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The problem of measurement errors in the national accounts has been recognized for a long time. The error chiefly arises from various source data and the timing of the flow of data received from providers. This chapter first discusses the type of measurement errors confronted by statistical agencies. Second, it presents a model of their behavior that illustrates the trade-offs that must be made in dealing with such errors. Third, the chapter discusses how the quality of the estimates can be gauged given measurement error and the inability to conduct standard statistical tests. Although the focus is on the production of U.S. Gross Domestic Product, the principles are applicable to all national statistical agencies.

This paper focuses on the role of manufacturer brands for resellers within retail channels. This topic is important because of the strategic value of manufacturer brands and the increasing influence of resellers within channels of distribution. Much of the branding research emphasizes a customer-brand knowledge perspective; however, emerging perspectives suggest that brands are also relevant to other stakeholders including resellers. In contrast, channels research recognizes the manufacturer sources of market power, but does not consider the impact of manufacturer “push and pull” strategies within channels. Existing theoretical frameworks, therefore, do not address the reseller perspective of the brand. As a result, the research approach is a multi-method design, consisting of two phases. The first phase involves in-depth interviews, allowing the development of a conceptual framework. In the second phase, a survey of supermarket buyers on brands in several product categories tests this framework. Structural equation modeling analyzes the survey responses and tests the hypotheses. The structural model shows very good fit to the data with good construct validity, reliability, and stability. The findings show that manufacturer support, brand equity, and customer demand reflect the manufacturer brand benefits to resellers. A key contribution of this research is the development of a validated scale on manufacturer brand benefits from the point of view of a reseller. This research shows that the resources that relate to the brand, not just the brand name itself, create value for resellers in channel relationships.

Prior analyses of racial bias in the New York City’s Stop-and-Frisk program implicitly assumed that potential bias of police officers did not vary by crime type and that their decision of which type of crime to report as the basis for the stop did not exhibit any bias. In this paper, we first extend the hit rates model to consider crime type heterogeneity in racial bias and police officer decisions of reported crime type. Second, we reevaluate the program while accounting for heterogeneity in bias along crime types and for the sample selection which may arise from conditioning on crime type. We present evidence that differences in biases across crime types are substantial and specification tests support incorporating corrections for selective crime reporting. However, the main findings on racial bias do not differ sharply once accounting for this choice-based selection.