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This study is concerned with the analysis of the long-run substitution pattern of primary energy sources for the Italian economy, over the period of 1960-1994. A neoclassical model, set in the cost function approach, has been used to retrieve the energy inputs derived demand functions, via Shephard's lemma, using a translog cost function specification. Four primary energy sources have been considered, namely, oil, electricity, natural gas and coal. Recent advances in time series econometric theory have provided tools devices for modelling long-run equilibrium relationships and their associated short-run dynamics jointly. The Engle and Granger (1987) and the Engle and Yoo (1989) cointegration approach has been utilised in this study to estimate the long-run share relationships, while the general to specific methodology has been followed to derive error correction formulations for the adjustment processes. Extensions to time-varying parameter cointegration, carried out in the framework of the structural time series approach, have also been considered. The applications of traditional and time-varying parameter cointegration to the Italian energy market are the main sources of originality of this work. The study is divided into three main parts. The first part introduces the economic and econometric frameworks employed in the analysis. The second part is concerned with the actual empirical analysis. This consists of data description, the structural time series approach and the application of traditional and time-varying parameter cointegration theory to estimate a derived factor demand model. Finally, the third part summarises and discusses the results of the analysis.

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This research aimed at investigating strategies for construction performance improvement in Tanzania. The research established that the Total Quality Management (TQM) philosophy provides a feasible long term performance improvement strategy. Benchmarking was identified as a tool for initiating and sustaining the TQM programme. Labour productivity was selected as the key construction performance indicator. A framework for labour productivity benchmarking was developed, on the basis of current mean productivity (CMP) and target mean productivity (TMP). Construction labour productivity at macroeconomic level and site level were also investigated. Analysis at macro economic level over a twenty five year period between 1969 and 1993 indicated a continuous decline in productivity expressed in value added per person engaged. Site labour productivity was investigated for eight construction activities on 46 sites belonging to 23 different contractors. Two significant findings emerged in the analysis: first, the variability quantified by coefficient of variation was considerably higher than in similar studies elsewhere; and secondly the distribution was skewed to the left suggesting that productivity was low for most of the operatives. These characteristics were indicative of the productivity improvement potential in the Tanzanian building construction industry. A distribution modelling exercise established that Johnson SB distribution (with shape parameters, 11=1 and y=1) model well represented productivity distribution for most activities. From this distribution, it was established that about 85 per cent of operatives productivity was below the median, which provided a basis for quantifying the potential for improvement. The benchmarking model established that there was an improvement potential of about 133 per cent. This potential was verified through an opinion survey of operatives. Factors that influence operatives productivity were identified through an opinion survey. Factor related to motivation were ranked highest in the survey. Possible influence of various factors on productivity was quantified through regression modelling based on actual construction operation observations. This analysis indicated that productivity depended on productive time which is largely influenced by operative motivation, supporting the results of the opinion survey.