Nathan H. Miller

Why do borrowers pledge collateral? New empirical evidence on the role of asymmetric information

An important theoretical literature motivates collateral as a mechanism that mitigates adverse selection, credit rationing, and other inefficiencies that arise when borrowers hold ex ante private information. There is no clear empirical evidence regarding the central implication of this literature—that a reduction in asymmetric information reduces the incidence of collateral. We exploit exogenous variation in lender information related to the adoption of an information technology that reduces ex ante private information, and compare collateral outcomes before and after adoption. Our results are consistent with this central implication of the private-information models and support the empirical importance of this theory.

Debt Maturity, Risk, and Asymmetric Information

We test the implications of Flannerys (1986) and Diamonds (1991) models concerning the effects of risk and asymmetric information in determining debt maturity, and we examine the overall importance of informational asymmetries in debt maturity choices. We employ data on over 6,000 commercial loans from 53 large U.S. banks. Our results for low-risk firms are consistent with the predictions of both theoretical models, but our findings for high-risk firms conflict with the predictions of Diamonds model and with much of the empirical literature. Our findings also suggest a strong quantitative role for asymmetric information in explaining debt maturity.

Automakers' Short-Run Responses to Changing Gasoline Prices*

We provide empirical evidence that automobile manufacturers use cash incentives to offset how gasoline price fluctuations affect the expected fuel expenses of automobile buyers. Regressions based on a database of incentives over 2003 to 2006 suggest that on average, manufacturers offset 40% of the change in relative fuel costs between vehicles due to gasoline price fluctuations. The results highlight that carbon taxes and emissions trading programs likely would generate substantial substitution within vehicle classes, and studies that ignore manufacturer discounting likely underestimate consumer demand for fuel economy. The results also have implications for the optimal design of feebate programs.

Using cost pass-through to calibrate demand ☆

We demonstrate that cost pass-through can be used to inform demand calibration, potentially eliminating the need for data on margins, diversion, or both. We derive the relationship between cost pass-through and consumer demand using a general oligopoly model of Nash–Bertrand competition and develop specific results for four demand systems: linear demand, logit demand, log-linear demand and the Almost Ideal Demand System (AIDS). The methods we propose may be useful to researchers and antitrust authorities when reliable measures of margins or diversion are unavailable. We also develop that cost pass-through can help illuminate the suitability of some demand systems to specific economic applications.

Competition Among Spatially Differentiated Firms: An Empirical Model with an Application to Cement

The theoretical literature of industrial organization shows that the distances between consumers and firms have first-order implications for competitive outcomes whenever transportation costs are large. To assess these effects empirically, we develop a structural model of competition among spatially differentiated firms and introduce a GMM estimator that recovers the structural parameters with only regional-level data. We apply the model and estimator to the portland cement industry. The estimation fits, both in-sample and out-of-sample, demonstrate that the framework explains well the salient features of competition. We estimate transportation costs to be

Competition Among Spatially Differentiated Firms: An Estimator with an Application to Cement

0.30 per tonne-mile, given diesel prices at the 2000 level, and show that these costs constrain shipping distances and provide firms with localized market power. To demonstrate policy-relevance, we conduct counter-factual simulations that quantify competitive harm from a hypothetical merger. We are able to map the distribution of harm over geographic space and identify the divestiture that best mitigates harm.

Understanding the Price Effects of the MillerCoors Joint Venture

We develop an estimator for models of competition among spatially differentiated firms. In contrast to existing methods (e.g., Houde (2009)), the estimator has flexible data requirements and is implementable with data that are observed at any level of aggregation. Further, the estimator is the first to be applicable to models in which firms price discriminate among consumers based on location. We apply the estimator to the portland cement industry in the U.S. Southwest over 1983-2003. We estimate transportation costs to be

Competition When Consumers Value Firm Scope

0.30 per tonne-mile and show that, given the topology of the U.S. Southwest, these transportation costs permit more geographically isolated plants to discriminate among consumers. We conduct a counterfactual experiment and determine that disallowing this spatial price discrimination would increase consumer surplus by

Approximating the Price Effects of Mergers: Numerical Evidence and an Empirical Application

12 million annually, relative to a volume of commerce of

Pass-Through and the Prediction of Merger Price Effects

1.3 billion. Heretofore it has not been possible examine the surplus implications of spatial price discrimination in specific, real-world settings; these implications have been known to be ambiguous theoretically since at least Gronberg and Meyer (1982) and Katz (1984). Additionally, our methodology can be used to construct transportation margins, which are an important component of input-output tables.