) policy contributes to economic growth? Should technological followers be able to license the products of technological leaders? Should a company with a large technological lead receive the same IPR protection as a company with a more limited lead? We develop a general equilibrium framework to investigate these questions. The economy consists of many industries and firms engaged in cumulative (step-by-step) innovation. IPR policy regulates whether followers in an industry can copy the technology of the leader and also how much they have to pay to license past innovations. With full patent protection, followers can catch up to the leader in their industry either by making the same innovation(s) themselves or by making some pre-specified payments to the technological leaders. We prove the existence of a steady-state equilibrium and characterize some of its properties. We then quantitatively investigate the implications of different types of IPR policy on the equilibrium growth rate. The two major results of this exercise are as follows. First, the growth rate in the standard models used in the (growth) literature can be improved significantly by introducing a simple form of licensing. Second, we show that full patent protection is not optimal from the viewpoint of maximizing the growth rate of the economy and that the growth-maximizing policy involves state-dependent IPR protection, providing greater protection to technological leaders that are further ahead than those that are close to their followers. This form of the growth-maximizing policy is a result of the "trickle-down" effect, which implies that providing greater protection to firms that are further ahead of their followers than a certain threshold increases the R&D incentives also for all technological leaders that are less advanced than this threshold.

The Role of Information in Competitive Experimentation

Technological progress is typically a result of trial-and-error research by competing firms. While some research paths lead to the innovation sought, others result in dead ends. Because firms benefit from their competitors working in the wrong direction, they do not reveal their dead-end findings. Time and resources are wasted on projects that other firms have already found to be dead ends. Consequently, technological progress is slowed down, and the society benefits from innovations with delay, if ever. To study this prevalent problem, we build a tractable two-arm bandit model with two competing firms. The risky arm could potentially lead to a dead end and the safe arm introduces further competition to make firms keep their dead-end findings private. We characterize the equilibrium in this decentralized environment and show that the equilibrium necessarily entails significant efficiency losses due to wasteful dead-end replication and a flight to safety – an early abandonment of the risky project. Finally, we design a dynamic mechanism where firms are incentivized to disclose their actions and share their private information in a timely manner. This mechanism restores efficiency and suggests a direction for welfare improvement.

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.

The Role of Information Innovation and Competition

Innovation is typically a trial-and-error process. While some research paths lead to the innovation sought, others result in dead ends. Because firms benefit from their competitors working in the wrong direction, they do not reveal their dead-end findings. Time and resources are wasted on projects that other firms have already found to be fruitless. This is a major problem, particularly in industries that rely heavily on trial-and-error research. We offer a simple model with two firms and two research lines to study this prevalent problem. We characterize the equilibrium in a decentralized environment that necessarily entails significant efficiency losses due to wasteful dead-end replication and a flight to safety--an early abandonment of the risky project. We show that different types of firms follow different innovation strategies and create different kinds of welfare losses. In an extension of the core model, we also study a centralized mechanism whereby firms are incentivized to disclose their actions and share their private information in a timely manner

Patent Value and Citations: Creative Destruction or Strategic Disruption?

Prior work suggests that more valuable patents are cited more and this view has become standard in the empirical innovation literature. Using an NPE-derived dataset with patent-specific revenues we find that the relationship of citations to value in fact forms an inverted-U, with fewer citations at the high end of value than in the middle. Since the value of patents is concentrated in those at the high end, this is a challenge to both the empirical literature and the intuition behind it. We attempt to explain this relationship with a simple model of innovation, allowing for both productive and strategic patents. We find evidence of greater use of strategic patents where it would be most expected: among corporations, in fields of rapid development, in more recent patents and where divisional and continuation applications are employed. These findings have important implications for our basic understanding of growth, innovation, and intellectual property policy

Essays on growth and innovation policies

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, 2009.Includes bibliographical references.This thesis consists of three chapters on innovation and economic growth. Chapter 1 is a joint work with Daron Acemoglu. We study the form of intellectual property rights (IPR) policy and licensing in the context of endogenous economic growth with step-by-step cumulative innovation. The main questions of the analysis are as follows. Should a company with a large technological lead receive the same IPR protection as a company with a more limited advantage? Should technological followers be able to license the products of technological leaders? We propose a general equilibrium framework to investigate these questions. IPR policy regulates whether followers in an industry can copy the technology of the leader and also how much they have to pay to license past innovations. We prove the existence of a steady-state equilibrium and characterize some of its properties. We then quantitatively investigate the implications of different types of IPR policy on the equilibrium growth rate and welfare. The two major results of this exercise are as follows. First, the growth rate and welfare in the standard models used in the (growth) literature can be improved significantly by introducing a simple form of licensing. Second and more importantly, full patent protection is not optimal from the viewpoint of maximizing welfare; instead, welfare-maximizing (and growth-maximizing) policy involves state-dependent IPR protection, providing greater protection to technological leaders that are further ahead than those that are close to their followers.(cont.) This form of the welfare-maximizing policy is a result of the "trickle-down"effect, which implies that providing greater protection to firms that are further ahead of their followers than a certain threshold increases the R&D incentives also for all technological leaders that are less advanced than this threshold. Chapter 2 is an empirical study that analyses the relationship between firm size and innovation. The common practice in the endogenous growth literature is to assume a constant innovation quality (size) and focus only on innovation frequency. In this chapter, I test the validity of this assumption using Compustat and USPTO patent data to examine the relationship between firm size and innovation quality. Since R&D investment is the input and firm growth is the result of innovation, this chapter studies the relationship between firm size - firm growth and firm size - R&D intensity as well. The reduced form results uncover three stylized facts: Smaller firm grow faster, are more R&D intensive and more interestingly, produce higher quality innovations. These results are robust, among many other things, to sample selection and to differences in patenting behaviors. In Chapter 3, I propose a theoretical model to understand the microfoundations underlying these stylized facts. In this model, technologically heterogenous firms compete for innovation. A novelty of this model is that firms can endogenously choose not only the probability of innovation, but also the innovation quality.(cont.) I prove the existence of the equilibrium and show that the model's predictions are consistent with the aforementioned reduced form evidences. These results rely on two assumptions: the concavity of the profit function with respect to firm size and the constant returns to scale property of the R&D production function. The intuition is that, when profits are concave, the incentives for radical innovation diminishes as firm size increases. As a result, R&D intensity and firm growth also decrease. Next, I estimate the structural parameters of the model using Simulated Methods of Moments and use the results to conduct a policy experiment. Since firms in this model do not internalize the positive externalities that they generate on other firms, there is underinvestment in R&D, so that there is scope for policy action through size-dependent R&D subsidies. In conclusion of this policy experiment, the optimal size-dependent R&D subsidy policy does considerably better than optimal uniform (size-independent) policy. Moreover, supporting small firms is more growth-enhancing than subsidizing big firms. For a large range of values for the elasticity of substitution, the growth enhancing effect dominates the negative impact of public spending on initial consumption. Therefore, the optimal (welfare-maximizing) policy provides higher subsidies to smaller firms.by Ufuk, Akcigit.Ph.D

Transition to Clean Technology

We develop a microeconomic model of endogenous growth where clean and dirty technologies compete in production and innovation, in the sense that research can be directed to either clean or dirty technologies. If dirty technologies are more advanced to start with, the potential transition to clean technology can be difficult both because clean research must climb several rungs to catch up with dirty technology and because this gap discourages research effort directed towards clean technologies. Carbon taxes and research subsidies may nonetheless encourage production and innovation in clean technologies, though the transition will typically be slow. We characterize certain general properties of the transition path from dirty to clean technology. We then estimate the model using a combination of regression analysis on the relationship between R&D and patents, and simulated method of moments using microdata on employment, production, R&D, firm growth, entry and exit from the US energy sector. The model's quantitative implications match a range of moments not targeted in the estimation quite well. We then characterize the optimal policy path implied by the model and our estimates. Optimal policy makes heavy use of research subsidies as well as carbon taxes. We use the model to evaluate the welfare consequences of a range of alternative policies

Innovation network

Technological progress builds upon itself, with the expansion of invention in one domain propelling future work in linked fields. Our analysis uses 1.8 million US patents and their citation properties to map the innovation network and its strength. Past innovation network structures are calculated using citation patterns across technology classes during 1975–1994. The interaction of this preexisting network structure with patent growth in upstream technology fields has strong predictive power on future innovation after 1995. This pattern is consistent with the idea that when there is more past upstream innovation for a particular technology class to build on, then that technology class innovates more