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The development of leading indicators for the South African building industry using qualitative and quantitative data

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 par...

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Main Author: Snyman, Gideon Johan Justus
Other Authors: Kilian, W.F.
Format: Thesis
Language:English
Published: Department of Construction Economics and Management 2020
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access_status_str Open Access
author Snyman, Gideon Johan Justus
author2 Kilian, W.F.
author_browse Kilian, W.F.
Snyman, Gideon Johan Justus
author_facet Kilian, W.F.
Snyman, Gideon Johan Justus
author_sort Snyman, Gideon Johan Justus
collection Thesis
description 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.
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institution University of Cape Town (South Africa)
language eng
last_indexed 2026-06-10T12:32:56.154Z
license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2020
publishDateRange 2020
publishDateSort 2020
publisher Department of Construction Economics and Management
publisherStr Department of Construction Economics and Management
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source_str UCTD — University of Cape Town Open Access Repository
spelling oai:open.uct.ac.za:11427/31855 The development of leading indicators for the South African building industry using qualitative and quantitative data Snyman, Gideon Johan Justus Kilian, W.F. van der M. Smit, E. Boaden, B economic indicators economics of building 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. 2020-05-12T12:06:11Z 2020-05-12T12:06:11Z 1994 2020-04-02T12:52:36Z Master Thesis Masters https://hdl.handle.net/11427/31855 eng application/pdf Department of Construction Economics and Management Faculty of Engineering and the Built Environment
spellingShingle economic indicators
economics of building
Snyman, Gideon Johan Justus
The development of leading indicators for the South African building industry using qualitative and quantitative data
thesis_degree_str Master's
title The development of leading indicators for the South African building industry using qualitative and quantitative data
title_full The development of leading indicators for the South African building industry using qualitative and quantitative data
title_fullStr The development of leading indicators for the South African building industry using qualitative and quantitative data
title_full_unstemmed The development of leading indicators for the South African building industry using qualitative and quantitative data
title_short The development of leading indicators for the South African building industry using qualitative and quantitative data
title_sort development of leading indicators for the south african building industry using qualitative and quantitative data
topic economic indicators
economics of building
url https://hdl.handle.net/11427/31855
work_keys_str_mv AT snymangideonjohanjustus thedevelopmentofleadingindicatorsforthesouthafricanbuildingindustryusingqualitativeandquantitativedata
AT snymangideonjohanjustus developmentofleadingindicatorsforthesouthafricanbuildingindustryusingqualitativeandquantitativedata