Prices In South Africa Research Articles

THE EFFECTS OF PRICE AND VOLATILITY INDICES OF STRATEGIC COMMODITIES ON STOCK MARKETS: A STUDY ON BRICS ECONOMIES

The effect of gold, oil prices, which are strategic commodities, and gold, oil volatility indices on the BRICS stock exchanges is investigated in this paper. The relationship between the variables is analysed for the short and long-run using the NARDL method. Gold prices have a negative effect on stock markets except Brazil and Russia, in the short and long-run. Changes in oil prices have a negative effect on stock prices in South Africa, which imported oil, and a positive effect in net oil exporters Brazil and Russia, in the short and long-run. It is concluded that positive and negative shocks of strategic commodity volatilities have an asymmetric effect on the stock exchanges of emerging countries in the short and long-run.

An Analysis of the Wool Characteristics That Determine the Wool Price for White Wool in South Africa

This study evaluates the effects of white wool's characteristics (fibre diameter/fineness, staple strength, vegetable matter, and staple length) that contribute to determining the wool price in South Africa. The analysis was based on wool price data for the 2009 to 2019 production seasons. A multiple regression analysis of the price (R/kg) of White wool was applied to four independent variables: fibre diameter/fineness, staple strength, vegetable matter and staple length. Fibre diameter, staple length and clean yield, except vegetable matter, made a significant contribution (p < 0.05) to the determination of wool price after all other independent variables were controlled. A one-unit increase in staple length was associated with a 0.018-unit increase in wool price (R/kg). One unit (micron) increase in fibre diameter/fineness resulted in a 0.331 unit decrease in wool price (R/kg). One unit (percentage) increase in clean yield resulted in a 0.115 unit increase in wool price (R/kg). The analysis found that a 1% increase in clean yield, a measure of the amount of clean, usable wool produced by a sheep, was associated with an average increase of 0.115 R/kg in the price of wool. This means that as clean yield increases, wool price tends to increase. Clean yield varies within sheep flocks due to varying amounts of wax and contaminants such as vegetable matter dirt, breed of sheep, and the environmental conditions during wool growth. There was no statistically significant association between vegetable matter and wool price. Wool farmers need to produce wool with low fibre diameter, good length of wool and high clean yield percentage for White wool. Additionally, farmers should focus on improving their production and marketing practices, and policymakers should consider implementing policies that support the wool industry and increase its competitiveness.

Mining activities and housing price nexus: evidence from South Africa

Purpose Several studies have examined the impact of market fundamentals on house prices. However, the effect of economic sectors on housing prices is limited despite the existence of two-speed economies in some countries, such as South Africa. Therefore, this study aims to examine the impact of mining activities on house prices. This intends to understand the direction of house price spreads and their duration so policymakers can provide remediation to the housing market disturbance swiftly. Design/methodology/approach This study investigated the effect of mining activities on house prices in South Africa, using quarterly data from 2000Q1 to 2019Q1 and deploying an auto-regressive distributed lag model. Findings In the short run, we found that changes in mining activities, as measured by the contribution of this sector to gross domestic product, impact the housing price of mining towns directly after the first quarter and after the second quarter in the non-mining cities. Second, we found that inflationary pressure is instantaneous and impacts house prices in mining towns only in the short run but not in the long run, while increasing housing supply will help cushion house prices in both submarkets. This study extended the analysis by examining a possible spillover in house prices between mining and non-mining towns. This study found evidence of spillover in housing prices from mining towns to non-mining towns without any reciprocity. In the long run, a mortgage lending rate and housing supply are significant, while all the explanatory variables in the non-mining towns are insignificant. Originality/value These results reveal that enhanced mining activities will increase housing prices in mining towns after the first quarter, which is expected to spill over to non-mining towns in the next quarter. These findings will inform housing policymakers about stabilising the housing market in mining and non-mining towns. To the best of the authors’ knowledge, this study is the first to measure the contribution of mining to house price spillover.

Market sentiment in emerging economies: evidence from the South African property market

Purpose Market sentiment has shown to influence housing prices in the global north, but in emerging economies, the nexus is rare to chance on in the current state of science for policy direction. More importantly in the recent decade where policymakers are yet to conclude on the myriad of factors confronting the housing market in sub-Saharan Africa inhibiting affordability. This paper therefore examines the impact of market sentiment on house prices in South Africa. Design/methodology/approach The study used the Autoregressive Distributed Lag (ARDL) approach with quarterly data spanning from 2005Q1 to 2020Q4. Findings In all, it was established that market sentiment plays a minimal role in the property market in South Africa. But there was enough evidence of cointegration from the bound test between sentiment and house prices. Nevertheless, the lag values of sentiment pointed to a rise in house prices. Exchange rate volatilities and inflation had a statistically significant effect on prices in both the long and short term, respectively. Research limitations/implications Policymakers could still monitor market sentiment in the housing market due to the strong chemistry between house prices and sentiment, as evidenced from the bound test, but focus on economic fundamentals as the main policy tool for house price reduction. Originality/value The findings and the creation of the sentiment index make an invaluable contribution to the paper and add to the paucity of literature on the study of market sentiment in the housing market.

Impact of Russia-Ukraine invasion on commodity prices in South Africa

Impact of Russia-Ukraine invasion on commodity prices in South Africa

Short-run dynamics and long-run effects of monetary policy on residential property prices in South Africa

PurposeThe study aims to estimate the short- and long-run effects of monetary policy on residential property prices in South Africa. Over the past decades, there has been a monetary policy shift, from targeting money supply and exchange rate to inflation. The shifts have affected residential property market dynamics.Design/methodology/approachThe Johansen cointegration approach was used to estimate the effects of changes in monetary policy proxies on residential property prices using quarterly data from 1980 to 2022.FindingsMortgage finance and economic growth have a significant positive long-run effect on residential property prices. The consumer price index, the inflation targeting framework, interest rates and exchange rates have a significant negative long-run effect on residential property prices. The Granger causality test has depicted that exchange rate significantly influences residential property prices in the short run, and interest rates, inflation targeting framework, gross domestic product, money supply consumer price index and exchange rate can quickly return to equilibrium when they are in disequilibrium.Originality/valueThere are limited arguments whether the inflation targeting monetary policy framework in South Africa has prevented residential property market boom and bust scenarios. The study has found that the implementation of inflation targeting framework has successfully reduced booms in residential property prices in South Africa.

An analysis of the wool characteristics that determine wool price for Merino wool in South Africa

Globally, wool characteristics determine wool price. As a result, wool that does not match the standards for fibre diameter, clean yield and staple length at auctions are sold at cheaper prices. At global level, very few studies in the literature of wool characteristics that determine wool price have attempted to evaluate the actual percentage of clean yield that is required at a wool auction. The actual percentage of clean yield that is required at the wool auction for Merino wool is important to consider for methods that can be applied to improve clean yield. The objective of this study was to investigate the effect of wool characteristics (fibre diameter, clean yield and staple length) on the determination of Merino wool price in South Africa. The data of wool prices from 2009 to 2019 wool seasons was used for analysis. A multiple regression analysis of price (Rand/kg) of Merino wool was applied to three variables (fibre diameter, clean yield and staple length). Taken each variable separately, fibre diameter, clean yield and staple length made a statistically significant (p < 0.05) contribution to the determination of wool price, after controlling all other independent variables. Considering each variable separately, a one unit (µ) increase in fibre diameter was associated with a 30.236 unit decrease in wool price (Rand/kg). A one decimal unit increase in clean yield (%) was associated with 1.353 unit increase in wool price (Rand/kg). A one unit (mm) increase in staple length was associated with 0.912 unit increase in wool price (Rand/kg). The results indicated that clean yield is a challenge for Merino wool farmers. It is important that the Merino sheep breeds are shorn first at the shearing sheds to avoid contamination of wool with coloured fibres, kemp or crossbreed wool.

An analysis of the wool characteristics that determine wool price in South Africa

Purpose South Africa’s wool industry plays an important role in the agricultural sector. The wool industry provides a valuable source of income for farmers who practice sustainable farming practices. However, wool farmers face numerous challenges, such as wool contamination, dirty wool and producing good-quality wool. Good-quality wool is determined by fibre diameter, clean yield, vegetable matter and staple length. This study aims to address these challenges. Design/methodology/approach A multiple regression analysis of price (R/kg) of White wool and Merino wool was applied to four variables fibre diameter: vegetable matter, clean yield and staple length. The analysis was based on the data for the 2009–2019 data from Cape Wools auctions. Findings Fibre diameter, clean yield and staple length, with exception of vegetable matter, made a statistically significant contribution to the determination of wool price after all other independent variables were controlled for (p &lt; 0.05). A one-unit (micron) increase in fibre diameter resulted in a 0.404-unit decrease in wool price (R/kg). A one-unit (mm) increase in staple length resulted in a 0.022-unit increase in wool price (R/kg). There was no statistically significant association between vegetable matter and wool price. A one-unit increase in clean yield was associated with a 0.111-unit increase in wool price (R/kg). Research limitations/implications Since wool fleeces consist of the largest portion of wool shorn from sheep, it is important for wool farmers to focus on wool with low fibre diameter, high clean yield percentage, low percentage of vegetable matter content and good length of the wool. Practical implications Since wool fleeces consist of the largest portion of wool shorn from sheep, it is important for wool farmers to focus on wool with low fibre diameter, high clean yield percentage, low percentage of vegetable matter content and good length of the wool. Social implications In a developing country such as South Africa, this study is important for the following reason. It is understanding the wool characteristics that have the most significance influence on the determination of wool price for Merino wool and White wool might effectively help the wool farmers to adapt their production systems to improve the wool characteristics that determine wool price. Originality/value This study identified a need for a study to be conducted on all wool classes.

Determinants of Housing Prices in South Africa: The Impact of Covid-19

Objectives: The present study aims to determine the relationship between selected macroeconomic and market variables, and South African housing prices, and the influence that Covid-19 had on South African housing prices, after holding for the effect of the change in selected macroeconomic, and market variables on housing prices. Method: Housing prices were determined via the macroeconomic and market variables of economic growth, unemployment, inflation, household debt-to-income, interest rates, foreign exchange rates, stock market returns, and Covid-19. Data collected were analysed using correlation and hierarchical multiple regression tests. Results: The findings indicated that pre-existing relationships between housing prices and traditional determinants of unemployment and household debt-to-income have changed. The results also indicated that housing prices increased during Covid-19 over-and-above the expected increase attributed to changes in the other selected predictor variables. Conclusion: These results provide an updated collection of housing price predictors for practitioners to utilise post-pandemic.

The time-varying impact of foreign capital flows on house prices: evidence from South Africa

This study employs a time-varying parameter VAR with stochastic volatility (TVP-VAR) to investigate the time-varying impact of foreign capital flows on house prices in South Africa. The study also analyses the behaviour of the house price index using recursive unit root tests. The results of these tests show a statistically significant period of house price exuberance. The results of the TVP-VAR show a contemporaneous positive impact of foreign capital on house prices throughout the sample period, with the largest impact occurring during the period of house price exuberance. In addition, the international capital flows are found to aggravate the imbalances between demand and supply sides, thus enforcing the future house prices to comove with the housing supply.

An analysis of the contribution of wool characteristics on price determination of Merino Wool and White Wool all combined in South Africa

Wool characteristics play an important role in the determination of wool prices in South Africa, like all over the world. Therefore, if wool does not meet the wool requirements of wool auctions for fibre diameter, staple length and staple strength it means farmers will receive lower prices. Understanding wool characteristics that determine wool price is important to improve sheep farming systems through management interventions. This research aimed to evaluate the effect of wool characteristics (fibre diameter/fineness, staple strength and staple length) on Merino and White wool all combined, which contributes to the determination of wool price in South Africa. The analysis was based on wool price data for the 2009–2019 production seasons. A multiple regression analysis of the price (R/kg) of Merino wool and White wool was applied to three variables fibre diameter/fineness, staple strength and staple length. Fibre diameter, staple strength and staple length made a statistically significant (p < 0.05) contribution to the determination of wool price after all other independent variables were controlled. A one-unit increase in staple strength (kilotex) was associated with a 0.697 unit increase in wool price (R/kg). One unit (micrometer) increase in fibre diameter/fineness resulted in a 7.616 unit decrease in wool price (R/kg). One unit (millimetre) increase in staple length resulted in a 0.142 unit increase in wool price (R/kg). To maximise profits wool farmers need to produce wool of low fibre diameter, good length of wool and good staple strength for White and Merino wool.

The Responsiveness of Liquid Fuel Price towards COVID-19 and Exchange Rate Fluctuations

The petrol price plays an important role in all types of business and economic activities, especially in South Africa. The outbreak of the COVID-19 pandemic and the volatility of the exchange rate are some of the current challenges in the South African economy and these factors might have significant implications on domestic petrol fuel prices. In the last two years, the petrol price has experienced a drastic increase in the South African commodity market. The current study investigated the effect of the COVID-19 pandemic and exchange rate fluctuations on petrol prices in South Africa for the period between March 2020 and June 2022. The autoregressive distributed lag (ARDL) model was employed to establish the long-run and short-run relationship between COVID-19 new infections, exchange rate and petrol price in South Africa. The result revealed that both exchange rate and COVID-19 infections negatively influence the petrol price in the long run. However, in the short-run exchange rate has a positive impact on petrol price while the latter is negatively affected by increases in COVID-19 new cases of infection. To maintain a steady state of petrol prices and reduce the impact of petrol price fluctuations, the study recommends the implementation of monetary policies that strengthen the domestic currency accompanied by social awareness programmes on COVID-19 management.

Trends estimation in annual numbers of merino sheep and wool production in South Africa, from 1980 to 2017

The economic important value of wool in South Africa is influenced by many characteristics that meet processor capacities and consumers’ preference. The study was conducted to characterize the trends of annual Merino sheep numbers, wool sales and wool auction price in South Africa, from 1980 to 2017. The data from year 1980 to 2017 was retrieved from the abstract of agricultural statistics which was published by the Department of Agriculture, Land Reform and Rural Development (DLRRD) in 2020 was used. Trends were analysed using the differences and percentage change between numbers of years in each independent variable (annual number of Merino sheep, wool sales and wool auction price). The findings indicated that there was a trend in annual number of Merino sheep, wool sales and wool auction prices. In annual numbers of Merino sheep, the highest decrease was observed from 1992 to 1993 (-1878) by 11.2 percent (%) while the huge increase was observed from 1999 to 2000 (+1177) by 10.6%. In wool sales, the findings showed that there was an increase (+5.4) from 1980 to 1982 with 7.7% while there was a decrease (-4.7) from 1982 to 1983 by 6.2%. In wool auction price, the highest increase was observed from 1986 to 1987 (+250903) by 77.2%. Regression findings indicated that all the predicted regression models were statistically significant at P &lt; 0.01. However, the results suggest that quadratic (R2 = 90) was the best fit model to predict the relationship between number of years and annual Merino sheep numbers. This study suggests that there was a trend in annual numbers of Merino sheep, wool sales and wool auction prices in South Africa from 1980 and 2017. Moreover, this study might help Merino sheep farmers to recognise the trends that might be helpful in planning for annual wool productions.

COVID-19, lockdown measures and their impact on food and healthcare prices: empirical evidence using a dynamic ARDL model

PurposeThis research examines the impact of lockdown stringency measures and COVID-19 cases on food and healthcare prices in six Brazil, Russia, India, China, South Africa and Turkey (BRICST) countries. This research is conducted in these countries since previous studies failed to examine the effect of COVID-19 reported cases on food and healthcare prices.Design/methodology/approachTo achieve the objectives of this study, food and healthcare services were regressed against CVC and lockdown stringency measures using the dynamic autoregressive distributed lag (DARDL) model. For this purpose, we used daily data for BRICST countries such as Brazil, Russia, India, China, South Africa and Turkey.FindingsThe empirical evidence indicates that, in the long run, COVID-19 cases significantly and positively affect both food and healthcare prices in India, South Africa and China. In contrast, in the short run, COVID-19 positively affects food and healthcare prices in all countries except Russia and Turkey. Similarly, in the long run, the government stringency index (GSI) and Containment and Health Index (CHI) significantly affect health prices in India and South Africa. In contrast, GSI and CHI significantly affect healthcare prices in South Africa only in the short run. Finally, GSI and CHI significantly affect the food prices in the long run in India, South Africa and China and in the short run in South Africa only.Originality/valueThe widespread impact of the new Coronavirus (COVID-19) has made the world panic. COVID-19 affected all spheres of life, including food supplies and healthcare services. However, most of the empirical research failed to examine the impact of COVID-19 cases on food and healthcare prices which is the main focus of this study. Moreover, in the given context, the authors use a recently developed model that the previous studies failed to use.

Evaluating Property Prices in South Africa using Machine Learning

Evaluating Property Prices in South Africa using Machine Learning

Exchange Rate Volatility and Oil Prices in South Africa

The study examines the oil prices and exchange rate volatilities in South Africa. The study employs monthly time series data spanning for the period from 1960 M1 to 2021M11 using data collected from the SARB. The study employs a TGARCH model to analyse the volatilities between oil prices and exchange rate. The study found that oil prices have a negative statistically significant impact on the exchange rates in South Africa. The study therefore recommends that the monetary authorities must monitor oil prices as they have an ability to cause exchange rate volatilities.

Political risk and macroeconomic effect of housing prices in South Africa

Political risk and macroeconomic effect of housing prices in South Africa

DEVELOPMENT OF A HOLISTIC DIESEL MANAGEMENT SYSTEM TO REDUCE WASTAGE IN OPEN-CAST GOLD MINING

Fuel prices in South Africa are variable and steadily rising. Diesel accounts for a large portion of operational expenditures in open-cast mining, placing pressure on fleet managers to address fuel theft and wastage. Raw data is often obtained in a variety of formats (handwritten or digital) in this environment. A need therefore exists to capture, interpret, and utilise raw diesel data to gain insights for decision-making. It is critical to develop a diesel management system that can monitor and track fuel usage to increase performance, lower operational and maintenance costs, and eliminate misappropriation. Mining companies could benefit from a comprehensive diesel management system that enabled them to control, report, and track usage. The ‘data-information-knowledge-wisdom’ hierarchy is used in this study to capture and utilise raw diesel data for wastage reduction, business intelligence insights, and data visualisation to assist with faster decision-making. Keywords open-cast mining; diesel management; business intelligence; DIKW; diesel management dashboard; decision making

Using EPIC to simulate the effects of different irrigation and fertilizer levels on maize yield in the Eastern Cape, South Africa

Growing water scarcity and increasing Nitrogen (N) fertiliser prices in South Africa require more prudent N fertiliser and irrigation water use approaches. If the goal of sustainable agricultural intensification is to be realised, it is vital to develop location-specific agricultural land management strategies that promote increased crop productivity while minimising negative environmental impacts. In this study, a calibrated and validated Environmental Policy Integrated Climate (EPIC) model was used to simulate a range of N fertiliser and irrigation water levels on maize (Zea mays L.) yield in the Eastern Cape of South Africa. Results showed that a fertiliser and irrigation water management schedule combining approximately 200 kg N ha-1 and 580 mm irrigation water per maize growing season provided the highest average maize yield of 12.2 Mg ha-1 (an increase of +69% above farmers’ current maize yield levels). Nitrogen fertiliser application levels greater than 160 kg N ha-1 resulted in potential N fertiliser leaching losses of more than 35 kg N ha-1. The EPIC model can be considered a valuable tool to aid decision-makers in identifying optimal, site-specific irrigation water and N fertiliser application levels that contribute to increased maize crop productivity while maximising water use.

A comparison study between public and private healthcare sector medicine prices in South Africa

Abstract Objectives The objectives of the study were to compare price trends, determine price differentials, and equate the average price index of a basket of medicines between the public and private healthcare sectors in South Africa. Methods A price list consisting of 32 essential medicines available in both the public and private healthcare systems of South Africa was chosen for this study. The price of medicines for the private sector were obtained from the Medicine Price Registry-Open Up website for the period 2014–2018. Public sector medicine prices were obtained from the Department of Health website for the corresponding period. Observations and price trends were identified and analyzed using Microsoft Excel version 2016. Key findings A total of 74 medicine brands were analyzed in the study. It was found that the prices across both sectors had increased over time, however, the majority of brands (87%) displayed higher prices in the private sector in comparison to the public sector. On average, the price differential between the private and public sector medicines were 395.47%. Conclusions The study found varying price differences between medicines in the public and private sectors because of the different methodologies used in each. The reasons for changes in medicine prices across the years in both sectors, could not always be clearly determined as both sectors lacked complete transparency in the processes applied to establish medicine prices. Therefore, more transparent medicine price systems need to be considered for the future of South Africa’s healthcare system as the country transitions toward universal health coverage.