Cost-effectiveness of electricity energy efficiency programs

We analyze the cost-effectiveness of electric utility ratepayer-funded programs to promote demand-side management (DSM) and energy efficiency (EE) investments. We specify a model that relates electricity demand to previous EE DSM spending, energy prices, income, weather, and other demand factors. In contrast to previous studies, we allow EE DSM spending to have a potential longterm demand effect and explicitly address possible endogeneity in spending. We find that current period EE DSM expenditures reduce electricity demand and that this effect persists for a number of years. Our findings suggest that ratepayer funded DSM expenditures between 1992 and 2006 produced a central estimate of 0.9 percent savings in electricity consumption over that time period and a 1.8 percent savings over all years. These energy savings came at an expected average cost to utilities of roughly 5 cents per kWh saved when future savings are discounted at a 5 percent rate. Copyright © 2012 by the IAEE. All rights reserved.

Energy efficiency policies: A retrospective examination

We review literature on several types of energy efficiency policies: appliance standards, financial incentive programs, information and voluntary programs, and management of government energy use. For each, we provide a brief synopsis of the relevant programs, along with available existing estimates of energy savings, costs, and cost-effectiveness at a national level. The literature examining these estimates points to potential issues in determining the energy savings and costs, but recent evidence suggests that techniques for measuring both have improved. Taken together, the literature identifies up to four quads of energy savings annually from these programs - at least half of which is attributable to appliance standards and utility-based demand-side management, with possible additional energy savings from the U.S. Department of Energy's (DOE's) ENERGY STAR, Climate Challenge, and Section 1605b voluntary programs to reduce carbon dioxide (CO 2) emissions. Related reductions in CO 2 and criteria air pollutants may contribute an additional 10% to the value of energy savings above the price of energy itself. Copyright © 2006 by Annual Reviews. All rights reserved.

Essays on the Economics of Higher Education

At least since the seminal works of Jacob Mincer, labor economists have sought to understand how students make higher education investment decisions. Mincer’s original work seeks to understand how students decide how much education to accrue; subsequent work by various authors seeks to understand how students choose where to attend college, what field to major in, and whether to drop out of college.

Broadly speaking, this rich sub-field of literature contributes to society in two ways: First, it provides a better understanding of important social behaviors. Second, it helps policymakers anticipate the responses of students when evaluating various policy reforms.

While research on the higher education investment decisions of students has had an enormous impact on our understanding of society and has shaped countless education policies, students are only one interested party in the higher education landscape. In the jargon of economists, students represent only the `demand side’ of higher education---customers who are choosing options from a set of available alternatives. Opposite students are instructors and administrators who represent the `supply side’ of higher education---those who decide which options are available to students.

For similar reasons, it is also important to understand how individuals on the supply side of education make decisions: First, this provides a deeper understanding of the behaviors of important social institutions. Second, it helps policymakers anticipate the responses of instructors and administrators when evaluating various reforms. However, while there is substantial literature understanding decisions made on the demand side of education, there is far less attention paid to decisions on the supply side of education.

This dissertation uses empirical evidence to better understand how instructors and administrators make decisions and the implications of these decisions for students.

In the first chapter, I use data from Duke University and a Bayesian model of correlated learning to measure the signal quality of grades across academic fields. The correlated feature of the model allows grades in one academic field to signal ability in all other fields allowing me to measure both ‘own category' signal quality and ‘spillover' signal quality. Estimates reveal a clear division between information rich Science, Engineering, and Economics grades and less informative Humanities and Social Science grades. In many specifications, information spillovers are so powerful that precise Science, Engineering, and Economics grades are more informative about Humanities and Social Science abilities than Humanities and Social Science grades. This suggests students who take engineering courses during their Freshman year make more informed specialization decisions later in college.

In the second chapter, I use data from the University of Central Arkansas to understand how universities decide which courses to offer and how much to spend on instructors for these courses. Course offerings and instructor characteristics directly affect the courses students choose and the value they receive from these choices. This chapter reveals the university preferences over these student outcomes which best explain observed course offerings and instructors. This allows me to assess whether university incentives are aligned with students, to determine what alternative university choices would be preferred by students, and to illustrate how a revenue neutral tax/subsidy policy can induce a university to make these student-best decisions.

In the third chapter, co-authored with Thomas Ahn, Peter Arcidiacono, and Amy Hopson, we use data from the University of Kentucky to understand how instructors choose grading policies. In this chapter, we estimate an equilibrium model in which instructors choose grading policies and students choose courses and study effort given grading policies. In this model, instructors set both a grading intercept and a return on ability and effort. This builds a rich link between the grading policy decisions of instructors and the course choices of students. We use estimates of this model to infer what preference parameters best explain why instructors chose estimated grading policies. To illustrate the importance of these supply side decisions, we show changing grading policies can substantially reduce the gender gap in STEM enrollment.

Auriculotherapy for pain management: a systematic review and meta-analysis of randomized controlled trials.

OBJECTIVES: Side-effects of standard pain medications can limit their use. Therefore, nonpharmacologic pain relief techniques such as auriculotherapy may play an important role in pain management. Our aim was to conduct a systematic review and meta-analysis of studies evaluating auriculotherapy for pain management. DESIGN: MEDLINE,(®) ISI Web of Science, CINAHL, AMED, and Cochrane Library were searched through December 2008. Randomized trials comparing auriculotherapy to sham, placebo, or standard-of-care control were included that measured outcomes of pain or medication use and were published in English. Two (2) reviewers independently assessed trial eligibility, quality, and abstracted data to a standardized form. Standardized mean differences (SMD) were calculated for studies using a pain score or analgesic requirement as a primary outcome. RESULTS: Seventeen (17) studies met inclusion criteria (8 perioperative, 4 acute, and 5 chronic pain). Auriculotherapy was superior to controls for studies evaluating pain intensity (SMD, 1.56 [95% confidence interval (CI): 0.85, 2.26]; 8 studies). For perioperative pain, auriculotherapy reduced analgesic use (SMD, 0.54 [95% CI: 0.30, 0.77]; 5 studies). For acute pain and chronic pain, auriculotherapy reduced pain intensity (SMD for acute pain, 1.35 [95% CI: 0.08, 2.64], 2 studies; SMD for chronic pain, 1.84 [95% CI: 0.60, 3.07], 5 studies). Removal of poor quality studies did not alter the conclusions. Significant heterogeneity existed among studies of acute and chronic pain, but not perioperative pain. CONCLUSIONS: Auriculotherapy may be effective for the treatment of a variety of types of pain, especially postoperative pain. However, a more accurate estimate of the effect will require further large, well-designed trials.

Improving supply chain performance: Real-time demand information and flexible deliveries

In some supply chains, materials are ordered periodically according to local information. This paper investigates how to improve the performance of such a supply chain. Specifically, we consider a serial inventory system in which each stage implements a local reorder interval policy; i.e., each stage orders up to a local basestock level according to a fixed-interval schedule. A fixed cost is incurred for placing an order. Two improvement strategies are considered: (1) expanding the information flow by acquiring real-time demand information and (2) accelerating the material flow via flexible deliveries. The first strategy leads to a reorder interval policy with full information; the second strategy leads to a reorder point policy with local information. Both policies have been studied in the literature. Thus, to assess the benefit of these strategies, we analyze the local reorder interval policy. We develop a bottom-up recursion to evaluate the system cost and provide a method to obtain the optimal policy. A numerical study shows the following: Increasing the flexibility of deliveries lowers costs more than does expanding information flow; the fixed order costs and the system lead times are key drivers that determine the effectiveness of these improvement strategies. In addition, we find that using optimal batch sizes in the reorder point policy and demand rate to infer reorder intervals may lead to significant cost inefficiency. © 2010 INFORMS.