The building industry is complex, diversified, and labour-intensive. These aspects, together with its inherent instability, are analysed. Improved forecasting methods can assist in economic planning within the industry and formulation of public policy. Economic stabilisation policies can benefit participants in the industry and society at large. In this study leading indicators are developed for the South African building industry to assist in forecasting future demand levels. Use is made of qualitative survey data and quantitative time series. The quarterly qualitative data emanate from the Bureau for Economic Research, University of Stellenbosch. These data are gathered by questionnaire from building contractors and sub-contractors according to the Konjunkturtest developed by the lfo Institute, Munich, Germany. Principal component analyses of the business survey variables reveal that respondents behave purposefully and that these qualitative data are suitable for use as cyclical indicators in a composite index. The monthly quantitative data are compiled by the South African Reserve Bank and the Central Statistical Service, Pretoria, South Africa. The variables used in the construction of the leading indicators are weighted according to the scoring system developed by the National Bureau of Economic Research, United States of America. The six criteria applied in this scoring system are: economic significance of the variables; statistical adequacy; timing at turning points; conformity to historical business cycles; currency; and smoothness. Separate composite leading indices are compiled from 33 qualitative variables and 8 quantitative time series, with the relevant scores as weights. It is found that these indices lead turnjng points of the reference cycle by between three and a half months and ten and a half months. However, the lead times are not consistent. This finding is in accordance with international experience. A combined leading indicator is constructed from these qualitative and quantitative indices (1971 to 1991). It is found that the statistical performance of the final composite leading indicator does not surpass the performance of the individual composite indices. It is suggested that the best forecasting results can be achieved if the qualitative and quantitative leading indices are · used independently, yet in conjunction with other economic indicators and other forecasting models.

No description available.

There is growing concern that human access into areas of wildlife habitat and the management of that access has become one of the most significant issues in sustaining wildlife populations worldwide. Although access management is recommended throughout primary wildlife research and provincial land management plans as a means of wildlife management, limited research has been conducted on measuring the status of access or on access management strategies. Based on a review of the literature on resource management plans and provincial management strategies, this thesis identifies and describes fifteen potential ecological indicators for measuring and monitoring access and access management. Five key findings are summarized from this review. (1) Meaning and implementation of the term `access management' remains vague and ambiguous. (2) Measures of human access are often tied to large mammal management and studies. (3) Access management is a big question, encompassing cumulative impacts, and when viewed from a systems approach should consider ecological indicators across multiple levels of biological organization. (4) Attention is brought to two sub-types of indicators to monitor access management, land use indicators and wildlife use indicators. (5) Ecological indicators of access and access management share one similar data layer, GIS access infrastructure data.

Background: Economic and Business cycle indicators are used when predicting a country’s Gross Domestic Products, GDP. During recent time, Purchasing Managers Index and its ability to signal changes in the economy have received attention. It provides inconsistent signals since the financial crisis in 2008. Decision makers in the society rely on macroeconomic forecast when implementing strategic decisions. It is therefore necessary for indicators to provide correct signals in relation to GDP. Previous research about indicators’ stability is mostly conducted in the U.S. According to the authors’ knowledge, scarce research has been made in Sweden. The area lacks observations where a wider range of indicators is included to get a broader perspective of the economy. Purpose: The purpose of this study is to examine Swedish indicators and observe if they are stable and provide accurate, reliable and consistent signals in relation to GDP growth. Furthermore, the financial crisis in 2008 is used as a benchmark when observing stability and indicators’ predictive ability. Method: Ten indicators within the categories financial, survey-based and real economy indicators are selected. Quarterly data with a time period of maximum 1993-2013 are analyzed. The statistical tests conducted include Correlation, Cross-Correlation and Simple Linear Regression, an interaction term is also included to account for the financial crisis. Conclusion: The results show that nine out of ten indicators are unstable. Purchasing Managers Index show largest changes compared to other indicators. Industry Production index is the best performing indicator. When it comes to the categories; survey-based, financial and real-economy indicators, no category overall provide stability.

Thesis (Ph.D.) - University of St Andrews, March 2008.

Thesis (M.S.)--University of Michigan, 1975.

Thesis (M.S.)--University of Michigan, 1975.

Thesis (M. Phil.)--University of Hong Kong, 1998. / Includes bibliographical references (leaves 145-151).

Thesis (M.A.) - Carleton University, 2007. / Includes bibliographical references (p. 160-168). Also available in electronic format on the Internet.

Thesis (Ph. D.)--UCLA, 2008. / Vita. Includes bibliographical references (leaves 356-365).