Bias and size effects of price-comparison search engines : theory and experimental evidence

We analyze the impact on consumer prices of the size and bias of price comparison search engines. In the context of a model related to Burdett and Judd (1983) and Varian (1980), we develop and test experimentally several theoretical predictions. The experimental results confirm the model’s predictions regarding the impact of the number of firms, and the type of bias of the search engine, but reject the model’s predictions regarding changes in the size of the index. The explanatory power of an econometric model for the price distributions is significantly improved when variables accounting for risk attitudes are introduced.

Optimal IV estimation of systems with stochastic regressors and var disturbances with applications to dynamic systems

This paper considers the general problem of Feasible Generalized Least Squares Instrumental Variables (FG LS IV) estimation using optimal instruments. First we summarize the sufficient conditions for the FG LS IV estimator to be asymptotic ally equivalent to an optimal G LS IV estimator. Then we specialize to stationary dynamic systems with stationary VAR errors, and use the sufficient conditions to derive new moment conditions for these models. These moment conditions produce useful IVs from the lagged endogenous variables, despite the correlation between errors and endogenous variables. This use of the information contained in the lagged endogenous variables expands the class of IV estimators under consideration and there by potentially improves both asymptotic and small-sample efficiency of the optimal IV estimator in the class. Some Monte Carlo experiments compare the new methods with those of Hatanaka [1976]. For the DG P used in the Monte Carlo experiments, asymptotic efficiency is strictly improved by the new IVs, and experimental small-sample efficiency is improved as well.