Buy, Keep, or Sell: Economic Growth and the Market for Ideas
Ufuk Akcigit, Murat Alp Celik, Jeremy Greenwood
Econometrica,
No. 3,
2016
Abstract
An endogenous growth model is developed where each period firms invest in researching and developing new ideas. An idea increases a firm's productivity. By how much depends on the technological propinquity between an idea and the firm's line of business. Ideas can be bought and sold on a market for patents. A firm can sell an idea that is not relevant to its business or buy one if it fails to innovate. The developed model is matched up with stylized facts about the market for patents in the United States. The analysis gauges how efficiency in the patent market affects growth.
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Does the Technological Content of Government Demand Matter for Private R&D? Evidence from US States
Viktor Slavtchev, Simon Wiederhold
American Economic Journal: Macroeconomics,
No. 2,
2016
Abstract
Governments purchase everything from airplanes to zucchini. This paper investigates the role of the technological content of government procurement in innovation. In a theoretical model, we first show that a shift in the composition of public purchases toward high-tech products translates into higher economy-wide returns to innovation, leading to an increase in the aggregate level of private R&D. Using unique data on federal procurement in US states and performing panel fixed-effects estimations, we find support for the model's prediction of a positive R&D effect of the technological content of government procurement. Instrumental-variable estimations suggest a causal interpretation of our findings.
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The Diablo 3 Economy: An Agent Based Approach
Makram El-Shagi, Gregor von Schweinitz
Computational Economics,
No. 2,
2016
Abstract
Designers of MMOs such as Diablo 3 face economic problems much like policy makers in the real world, e.g. inflation and distributional issues. Solving economic problems through regular updates (patches) became as important to those games as traditional gameplay issues. In this paper we provide an agent framework inspired by the economic features of Diablo 3 and analyze the effect of monetary policy in the game. Our model reproduces a number of features known from the Diablo 3 economy such as a heterogeneous price development, driven almost exclusively by goods of high quality, a highly unequal wealth distribution and strongly decreasing economic mobility. The basic framework presented in this paper is meant as a stepping stone to further research, where our evidence is used to deepen our understanding of the real-world counterparts of such problems. The advantage of our model is that it combines simplicity that is inherent to model economies with a similarly simple observable counterpart (namely the game environment where real agents interact). By matching the dynamics of the game economy we can thus easily verify that our behavioral assumptions are good approximations to reality.
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Transition to Clean Technology
Daron Acemoglu, Ufuk Akcigit, Douglas Hanley, William R. Kerr
Journal of Political Economy,
No. 1,
2016
Abstract
We develop an endogenous growth model in which clean and dirty technologies compete in production. Research can be directed to either technology. If dirty technologies are more advanced, the transition to clean technology can be difficult. Carbon taxes and research subsidies may encourage production and innovation in clean technologies, though the transition will typically be slow. We estimate the model using microdata from the US energy sector. We then characterize the optimal policy path that heavily relies on both subsidies and taxes. Finally, we evaluate various alternative policies. Relying only on carbon taxes or delaying intervention has significant welfare costs.
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Types of Cooperation Partners as Determinants of Innovation Failures
Walter Hyll, Gunnar Pippel
Technology Analysis and Strategic Management,
No. 4,
2016
Abstract
In this paper we analyse if specific R&D cooperation partners are related to an increase in the probability of innovation failures in terms discontinuing innovation projects. We distinguish between seven different R&D cooperation partner types, and we discriminate between product innovation failures and process innovation failures. Using German Community Innovation Survey data we find that, firstly, each type of R&D cooperation partner has a different effect on innovation failures. Secondly, we show that product innovation failures and process innovation failures are not affected in equal measure by the same type of R&D cooperation partner. Our results suggest that while R&D cooperation with public research institutes is significantly and negatively related to the probability to cancel a process innovation project, the coefficient is positive but insignificant for product innovation failures. Firms conducting partnerships with suppliers, however, run the risk of both product and process innovation failures. In turn, cooperation with competitors is positively correlated only to process innovation failures.
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Im Fokus: Industrielle Kerne in Ostdeutschland und wie es dort heute aussieht – Das Beispiel des Chemiestandorts Bitterfeld-Wolfen
Gerhard Heimpold
Wirtschaft im Wandel,
No. 6,
2015
Abstract
Der Erhalt industrieller Kerne war eines der wirtschaftspolitischen Ziele beim Aufbau Ost. Einer dieser Kerne ist der Chemiestandort Bitterfeld-Wolfen in Sachsen-Anhalt. Der Beitrag untersucht, wie es nach 25 Jahren Deutscher Einheit um diesen industriellen Kern bestellt ist. In einem Satz: Der Kern ist nicht mehr der alte. Die Kombinate der Großchemie waren als Ganzes nicht privatisierbar. An ihre Stelle sind moderne mittelständische Chemiebetriebe getreten. Daneben haben sich neue Branchen, etwa die Glasindustrie, angesiedelt, und in Gestalt einer attraktiven Seenlandschaft ist aus den Braunkohlentagebauen etwas völlig Neues entstanden. Bei den Forschungsaktivitäten kann die Region aber mit westdeutschen Verhältnissen nicht mithalten. Die vielleicht größte künftige Herausforderung wird in einer demographisch bedingt rückläufigen Erwerbspersonenzahl liegen.
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A Review of Empirical Research on the Design and Impact of Regulation in the Banking Sector
Sanja Jakovljević, Hans Degryse, Steven Ongena
Annual Review of Financial Economics,
2015
Abstract
We review existing empirical research on the design and impact of regulation in the banking sector. The impact of each individual piece of regulation may inexorably depend on the set of regulations already in place, the characteristics of the banks involved (from their size or ownership structure to operational idiosyncrasies in terms of capitalization levels or risk-taking behavior), and the institutional development of the country where the regulation is introduced. This complexity is challenging for the econometrician, who relies either on single-country data to identify challenges for regulation or on cross-country data to assess the overall effects of regulation. It is also troubling for the policy maker, who has to optimally design regulation to avoid any unintended consequences, especially those that vary over the credit cycle such as the currently developing macroprudential frameworks.
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Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information
Christiane Baumeister, James D. Hamilton
Econometrica,
No. 5,
2015
Abstract
This paper makes the following original contributions to the literature. (i) We develop a simpler analytical characterization and numerical algorithm for Bayesian inference in structural vector autoregressions (VARs) that can be used for models that are overidentified, just‐identified, or underidentified. (ii) We analyze the asymptotic properties of Bayesian inference and show that in the underidentified case, the asymptotic posterior distribution of contemporaneous coefficients in an n‐variable VAR is confined to the set of values that orthogonalize the population variance–covariance matrix of ordinary least squares residuals, with the height of the posterior proportional to the height of the prior at any point within that set. For example, in a bivariate VAR for supply and demand identified solely by sign restrictions, if the population correlation between the VAR residuals is positive, then even if one has available an infinite sample of data, any inference about the demand elasticity is coming exclusively from the prior distribution. (iii) We provide analytical characterizations of the informative prior distributions for impulse‐response functions that are implicit in the traditional sign‐restriction approach to VARs, and we note, as a special case of result (ii), that the influence of these priors does not vanish asymptotically. (iv) We illustrate how Bayesian inference with informative priors can be both a strict generalization and an unambiguous improvement over frequentist inference in just‐identified models. (v) We propose that researchers need to explicitly acknowledge and defend the role of prior beliefs in influencing structural conclusions and we illustrate how this could be done using a simple model of the U.S. labor market.
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Support for Public Research Spin-offs by the Parent Organizations and the Speed of Commercialization
Viktor Slavtchev, D. Göktepe-Hultén
Abstract
We empirically analyze whether support by the parent organization in the early (nascent and seed) stage speeds up the process of commercialization and helps spin-offs from public research organizations generate first revenues sooner. To identify the impact of support by the parent organization, we apply multivariate regression techniques as well as an instrumental variable approach. Our results show that support in the early stage by the parent organization can speed up commercialization. Moreover, we identify two distinct channels - the help in developing a business plan and in acquiring external capital - through which support by the parent organization can enable spin-offs to generate first revenues sooner.
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The Structure and Evolution of Inter-sectoral Technological Complementarity in R&D in Germany from 1990 to 2011
T. Broekel, Matthias Brachert
Journal of Evolutionary Economics,
No. 4,
2015
Abstract
Technological complementarity is argued to be a crucial element for effective R&D collaboration. The real structure is, however, still largely unknown. Based on the argument that organizations’ knowledge resources must fit for enabling collective learning and innovation, we use the co-occurrence of firms in collaborative R&D projects in Germany to assess inter-sectoral technological complementarity between 129 sectors. The results are mapped as complementarity space for the Germany economy. The space and its dynamics from 1990 to 2011 are analyzed by means of social network analysis. The results illustrate sectors being complements both from a dyadic and portfolio/network perspective. This latter is important, as complementarities may only become fully effective when integrated in a complete set of different knowledge resources from multiple sectors. The dynamic perspective moreover reveals the shifting demand for knowledge resources among sectors at different time periods.
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