Suicide and the South African business cycle: a time series approach, 2006-2015
- Authors: Pitot, Amaury
- Date: 2018
- Subjects: Suicide -- South Africa , Business cycles -- South Africa , Autoregression (Statistics) , Divorce -- South Africa , AutoRegressive Distributed Lagged model (ARDL)
- Language: English
- Type: text , Thesis , Masters , MCom
- Identifier: http://hdl.handle.net/10962/62286 , vital:28150
- Description: Suicide is a major public health issue and imposes substantial economic cost on society every year. For example, the World Health Organisation has estimated that there are over one million completed suicides every year, of which about 75% occur in middle and low income countries. In South Africa, suicide is one of the leading causes of non-natural death, but remains under-researched from an economic point of view due to limited data availability. Using monthly data for the period 2006-2015, this study explores whether there is a relationship between suicide and the South African business cycle. This is further broken down to examine how, if at all, this relationship with the business cycle differs across age-, gender-, and racial groups. The primary source of data for suicide and demographic groups were obtained from Statistics South Africa’s Mortality and Causes of Death Data from Death Notification released since 2006. The coincident indicator was used as a proxy for the business cycle as it represents the business cycle in real time. Using an autoregressive distributed lagged model (ARDL), a long run relationship was established with suicide being a function of the coincident indicator, divorce and fertility rate. The findings of this paper show that the overall suicide rate moves with the South African business cycle (i.e. pro-cyclical relationship) in the long run. This relationship holds for males, the black population group and the 15-29 and 30-44 age categories. In addition, the divorce rate had a positive and significant relationship with the overall suicide rate, as well as suicide among the black population group and for the 30-44 age category, whereas fertility rates had no significant relationship with suicide.
- Full Text:
- Authors: Pitot, Amaury
- Date: 2018
- Subjects: Suicide -- South Africa , Business cycles -- South Africa , Autoregression (Statistics) , Divorce -- South Africa , AutoRegressive Distributed Lagged model (ARDL)
- Language: English
- Type: text , Thesis , Masters , MCom
- Identifier: http://hdl.handle.net/10962/62286 , vital:28150
- Description: Suicide is a major public health issue and imposes substantial economic cost on society every year. For example, the World Health Organisation has estimated that there are over one million completed suicides every year, of which about 75% occur in middle and low income countries. In South Africa, suicide is one of the leading causes of non-natural death, but remains under-researched from an economic point of view due to limited data availability. Using monthly data for the period 2006-2015, this study explores whether there is a relationship between suicide and the South African business cycle. This is further broken down to examine how, if at all, this relationship with the business cycle differs across age-, gender-, and racial groups. The primary source of data for suicide and demographic groups were obtained from Statistics South Africa’s Mortality and Causes of Death Data from Death Notification released since 2006. The coincident indicator was used as a proxy for the business cycle as it represents the business cycle in real time. Using an autoregressive distributed lagged model (ARDL), a long run relationship was established with suicide being a function of the coincident indicator, divorce and fertility rate. The findings of this paper show that the overall suicide rate moves with the South African business cycle (i.e. pro-cyclical relationship) in the long run. This relationship holds for males, the black population group and the 15-29 and 30-44 age categories. In addition, the divorce rate had a positive and significant relationship with the overall suicide rate, as well as suicide among the black population group and for the 30-44 age category, whereas fertility rates had no significant relationship with suicide.
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The yield curve as a forecasting tool : does the yield spread predict recessions in South Africa?
- Authors: Khomo, Melvin Muzi
- Date: 2006
- Subjects: Recessions -- South Africa , Monetary policy -- South Africa , Economic development -- South Africa , Economic indicators -- South Africa , Business cycles -- History -- 20th century , Business cycles -- South Africa , South Africa -- Economic conditions
- Language: English
- Type: Thesis , Masters , MCom
- Identifier: vital:1040 , http://hdl.handle.net/10962/d1004722 , Recessions -- South Africa , Monetary policy -- South Africa , Economic development -- South Africa , Economic indicators -- South Africa , Business cycles -- History -- 20th century , Business cycles -- South Africa , South Africa -- Economic conditions
- Description: This paper examines the ability of the yield curve to predict recessions in South Africa, and compares its predictive power with other commonly used variables that include the growth rate in real money supply, changes in stock prices and the index of leading economic indicators. The study also makes an attempt to find out if monetary policy explains the yield spread's predictive power with regards to future economic activity. Regarding methodology, the standard probit model proposed by Estrella and Mishkin (1996) that directly estimates the probability of the economy going into recession is used. Results from this model are compared with a modified probit model suggested by Dueker (1997) that includes a lagged dependent variable. Results presented in the paper provide further evidence that the yield curve, as represented by the yield spread between 3-month and IO-year government paper, can be used to estimate the likelihood of recessions in South Africa. The yield spread can produce recession forecasts up to 18 months, although it's best predictive power is seen at two quarters. Results from the standard probit model and the modified pro bit model with a lagged dependent variable are somewhat similar, although the latter model improves forecasts at shorter horizons up to 3 months. Compared with other indicators, real M3 growth is a noisy indicator and does not provide much information about future recessions, whilst movements in the All-Share index can provide information for up to 12 months but does not do better than the yield curve. The index of leading economic indicators outperforms the yield spread in the short run up to 4 months but the spread performs better at longer horizons. Based on the results from the study, it appears that changes in monetary policy explain the yield spread's predictive power. This is because the yield spread loses its explanatory power when combined with a variable representing the monetary policy stance of the central bank.
- Full Text:
- Authors: Khomo, Melvin Muzi
- Date: 2006
- Subjects: Recessions -- South Africa , Monetary policy -- South Africa , Economic development -- South Africa , Economic indicators -- South Africa , Business cycles -- History -- 20th century , Business cycles -- South Africa , South Africa -- Economic conditions
- Language: English
- Type: Thesis , Masters , MCom
- Identifier: vital:1040 , http://hdl.handle.net/10962/d1004722 , Recessions -- South Africa , Monetary policy -- South Africa , Economic development -- South Africa , Economic indicators -- South Africa , Business cycles -- History -- 20th century , Business cycles -- South Africa , South Africa -- Economic conditions
- Description: This paper examines the ability of the yield curve to predict recessions in South Africa, and compares its predictive power with other commonly used variables that include the growth rate in real money supply, changes in stock prices and the index of leading economic indicators. The study also makes an attempt to find out if monetary policy explains the yield spread's predictive power with regards to future economic activity. Regarding methodology, the standard probit model proposed by Estrella and Mishkin (1996) that directly estimates the probability of the economy going into recession is used. Results from this model are compared with a modified probit model suggested by Dueker (1997) that includes a lagged dependent variable. Results presented in the paper provide further evidence that the yield curve, as represented by the yield spread between 3-month and IO-year government paper, can be used to estimate the likelihood of recessions in South Africa. The yield spread can produce recession forecasts up to 18 months, although it's best predictive power is seen at two quarters. Results from the standard probit model and the modified pro bit model with a lagged dependent variable are somewhat similar, although the latter model improves forecasts at shorter horizons up to 3 months. Compared with other indicators, real M3 growth is a noisy indicator and does not provide much information about future recessions, whilst movements in the All-Share index can provide information for up to 12 months but does not do better than the yield curve. The index of leading economic indicators outperforms the yield spread in the short run up to 4 months but the spread performs better at longer horizons. Based on the results from the study, it appears that changes in monetary policy explain the yield spread's predictive power. This is because the yield spread loses its explanatory power when combined with a variable representing the monetary policy stance of the central bank.
- Full Text:
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