Evaluating the Impact of Education on Earnings in the UK: Models, Methods and Results from the NCDS

Education

Water utility efficiency and stated choice responses: status quo effects, effects of presentation format and response time

Water regulators and policymakers around the world are increasingly influencing water systems towards efficiency and sustainable consumption. In pursuit of these, most regulators mainly use traditional economic-analysis methods to benchmark water utilities and elicit water-service preferences. There have been discussions of several other techniques that extend the commonly used traditional economic analysis tools in the literature. Regardless of these discussions, the practical application of new economic analysis tools in the water sector remains relatively low. This study intends to extend the existing literature by providing more robust methods that could be useful to water regulators. The study asks four research questions to shed light on whether more robust methods are the way forward in water regulation. More precisely, the study investigates the consistency of efficiency scores obtained from the data envelopment analysis (DEA), stochastic frontier analysis (SFA) and stochastic non-parametric envelopment of data (StoNED) techniques on a sample of South African water utilities. Additionally, the study examines the impact of status quo bias, presentation format and response time on results from discrete choice experiments conducted using a case of the South African water sector. The study reports four main findings. First, we find that the StoNED method (based on the methods of moments estimator) outperformed both SFA and DEA. However, SFA outperformed StoNED, when the latter was based on the pseudolikelihood estimator. Second, we find that including a partially relevant status quo reduced status quo bias but did not significantly affect empirical estimates. Major differences are noted in the marginal willingness to pay (MWTP) estimates reported for one of the sub-samples. Third, we find that presenting attributes and levels using the visuals format generated more statistically significant coefficients than presenting them as text or text-and-visuals. Generally, we find that the presentation format significantly affects choice. Finally, we find that removing fast or slow responses from the sample did not significantly affect both utility function and MWTP results. Based on these findings, the study makes four main recommendations. Firstly, the study argues that StoNED (method of moments estimator) and SFA are more appropriate for estimating efficiency in heterogenous water sectors. The study makes recommendations for future studies that seek to do a methodological cross-checking of the three efficiency analysis techniques in the water sector. Secondly, the study argues that a text-and-visuals experiment improves choice task clarity and yields more robust estimates. Thus, more research on the effects of presentation formats is required in environmental economics so that guidelines on developing valid presentation formats for choice tasks can be established. Finally, the study argues against the exclusion of fast and slow responses from the dataset; and recommends approaches for future studies that investigate the impact of response time on choice

Transit productivity analysis in heterogeneous conditions using data envelopment analysis with an application to rail transit

This dissertation extends transit productivity analysis by developing a new method of Data Envelopment Analysis (DEA), the linear programming approach to productivity analysis. The new model analyzes productivity of transit working under heterogeneous operating conditions. It is named Two-Farrell DEA for it applies DEA in two stages, DEA (1), that calculates the productivity frontiers at given operating conditions and DEA (2), that uses inputs adjusted by multipliers calculated in DEA (l). The model Two Farrell DEA calculated productivity benchmarks for each rail transit agency and estimated its potential for higher revenue or lower expense improvement. Additionally, the results identify two production techniques of rail transit, the sources of increasing returns to scale, the degree of flexibility to changes in the shadow prices of the inputs, and a method to prioritize investment for expansion of operations. Its indirect contribution to transit operations planning consists of checking the consistency and feasibility of new rail projects. Moreover, this dissertation includes the first correlation analysis made between productivity and operating conditions related to network form, factor analysis of transit operating conditions, the comparison of results between the new model to four other methods, and the evaluation of the empirical accuracy of methods with cluster analysis

Examining Corrective Instruction with the Balanced Literacy Framework and Middle School Students’ Academic Achievement in Reading

The purpose of this study was to evaluate the effects on reaching achievement for middle school students using Test one and Test three of the Discovery Education™ assessments. Students took the pretest and participated in corrective instruction and interventions. After interventions, students took Test three. A quantitative research design was used to examine data collected from 116 students from three southeastern state public schools from the school years of 2014-2015 and 2015-2016. This research study explored teachers’ perceptions of time using the 2014 North Carolina Working Conditions Survey time construct from the three public schools. An additional research question addressed the correlational relationships among the variables of students’ reading growth and teachers’ strongly agree and agree respondent percentages of action planning time as measured by the North Carolina Working Conditions Survey. This study found no significant relationships among the primary variables of student reading growth and teachers’ perceptions of action planning time. However, statistically significant relationships were found between students’ Test one to Test three scores who participated in interventions. The findings in this study will be beneficial to elementary and secondary principals who are held accountable for literacy development, implementation, and evaluation as the school instructional leader. In addition, school leaders can use this in order to gain insight as to the skill sets and strategies to use to create positive working and learning conditions for their teachers and students. The findings in this study will also be beneficial to directors of curriculum instruction as well as district superintendents in how recommendations are made to school boards for changes in policies of implementation and monitoring effective reading interventions for students and building positive teacher morale and teacher efficacy

Prioritizing Offshore Vendor Selection Criteria for the North American Geospatial Industry

The U.S. market for geospatial services totaled US $2.2 billion in 2010, representing 50% of the global market. Data-processing firms subcontract labor-intensive portions of data services to offshore providers in South and East Asia and Eastern Europe. In general, half of all offshore contracts fail within the first 5 years because one or more parties consider the relationship unsuccessful. Despite the high failure rates, no study has examined the offshore vendor selection process in the geospatial industry. The purpose of this study was to determine the list of key offshore vendor selection criteria and the efficacy of the analytic hierarchy process (AHP) for ranking the criteria that North American geospatial companies consider in the offshore vendor selection process. After the selection of the initial list of factors from the literature and their validation in a pilot study, a final survey instrument was developed and administered to 15 subject matter experts (SMEs) in North America. The SMEs expressed their preferences for one criterion over another by pairwise comparisons, which served as input to the AHP procedure. The results showed that the quality of deliverables was the top ranked (out of 26) factors, instead of the price, which ranked third. Similarly, SMEs considered social and environmental consciousness on the vendor side as irrelevant. More importantly, the findings indicated that the structured AHP process provides a useful and effective methodology whose application may considerably improve the quality of the overall vendor selection process. Last, improved and stabilized business relationships leading to predictable budgets might catalyze social change, supporting stable employment. Consumers could benefit from derivative improvements in product quality and pricing

Convex Non-Parametric Least Squares, Causal Structures and Productivity

In this paper we consider Convex Nonparametric Least Squares (CNLS) when productivity is introduced. In modern treatments of production function estimation, the issue has gained great importance as when productivity shocks are known to the producers, input choices are endogenous and estimators of production function parameters become inconsistent. As CNLS has excellent properties in terms of approximating arbitrary monotone concave functions, we use it, along with flexible formulations of productivity, to estimate inefficiency and productivity growth in Chilean manufacturing plants. Inefficiency and productivity dynamics are explored in some detail along with marginal effects of contextual variables on productivity growth, inputs, and output. Additionally, we examine the causal structure between inefficiency and productivity as well as model validity based on a causal deconfounding approach. Unlike the Cobb-Douglas and translog production functions, the CNLS system is found to admit a causal interpretation

Bayesian inference for multiple Gaussian graphical models with application to metabolic association networks

We investigate the effect of cadmium (a toxic environmental pollutant) on the correlation structure of a number of urinary metabolites using Gaussian graphical models (GGMs). The inferred metabolic associations can provide important information on the physiological state of a metabolic system and insights on complex metabolic relationships. Using the fitted GGMs, we construct differential networks, which highlight significant changes in metabolite interactions under different experimental conditions. The analysis of such metabolic association networks can reveal differences in the underlying biological reactions caused by cadmium exposure. We consider Bayesian inference and propose using the multiplicative (or Chung–Lu random graph) model as a prior on the graphical space. In the multiplicative model, each edge is chosen independently with probability equal to the product of the connectivities of the end nodes. This class of prior is parsimonious yet highly flexible; it can be used to encourage sparsity or graphs with a pre-specified degree distribution when such prior knowledge is available. We extend the multiplicative model to multiple GGMs linking the probability of edge inclusion through logistic regression and demonstrate how this leads to joint inference for multiple GGMs. A sequential Monte Carlo (SMC) algorithm is developed for estimating the posterior distribution of the graphs

Tacit collusion, firm asymmetries and numbers:evidence from EC merger cases

The purpose of this paper is to identify empirically the implicit structural model, especially the roles of size asymmetries and concentration, used by the European Commission to identify mergers with coordinated effects (i.e. collective dominance). Apart from its obvious policy-relevance, the paper is designed to shed empirical light on the conditions under which tacit collusion is most likely. We construct a database relating to 62 candidate mergers and find that, in the eyes of the Commission, tacit collusion in this context virtually never involves more than two firms and requires close symmetry in the market shares of the two firms

FRACTIONATION AND CHARACTERIZATION OF LIGNIN STREAMS FROM GENETICALLY ENGINEERED SWITCHGRASS

Development of biomass feedstocks with desirable traits for cost-effective conversion is one of the main focus areas in biofuels research. As suggested by techno-economic analyses, the success of a lignocellulose-based biorefinery largely relies on the utilization of lignin to generate value-added products, i.e. fuels and chemicals. The fate of lignin and its structural/compositional changes during pretreatment have received increasing attention; however, the effect of genetic modification on the fractionation, depolymerization and catalytic upgrading of lignin from genetically engineered plants is not well understood. This study aims to fractionate and characterize the lignin streams from a wild-type and two genetically engineered switchgrass (Panicum virgatum) species (low lignin content with high S/G ratio and high lignin content) using three different pretreatment methods, i.e. dilute sulfuric acid, ammonia hydroxide, and aqueous ionic liquid (cholinium lysinate). The structural and compositional features and impact of lignin modification on lignin-carbohydrate complex characteristics and the deconstruction of cell-wall compounds were investigated. Moreover, a potential way to upgrade low molecular weight lignin to lipids by Rhodococcus opacus was evaluated. Results from this study provide a better understanding of how lignin engineering of switchgrass influences lignin fractionation and upgrading during conversion processes based on different pretreatment technologies