Productivity and labour demand effects of inward and outward foreign direct investment on UK industry

We relate the technological and factor price determinants of inward and outward foreign direct investment (FDI) to its potential productivity and labour market effects on both host and home economies. This allows us to distinguish clearly between technology-sourcing and technologyexploiting FDI, and to identify FDI that is linked to labour cost differentials. We then empirically examine the effects of different types of FDI into and out of the UK on domestic (i.e. UK) productivity and on the demand for skilled and unskilled labour at the industry level.

Creating demand for better health by using social marketing techniques

The most significant environmental change to support people who want to give up smoking is the legislation to ban smoking in public places. Following Scotland in March 2006, and Wales and Northern Ireland in April 2007, England moves one step closer to being smoke free on 1 July 2007, when it becomes illegal to smoke in almost every enclosed public place and workplace. Social marketing will be used to support this health promoting policy and will become more prominent in the design of health promotion campaigns of the future. Social marketing is not a new approach to promoting health but its adoption by the Government does represent a paradigm shift in the challenge to change public opinion and social norms. As a result some behaviours, like smoking or excessive alcohol consumption, will no longer be socially acceptable. The Department of Health has decided that social marketing should be used in England to guide all future health promotion efforts directed at achieving behavioural goals. This paradigm shift was announced in Chapter 2 of the “Choosing health” White Paper with its emphasis on the consumer, noting that a wide range of lifestyle choices are marketed to people, although health as a commodity itself has not been marketed. The DoH has an internal social marketing development unit to integrate social marketing principles into its work and ensure that providers deliver. The National Centre for Social Marketing has funding to provide ongoing support, to build capacity and capability in the workforce. This article describes the distinguishing features of the social marketing approach. It seeks to answer some questions. Is this really a new idea, a paradigm shift, or simply a change in terminology? What do the marketing principles offer that is new, or are they merely familiar ideas repackaged in marketing jargon? Will these principles be more effective than current health promotion practice and, if so, how does it work? Finally, what are the implications for community pharmacy?

Productivity and labour demand effects of inward and outward FDI on UK industry

We relate the technological and factor price determinants of inward and outward FDI to its potential productivity and labour market effects on both host and home economies. This allows us to distinguish clearly between technology sourcing and technology exploiting FDI, and to identify FDI which is linked to labour cost differentials. We then empirically examine the effects of different types of FDI into and out of the United Kingdom on domestic (i.e. UK) productivity and on the demand for skilled and unskilled labour at the industry level. Inward investment into the UK comes overwhelmingly from sectors and countries which have a technological advantage over the corresponding UK sector. Outward FDI shows a quite different pattern, dominated by investment into foreign sectors which have lower unit labour costs than the UK. We find that different types of FDI have markedly different productivity and labour demand effects, which may in part explain the lack of consensus in the empirical literature on the effects of FDI. Our results also highlight the difficulty for policy makers of simultaneously improving employment and domestic productivity through FDI.

Promoting creativity at work:the role of problem-solving demand

We propose that problem-solving demand (PSD) is an important job attribute for employees' creative performance. Applying job design theory, we examined the relationship between PSD and employee creativity. The theorised model was tested with data obtained from a sample of 270 employees and their supervisors from three Chinese organisations. Regression results revealed that PSD was positively related to creativity, and this relationship was mediated by creative self-efficacy. Additionally, intrinsic motivation moderated the relationship between PSD and creative self-efficacy such that the relationship was stronger for individuals with high rather than low intrinsic motivation. We discuss our findings, implications for practice, and future research.

Techniques to improve forecasting models: applications to energy demand and price

This thesis is a study of three techniques to improve performance of some standard fore-casting models, application to the energy demand and prices. We focus on forecasting demand and price one-day ahead. First, the wavelet transform was used as a pre-processing procedure with two approaches: multicomponent-forecasts and direct-forecasts. We have empirically compared these approaches and found that the former consistently outperformed the latter. Second, adaptive models were introduced to continuously update model parameters in the testing period by combining ?lters with standard forecasting methods. Among these adaptive models, the adaptive LR-GARCH model was proposed for the fi?rst time in the thesis. Third, with regard to noise distributions of the dependent variables in the forecasting models, we used either Gaussian or Student-t distributions. This thesis proposed a novel algorithm to infer parameters of Student-t noise models. The method is an extension of earlier work for models that are linear in parameters to the non-linear multilayer perceptron. Therefore, the proposed method broadens the range of models that can use a Student-t noise distribution. Because these techniques cannot stand alone, they must be combined with prediction models to improve their performance. We combined these techniques with some standard forecasting models: multilayer perceptron, radial basis functions, linear regression, and linear regression with GARCH. These techniques and forecasting models were applied to two datasets from the UK energy markets: daily electricity demand (which is stationary) and gas forward prices (non-stationary). The results showed that these techniques provided good improvement to prediction performance.

Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models

This paper presents some forecasting techniques for energy demand and price prediction, one day ahead. These techniques combine wavelet transform (WT) with fixed and adaptive machine learning/time series models (multi-layer perceptron (MLP), radial basis functions, linear regression, or GARCH). To create an adaptive model, we use an extended Kalman filter or particle filter to update the parameters continuously on the test set. The adaptive GARCH model is a new contribution, broadening the applicability of GARCH methods. We empirically compared two approaches of combining the WT with prediction models: multicomponent forecasts and direct forecasts. These techniques are applied to large sets of real data (both stationary and non-stationary) from the UK energy markets, so as to provide comparative results that are statistically stronger than those previously reported. The results showed that the forecasting accuracy is significantly improved by using the WT and adaptive models. The best models on the electricity demand/gas price forecast are the adaptive MLP/GARCH with the multicomponent forecast; their MSEs are 0.02314 and 0.15384 respectively.

Development of an on-demand beam pulsing system for Pixe-analysis of thick targets

This work concerns the developnent of a proton irduced X-ray emission (PIXE) analysis system and a multi-sample scattering chamber facility. The characteristics of the beam pulsing system and its counting rate capabilities were evaluated by observing the ion-induced X-ray emission from pure thick copper targets, with and without beam pulsing operation. The characteristic X-rays were detected with a high resolution Si(Li) detector coupled to a rrulti-channel analyser. The removal of the pile-up continuum by the use of the on-demand beam pulsing is clearly demonstrated in this work. This new on-demand pu1sirg system with its counting rate capability of 25, 18 and 10 kPPS corresponding to 2, 4 am 8 usec main amplifier time constant respectively enables thick targets to be analysed more readily. Reproducibility tests of the on-demard beam pulsing system operation were checked by repeated measurements of the system throughput curves, with and without beam pulsing. The reproducibility of the analysis performed using this system was also checked by repeated measurements of the intensity ratios from a number of standard binary alloys during the experimental work. A computer programme has been developed to evaluate the calculations of the X-ray yields from thick targets bornbarded by protons, taking into account the secondary X-ray yield production due to characteristic X-ray fluorescence from an element energetically higher than the absorption edge energy of the other element present in the target. This effect was studied on metallic binary alloys such as Fe/Ni and Cr/Fe. The quantitative analysis of Fe/Ni and Cr/Fe alloy samples to determine their elemental composition taking into account the enhancement has been demonstrated in this work. Furthermore, the usefulness of the Rutherford backscattering (R.B.S.) technique to obtain the depth profiles of the elements in the upper micron of the sample is discussed.

An econometric analysis of international tourism demand in Hong Kong : a cointegration and error correction approach

The purpose of this study is to develop econometric models to better understand the economic factors affecting inbound tourist flows from each of six origin countries that contribute to Hong Kong’s international tourism demand. To this end, we test alternative cointegration and error correction approaches to examine the economic determinants of tourist flows to Hong Kong, and to produce accurate econometric forecasts of inbound tourism demand. Our empirical findings show that permanent income is the most significant determinant of tourism demand in all models. The variables of own price, weighted substitute prices, trade volume, the share price index (as an indicator of changes in wealth in origin countries), and a dummy variable representing the Beijing incident (1989) are also found to be important determinants for some origin countries. The average long-run income and own price elasticity was measured at 2.66 and – 1.02, respectively. It was hypothesised that permanent income is a better explanatory variable of long-haul tourism demand than current income. A novel approach (grid search process) has been used to empirically derive the weights to be attached to the lagged income variable for estimating permanent income. The results indicate that permanent income, estimated with empirically determined relatively small weighting factors, was capable of producing better results than the current income variable in explaining long-haul tourism demand. This finding suggests that the use of current income in previous empirical tourism demand studies may have produced inaccurate results. The share price index, as a measure of wealth, was also found to be significant in two models. Studies of tourism demand rarely include wealth as an explanatory forecasting long-haul tourism demand. However, finding a satisfactory proxy for wealth common to different countries is problematic. This study indicates with the ECM (Error Correction Models) based on the Engle-Granger (1987) approach produce more accurate forecasts than ECM based on Pesaran and Shin (1998) and Johansen (1988, 1991, 1995) approaches for all of the long-haul markets and Japan. Overall, ECM produce better forecasts than the OLS, ARIMA and NAÏVE models, indicating the superiority of the application of a cointegration approach for tourism demand forecasting. The results show that permanent income is the most important explanatory variable for tourism demand from all countries but there are substantial variations between countries with the long-run elasticity ranging between 1.1 for the U.S. and 5.3 for U.K. Price is the next most important variable with the long-run elasticities ranging between -0.8 for Japan and -1.3 for Germany and short-run elasticities ranging between – 0.14 for Germany and -0.7 for Taiwan. The fastest growing market is Mainland China. The findings have implications for policies and strategies on investment, marketing promotion and pricing.