Economies of scope in research and teaching: A non-parametric investigation

We propose a non-parametric methodology to study the presence of economies of scope between teaching and research (i.e., the teaching–research nexus). In particular, the paper advocates a conditional version of the ‘benefit-of-the-doubt’ approach to estimate the relationship between professors’ overall academic output, measured by a composite measure of multi-dimensional and importance-adjusted scores of teaching effectiveness and research productivity, and the time devoted to teaching and to research. The methodology is illustrated with a dataset of professors working at a Business & Administration department of a university college where the time allocation of teaching and research was assigned exogenously. The outcome of the analysis indicates the presence of limited scope economies for professors with an extensive research time.     

Hypothesis tests to determine if all true positives have been identified on a receiver operating characteristic curve

For classification problems where the test data are labeled sequentially, the point at which all true positives are first identified is often of critical importance. This article develops hypothesis tests to assess whether all true positives have been labeled in the test data. The tests use a partial receiver operating characteristic (ROC) that is generated from a labeled subset of the test data. These methods are developed in the context of unexploded ordnance (UXO) classification, but are applicable to any binary classification problem. First, the likelihood of the observed ROC given binormal model parameters is derived using order statistics, leading to a nonlinear parameter estimation problem. I then derive the approximate distribution of the point on the ROC at which all true instances are found. Using estimated binormal parameters, this distribution can be integrated up to a desired confidence level to define a critical false alarm rate (FAR). If the selected operating point is before this critical point, then additional labels out to the critical point are required. A second test uses the uncertainty in binormal parameters to determine the critical FAR. These tests are demonstrated with UXO classification examples and both approaches are recommended for testing operating points.