The development of leading indicators for the South African building industry using qualitative and quantitative data
| dc.contributor.advisor | Kilian, W.F. | |
| dc.contributor.advisor | van der M. Smit, E. | |
| dc.contributor.advisor | Boaden, B | |
| dc.contributor.author | Snyman, Gideon Johan Justus | |
| dc.date.accessioned | 2020-05-12T12:06:11Z | |
| dc.date.available | 2020-05-12T12:06:11Z | |
| dc.date.issued | 1994 | |
| dc.date.updated | 2020-04-02T12:52:36Z | |
| dc.description.abstract | 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 ยท used independently, yet in conjunction with other economic indicators and other forecasting models. | |
| dc.identifier.apacitation | Snyman, G. J. J. (1994). <i>The development of leading indicators for the South African building industry using qualitative and quantitative data</i>. (). ,Engineering and the Built Environment ,Department of Construction Economics and Management. Retrieved from | en_ZA |
| dc.identifier.chicagocitation | Snyman, Gideon Johan Justus. <i>"The development of leading indicators for the South African building industry using qualitative and quantitative data."</i> ., ,Engineering and the Built Environment ,Department of Construction Economics and Management, 1994. | en_ZA |
| dc.identifier.citation | Snyman, G.J.J. 1994. The development of leading indicators for the South African building industry using qualitative and quantitative data. . ,Engineering and the Built Environment ,Department of Construction Economics and Management. | en_ZA |
| dc.identifier.ris | TY - Thesis / Dissertation AU - Snyman, Gideon Johan Justus AB - 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 ยท used independently, yet in conjunction with other economic indicators and other forecasting models. DA - 1994 DB - OpenUCT DP - University of Cape Town KW - economic indicators KW - economics of building LK - https://open.uct.ac.za PY - 1994 T1 - The development of leading indicators for the South African building industry using qualitative and quantitative data TI - The development of leading indicators for the South African building industry using qualitative and quantitative data UR - ER - | en_ZA |
| dc.identifier.uri | https://hdl.handle.net/11427/31855 | |
| dc.identifier.vancouvercitation | Snyman GJJ. The development of leading indicators for the South African building industry using qualitative and quantitative data. []. ,Engineering and the Built Environment ,Department of Construction Economics and Management, 1994 [cited yyyy month dd]. Available from: | en_ZA |
| dc.language.rfc3066 | eng | |
| dc.publisher.department | Department of Construction Economics and Management | |
| dc.publisher.faculty | Faculty of Engineering and the Built Environment | |
| dc.subject | economic indicators | |
| dc.subject | economics of building | |
| dc.title | The development of leading indicators for the South African building industry using qualitative and quantitative data | |
| dc.type | Master Thesis | |
| dc.type.qualificationlevel | Masters |