Guy Judge

Underlying trends and seasonality in UK energy demand: a sectoral analysis

This paper demonstrates the importance for energy demand modelling of allowing for trends and seasonal effects that are stochastic in form. Inherent underlying trends may be non-linear and reflect not only technical progress, which usually produces greater energy efficiency, but also other factors such as changes in consumer tastes and the economic structure that may be working in the opposite direction. Using quarterly unadjusted data for various sectors in the UK, it is shown that unless energy demand models are formulated so as to allow for stochastic trends and seasonals, estimates of price and income elasticities could be seriously biased.

Estimating underlying energy demand trends using UK annual data

Employing the Structural Time Series Model (STSM) approach suggested by Harvey (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, 2003b) 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.

Modelling Underlying Energy Demand Trends

This fine collection of original essays is in recognition of Colin Robinson, who has been at the forefront of thinking in energy economics for over 30 years. Energy in a Competitive Market brings together both prominent academics and practitioners to honour his outstanding and unique contribution. The authors cover a wide and fascinating selection of topics incorporating the whole spectrum of energy economics. In doing so, they examine the belief that markets are the key to the effective allocation of resources, a notion which arguably applies as much to energy as it does to any other commodity.

Searching for the picture: forecasting UK cinema admissions using Google Trends data

This article investigates whether Google Trends search information can improve forecasts of cinema admissions. Using monthly data for the United Kingdom for the period 1 January 2004 to 31 December 2008, we examine various forecasting models that incorporate Google Trends search information. We find clear evidence that Google Trends data on searches relevant to cinema visits (as opposed to searches for specific films) do have the potential to increase the accuracy of cinema admissions forecasting models.

How stable is the seasonal pattern in cinema admissions? evidence from the UK

Conventionally, the seasonal pattern in a time series is taken as exogenous. However, two recent studies from the US have suggested, the seasonal component in box office revenue may in part be endogenously determined. Films that are expected to do well tend to be released at times of peak demand. Hence, the seasonal pattern may reflect both the underlying seasonal pattern and the market expansion effect of the films; evidence from the US suggests the former dominates the latter. This article investigates the same issue for the UK using a structural time series model. We find that, although the seasonal pattern varies over time, we are unable to reject the hypothesis that the seasonal factors are constant. This is consistent with findings from the US.

Econometric investigation of internet banking adoption in Greece

Purpose - – 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. Design/methodology/approach - – The authors employed the logistic regression model to examine the probability of Greek customers adopting internet banking based on certain demographic characteristics but also due to high branch fees, any dissatisfaction with branch services or due to previous experience of electronic banking technologies (ATMs). Findings - – After estimating a logistic model, the authors report that branch dissatisfaction and high branch fees have no impact to the internet banking adoption in Greece, therefore Greek customers prefer to visit branches and are willing to pay high fees for the transactions. However, the authors find that ATM users are more likely to adopt internet banking services in Greece. Research limitations/implications - – The authors should employ a technology acceptance model, to test the effect of perceived ease-of-use, perceived usefulness and technology self-efficacy of customers on the probability of e-banking adoption. The authors should also examine other hypotheses using recent data from other European countries and compare the results with those from Greece. Practical implications - – The findings are strongly recommended to Greek bank managers. Originality/value - – The research is primarily motivated by the lack of similar studies to explain empirically the characteristics of Greek bank customers which affect the adoption of internet banking.

Internet banking services and fees: the case of Greece

In this paper, we examine the internet banking services that Greek commercial banks are offering. We also present the associated costs and fees that customers face when using these services. The findings show that there are disparities in the fees that Greek commercial banks impose on their customers for performing banking transactions over the internet. When we compare Automated Teller Machine (ATM) fees with branch fees, we find that ATM charges are lower than branch fees. Finally, we conclude that internet banking fees are lower than both ATM fees and branch fees.

EVOLVING SEASONAL PATTERNS IN UK ENERGY SERIES

AbstractUK Energy series exhibit pronounced regular but not necessarily fixed seasonal patterns. Failure to reflect such changing patterns in econometric models of energy use can result both in misleading estimates of elasticities and policy responses and in forecasts which under- and over-predict seasonal peaks and troughs. Structural Times Series models permit the formulation, estimation and testing of models which allow for evolving stochastic seasonal components and reflect changing patterns of economic behaviour. Moreover such components can be incorporated into causal regression equations to permit greater flexibility in modelling the seasonal variation than is possible using ordinary dummy variables. By estimating suitable dynamic models which allow for evolving seasonal effects and then nesting the fixed effects models, we compare estimated elasticities and test the restriction of fixed seasonal effects.