Are Estimates of Asymmetric First-Price Auction Models Credible? Semi & Nonparametric Scrutinizations

Structural first-price auction estimation methods, built upon Bayesian Nash Equilibrium (BNE), have provided prolific empirical findings. However, due to the latent nature of underlying valuations, the assumption of BNE is not feasibly testable with field data, a fact that evokes harsh criticism on the literature. To respond to skepticism regarding credibility, we provide a focused answer by scrutinizing estimates derived from experimental asymmetric auction data in which researchers observe valuations. We test the statistical equivalence between the estimated and true value distributions. The Kolmogorov-Smirnov test fails to reject the distributional equivalence, strongly supporting the credibility of structural asymmetric auction estimates

Are Estimates of Asymmetric First-Price Auction Models Credible? Semi & Nonparametric Scrutinizations

Structural first-price auction estimation methods, built upon Bayesian Nash Equilibrium (BNE), have provided prolific empirical findings. However, due to the latent nature of underlying valuations, the assumption of BNE is not feasibly testable with field data, a fact that evokes harsh criticism on the literature. To respond to skepticism regarding credibility, we provide a focused answer by scrutinizing estimates derived from experimental asymmetric auction data in which researchers observe valuations. We test the statistical equivalence between the estimated and true value distributions. The Kolmogorov-Smirnov test fails to reject the distributional equivalence, strongly supporting the credibility of structural asymmetric auction estimates

How accurately do structural asymmetric first-price auction estimates represent true valuations?

Structural asymmetric first-price auction estimation methods have provided numerous empirical studies. However, due to the latent nature of underlying valuations, the accuracy of estimates is not feasibly testable with field data, a fact that could inhibit empirical auction market designs and applications based on structural estimates. To assess their accuracy, we provide an analysis of estimates derived from experimental asymmetric auction data, in which researchers observe valuations. We test the null of statistical equivalence between the estimated and true value distributions against the alternative of non-equivalence. When advanced models are used, the Modified Kolmogorov-Smirnov test fails to reject the distributional equivalence, supporting structural asymmetric auction estimations for auction market studies. In addition, recovered efficiencies have plus-minus 2.5 percent precision, compared to the true efficiencies

Pricing and travelers' decision to use frequent flyer miles: evidence from the U.S. airline industry

Previous research on Frequent Flyer Programs (FFP) covered various topics, from analyzing the effect of international airline alliances on domestic travel demand to the effect of airport dominance and FFP on pricing. However, one important constraint in previous empirical research on FFP is the lack of a measure of these programs at a specific time-variant route and carrier level. In this chapter we use a novel way to measure the extent of FFP which allows us to analyze how these programs change from route to route, across carriers and over time. The dataset, that covers the quarters from 1993.1 to 2009.3, was constructed with data obtained from the Bureau of Transportation and Statistics and it has information on prices, proportion of frequent flyer tickets as well as various route and carrier variables. Using panel data techniques to control for unobservables along with the use of instrumental variables to control for potentially endogenous regressors, the results found are consistent with our economic model: travelers are more likely to redeem their frequent flyer miles in more expensive routes. Moreover, business travelers, who usually pay higher prices, were found to be less price sensitive than tourists when switching to buy with accumulated miles

Pricing and travelers' decision to use frequent flyer miles: evidence from the U.S. airline industry

Previous research on Frequent Flyer Programs (FFP) covered various topics, from analyzing the effect of international airline alliances on domestic travel demand to the effect of airport dominance and FFP on pricing. However, one important constraint in previous empirical research on FFP is the lack of a measure of these programs at a specific time-variant route and carrier level. In this chapter we use a novel way to measure the extent of FFP which allows us to analyze how these programs change from route to route, across carriers and over time. The dataset, that covers the quarters from 1993.1 to 2009.3, was constructed with data obtained from the Bureau of Transportation and Statistics and it has information on prices, proportion of frequent flyer tickets as well as various route and carrier variables. Using panel data techniques to control for unobservables along with the use of instrumental variables to control for potentially endogenous regressors, the results found are consistent with our economic model: travelers are more likely to redeem their frequent flyer miles in more expensive routes. Moreover, business travelers, who usually pay higher prices, were found to be less price sensitive than tourists when switching to buy with accumulated miles

Are Estimates of Asymmetric First-Price Auctions Credible? Semi & Nonparametric Analyses: Online Appendix

This online appendix contains figures, tables, comments, and details of payoff functions, that supplement the main article, "Are Estimates of Asymmetric First-Price Auctions Credible? Semi- and Nonparametric Analyses.

Are Estimates of Asymmetric First-Price Auctions Credible? Semi & Nonparametric Analyses: Online Appendix

This online appendix contains figures, tables, comments, and details of payoff functions, that supplement the main article, "Are Estimates of Asymmetric First-Price Auctions Credible? Semi- and Nonparametric Analyses.

Voting in Three-Alternative Committees: An Experiment

We design an experiment to test how voters vote in a small committee election with three alternatives. Voters have common preferences that depend on an unknown state of nature. Each voter receives an imprecise private signal prior to the election and then casts a vote. The alternative with the most votes wins. We fix the number of voters in our experiment to be five and focus on differences in the information structure (prior and signal distributions). We test three different treatments (different prior and signal distributions) that pose different challenges for the voters. In one, simply voting for one’s signal is an equilibrium. In the other two, it is not. Despite the different levels of complexity for the voters, they come relatively close to the predicted strategies (that sometimes involve mixing). As a consequence, the efficiency of the decision is also relatively high and comes close to predicted levels. In one variation of the experiment, we calculate posterior beliefs for the subjects and post them. In another, we do not. Interestingly, the important findings do not change