Two-stage DEA: <Emphasis Type="Italic">caveat emptor</Emphasis>

This paper examines the wide-spread practice where data envelopment analysis (DEA) efficiency estimates are regressed on some environmental variables in a second-stage analysis. In the literature, only two statistical models have been proposed in which second-stage regressions are well-defined and meaningful. In the model considered by Simar and Wilson (J Prod Anal 13:49–78, 2007), truncated regression provides consistent estimation in the second stage, where as in the model proposed by Banker and Natarajan (Oper Res 56: 48–58, 2008a), ordinary least squares (OLS) provides consistent estimation. This paper examines, compares, and contrasts the very different assumptions underlying these two models, and makes clear that second-stage OLS estimation is consistent only under very peculiar and unusual assumptions on the data-generating process that limit its applicability. In addition, we show that in either case, bootstrap methods provide the only feasible means for inference in the second stage. We also comment on ad hoc specifications of second-stage regression equations that ignore the part of the data-generating process that yields data used to obtain the initial DEA estimates.     

A Guide to Information on Australian Resource Projects

This article provides a guide to economic information on Australian resource projects. Three sources are described in some detail and their differences, strengths and weaknesses are discussed. As the data are under‐researched, some examples of how they can be used in economic analysis are mentioned.     

Seatbelt use among drivers in an urban city in Nigeria: an observational study

Studies from parts of Nigeria reported low compliance with seatbelt. This study sought to establish driver seatbelt use in Enugu, Nigeria by gender, vehicle type/use and time of day. Observations were done day and night at randomly selected locations. Data were analysed with SPSS version 15. Differences in response were checked with chi-square for trend. Confidence interval was 95% and P value < 0.05 was regarded as significant. Average compliance was 37.6% for the 510 males (85%) and 90 females (15%) observed. It was 74.8% in the day and 0.3% at night. Among males, 218 (42.7%) wore seatbelt while 9 (10%) females did. For commercial drivers 159 (65.2%) complied while 68 (19.1%) private drivers did. Truck drivers had 100% compliance while sports utility vehicle drivers had the lowest (18.8%). There is poor seatbelt compliance in Enugu, Nigeria and need for educational campaigns and stricter enforcement.     

Dimensions of entrepreneurial orientation and small and medium enterprise performance in emerging economies

The removal of trade barriers has encouraged the entry of new competitors into formerly protected markets. This situation creates pressure on many small and medium enterprises (SMEs) in emerging economies such as Tanzania. Using a survey method and cross-sectional research design, the research examines three dimensions of entrepreneurial orientation (EO), namely: pro-activeness, risk-taking and competitive aggressiveness. Understanding their relationships and variance may help to improve our ability to explain SME performance. The findings contribute to how SME performance in emerging economies can be enhanced to enable SMEs to face challenges posed by competitor influx in the context of an open market economy. The findings indicate a strong relationship between EO dimensions and performance, with risk-taking and competitive aggressiveness moderating the effect of pro-activeness. The proposed model could predict 72% of the variance explained in SME performance.     

Nondiscretionary residential water use: the impact of habits and water‐efficient technologies

Several studies published in the last few decades have demonstrated a low price‐elasticity for residential water use. In particular, it has been shown that there is a quantity of water demanded that remains constant regardless of prices and other economic factors. In this research, we characterise residential water demand based on a Stone‐Geary utility function. This specification is not only theory‐compatible but can also explicitly model a minimum level of consumption not dependent on prices or income. This is described as minimum threshold or nondiscretionary water use. Additionally, the Stone‐Geary framework is used to model the subsistence level of water consumption that is dependent on the temporal evolution of consumer habits and stock of physical capital. The main aim of this study is to analyse the impact of water‐saving habits and water‐efficient technologies on residential water demand, while additionally focusing attention on nondiscretionary uses. This is informed by an empirical application using data from a survey conducted among residents of Brisbane City Council, Australia. The results will be especially useful in the design of water tariffs and other water‐saving policies.     

Are batteries ready for plug-in hybrid buyers?

The notion persists that battery technology and cost remain as barriers to commercialization of electric-drive passenger vehicles. Within the context of starting a market for plug-in hybrid electric vehicles (PHEVs), we explore two aspects of the purported problem: (1) PHEV performance goals and (2) the abilities of present and near-term battery chemistries to meet the resulting technological requirements. We summarize evidence stating that battery technologies do not meet the requirements that flow from three sets of influential PHEV goals due to inherent trade-offs among power, energy, longevity, cost, and safety. However, we also show that part of this battery problem is that those influential goals are overly ambitious compared to goals derived from consumers’ PHEV designs. We elicited PHEV designs from potential early buyers among U.S. new car buyers; most of those who are interested in a PHEV are interested in less technologically advanced PHEVs than assumed by experts. Using respondents’ PHEV designs, we derive peak power density and energy density requirements and show that current battery chemistries can meet them. By assuming too aggressive PHEV goals, existing policy initiatives, battery research, and vehicle development programs mischaracterize the batteries needed to start commercializing PHEVs. To answer the question whether batteries are ready for PHEVs, we must first answer the question, “whose PHEVs?”     

A Brief Survey of Modern Optimization for Statisticians

Modern computational statistics is turning more and more to high‐dimensional optimization to handle the deluge of big data. Once a model is formulated, its parameters can be estimated by optimization. Because model parsimony is important, models routinely include non‐differentiable penalty terms such as the lasso. This sober reality complicates minimization and maximization. Our broad survey stresses a few important principles in algorithm design. Rather than view these principles in isolation, it is more productive to mix and match them. A few well‐chosen examples illustrate this point. Algorithm derivation is also emphasized, and theory is downplayed, particularly the abstractions of the convex calculus. Thus, our survey should be useful and accessible to a broad audience.