Knowledge that Transforms

In this article we introduce a new computationally tractable framework for Ericson and Pakes-style dynamic oligopoly models that overcomes the computational complexity involved in computing Markov perfect equilibrium (MPE). First, we define a new equilibrium concept that we call moment-based Markov equilibrium (MME), in which firms keep track of their own state, the detailed state of dominant firms, and few moments of the distribution of fringe firms’ states. Second, we provide guidelines to use MME in applied work and illustrate with an application how it can endogenize the market structure in a dynamic industry model even with hundreds of firms. Third, we develop a series of results that provide support for using MME as an approximation. We present numerical experiments showing that MME approximates MPE for important classes of models. Then, we introduce novel unilateral deviation error bounds that can be used to test the accuracy of MME as an approximation in large-scale settings. Overall, our new framework opens the door to study new issues in industry dynamics.

Financial innovations are a common explanation for the rise in credit card debt and bankruptcies. To evaluate this story, we develop a simple model that incorporates two key frictions: asymmetric information about borrowers' risk of default and a fixed cost of developing each contract lenders offer. Innovations that ameliorate asymmetric information or reduce this fixed cost have large extensive margin effects via the entry of new lending contracts targeted at riskier borrowers. This results in more defaults and borrowing, and increased dispersion of interest rates. Using the Survey of Consumer Finances and Federal Reserve Board interest rate data, we find evidence supporting these predictions. Specifically, the dispersion of credit card interest rates nearly tripled while the “new” cardholders of the late 1980s and 1990s had riskier observable characteristics than existing cardholders. Our calculations suggest that these new cardholders accounted for over 20% of the rise in bank credit card debt and delinquencies between 1989 and 1998.

This article provides direct empirical evidence on the relationship between technology and firms’ global sourcing strategies. Using new data on U.S. firms’ decisions to contract for manufacturing services from domestic or foreign suppliers, I show that a firm’s adoption of communication technology between 2002 and 2007 is associated with a 3.1 point increase in its probability of fragmentation. The effect of firm technology also differs significantly across industries; in 2007, it is 20% higher, relative to the mean, in industries with production specifications that are easier to codify in an electronic format. These patterns suggest that technology lowers coordination costs, though its effect is disproportionately higher for domestic rather than foreign sourcing. The larger impact on domestic fragmentation highlights its importance as an alternative to offshoring, and can be explained by complementarities between technology and worker skill. High technology firms and industries are more likely to source from high human capital countries, and the differential impact of technology across industries is strongly increasing in country human capital.

We present a model of market competition in which consumers' attention is drawn to the products' most salient attributes. Firms compete for consumer attention via their choices of quality and price. Strategic positioning of a product affects how all other products are perceived. With this attention externality, depending on the cost of producing quality some markets exhibit "commoditized" price salient equilibria, while others exhibit "de-commoditized" quality salient equilibria. When the costs of quality change, innovation can lead to radical shifts in markets, as in the case of decommoditization of the coffee market by Starbucks. In the context of financial innovation, the model generates the phenomenon of "reaching for yield".

This article estimates peer effects originating from the ability composition of tutorial groups for undergraduate students in economics. We manipulated the composition of groups to achieve a wide range of support, and assigned students—conditional on their prior ability—randomly to these groups. The data support a specification in which the impact of group composition on achievement is captured by the mean and standard deviation of peers’ prior ability, their interaction, and interactions with students’ own prior ability. When we assess the aggregate implications of these peer effects regressions for group assignment, we find that low- and medium-ability students gain on an average 0.19 SD units of achievement by switching from ability mixing to three-way tracking. Their dropout rate is reduced by 12 percentage points (relative to a mean of 0.6). High-ability students are unaffected. Analysis of survey data indicates that in tracked groups, low-ability students have more positive interactions with other students, and are more involved. We find no evidence that teachers adjust their teaching to the composition of groups.

Searching for partners involves informational persistence that reduces future traders’ matching probability. In this article, traders who are no longer available but who left tracks on the market are called phantoms. We examine a dynamic matching market in which phantoms are a by-product of search activity, no coordination frictions are assumed, and non-phantom traders may lose time trying to match with phantoms. The resulting aggregate matching technology features increasing returns to scale in the short run, but has constant returns to scale in the long run. We embed a generalized version of this matching function in the canonical continuous-time equilibrium search unemployment model. Long-run constant returns to scale imply there is a unique steady state, whereas short-run increasing returns generate excess volatility in the short run and endogenous fluctuations based on self-fulfilling prophecies.

This paper studies the nonparametric identification and estimation of voters' preferences when voters are ideological. We build on the methods introduced by Degan and Merlo (2009) representing elections as Voronoi tessellations of the ideological space. We exploit the properties of this geometric structure to establish that voter preference distributions and other parameters of interest can be identi ed from aggregate electoral data. We also show that these objects can be consistently estimated using the methodology proposed by Ai and Chen (2003) and we illustrate our analysis by performing an actual estimation using data from the 1999 European Parliament elections.