EconomicDynamics Newsletter
Volume 18, Issue 2 (November 2017)
The EconomicDynamics Newsletter is a free supplement to the Review of Economic Dynamics (RED). It is published twice a year in April and November.
In this issue
Christian Zimmermann, Jonathan Heathcote and Vincenzo Quadrini, Editors.
Research Agenda: Ufuk Akcigit on Innovation and Economic Growth
Ufuk Akcigit is Assistant Professor of Economics at the University of Chicago. He is interested in researching how firm dynamics and entrepreneurship influence economic growth through innovation. Akcigit’s RePEc/IDEAS entry.
Technological progress and innovation are the central determinants of economic growth. As a macroeconomist, the main focus of my research has been to understand the exact links between innovation and economic growth and to study the optimal policies to bolster them. The mapping between innovation and economic growth can be described broadly as
Firms → Inventors → Ideas → Aggregate Growth
where firms hire inventors to produce new ideas/technologies which lead to economic growth. In line with this mapping, my research topics can be broadly grouped into three categories: (i) firm studies, (ii) inventor studies, and (iii) idea (patent) studies. I have been a big proponent of the idea that our understanding of macroeconomic growth and technological progress can be significantly improved by combining micro and macro perspectives. A macroeconomy is made of micro firms that hire inventors to produce new innovative ideas. Therefore, my research–by focusing on the microeconomics of firms, inventors, and ideas–has aimed to shed light on economic growth by capturing the rich heterogeneity in innovation behavior at the firm level by using the wealth of information on firms and their innovations. Below, I describe my research projects related to these categories.
Firms
My first line of research consists of a series of papers that study various aspects of industry and firm dynamics. In Akcigit (2017), I explain the importance of firm-level studies and firm heterogeneity to provide a better connection between endogenous growth theory and micro-level data. I have also written a handbook chapter (Aghion, Akcigit, and Howitt, 2014) that succinctly documents part of my research agenda on firms. My research on firms can be grouped into three subgroups: (i) firms in developed countries, (ii) firms in developing countries, and (iii) networks.
Firms in Developed Countries
At the national and state level, governments transfer money from taxpayers to firms to encourage more research and development (R&D). Why do we do this? Aren’t there enough incentives already to develop new inventions and reap the corresponding rewards? On the one hand, competition among firms is encouraging firms to spend (potentially) too much in R&D. On the other hand, non-internalized positive spillovers from new technologies could mean that we do not invest enough into R&D. Which force is bigger? In addition, suppose that we did, in fact, have a shortfall in R&D spending. Does this mean every firm should receive the same amount of subsidy? How should we design the optimal innovation policies? These are some of the key questions that I have tried to answer in my research on firms. To this end, I have used general equilibrium models built on large databases of firms, to help determine whether, for example, enough R&D is already occurring in a given firm, industry, or region.
In Akcigit and Kerr (2017), we study how external versus internal innovations promote economic growth through a tractable endogenous growth framework with heterogeneous innovation qualities, multi-product firms, and entry/exit. Firms invest in external R&D to acquire new product lines and in internal R&D to improve their existing product lines. After estimating this model using patent data and the U.S. Census of firms, we study how firm size interacts with innovation incentives. We show that small firms produce disproportionately more and higher quality innovations and have larger spillovers. In Acemoglu, Akcigit, Alp, Bloom, and Kerr (2017), we build a model of firm-level innovation, productivity growth, and reallocation featuring endogenous entry and exit. A key feature is the selection between high- and low-type firms, which differ in terms of their innovative capacity. We find that industrial policy that subsidizes either the R&D or the continued operation of incumbents reduces growth and welfare. This illustrates the importance of firm heterogeneity in shaping policy. In Akcigit, Hanley, and Serrano-Velarde (2016), we study French firms and their incentives to do basic versus applied research. We find that firms that have a broader technological base are more likely to invest in basic research due to cross-industry spillovers. In addition, we study the role of universities in the macroeconomic growth process. In Acemoglu, Akcigit, and Celik (2017), we argue that openness to new, unconventional and disruptive ideas has a first-order impact on creative innovations. Using data on U.S. firms, their managers, and patents, we present robust evidence that openness to disruption is associated with more creative innovations. In Acemoglu, Akcigit, Hanley, and Kerr (2016), we study the optimal industrial policy to preserve natural resources and encourage firms to switch from dirty to green (clean) technologies. In Acemoglu and Akcigit (2012), we study the design of the optimal patent policy to bolster competition and innovation. In Aghion, Akcigit, Cagé, and Kerr (2016), we analyze the relationships between taxation, corruption, and economic growth and in Aghion, Akcigit, and Fernandez-Villaverde (2013), we study optimal capital taxation in an endogenous growth model.
While conducting this research, I noticed that informational frictions are among the biggest obstacles that prevent innovation. Therefore two of my projects are aimed at addressing this problem. First, 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. In Akcigit and Liu (2016), we provide a model to study this prevalent problem. We characterize the significant efficiency losses due to wasteful dead-end replication and a “flight to safety”–an early abandonment of the risky project. We also study a centralized mechanism whereby firms are incentivized to disclose their actions and share their private information in a timely manner. In Akcigit, Hanley, and Stantcheva (2016), we study the optimal design of R&D policies and corporate taxation to correct for technology spillovers across firms and the non-appropriability of innovations. Our key contribution is the consideration of asymmetric information: the government does not know which firms are the most productive. Simple, often used innovation policies, such as linear R&D subsidies and linear profit taxes, lead to large revenue losses relative to the optimal mechanism.
Firms in Developing Countries
An important part of my work has also focused on developing economies. Firm dynamics in developing countries show striking differences to those in developed countries. While some firms do grow as they age, most firms are simply stagnant and do not exit despite being small. In Akcigit, Alp, and Peters (2016), we ask to what extent these patterns could be driven by cross-country differences in the rule of law and the efficiency of managerial delegation. Three results emerge from our analysis: (i) The Indian economy suffers from a lack of selection, whereby a low rate of creative destruction allows lower-quality producers to survive. (ii) The high delegation efficiency in the U.S. is an important determinant of why U.S. firms are large. (iii) While managerial delegation is inefficient in India, its effect on the lifecycle of Indian firms is limited due to important complementarities between the delegation efficiency and other factors affecting firm growth. In Akcigit, Alp, Eden, and Nguyen (2017) we study the dynamics of technology adoption in Latin American countries. We present various empirical evidence to show the Latin America’s technology adoption patterns from the U.S. and their implications on their income gap relative to the U.S. economy.
Networks
The propagation of macroeconomic shocks through input-output and geographic networks can be a powerful driver of macroeconomic fluctuations. Understanding the nature and direction of these propagations are crucial for designing the right policies to mitigate their potential costs on the aggregate economy. Therefore in Acemoglu, Akcigit, and Kerr (2016a), we show that in the presence of Cobb-Douglas production functions and consumer preferences, which are the most commonly used functional forms in the literature, there is a specific pattern of economic transmission whereby demand-side shocks propagate upstream (to input supplying industries) and supply-side shocks propagate downstream (to customer industries) and that there is a tight relationship between the direct impact of a shock and the magnitudes of the downstream and the upstream indirect effects. We then provide supporting empirical evidence on these predictions from the U.S. economy.
Networks are also useful to understand economic growth. Technological progress builds upon itself, with the expansion of invention in one domain propelling future work in linked fields. In Acemoglu, Akcigit, and Kerr (2016b), we use 1.8 million U.S. patents and their citation properties to map the innovation network and its strength. The interaction of this pre-existing network with patent growth in upstream technology fields has strong predictive power on future innovation. 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.
In my various other projects, I continue to investigate the determinants of firm dynamics. What are the welfare impacts of international technological convergence? Relatedly, what are the impacts of policies that are used against this convergence, especially trade and innovation policies, on the U.S. economy and welfare? In Akcigit, Ates, and Impullitti (2017), we investigate these questions. We provide new empirical evidence, propose an original dynamic general equilibrium theory of international technology competition and economic growth, with a focus on transitional dynamics, and quantify the welfare implications. We assess the role of import tariffs and R&D subsidies as policy responses to foreign technological competition.
The process of creative destruction, whereby resources are reallocated from less productive incumbents to more productive new entrants, is key for productivity growth. Does this process take place seamlessly or do some firms rely on various means to prevent this from happening? In another ongoing work (Akcigit, Baslandze, and Lotti, 2017), we study the impact of political connections on creative destruction and reallocation in Italy. More specifically, incumbents might slow down new entry into their industries by relying on their political connections. On the other hand, new technologies might hit existing regulations (see the case of UBER in various countries, for instance) and political connections might help overcome such regulatory challenges. Our project sheds light on these different channels through which political connections shape firm dynamics and productivity growth in Italy. Among many other interesting results, we show that innovation intensity (patents per employee) decreases whereas politician intensity (number of politicians per employee) increases as a firm gains market power.
Many policies and fiscal incentives target self-employed entrepreneurs in an attempt to improve productivity. Key questions for these policies are, first, what and how strong effects they have on entry into self-employment and on self-employed incomes. Second, are the effects mostly due to real economic reactions, or rather to changes in the reporting of income? Do financial incentives matter most or are simpler administrative requirements key? In a recent project (Aghion, Akcigit, Lequien, and Stantcheva, 2017), we try to answer these questions, making use of individual tax returns data from the French internal revenue service over the period 1994-2012. We estimate a large value for tax simplicity of up to 650 euros per year per individual depending on the regime and activity. We also find sizable costs of tax complexity; agents are not immediately able to understand what the right regime choice is, leave significant money on the table, and learn over time. The cost of complexity is “regressive” in that it affects mostly the uneducated, low income, and low skill agents.
Inventors and Society
My second line of research has focused on understanding the incentives of inventors and the impact of innovations on individuals in the society. My papers on this topic can be grouped into three subgroups: (i) Modern-time inventors, (ii) historical inventors, and (iii) innovation and the society.
Modern-time Inventors
How does tax policy affect inventors? In Akcigit, Baslandze, and Stantcheva (2016), we study this question by examining the effect of top tax rates on inventors’ mobility across OECD countries since 1977. We put special emphasis on “superstar” inventors, those with the most and most valuable patents. We use data on inventors from the United States Patent Office to track inventors’ locations over time and combine it with international effective top tax rate data. We find that superstar top 1% inventors are significantly affected by top taxes rates when deciding on where to locate. Inventors who have worked in multinational companies are more likely to take advantage of tax differentials.
Who becomes an inventor? Allocating the right individuals into those jobs with large spillovers enhances economic growth. In Aghion, Akcigit, Hyytinen, and Toivanen (2017), using individual level data on a half million Finnish men, we study the relative importance of social origins, parental income, socioeconomic status, education, and own ability–as measured by IQ–on the probability of becoming an inventor. A first striking finding is that the relation between parental income and the probability to invent in our data mirrors that in both the contemporary and historical US even though Finland is one of the most equal and socially mobile societies. We find that the monetary resources of parents matter less than their education and that all parental characteristics are less important than a person’s own ability. IQ is a key determinant of whether someone obtains higher education. Thus, IQ impacts the probability to become an inventor both directly and also indirectly through education. We further find that family structure matters: parental divorce reduces the probability to become an inventor, and father’s income matters only if he lives with his son. Step-parents’ resources do not seem to matter. Finally, we find that IQ and father’s income are complements in the sense that having a high income father increases the probability of inventing more for high IQ individuals, suggesting that high IQ individuals may fall victims to misallocation of talent.
Does interacting with others in the society contribute to human capital accumulation? In Akcigit, Caicedo, Miguelez, Stantcheva, and Sterzi (2017), we answer this question by using a new panel dataset on European inventors matched to their employers and patents since the 1980s. We first document some key empirical facts in the data that motivate the key ingredients in our model. Most patents are the result of collaborative work. More interactions are very strongly correlated with higher subsequent productivities of inventors, especially interactions with superstars. We build an innovation-led growth model in which inventors can learn in two ways: by meeting other inventors, at an endogenously chosen rate, and through an exogenous, age-dependent process that can capture alternative learning channels, such as learning-by-doing. We find that the endogenous interaction channel among inventors accounts for a very large fraction of overall economic growth and that policies that hampers worker mobility across firms can hinder this process.
Historical Inventors
An important part of my research has been devoted on understanding innovations, inventors, and economic growth from a historical perspective. To this end, in Akcigit, Grigsby, and Nicholas (2017b), we examine the golden age of U.S. innovation by undertaking a major data collection exercise, digitizing the hard copies of the historical patent records since 1836 and linking inventors from those historical patents to Federal Censuses between 1880 and 1940, and to state and county-level aggregates. We identify a strong relationship between patented inventions and long-run economic growth. We find that patenting activity is positively related to commonly postulated drivers of regional performance including population density, financial development and geographic connectedness. We then profile the characteristics of inventors and their life cycle, and find that inventors were highly educated. They delayed marriage, and tended to migrate to places that were conducive to innovation. Father’s income and education were positively correlated with becoming an inventor, though not when controlling for the child’s education. There were strong financial returns to technological development. Finally, we document a negative relationship between income inequality and innovation. Innovative places also tended to be more socially mobile. Our new data help to address important questions related to innovation and long-run growth dynamics.
Using this new data, in Akcigit, Grigsby, and Nicholas (2017a) we provide new evidence of the impact of immigrants on US innovation and document labor market outcomes for migrant inventors. We show that technology areas where immigrant inventors were more prevalent between 1880 and 1940 experienced faster growth between 1940 and 2000. We also show that immigrant inventors were more productive during their life cycle than native born inventors, although they received significantly lower wage levels than their native born counterparts.
In an ongoing project, Akcigit, Grigsby, Nicholas, and Stantcheva (2017), we take a historical perspective to study the effects of personal and corporate income taxation on innovation by firms and inventors in the United States since 1880. Despite the visceral debates about the negative impacts of taxation on growth, there has been a lack of empirical evidence on this issue. We fill this gap by making use of our new historical data on patents, inventors, firms, and state-level taxes in the United States. First, we specifically study the effects of taxation on the quantity and, importantly, quality of innovation, which we can directly measure using the long-run patent and inventor data since 1880. Second, we provide very long-run evidence on the effects of both personal income and corporate income taxation in the U.S. Third, we assess the impacts of these taxes on individual inventors and on firms and their R&D labs.
Innovation and Society
Some of my research effort has been devoted to understanding the social implications of innovation. Does higher GDP per capita or GDP growth increase happiness? The existing empirical literature on happiness and income looks at how various measures of subjective wellbeing (SWB) relate to income or income growth, but without looking in further detail at what drives the growth process and at how the determinants of growth affect wellbeing. In Aghion, Akcigit, Deaton, and Roulet (2016), we analyze the relationship between turnover-driven growth and subjective wellbeing. We show that: (i) the effect of creative destruction on expected individual welfare should be unambiguously positive if we control for unemployment, less so if we do not; (ii) job creation has a positive and job destruction has a negative impact on wellbeing; (iii) job destruction has a less negative impact in US Metropolitan Statistical Areas (MSA) within states with more generous unemployment insurance policies; (iv) job creation has a more positive effect on individuals that are more forward-looking.
The past decades have witnessed a sharp increase in top income inequality in many countries. However no consensus has been reached as to the main underlying factors behind this increase. In Aghion, Akcigit, Bergeaud, Blundell, and Hémous (2015b), we argue that in the U.S., innovation has certainly been one such factor. We use cross-state panel data to show that top income inequality is related to innovation. Second, we argue that this correlation reflects a causal effect of innovation-led growth on top income inequality. Third, we show that the effect of innovation is strongest after two years and disappears after five years. Finally, we show that innovation is positively correlated with social mobility, but less so in states with more intense lobbying activities.
Ideas
The third line of my research has focused on ideas. New ideas are the seeds for economic growth. The rise in living standards depends on the effectiveness of transforming new ideas into consumer products or production processes. Incarnating an idea into a product or a production process is by no means immediate. What happens to ideas and patents once they are produced? While a lot of the policy discussions center around increasing the number of ideas/patents/technologies produced, very little attempt is made at understanding how these new ideas are utilized after their invention. I have tried to fill this gap in a number of papers described next.
Ideas are not necessarily born to their best users and firms often develop patents that are not close to their primary business activity. This initial “mismatch” could potentially be mitigated in a secondary market where firms can buy and sell patents through patent agents (intermediaries). In Akcigit, Celik, and Greenwood (2016), we study the secondary market for ideas (patents) in the U.S. We build an endogenous growth model where firms invest in R&D to produce new ideas. An idea increases a firm’s productivity. By how much depends on the technological distance 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 U.S. The analysis gauges how efficiency in the patent market affects growth.
What determines the value of a patent? How can we proxy for a patent’s value? Prior work suggests that more valuable patents are cited more and this view has become standard in the empirical innovation literature. In Abrams, Akcigit, and Popadak (2013), we make use of a completely new dataset that contains patent-specific revenues from various non-practicing entities (NPEs) and 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. We explain this relationship with a simple model of innovation, allowing for both productive and strategic patents, which are used to block entry. We find evidence of greater use of strategic patents where it would be most expected: among corporations, in fields of rapid development, and for more recent patents. These findings have important implications for our basic understanding of growth, innovation, and intellectual property policy.
The market for patents suffers from various frictions and so-called “patent trolls” or NPEs have emerged due to these frictions. Despite the popularity of NPEs in the media and among policy circles, there is almost no systematic evidence on their business activities. How do non-practicing entities impact innovation and technological progress? The question has enormous importance for industrial policy, with virtually no direct empirical evidence to start answering it. In ongoing work (Abrams, Akcigit, and Oz, 2017), we take a major step in this direction and make use of our NPE-derived patent and financial data to answer this question. In doing so we inform the debate that has portrayed NPEs alternatively as benign middlemen that help to reallocate IP to where it is most productive or stick-up artists that exploit the patent system to extract rents, thereby hurting innovation. We find that NPEs target patents coming from small firms that are more litigation-prone, and patents from large firms that are not core to a company’s business. When NPEs license patents, those that generate higher fees are closer to the licensee’s business and more likely to be litigated.
Where do ideas come from? How does technological progress occur? Is the nature of idea creation stable over time? In ongoing work (Akcigit, Kerr, and Nicholas, 2017), we shed new light on these questions through a mixture of empirics and theory. We begin with an empirical analysis of all the U.S. patents granted since 1836. This analysis reveals several striking facts that emphasize the increasing importance of novel combinations of technologies for U.S. patents, compared to either new technology development or the reuse/refinement of older technology combinations, and the localized nature of these recombinations. We also build an endogenous growth model that can match these facts and illustrate the underlying mechanics of the technological development process.
Going forward, my research will continue to investigate the determinants of economic growth and innovation using historical and modern-time data, new theoretical frameworks and structural and quantitative analysis.
References
Abrams, David S., Ufuk Akcigit, and Gokhan Oz. 2017. “Patent Trolls: Benign Middleman or Stick-Up Artist?,” University of Chicago, Working Paper.
Abrams, David S., Ufuk Akcigit, and Jilian Popadak. 2013. “Patent Value and Citations: Creative Destruction or Strategic Disruption?,” NBER Working Paper 19647.
Acemoglu, Daron, and Ufuk Akcigit. 2012. “Intellectual Property Rights Policy, Competition and Innovation,” Journal of the European Economic Association, 10(1), 1–42.
Acemoglu, Daron, Ufuk Akcigit, Harun Alp, Nicholas Bloom, and William R. Kerr. 2017. “Innovation, Reallocation, and Growth,” NBER Working Paper 18993.
Acemoglu, Daron, Ufuk Akcigit, and Murat A. Celik. 2017. “Young, Restless and Creative: Openness to Disruption and Creative Innovations,” NBER Working Paper 19894.
Acemoglu, Daron, Ufuk Akcigit, Douglas Hanley, and William Kerr. 2016. “Transition to Clean Technology,” Journal of Political Economy, 124(1), 52–104.
Acemoglu, Daron, Ufuk Akcigit, and William R. Kerr. 2016a. “Networks and the Macroeconomy: An Empirical Exploration,” NBER Macroeconomics Annual, 30(1), 273–335.
Acemoglu, Daron, Ufuk Akcigit, and William R. Kerr. 2016b. “Innovation Network,” Proceedings of the National Academy of Sciences, 113(41), 11483–11488.
Aghion, Philippe, Ufuk Akcigit, Antonin Bergeaud, Richard Blundell, and David Hémous. 2015b. “Innovation and Top Income Inequality,” NBER Working Paper 21247.
Aghion, Philippe, Ufuk Akcigit, Julia Cagé, and William R. Kerr. 2016. “Taxation, Corruption, and Growth,” European Economic Review, 86, 24–51.
Aghion, Philippe, Ufuk Akcigit, Angus Deaton, and Alexandra Roulet. 2016. “Creative Destruction and Subjective Wellbeing,” American Economic Review, 106(12), 3869–3897.
Aghion, Philippe, Ufuk Akcigit, and Jesús Fernández-Villaverde. 2013. “Optimal Capital versus Labor Taxation with Innovation-Led Growth,” NBER Working Paper 19086.
Aghion, Philippe, Ufuk Akcigit, and Peter Howitt. 2014. “What Do We Learn From Schumpeterian Growth Theory?,” in Handbook of Economic Growth, vol. 2, pp. 515–563. Elsevier.
Aghion, Philippe, Ufuk Akcigit, Ari Hyytinen, and Otto Toivanen. 2017. “Social Origins of Inventors,” University of Chicago, work in progress.
Aghion, Philippe, Ufuk Akcigit, Matthieu Lequien, and Stefanie Stantcheva. 2017. “Tax Simplicity and Heterogeneous Learning,” NBER Working Paper 24049.
Akcigit, Ufuk. 2017. “Economic Growth: The Past, the Present, and the Future,” Journal of Political Economy, 125, Commemorative essay in “The Past, Present, and Future of Economics: A Celebration of the 125 Year Anniversary of the JPE and of Chicago Economics,” edited by John List and Harald Uhlig.
Akcigit, Ufuk, Harun Alp, Maya Eden, and Ha Nguyen. 2017. “Technology Adoption and the TFP Gap in Latin American Countries,” University of Chicago, Working Paper.
Akcigit, Ufuk, Harun Alp, and Michael Peters. 2016. “Lack of Selection and Limits to Delegation: Firm Dynamics in Developing Countries,” NBER Working Paper 21905.
Akcigit, Ufuk, Sina Ates, and Giammario Impullitti. 2017. “Innovation and Trade Policy in a Globalized World,” University of Chicago, Working Paper.
Akcigit, Ufuk, Salomé Baslandze, and Francesca Lotti. 2017. “Connecting to Power: Political Connections, Innovation, and Firm Dynamics,” University of Chicago, work in progress.
Akcigit, Ufuk, Salomé Baslandze, and Stefanie Stantcheva. 2016. “Taxation and the International Migration of Inventors,” American Economic Review, 106(10), 2930–2981.
Akcigit, Ufuk, Santiago Caicedo, Ernest Miguelez, Stefanie Stantcheva, and Valerio Sterzi. 2017. “Dancing with the Stars: Interactions and Human Capital Accumulation,” University of Chicago, work in progress.
Akcigit, Ufuk, Murat A. Celik, and Jeremy Greenwood. 2016. “Buy, Keep or Sell: Economic Growth and the Market for Ideas,” Econometrica, 84(3), 943–984.
Akcigit, Ufuk, John Grigsby, and Tom Nicholas. 2017a. “Immigration and the Rise of American Ingenuity,” American Economic Review, Papers and Proceedings, 107(5), 327–331.
Akcigit, Ufuk, John Grigsby, and Tom Nicholas. 2017b. “The Rise of American Ingenuity: Innovation and Inventors of the Golden Age,” NBER Working Paper 23047.
Akcigit, Ufuk, John Grigsby, Tom Nicholas, and Stefanie Stantcheva. 2017. “The Long-run Effects of Corporate and Personal Income Taxes on Innovation in the U.S.: Evidence from Historical Patent Data,” University of Chicago, work in progress.
Akcigit, Ufuk, Douglas Hanley, and Nicolas Serrano-Velarde. 2016. “Back to Basics: Basic Research Spillovers, Innovation Policy and Growth,” CEPR Discussion Paper 11707.
Akcigit, Ufuk, Douglas Hanley, and Stefanie Stantcheva. 2016. “Optimal Taxation and R&D Policies,” NBER Working Paper 22908.
Akcigit, Ufuk, and William R. Kerr. 2017. “Growth through Heterogeneous Innovations,” Journal of Political Economy, forthcoming.
Akcigit, Ufuk, William R. Kerr, and Tom Nicholas. 2017. “Mechanics of Innovation and Growth: Evidence from Historical Patents,” University of Chicago, work in progress.
Akcigit, Ufuk, and Qingmin Liu. 2016. “The Role Of Information In Innovation And Competition,” Journal of the European Economic Association, 14(4), 828–870.
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Esteban Rossi-Hansberg on Spatial Dynamic General Equilibrium Modelling
Esteban Rossi-Hansberg is the Theodore A. Wells ’29 Professor of Economics at Princeton University. He has been interested in the spatial dimension of economic problems, in particular in the economic structure of cities, regions and countries, the diffusion of technology, and offshoring. Rossi-Hansberg’s RePEc/IDEAS entry.
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EconomicDynamics: Cities are dynamic because lots is happening there and because they adapt to change. Coastal cities will face an ultimate challenge, though: their location in the face of rising oceans. How can they adapt? Can they do it fast enough?
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Esteban Rossi-Hansberg: A delicate balance between agglomeration and congestion forces determines the geography of economic activity and its evolution. Over time, the fundamentals that determine these forces in a given location (productivity, amenities, and geography, among many others) are affected by explicit investment decisions, spillovers from other regions, or a variety of local, industry, and global shocks. As these fundamentals evolve, so does the distribution of economic activity, and therefore the prospects of particular cities. San Jose has grown relative to Detroit, probably because of growing productivity in the software, computer, and electronics industries that have specialized in the Bay Area, relative to the automotive sector that traditionally located in Michigan. These reversals in relative size are not particularly rare and can happen relatively fast, probably facilitated by regional specialization. So industry shocks (as well as other regional shocks) definitely have the potential to affect the distribution of economic activity and the prospect of specific cities (see Caliendo et al. 2017). Of course, some large diversified cities have also proven to be quite stable over time. New York has stayed at the top of the US urban hierarchy almost throughout its history. This persistence has several causes, but it is probably the case that local productivity and amenity enhancing investments, incentivized by the large market size in these large cities, is the main source of persistence (as in Desmet, et al. 2017a).
Understanding the resilience of particular cities to climate related phenomena, like the expected rise in sea levels, involves balancing the benefits from moving to new locations and the potential gains from investing in them, with the cost of moving economic activity that result from moving costs and the loss of local past investments in technology, amenities, capital and infrastructure. Ultimately, because climate-related phenomena evolve slowly and the set of potential sites for new cities are plentiful, the economy can easily invest in alternative locations while past investments depreciate in locations threatened by the natural phenomena. That is, in the next 100 years, as sea levels rise, the houses in coastal regions will depreciate fully a couple of times. So the losses from these phenomena are likely associated with the cost of moving, together with the differences in the efficiency of the new resulting dynamic equilibrium. We have done this type of evaluation in Desmet, et al. (2015) for global warming and Desmet, et al. (2017) for sea level rise. For example, the results indicate that permanent flooding as a result of sea level rise will decrease welfare by 2100 by about 1%.
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ED: Should cities develop by laissez-faire or is urban policy crucial?
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ER: The presence of agglomeration and congestion externalities in cities has traditionally been used to justify urban policy. Many empirical studies suggest that these forces exist and are non-trivial in size. For example, the flow of knowledge between individuals is naturally aided by urban density. In addition, individuals clearly do not internalize the cost they impose on others by increasing road congestion when they use their cars (in the absence of congestion pricing). These mechanisms alone, and there are many others, imply that cities can benefit from using urban policy. Of course, competition between cities also implies that if some cities use better urban policy, other cities benefit from doing so as well (at least in terms of their total size and output, welfare for marginal residents probably equalizes across cities). City governments that implement optimal urban policy can improve the city structure, however competition between city planners in the aggregate equilibrium tends to work well. The evidence of cross-city interactions that are not priced in an appropriate market is much weaker.
Governments can also easily abuse urban policy. Particularly if they are captured by particular interests. For example, in the presence of knowledge spillovers between workers, optimal zoning policy will aim to increase employment density by restricting the size of business areas. The resulting equilibrium will then exhibit a discontinuous drop in land rents at the boundary of districts zoned for business purposes. Even though the zoning policy is optimal for the city as a whole, the discontinuity implies that firms will lobby against the policy, while residents will be in favor (Rossi-Hansberg, 2004). If, in this context, business interests prevail, the resulting policy will be suboptimal and can hurt the city.
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ED: Innovation disseminates faster than ever. Do locations like Silicon Valley then still matter? Why?
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ER: I believe they do. A very natural mechanism that makes cities centers of innovation is their market size. The market of many goods and services is extremely concentrated in space due to large transport costs. This is clearly the case for restaurants and several forms of entertainment, but it is also the case for a variety of retail and professional services. In addition, many goods that are relatively cheap to transport are intermediate inputs in a production process that incorporates local goods. Naturally, then, local market size matters for the incentives to create new technologies and products. Most of these innovations are small and gradual, and essentially all of them are non-rival. They can be used repeatedly, and the more times they are used, the more profitable they become. So market size is an essential component of the benefits of any revenue enhancing investment.
Of course, the market size of a given product depends on the concentration of the people that exhibit high demand for them. So certain products will naturally be developed in cities like New York, Paris, or regions like the Bay Area because of the concentration of consumers that make their innovation profitable, at least initially. This mechanism in turn attracts more of these agents leading, to dynamic agglomeration effects that generates urban concentration, increases in land rents, and growth (Desmet and Rossi-Hansberg, 2014). Why is Silicon Valley developing driverless cars when the relative price of taxi drivers (or low skilled workers) has never been lower at the national level? Probably because the local demand is high and all those potential low skilled workers cannot pay the Palo Alto land rents. Particularly given the current housing supply restrictions. In fact, the increasing skill segregation that the U.S. has experienced in the last few decades might be good for innovation and the future of these cities (as it concentrates market size further). Of course, the downside is the many declining cities in the rustbelt (e.g. Detroit as explained in Owens et al. 2017) and the large overall increases in income inequality.
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ED: Using dynamic general equilibrium in spatial models is relatively new. Where does this approach need further development to be fully embraced by policy makers?
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ER: Combining space and time in general equilibrium has proven quite hard, and until recently utterly intractable. Particularly in models in which locations are ordered in space and where they interact in meaningful ways. That is, in models in which locations are not simply a collection of heterogeneous entities but instead have a specific location in space that determines their proximity to other locations. Ultimately, location is the fundamental source of heterogeneity in land not because of the properties of the soil but because of the relative closeness to other areas. This relative closeness is relevant because of a number of important interactions between regions. Regions trade goods and services, they influence each other’s technology via diffusion and spillovers, people migrate and commute between them, etc. All these interactions affect the evaluation of virtually all policies. These quantitative spatial models are already quite rich and so adding dynamics is naturally complicated (see Redding and Rossi-Hansberg, 2017, for a recent survey). The main issue is that any forward-looking decision has as a state variable the evolution of the whole distribution of local characteristics across space. This is harder than in heterogeneous agent models because that evolution cannot be summarized with a few paths of prices (like the interest rate). Agents in a location are influenced more by the future characteristics of locations that are close-by than those that are far away.
Nevertheless, the literature has made some progress. Part of the literature has focused on transitional effects that result from capital investments or migration restrictions (see the work of Caliendo, Dvorkin, McLaren, Sposi, Parro, Ravikumar). These papers have been able to incorporate transitional effects using numerical algorithms that are shown to converge in particular applications. These studies have provided good accounts of the long and short-term implications of trade and migration policy. Incorporating long-run growth effects is more challenging and requires using simplifications that effectively limit how much current agent’s decisions affect their future profits or welfare, as in my work, or specifications of preferences and technology that imply constant investment rules over time (as in the work of Anderson and Yotov). Can we generalize these frameworks to relax some of these shortcuts? I hope so, but it is not obvious how to do it. Still, several tests seem to indicate that the quantification of these models can be fairly accurate in reproducing the evolution of the distribution of economic activity in the past (as in Desmet, et al., 2017). More testing and more careful quantifications are needed. We can do this by taking these frameworks seriously and using them to evaluate phenomena and policies that we care about. For example, to evaluate the potential cost of reversing globalization in both the move of goods and services and the move of people. For these policies, incorporating growth effects is essential and, from the lens of these models, the costs of isolation look enormous.
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ED: Where is this approach used in policy making?
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ER: Unfortunately the use of this approach in actual policy making is still quite limited. Quantitative spatial theories have been used to analyze the effects of Brexit and the gains from European integration, NAFTA, many types of infrastructure projects and urban policies, and several aspects of climate change and policies to address them. Some of these studies are part of the knowledge base that informs the political debate that leads to implementation decisions. However, it is probably fair to say that the use of this approach is still not widespread in governmental and multinational institutions, or the many private and public institution they consult with. Development banks are lending and advocating for multibillion projects without using this analysis to inform their decisions. My guess is that this will change dramatically in the next decade. The current limited use of this approach is probably the reflection of the relatively recent development of these techniques. We need to work to standardize it further, make it more robust, and train the students that will be in a position to implement it in the future.
References:
Caliendo, Lorenzo, Fernando Parro, Esteban Rossi-Hansberg and Pierre-Daniel Sarte. 2017. “The Impact of Regional and Sectoral Productivity Changes on the U.S. Economy.” Forthcoming in the Review of Economic Studies.
Desmet, Klaus, Dávid Nagy and Esteban Rossi-Hansberg. 2017a. “The Geography of Development.” Forthcoming in the Journal of Political Economy.
Desmet, Klaus, Koop, Dávid Nagy, Michael Oppenheimer and Esteban Rossi-Hansberg. 2017b. “Dynamic Geography of the Population and Economic Response to Sea Level Rise.” Working paper.
Desmet, Klaus, and Esteban Rossi-Hansberg. 2015. “On the Spatial Economic Impact of Global Warming.” Journal of Urban Economics, 88, 16-37
Desmet, Klaus, and Esteban Rossi-Hansberg. 2014. “Spatial Development.” American Economic Review, 104(4), 1211-1243.
Owens, Raymond III, Esteban Rossi-Hansberg and Pierre-Daniel Sarte. 2017. “Rethinking Detroit.” Federal Reserve Bank of Richmond Working paper 17-4.
Esteban Rossi-Hansberg. 2004. “Optimal Urban Land Use and Zoning.” Review of Economic Dynamics, 7, 69-106.
Redding, Stephen, and Esteban Rossi-Hansberg. 2017. “Quantitative Spatial Economics.” Annual Review of Economics, 9, 21-58.
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Society for Economic Dynamics: Call for Papers, 2018 Meeting
The next annual meeting of the Society of Economic Dynamics will take place in Mexico City, Mexico from June 28th to June 30th 2018. Conference details can be found on the SED 2018 meeting page.
We are pleased to announce plenary talks by Joseph Altonji, Enrique Mendoza and Nancy Stokey. You can now submit your paper for the conference using ConferenceMaker until February 15th, 2018. We are looking forward to receiving many exciting submissions for the academic program!
David Lagakos and Guillermo Ordonez
2018 SED Program Chairs
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Letter from the President
Dear Friends:
The 28th Meeting of the SED in Edinburgh that was held on 22–24 June 2017 was one of our best Meetings so far. The Program Committee, headed by Veronica Rappoport and Kim Ruhl, put together a high quality, exciting program. The plenary lectures given by Francesco Caselli, Eric Hurst, and Ayse Imrohologu were both well attended and stimulating. Listening to Eric’s lecture, which was the third Dale Mortensen Lecture, I learned something about the effects on the labor market of large numbers of single young men living in their parents’ basements and spending large amounts of time playing electronic games. The Local Organizing Committee, led by Sevi Rodriguez-Mora, put together an excellent set of social events. Edinburgh is a beautiful city, and I will always remember John Moore’s speech-cum-comedy act following the dinner in the Assembly Rooms, which was in turn followed by dancing the ceilidh. All of the details of the Meeting, including the slides from the plenary lectures, can be found on the Society’s web site. I personally want to thank all of the people that I have mentioned and all of you who participated in helping to make the 2017 Meeting of the SED one of the best conferences in economics last year!
As high as was the standard set by the Edinburgh Meeting, I am confident that the 29th Meeting of the SED to be held 28–30 June 2018 in Mexico City will rise to a comparable level. David Lagakos and Guillermo Ordoñez are chairing the Program Committee. They have already lined up Plenary Lectures by Joseph Altonji, Enrique Mendoza, and Nancy Stokey. Joe’s lecture will be the fourth Dale Mortensen Lecture in memory of our past President, inspiration, and friend, Dale Mortensen. David, Guillermo, and their committee are waiting for your submissions from now through 15 February 2018.
The Instituto Tecnológico Autónomo de México (ITAM), in collaboration with the Banco de México, is hosting the 2018 Meeting, and the chairs of the Local Organizing Committee are Diego Domínguez, Germán Rojas, and Carlos Urrutia. I spent a week in early October at ITAM discussing plans for the SED Meeting with the local organizers from ITAM and the Banco de México. As well as being an excellent conference in intellectual terms, I expect the 2018 SED Meeting to be a lot of fun with some truly excellent food and drinks. Many of you may not know that I spent 2016 at ITAM doing research and teaching. My wife and I rented an apartment in the La Condesa neighborhood, which, together with the nearby neighborhoods of Polanco and La Roma, is the scene of an ongoing cultural and gastronomic revolution. The New York Times named Mexico City one of the most exciting cities in the world to visit in 2016. It is precisely in the Polano-Condesa-Roma area that the conference hotels are located. I will make sure that our web site has an extensive list of places to go and things to see and do, especially restaurants where to eat.
The 2019 Meeting will be hosted by the Washington University in St. Louis and the Federal Reserve Bank of St. Louis on 27–29 June. The Local Organizing Committee, headed by Carlos Garriga, Rody Manuelli, B Ravikumar, and Chris Waller is already arranging what promises to be an excellent meeting.
Our journal, the Review of Economic Dynamics, continues to do well under the able guidance of Coordinating Editors Jonathan Heathcoate and Vincenzo Quadrini.
Benjamin Lester, Pierre-Olivier Weill, and Ariel Zeitlin-Jones are currently planning a Special Issue on Fragmented Financial Markets. They are looking for high quality theoretical and empirical work that sheds light on liquidity, asset prices, and issues related to efficiency and/or fragility that may emerge in decentralized or fragmented financial markets. If you are interested in having your work considered, please submit your paper via email to [email protected] by December 15th, 2017.
For all those who are going to attend the 2018 ASSA Meetings in Philadelphia on 5–7 January 2018, the SED is sponsoring two sessions: the first at 8:00-10:00 am on 5 January on “Behavioral Macroeconomics” and the second at 12:30–2:15 pm on 6 January on “New Approaches in Measuring Uncertainty.” The expansion of the number of sessions for a small society like ours depends on attendance. The SED would like to expand our presence at the ASSA Meetings, and I urge you to try to attend one or both of our sessions in Philadelphia.
I look forward to seeing you in Mexico and, if you are going to be at the ASSA Meetings, in Philadelphia!
Tim Kehoe
President, Society for Economic Dynamics
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2017 Report of the Coordinating Editors
The Review of Economic Dynamics (RED) is the official journal of the Society for Economic Dynamics. The journal publishes meritorious original contributions to dynamic economics. The scope of the journal is intended to be broad. We publish contributions in any area of economics provided they meet the highest standards of scientific research. In particular, RED publishes original articles on applications of dynamic economic theory to a wide variety of problems in economics. Related measurement and empirical papers are also welcomed.
Editorial Board Composition
Since last year, there have been a number of changes to the Editorial Board. Matthias Doepke completed his term as Coordinating Editor. He did a fantastic job in continuing to build the quality and visibility of RED, while maintaining a fast and professional review process. The Society is very grateful for his service.
Gianluca Violante (Princeton) has stepped down as an Editor, after many years of service to the journal, including as Coordinating Editor prior to Matthias. Greg Kaplan (Chicago) is also stepping down as an Editor, though he will continue to handle existing submissions. The Society also thanks Richard Rogerson (Princeton), a former Editor and former President of the Society, and Fatih Guvenen (Minnesota), both of whom have stepped down as Associate Editors.
Jonathan Heathcote (FRB Minneapolis) and Vincenzo Quadrini (USC Marshall) are the new joint Coordinating Editors.
We have been happy to welcome a number of new Associate Editors this year. These are Alejandro Justiniano (FRB Chicago), David Lagakos (UCSD), Lance Lochner (Western Ontario), Luigi Paciello (EIEF), Kim Ruhl (Penn State), and Julia Thomas (Ohio State). Mariacristina de Nardi (FRB Chicago) is now an Editor.
As of November 2017, the Editors of RED are: Marco Bassetto (FRB Chicago), Matthias Doepke (Northwestern), Mariacristina de Nardi (FRB Chicago), and Diego Restuccia (Toronto).
The Associate Editors are: Stefania Albanesi (Pittsburgh), Cristina Arellano (FRB Minneapolis), Javier Bianchi (FRB Minneapolis), Ariel Burstein (UCLA), Hector Chade (ASU), Tim Cogley (NYU), Jan Eeckhout (UCL), Andrea Eisfeldt (UCLA Anderson), Gino Gancia (CREI), Matteo Iacoviello (Federal Reserve Board), Alejandro Justiniano (FRB Chicago), David Lagakos (UCSD), Jeremy Lise (UCL), Lance Lochner (Western Ontario), Maurizio Mazzocco (UCLA), Guillermo Ordonez (Penn), Luigi Paciello (EIEF), Fabien Postel-Vinay (UCL), Juan Rubio-Ramirez (Emory), Kim Ruhl (Penn State), Andrea Tambalotti (FRB New York), Julia Thomas (Ohio State), Galina Vereshchagina (ASU), Pierre-Oliver Weill (UCLA), and Christian Zimmermann (FRB St. Louis).
Turnaround Statistics
RED strives to deliver fast and efficient turnaround of manuscripts, without compromising the quality of the refereeing process. Besides desk rejections, virtually all submitted manuscripts receive two referee reports. In 2016, RED received 393 submissions (we received 379 in 2015 and 337 in 2014). The mean processing time from submission to first decision was 59 days (the average was 57 days in 2015 and 60 in 2014).
The table below describes the distribution of first decisions for new submissions in 2016 by type: desk reject, reject after review, and revise and resubmit (which includes both minor and major revisions requested).
Distribution of First Decision Times on 2016 Submissions |
||||
Total |
Desk reject |
Reject |
R&R |
|
Total |
393 |
187 |
147 |
59 |
Within 3 months |
70% |
100% |
48% |
29% |
3 to 4 months |
14% |
0% |
14% |
20% |
4 to 5 months |
8% |
0% |
27% |
25% |
More than 5 months |
8% |
0% |
11% |
25% |
Average days since submission |
59 |
4 |
100 |
132 |