Plagiarism: Bringing Economics and Education Together (With a Little Help from IT)

Plagiarism has been acknowledged to be a growing problem for Higher Education Institutions, and indeed in other areas of society. Various reasons have been advanced to explain the growth of this problem, including improvements in IT in general and the Internet in particular, along with changed attitudes towards study amongst some of today’s students. Improved access to the Internet, combined with the development of simple-to-use search tools such as Google, have enabled students quickly and easily to locate relevant material, while improvements in IT training have meant that a greater number of students possess the skills for copying, pasting and reformatting text. In addition a number websites have sprung up offering for sale essays and dissertations to order. Universities have sought to combat plagiarism by making use of text matching tools linked to databases of essays and other content to track down plagiarists. They have also sought to educate both students and staff about what is meant by plagiarism and how to avoid it. This paper describes the experience of one department in a university that has been running a pilot project using the Turnitin software available via JISCiPAS (the JISC Internet Plagiarism Advisory Service) as part of an anti-plagiarism initiative. The discussion also reports on a research project that is underway in the department which seeks to set the problem of plagiarism in an economic context.

Modelling Technical Progress: An Application of the Stochastic Trend Model to UK Energy Demand

The precise role of technical progress in estimated energy demand functions has not been well researched. Traditionally a deterministic time trend has been used, implicitly assuming technical progress continues at a fixed rate over time. In this paper, the structural time series model is employed allowing for a stochastic time trend and stochastic seasonal dummies. Therefore, technical progress and seasonal variation are treated as unobservable components that evolve over time. The conventional deterministic trend model is a restricted case of the structural time series model and found not to be accepted by the data for a number of energy types. Energy demand functions for a variety of energy types are estimated for the UK using unadjusted quarterly data. It is found that technical progress in energy usage does not always exhibit a deterministic trend pattern as the conventional model assumes. It often fluctuates over time and is likely to be affected by a range of exogenous factors but also by changes in energy prices (and possibly income also).energy demand, technical progress, stochastic trend model, seasonality;

Modelling Underlying Energy Demand Trends

Energy Demand Trends

Estimating Underlying Energy Demand Trends using UK Annual Data

Employing the Structural Time Series Model (STSM) approach suggested by Harvey (1989, 1997), and based on annual data for the UK from 1967-2002, this paper reiterates the importance of using a stochastic rather than a linear deterministic trend formulation when estimating energy demand models, a practice originally established by Hunt et al. (2003a,b) using quarterly UK data. The findings confirm that important non-linear and stochastic trends are present as a result of technical change and other exogenous factors driving demand, and that a failure to account for these trends will lead to biased estimates of the long-run price and income elasticities. The study also establishes that, provided these effects are allowed for, the estimated long-run elasticities are robust to the different data frequencies used in the modelling.Energy Demand, Underlying Trends.

Econometric investigation of internet banking adoption in Greece

The purpose of this paper is to examine if high branch fees, branch dissatisfaction as well as any previous experience of Greek banking customers with other banking technologies (i.e. Automated Teller Machines (ATMs)) have any impact on the probability of internet banking adoption. Further, the authors comment on the socio-economic and demographic characteristics of Greek banking customers, which effect the decision to adopt internet banking services

Asymmetric Price Responses and the Underlying Energy Demand Trend: Are they Substitutes or Complements? Evidence from Modelling OECD Aggregate Energy Demand

A number of energy demand studies have considered the importance of modelling Asymmetric Price Responses (APR), for example, the often-cited work of Gately and Huntington (2002). Griffin and Schulman (2005) questioned the asymmetric approach arguing that this is only capturing energy saving technical progress. Huntington (2006), however, showed that for whole economy aggregate energy and oil demand there is a role statistically for both APR and exogenous energy saving technical change. In a separate strand of the literature the idea of the Underlying Energy Demand Trend (UEDT) has been developed, see for example Hunt et al. (2003a and 2003b) and Dimitropoulos et al. (2005). They argue that it is important, in time series energy demand models, to allow for stochastic trends (or UEDTs) based upon the structural time series/dynamic regression methodology recommended by Harvey (1989, 1997). This paper attempts to bring these strands of the literature together by conducting tests for the UEDT and APR in energy demand models within both a panel context (consistent with the Huntington, 2006 approach) and the structural time series modelling framework. A set of tests across a range of specifications using time-series and panel data are therefore undertaken in order to ascertain whether energy saving technical change (or the more general UEDT) and APR are substitutes for each other when modelling energy demand or whether they are actually picking up different influences and are therefore complements. Using annual whole economy data for 17 OECD countries over the period 1960 – 2004 the results suggest that in general the UEDT and ARP are complementary estimation methodologies when modelling aggregate energy demand. It is argued therefore that energy demand modellers should not assume at the outset that one method is superior to the other. Moreover, wherever possible, a general model (be it in a time series or panel context) that includes a ‘non linear UEDT’ and APR should be initially estimated, and only if accepted by the data should symmetry and/or a more restrictive UEDT be imposed.Energy Demand, OECD, Asymmetric Price Responses, Underlying Energy Demand Trend.

Pathways between probation and addiction treatment in England

Objectives The Criminal Justice Act (2003) introduced Alcohol Treatment Requirements (ATR) and Drug Rehabilitation Requirements (DRR). The study’s objective was to better understand the pathways between ATRs/DRRs and specialist addiction treatment services. Methods The Ministry of Justice's Splink software was used to probabilistically link individuals present in MoJ's nDelius probation data with those in structured substance misuse treatment in the community from the National Drug Treatment Monitoring System (NDTMS), for individuals in England sentenced between 2018 and 2022. The sociodemographic characteristics and clinical profiles of the group were explored, as well as their treatment outcomes. Mixed-effects logistic regressions were used to investigate what factors influence positive outcomes from ATRs/DRRs. Results Overall, 38.9% of offenders on ATRs/DRRs were either engaged with treatment services on their sentence date or engaged with treatment services after being sentenced. Offenders with an ATR appeared to engage more (45.9%) than those with a DRR (33.1%). At three weeks after the sentence date, 26% of offenders with an ATR were identified in treatment, compared to 20% of offenders with a DRR. Of the 15,121 offenders engaged in treatment, 27% remained on the same initial treatment journey until the end of the observation period. 37% dropped out of treatment, while 35% successfully completed this treatment journey (i.e., recovered from their substance use). 1.4% died. Results were also produced on factors were associated with making it into treatment, and with successful treatment outcomes. Conclusions For the first time in England, addiction treatment data and probation data have been linked to produce a more accurate picture of the journey of individuals sentenced to ATRs/DRRs. The findings suggest more work is required to optimise the pathways between probation and specialist addiction treatment services