Published Papers

Equilibrium Imitation and Growth»


The least productive agents in an economy can be vital in generating growth by spurring technology diffusion. We develop an analytically tractable model in which growth is created as a positive externality from risk taking by firms at the bottom of the productivity distribution imitating more productive firms. Heterogeneous firms choose to produce or pay a cost and search within the economy to upgrade their technology. Sustained growth comes from the feedback between the endogenously determined distribution of productivity, as evolved from past search decisions, and an optimal, forward-looking search policy. The growth rate depends on characteristics of the productivity distribution, with a thicker-tailed distribution leading to more growth.

Journal of Political Economy, 2014 (with Christopher Tonetti) Paper Appendix Citation

Catch-up and Fall-back through Innovation and Imitation»


Will fast growing emerging economies sustain rapid growth rates until they "catch-up" to the technology frontier? Are there incentives for some developed countries to free-ride off of innovators and optimally "fall-back" relative to the frontier? This paper models agents growing as a result of investments in innovation and imitation. Imitation facilitates technology diffusion, with the productivity of imitation modeled by a catch-up function that increases with distance to the frontier. The resulting equilibrium is an endogenous segmentation between innovators and imitators, where imitating agents optimally choose to "catch-up" or "fall-back" to a productivity ratio below the frontier.

Journal of Economic Growth, 2014 (with Jess Benhabib and Christopher Tonetti) Paper Appendix Citation

Working Papers

Product Awareness, Industry Life Cycles, and Aggregate Profits»


Do frictions in the expansion of consumer choice sets for new products explain firm growth, the industry life cycle, and aggregate profits? To explain industry and aggregate patterns, I introduce a mechanism by which consumers slowly become `aware' of differentiated products, expanding their choice sets. When aggregated, this information friction creates a wedge in an otherwise standard neoclassical growth model, which can help explain secular changes in factor shares in the calibrated model. New empirical evidence is shown to be consistent with this model: product creation and obsolescence rates are high, and markups tend to decrease as industries age.

(R&R at Econometrica), September 2016 Paper Appendix Citation Slides

Equilibrium Technology Diffusion, Trade, and Growth»


This paper studies how opening to trade affects economic growth in a model where heterogeneous firms can choose to adopt a new technology already in use by other firms. We characterize the equilibrium growth rate as a simple function of summary statistics of the profit distribution -- the ratio of profits between the average and marginal firm. Opening to trade increases the spread in profits through expanded export opportunities and foreign competition, induces firms to adopt new technologies more rapidly, and generates faster economic growth. Quantitatively, opening to trade yields large increases in growth, but welfare effects are muted due to loss of variety and reallocation of labor away from production..

(R&R at the American Economic Review) December 2015 (with Christopher Tonetti and Michael E. Waugh) Paper Citation

Reconciling Models of Diffusion and Innovation: A Theory of the Productivity Distribution and Technology Frontier»


We study how innovation and technology diffusion interact to endogenously determine the productivity distribution and generate aggregate growth. We model firms that choose to innovate, adopt technology, or produce with their existing technology. Costly adoption creates a spread between the best and worst technologies concurrently used to produce similar goods. The balance of adoption and innovation determines the shape of the distribution; innovation stretches the distribution, while adoption compresses it. Whether and how innovation and diffusion contribute to aggregate growth depends on the support of the productivity distribution. With finite support, the aggregate growth rate cannot exceed the maximum growth rate of innovators. Infinite support allows for ``latent growth'': extra growth from initial conditions or auxiliary stochastic processes. While innovation drives long-run growth, changes in the adoption process can influence growth by affecting innovation incentives, either directly, through licensing excludable technologies, or indirectly, via the option value of adoption.

(R&R at Econometrica) January 2017 (with Jess Benhabib and Christopher Tonetti)Paper Appendix Citation

Works in Progress (i.e. >= Preliminary Bellman Equations, Game, Equilibrium, and/or Data)

Isolating Limited Liability as a Financial Friction


In Progress

In Progress (with Carolin Pflueger and Michal Szkup)

When (and Why) Doesn’t Technology Diffuse Towards Cheap Labor?


Not only are some countries richer than others, but the differences also seem to be stubbornly persistent – with many countries stagnating and, over time, becoming even poorer relative to more-advanced economies. Significant differences and possibilities for stagnation also occur between cities and regions within countries, even when they have similar levels of education and capital. Moreover, since comparatively educated and trained labor is systematically cheaper in some of the poorer locations, entrepreneurs or highly-skilled migrants stand to benefit from large arbitrage opportunities by moving to a location, hiring the cheaper labor and competing locally or internationally.

The primary research question is: Why doesn't migration, joint ventures and foreign direct investment rapidly diffuse technology by investing in or moving to cheaper locations? An answer to this question, both theoretically and empirically, is central to development economics, urban economics, regional studies, and growth. To address these questions, I propose a new theoretical model with workers tied to a location and managers who embody the technology and can easily move to use cheap labor. Even if there are no direct costs of adopting new technologies or migrating between locations, coordination frictions (i.e., the difficulty of hiring well-matched resources/employees and coordinating their production) are enough to explain why technology can be slow to diffuse in economies with production complementarities.

In Progress (with Michael Peters)

Information, Trading Technology, and Financial Sector Profits


Common wisdom in financial markets is that there is temporary arbitrage, or at least a skewed split of surplus, that can be exploited by agents using private information. This is reflected in the enormous investment in market data and trading technologies in the financial services sector. However, Milgrom and Stokey (1982) and Grossman and Stiglitz (1980) show that asymmetric information alone cannot be exploited by an agent in a Walrasian equilibrium, and that this prevents private gains to investment in information precision - which, in turn, can make markets informationally inefficient. This research attempts to resolve this paradox by introducing a model with asymmetric information and precision, but where the micro-structure of market clearing introduces private returns to investment in signal precision, and frictions in the speed of information diffusion are reflected in the aggregate price distribution.

In Progress (with Shengxing Zhang)

Complexity Constrained Walrasian Equilibria: Welfare Loss and Market Structure


Walrasian market clearing requires solving a large-scale optimization (or, potentially, fixed-point) problem. Algorithms for the auctioneer to solve these problems may be bounded by the curse-of-dimensionality - known in computer science as `infeasibility' - or, with some luck and structure, `polynomial' algorithms in number of agents and/or the number of signals. Moreover, high information content of idiosyncratic states could exhaust the limited (information-theoretic) bandwidth or computational resources of the auctioneer. The core questions in applying computational bounds to equilibrium are: (1) if there are a huge number of agents, do limitations on the computability and/or bandwidth in calculating the equilibrium lead to misallocation?; and (2) do these constraints change the optimial market structure?

In Progress