Daniel A. Ackerberg

Empirically Distinguishing Informative and Prestige Effects of Advertising

This article introduces techniques to empirically distinguish different effects of brand advertising in nondurable, experience goods markets. I argue that advertisements that give consumers product information should primarily affect consumers who have never tried the brand, whereas advertisements that create prestige or image effects should affect both inexperienced and experienced users. I apply this empirical argument to consumer-level data on purchases of a newly introduced brand of yogurt. Empirical results indicate that the advertisements for this brand primarily affect inexperienced users of the brand. I conclude that the primary effect of these advertisements was that of informing consumers. Copyright 2001 by the RAND Corporation.

Unobserved Product Differentiation in Discrete Choice Models: Estimating Price Elasticities and Welfare Effects

This document is a supplement to Ackerberg and Rysman (2005). In that paper, we discuss problems with standard techniques for discrete choice estimation in the context of consumers that face different numbers of products. We propose a solution based on adding a function of the number of products to the estimation equation, which we motivate with a model of retail conjestion. Section 6 of the main paper introduces a second solution that allows the variance of the logit error to be smaller in markets with more products. This solution entails a multiplicative adjustment rather than an additive adjustment. Here, we elaborate on the multiplicative solution. We show how this feature can arise from a model in which products in crowded markets differentiate into dimensions that consumers care less about. We provide Monte Carlo analysis and an empirical example.

Identification Properties of Recent Production Function Estimators

This paper examines some of the recent literature on the estimation of production functions. We focus on techniques suggested in two recent papers, Olley and Pakes (1996) and Levinsohn and Petrin (2003). While there are some solid and intuitive identification ideas in these papers, we argue that the techniques can suffer from functional dependence problems. We suggest an alternative approach that is based on the ideas in these papers, but does not suffer from the functional dependence problems and produces consistent estimates under alternative data generating processes for which the original procedures do not.

Quantifying Equilibrium Network Externalities in the ACH Banking Industry

We seek to estimate the causes and magnitudes of network externalities for the automated clearinghouse (ACH) electronic payments system, using a panel data set on individual bank usage of ACH. We construct an equilibrium model of consumer and bank adoption of ACH in the presence of a network. The model identifies network externalities from correlations of changes in usage levels for banks within a network, from changes in usage following changes in market concentration or sizes of competitors and from adoption decisions of banks outside the network with small branches in the network, and can separately identify consumer and bank network effects. We structurally estimate the parameters of the model by matching equilibrium behavior to the data, using simulated maximum likelihood and a data set of localized networks, and use a bootstrap to recover confidence intervals. The parameters are estimated with high precision and fit various moments of the data reasonably well. We find that most of the impediment to ACH adoption is due to large consumer fixed costs of adoption. The deadweight loss from the network externality is moderate: the optimal number of ACH transactions is about 16% higher than the equilibrium level.

A Practical Asymptotic Variance Estimator for Two-Step Semiparametric Estimators

The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using standard formulas derived in the well-known parametric literature. This means that for computational purposes, an empirical researcher can ignore the semiparametric nature of the problem and do all calculations as if it were a parametric situation. We hope that this simplicity will promote the use of semiparametric procedures.

Chapter 63 Econometric Tools for Analyzing Market Outcomes

Abstract This paper outlines recently developed techniques for estimating the primitives needed to empirically analyze equilibrium interactions and their implications in oligopolistic markets. It is divided into an introduction and three sections; a section on estimating demand functions, a section on estimating production functions, and a section on estimating “dynamic” parameters (parameters estimated through their implications on the choice of controls which determine the distribution of future profits). The introduction provides an overview of how these primitives are used in typical I.O. applications, and explains how the individual sections are structured. The topics of the three sections have all been addressed in prior literature. Consequently each section begins with a review of the problems I.O. researchers encountered in using the prior approaches. The sections then continue with a fairly detailed explanation of the recent techniques and their relationship to the problems with the prior approaches. Hopefully the detail is rich enough to enable the reader to actually program up a version of the techniques and use them to analyze data. We conclude each section with a brief discussion of some of the problems with the more recent techniques. Here the emphasis is on when those problems are likely to be particularly important, and on recent research designed to overcome them when they are.

Improved JIVE Estimators for Overidentified Linear Models with and without Heteroskedasticity

We introduce two simple new variants of the jackknife instrumental variables (JIVE) estimator for overidentified linear models and show that they are superior to the existing JIVE estimator, significantly improving on its small-sample-bias properties. We also compare our new estimators to existing Nagar (1959) type estimators. We show that, in models with heteroskedasticity, our estimators have superior properties to both the Nagar estimator and the related B2SLS estimator suggested in Donald and Newey (2001). These theoretical results are verified in a set of Monte Carlo experiments and then applied to estimating the returns to schooling using actual data.

Comments on "Convergence Properties of the Likelihood of Computed Dynamic Models"

We show by counterexample that Proposition 2 in Fernandez-Villaverde, Rubio-RamIrez, and Santos (Econometrica (2006), 74, 93-119) is false. We also show that even if their Proposition 2 were corrected, it would be irrelevant for parameter estimates. As a more constructive contribution, we consider the effects of approximation error on parameter estimation, and conclude that second order approximation errors in the policy function have at most second order effects on parameter estimates. Copyright 2009 The Econometric Society.

Benchmarking for productivity improvement: A health-care application

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, costs 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. The policy experiment of transferring the treatment practices of more cost-effective agencies suggests that Maine could have significantly reduced treatment costs without compromising health outcomes by identifying and transferring best practices. Copyright 2006 by the Economics Department Of The University Of Pennsylvania And Osaka University Institute Of Social And Economic Research Association.