Krazy Kimmy's: A Case in Fraud Examination

This two‐part case allows for maximum student engagement through preparation, in‐class discussion, and through a Part B case that is part of the Teaching Note. Through this case, students work to identify possible fraud schemes, plan an investigation, and perform horizontal analysis calculations. Students will learn about the concept of ethical hacking, red flag identification, internal control weaknesses, and investigation considerations for fraud schemes. Further, in‐class planning for next steps and investigation can occur, providing an opportunity for group work and in‐depth learning. This case offers flexibility for instructors in that it can be covered over one class or multiple classes, or can be assigned as an independent or group assignment. This teaching note provides an overview of the case along with guidance for teaching this case.     

Productivity and technical change: the case of Taiwan

This paper analyses productivity growth in 16 of Taiwan's manufacturing industries during the period 1978–1992. The non-parametric Data Envelopment Analysis approach is used to compute Malmquist productivity indexes. These are decomposed into efficiency change and technical change. The latter is further decomposed into an output bias, an input bias and a magnitude component. In addition, the direction of input bias is identified. Empirical results indicate that the sector's TFP increased at a rate of 2.89% per annum, which could be ascribed to a technical progress (2.56%) and an efficiency improvement (0.33%).     

Generalized quadratic revenue functions

In this paper we focus on the specification of revenue functions in their dual price space. We consider two distance functions–the Shephard output distance function and the directional output distance function–and define both in price space. The former is multiplicative in nature and satisfies homogeneity, whereas the latter is additive and satisfies the translation property. Functional equation methods yield the translog specification in the case of the Shephard distance function and a quadratic specification in the case of the directional distance function. Monte Carlo evidence suggests that the quadratic specification outperforms the translog in large samples and in true models with plenty of curvature.     

Technological change and timing reductions in greenhouse gas emissions

In 2007 Nicholas Stern’s Review (in Science 317:201–202, 2007) estimated that global GDP would shrink by 5–20% due to climate change which brought forth calls to reduce emissions by 30–70% in the next 20 years. Stern’s results were contested by Weitzman (in J Econ Lit XLV(3):703–724, 2007) who argued for more modest reductions in the near term, and Nordhaus (in Science 317:201–202, 2007) who questioned the low discount rate and coefficient of relative risk aversion employed in the Stern Review, which caused him to argue that ‘the central question about global-warming policy—how much how, how fast, and how costly—remain open.’ We present a simulation model developed by Färe et al. (in Time substitution with application to data envelopment analysis, 2009) on intertemporal resource allocation that allows us to shine some light on these questions. The empirical specification here constrains the amount of undesirable output a country can produce over a given period by choosing the magnitude and timing of those reductions. We examine the production technology of 28 OECD countries over 1992–2006, in which countries produce real GDP and CO₂ using capital and labor and simulate the magnitude and timing necessary to be in compliance with the Kyoto Protocol. This tells us ‘how fast’ and ‘how much’. Comparison of observed GDP and simulated GDP with the emissions constraints tells us ‘how costly’. We find these costs to be relatively low if countries are allowed reallocate production decision across time, and that emissions should be cut gradually at the beginning of the period, with larger cuts starting in 2000.     

A Comment on Weak Disposability in Nonparametric Production Analysis

In his 2005 paper in this journal, Kuosmanen argues that Shephard's specification of weak disposability in activity analysis (DEA) models is not correct. We show that Shephard's specification does satisfy weak disposability and is the "smallest" technology to do so.     

Estimating demand with distance functions: Parameterization in the primal and dual

Our purpose is to investigate the ability of different parametric forms to ‘correctly’ estimate consumer demands based on distance functions using Monte Carlo methods. Our approach combines economic theory, econometrics and quadratic approximation. We begin by deriving parameterizations for transformed quadratic functions which are linear in parameters and characterized by either homogeneity or which satisfy the translation property. Homogeneity is typical of Shephard distance functions and expenditure functions, whereas translation is characteristic of benefit/shortage or directional distance functions. The functional forms which satisfy these conditions and include both first- and second-order terms are the translog and quadratic forms, respectively. We then derive a primal characterization which is homogeneous and parameterized as translog and a dual model which satisfies the translation property and is specified as quadratic. We assess functional form performance by focusing on empirical violations of the regularity conditions. Our analysis corroborates results from earlier Monte Carlo studies on the production side suggesting that the quadratic form more closely approximates the ‘true’ technology or in our context consumer preferences than the translog.     

Productivity and efficiency in the US: effects of business cycles and public capital

We add to the literature on the US productivity slowdown and effects of public capital on productivity by employing Malmquist productivity indexes to measure productivity. These indexes allow us to decompose productivity growth into efficiency change and technological innovation. We derive these components for each observation, which we exploit to explore factors which may lead to differences in productivity across regions, including business cycles, both own-state and cross-border public infrastructure investment, and relative sizes of the manufacturing, service and public sector. Our results suggest that the components of total factor productivity change lend important insights into the fairly complex effects of public capital on productivity growth.     

Environmental regulation and profitability: An application to Swedish pulp and paper mills

In this paper we analyze the impact on firm profits of the environmental regulations in the Swedish pulp and paper industry. The approach taken is a non-parametric programming model of the technology. A feature of this industry is that environmental regulations are determined individually for each mill. A question, then, is if these individual regulations have a similar impact on firm profits. The approach in this paper allows us to calculate both the regulated and unregulated profits, which means that the severity of the regulations, in terms of foregone profits, can be calculated for each mill. The empirical result shows that the impact on the mills varies substantially, and that the burden from the regulations is less severe in 1990 than in 1989.     

Theory and Application of Directional Distance Functions

In 1957 Farrell demonstrated how cost inefficiency could be decomposed into two mutually exclusive and exhaustive components: technical and allocative inefficiency. This result is consequence of the fact that—as shown by Shephard—the cost function and the input distance function (the reciprocal of Farrell's technical efficiency measure) are dual to each other. Similarly, the revenue function and the output distance function are dual providing the basis for the decomposition of revenue inefficiency into technical and allocative components (see for example, Färe, Grosskopf and Lovell (1994)). Here we extend those results to include the directional distance function and its dual, the profit function. This provides the basis for defining and decomposing profit efficiency. As we show, the output and input distance functions (reciprocals of Farrell efficiency measures) are special cases of the directional distance function. We also show how to use the directional distance function as a tool for measuring capacity utilization using DEA type techniques.