From universal service to universal connectivity

Two features of the century-old policy goal of promoting universal telephone service in the United States have been enduring. Policymakers have focused on (1) wireline telephone (and more recently, fixed-line broadband) services and (2) households. The widespread adoption of mobile telephones compels a fresh examination of this focus. We construct a new measure of universal connectivity which accounts for consumers’ choices of communications technologies and for their geographic mobility over the course of the day. This measure, in turn, compels a conceptual and empirical investigation of the determinants of mobile telephone diffusion within families. Our estimations of intra-household demand for mobile service permit us to develop simulations that estimate the economic impact of modernizing a key element of existing universal service policy (viz., the Lifeline Program) to reflect the goal of improving individual connectivity. We find that a policy expansion from a single subsidy per household to multiple subsidies per eligible household members would increase mobile subscriptions by 2.25 million and Lifeline costs by $250 million

Raising the BAR: Bias adjustment of recognition tests in advertising

Advertising recognition tests use advertisements as visual retrieval cues; they require consumers to report which advertisements they remember having seen earlier and whether they noticed the advertised brand and read most of the text at the time. Using a heterogeneous randomly stopped sum model, the authors establish the relationship between consumers' actual attention to print advertisements, as measured through eye tracking, and subsequent ad recognition measures. They find that ad recognition measures are systematically biased because consumers infer prior attention from the ad layout and their familiarity with the brands in the advertisements. Such biases undermine the validity of recognition tests for advertising practice and theory development. The authors quantify the positive and negative diagnostic value of ad recognition for prior attention and demonstrate how these diagnostic values can be used to develop bias-adjusted recognition (BAR) scores that more accurately reflect prior attention. Finally, the authors show that differences in the scores from ad recognition tests based on in-home versus lab exposure attenuate when the bias-adjustment procedure is applied

Raising the BAR:Bias adjustment of recognition tests in advertising

Advertising recognition tests use advertisements as visual retrieval cues; they require consumers to report which advertisements they remember having seen earlier and whether they noticed the advertised brand and read most of the text at the time. Using a heterogeneous randomly stopped sum model, the authors establish the relationship between consumers' actual attention to print advertisements, as measured through eye tracking, and subsequent ad recognition measures. They find that ad recognition measures are systematically biased because consumers infer prior attention from the ad layout and their familiarity with the brands in the advertisements. Such biases undermine the validity of recognition tests for advertising practice and theory development. The authors quantify the positive and negative diagnostic value of ad recognition for prior attention and demonstrate how these diagnostic values can be used to develop bias-adjusted recognition (BAR) scores that more accurately reflect prior attention. Finally, the authors show that differences in the scores from ad recognition tests based on in-home versus lab exposure attenuate when the bias-adjustment procedure is applied