Daniel Ackerberg

Department of Economics
University of Michigan
Lorch Hall
Ann Arbor, MI 48109

E-Mail: EmailAddress: hidden: you can email any NBER-related person as first underscore last at nber dot org
Institutional Affiliation: University of Texas at Austin

NBER Working Papers and Publications

August 2006Quantifying Equilibrium Network Externalities in the ACH Banking Industry
with Gautam Gowrisankaran: w12488
We seek to determine the causes and magnitudes of network externalities for the automated clearinghouse (ACH) electronic payments system. We construct an equilibrium model of customer and bank adoption of ACH. We structurally estimate the parameters of the model using an indirect inference procedure and panel data. The parameters are identified from exogenous variation in the adoption decisions of banks based outside the network and other factors. We find that most of the impediment to ACH adoption is from large customer fixed costs of adoption. Policies to provide moderate subsidies to customers and larger subsidies to banks for ACH adoption could increase welfare significantly.

Published: Daniel Ackerberg & Gautam Gowrisankaran, 2006. "Quantifying Equilibrium Network Externalities in the ACH Banking Industry," RAND Journal of Economics, The RAND Corporation, vol. 37(3), pages 738-761, Autumn. citation courtesy of

February 2002Unobserved Product Differentiation in Discrete Choice Models: Estimating Price Elasticities and Welfare Effects
with Marc Rysman: w8798
Standard discrete choice models such as logit, nested logit, and random coefficients models place very strong restrictions on how unobservable product space increases with the number of products. We argue (and show with Monte Carlo experiments) that these restrictions can lead to biased conclusions regarding price elasticities and welfare consequences from additional products. In addition, these restrictions can identify parameters which are not intuitively identified given the data at hand. We suggest two alternative models that relax these restrictions, both motivated by structural interpretations. Monte-Carlo experiments and an application to data show that these alternative models perform well in practice.

Published: Daniel A. Ackerberg & Marc Rysman, 2005. "Unobserved Product Differentiation in Discrete-Choice Models: Estimating Price Elasticities and Welfare Effects," RAND Journal of Economics, The RAND Corporation, vol. 36(4), pages 771-788, Winter. citation courtesy of

July 2001A New Use of Importance Sampling to Reduce Computational Burden in Simulation Estimation
Method of Simulated Moments (MSM) estimators introduced by McFadden (1989)and Pakes and Pollard (1989) are of great use to applied economists. They are relatively easy to use even for estimating very complicated economic models. One simply needs to generate simulated data according to the model and choose parameters that make moments of this simulated data as close as possible to moments of the true data. This paper uses importance sampling techniques to address a significant computational caveat regarding these MSM estimators - that often one's economic model is hard to solve. Examples include complicated equilibrium models and dynamic programming problems. We show that importance sampling can reduce he number of times a particular model needs to be solved in an estimation procedure, sign...
Measuring the Relative Performance of Providers of a Health Service
with Matilde P. Machado, Michael H. Riordan: w8385
A methodology is developed and applied to compare the performance of publicly funded agencies providing treatment for alcohol abuse in Maine. The methodology estimates a Wiener process that determines the duration of completed treatments, while allowing for agency differences in the effectiveness of treatment, standards for completion of treatment, patient attrition, and the characteristics of patient populations. Notably, the Wiener process model separately identifies agency fixed effects that describe differences in the effectiveness of treatment ('treatment effects'), and effects that describe differences in the unobservable characteristics of patients ('population effects'). The estimated model enables hypothetical comparisons of how different agencies would treat the same populations....
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