scholarly journals IMPACT OF ECONOMIC, FINANCIAL AND POLITICAL RISKS ON TOURISM PERFORMANCE: A CASE OF SOUTH AFRICA

2021 ◽  
Vol 38 (4) ◽  
pp. 1309-1316
Author(s):  
Paul-Francois MUZINDUTSI ◽  
◽  
Fikile DUBE ◽  
Jean-Claude MANALIYO ◽  
◽  
...  
Keyword(s):  
Risk Factors ◽  
South African ◽  
Political Risk ◽  
Tourism Industry ◽  
Country Risk ◽  
Series Data ◽  
The South ◽  
Long Run ◽  
International Tourist ◽  
Tourism Revenue

The contribution of tourism to a country’s economy is determined by country risk measures such as economic, financial and political risk. This study aimed to investigate short and long-run effects of country risk factors on international tourist arrivals and tourism revenue for the South African tourism industry. The sample period consists of monthly time series data of tourist arrivals, tourism revenue, and country risk factors from January 2004 to December 2018. Data was analysed using the Autoregressive distributed lag (ARDL) and non-linear ARDL (NARDL) models. The findings showed that the long-run effects of country risk factors on tourist arrivals and revenue are asymmetric. Economic, financial, and political measures of country risk negatively affect tourist arrivals, however, tourism revenue responds differently to changes in these risk factors. Political risk has the highest effect on the tourism industry compared to economic and financial risk factors. Overall, this study established that both international tourist arrivals and tourism revenue are threatened by financial shocks indicating that an unconducive financial environment has long-term negative implications on the South African tourism industry.

The effects of political, economic and financial components of country risk on housing prices in South Africa

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Paul-Francois Muzindutsi ◽  
Sanelisiwe Jamile ◽  
Nqubeko Zibani ◽  
Adefemi A. Obalade
Keyword(s):  
Risk Factors ◽  
South Africa ◽  
Housing Market ◽  
Time Series Data ◽  
Housing Prices ◽  
Political Risk ◽  
Country Risk ◽  
Series Data ◽  
Content Type ◽  
Short Run

Purpose The housing market in South Africa has the potential to drive economic growth and attract foreign investment, but it can be affected by various risk factors. This paper aims to conduct an empirical analysis of the effect of country risk components on the housing market in South Africa. Design/methodology/approach Linear and nonlinear autoregressive distributed lag (ARDL) models were used to evaluate the effects of the economic, financial and political risk factors of country risk on the prices of different segments of houses based on 276 monthly time-series data from January1995 to December 2015. Findings First, the results established that the three housing indices were more sensitive to political risk in the long run. Second, short run results showed that the three housing indices were largely influenced by their own preceding adjustments in the short run albeit minimal influences from political risk. Third, large housing segments indicated a higher magnitude of the country risk effect in South Africa. Originality/value This paper concluded that the response of housing prices to changes in the country risk components differed across the three segments of the housing market in South Africa. Consequently, this study presented the first comparison of the reactions of different housing segments to different components country risk.

scholarly journals The Impact of Productivity, Investment and Real Wages on Employment Absorption Rate in South Africa

2019 ◽  
Vol 8 (12) ◽  
pp. 330 ◽  
Author(s):  
Thomas Habanabakize ◽  
Daniel Francois Meyer ◽  
Judit Oláh
Keyword(s):  
South Africa ◽  
South African ◽  
Absorption Rate ◽  
Labour Productivity ◽  
Series Data ◽  
The South ◽  
Real Wages ◽  
Long Run ◽  
Investment Spending ◽  
The Impact

Many developing countries are facing high levels of unemployment and most people who are employed are poorly remunerated due to low skills and productivity levels. Although jobs are important, a productive job is even more important, not only for employees, but also for employers. South Africa, being a developing country, is also facing the challenge of dramatically high levels of unemployment. This study’s aim was to examine both the short- and long-term impacts of real wages, labour productivity and investment spending on employment absorption rates in South Africa. To establish the existing relationship between variables, the study applied several econometric approaches, such as an autoregressive distributed lag (ARDL) model, error correction model (ECM) and a Toda–Yamamoto causality analysis on quarterly time series data from 1995Q1 to 2019Q1. The results revealed the existence of both short- and long-run relationships among the variables. While a positive relationship was found between employment absorption, investment spending and labour productivity, it was found that real wages negatively impact on long-run employment absorption rates. Additionally, the short-run analysis indicated that the lagged employment absorption rate influences the current rate of employment. Furthermore, the causality tests indicated that a bi-directional causal relationship exists between employment absorption and investment spending; and a uni-directional relationship between employment and both real wages and labour productivity. Based on the findings, the study recommends increments of investment spending and labour productivity that enables the South African economy to carry out more activities that would require more workers, thereby improving the employment absorption rate. The fact that labour productivity positively impacts the employment absorption rate infers the requirement for quality and skilled workers to be absorbed in the South African labour market. Therefore, labour skills improvements appear to be a prerequisite for productivity enhancement and job creation.

scholarly journals Cointegration and stock market interdependence: Evidence from South Africa, India and the USA

2015 ◽  
Vol 18 (4) ◽  
pp. 475-485 ◽  
Author(s):  
Mohanasundaram Thangamuthu ◽  
Karthikeyan Parthasarathy
Keyword(s):  
South Africa ◽  
Stock Market ◽  
South African ◽  
Stock Markets ◽  
Predictive Ability ◽  
Series Data ◽  
The South ◽  
Long Run ◽  
The Usa ◽  
Short Run

The purpose of this study is to explore the nature of the association and the possible existence of a shortrun and long-run relationship between the stock-market indices of South Africa, India and the USA. The idea behind this combination is to know how the stock markets of these three prominent countries are related to each other. The study employs monthly data from the stock indices, namely JALSH (South Africa), NIFTY (India) and NASDAQ (USA) composite from April 2004 to March 2014. After testing for the normality of the data distribution and the stationarity of the time series data, this paper discovered a strong correlation between the stock market indices of South Africa, India and the USA. The correlation among the stock markets is high, particularly between South Africa and India. In addition, the paper attempts to discover the presence of any predictive ability among these markets by applying the Granger causality test. The result indicates that the NASDAQ index has no predictive ability as far as the JALSH and NIFTY indices are concerned. However, the JALSH index has a predictive ability on the NIFTY index. After testing the Granger cause relationship, the existence of a long-run and short-run relationship is tested. The long-run relationships among the stock market indices are analysed, following the Johansen and Juselius multivariate cointegration approach. The result suggests the absence of a long-run relationship among the three stock market indices. Short-run relationship is investigated with the Vector Autoregression (VAR) model, and the outcome obtained shows that both the USA and the South African stock markets are predicted only by their own past lags. However, the Indian stock market is seen to be a function of its own past lags and the past lags of the South African stock index. 

scholarly journals Achieving Food Security in a Climate Change Environment: Considerations for Environmental Kuznets Curve Use in the South African Agricultural Sector

Climate ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 108 ◽  
Author(s):  
Ngarava ◽  
Zhou ◽  
Ayuk ◽  
Tatsvarei
Keyword(s):  
Climate Change ◽  
South Africa ◽  
Energy Consumption ◽  
South African ◽  
Co2 Emissions ◽  
Agricultural Sector ◽  
Series Data ◽  
The South ◽  
Agricultural Income ◽  
Long Run

This study relates agricultural income and agricultural carbon dioxide (CO2) emissions in the context of environmental Kuznets curves for South Africa. We posit likely relationships between UN Sustainable Development Goals (SDG) 1, 2 and 13, relating food production to climate change action. CO2 emissions, income, coal energy consumption and electricity energy consumption time series data from 1990 to 2012 within the South African agricultural sector were used. The autoregressive distributive lag bounds-test and the error correction model were used to analyse the data. The results show long-run relationships. However, agricultural income was only significant in the linear and squared models. Changes in agricultural CO2 emissions from the short run towards the long run are estimated at 71.9%, 124.7% and 125.3% every year by the linear, squared and cubic models, respectively. Exponentially increasing agricultural income did not result in a decrease in agricultural CO2 emissions, which is at odds with the Kuznets hypothesis. The study concludes that it will be difficult for South Africa to simultaneously achieve SDGs 1, 2 and 13, especially given that agriculture is reliant upon livestock production, the largest CO2 emitter in the sector. The sector needs to shift to renewable energy consumption with fewer CO2 emissions.

scholarly journals THE RELATIONSHIP BETWEEN POLITICAL RISK AND EMPLOYMENT IN TOURISM: A CASE OF SOUTH AFRICA

2021 ◽  
Vol 9 (2) ◽  
pp. 78-88
Author(s):  
Jean Claude Manaliyo ◽  
Keyword(s):  
Time Series Data ◽  
Political Risk ◽  
Tourism Industry ◽  
Series Data ◽  
Long Run ◽  
Tourism Sector ◽  
Short Run ◽  
High Level ◽  
The Impact ◽  
The Relationship

Political risk is one of the determinants of employment in the tourism industry. Changes in the level of political risk in a country result in fluctuations in employment in the tourism sector. Countries with a high level of political risk experience a decline in employment whereas countries with a low level of political risk experience an increase in employment. This paper investigates the impact of political risk on employment in South Africa’s tourism industry using quarterly time series data for the period between 2007 and 2017. The study employs the Autoregressive Distribution Lag (ARDL) model to determine the impact of political risk on employment in tourism in both the short- and long-run. The results from the analysis reveal that political risk has both short- and long-run effects on employment in South Africa’s tourism industry. When the level of political risk declines by 1%, employment grows by 5.016% in the long-run whereas employment increases by 1.51% in the short-run when the level of political risk declines by 1%. These results imply that governments have to keep the level of political risk low by avoiding political risk events and actions for the tourism industry to create additional employment opportunities.

scholarly journals Analysis of the Keynesian Theory of Employment and Sectoral Job Creation: The Case of the South African Manufacturing Sector

2018 ◽  
Vol 18 (1) ◽  
pp. 123-143
Author(s):  
Thomas Habanabakize ◽  
Paul-Francois Muzindutsi
Keyword(s):  
South African ◽  
Manufacturing Sector ◽  
Job Creation ◽  
The South ◽  
Economic Sectors ◽  
Vector Autoregressive ◽  
Integration Approach ◽  
Long Run ◽  
Short Run ◽  
Investment Spending

Abstract The manufacturing sector is one of the backbones of the South African economy, and yet is one of the economic sectors facing challenges in job creation. This study analysed the long-run and short-run effects of aggregate expenditure components on job creation in the South African manufacturing sector. A Vector Autoregressive (VAR) with Johansen co-integration approach was used to analyse quarterly data from 1994 to 2015. The findings are that there is a long-run relationship between aggregate expenditure and job creation in the South African manufacturing sector, with government and investment spending being the major components of aggregate expenditure that create jobs in the South African manufacturing sector. Conversely, consumption spending destroys jobs in the manufacturing sector, while net exports have no significant effect on job creation. The short-run relationship between variables was not significant. Recommendations are that more effort should be put into investment spending, and government should spend more on investment than on consumption spending - in order to increase job creation in the manufacturing sector.

scholarly journals The Contribution of Foreign Direct Investment (FDI) To Domestic Employment Levels in South Africa: A Vector Autoregressive Approach

2019 ◽  
Vol 11 (1(J)) ◽  
pp. 110-121
Author(s):  
Bongumusa Prince Makhoba, ◽  
Irrshad Kaseeram
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Least Squares ◽  
South African ◽  
Empirical Analysis ◽  
Negative Relationship ◽  
Ordinary Least Squares ◽  
Series Data ◽  
The South ◽  
Vector Autoregressive

Several empirical works have yielded mixed and controversial results with regard to the effects of FDI on employment and economic growth. The primary focus of this study is to investigate the contribution of FDI to domestic employment levels in the context of the South African economy. The analyses of the study were carried out using the annual time series data from 1980 to 2015. The macroeconomic variables employed in the empirical investigation include employment, FDI, GDP, inflation, trade openness and unit labour costs. The study used secondary data from the South African Reserve Bank and Statistics South Africa database. The study estimated a Vector Autoregressive/ Vector Error Correction Mechanism (VAR/VECM) approach to conduct empirical analysis. However, the study also employed single equation estimation techniques, including the Ordinary Least Squares (OLS), Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS) and Canonical Cointegrating Regression (CCR) models as supporting tools to verify the VAR/VECM results. This study provides strong evidence of a significant negative relationship between FDI and employment levels in the South African economy. Empirical analysis of the study suggests that the effect of economic growth on employment is highly positive and significant in South Africa’s economy. The study recommends that policymakers ought to invest more in productive sectors that aim to promote economic growth and development to boost employment opportunities in South Africa.

scholarly journals Prediction of Urban and Rural Tourism Economic Forecast Based on Machine Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Wusheng Zhou
Keyword(s):  
Time Series ◽  
Economic Development ◽  
Causal Relationship ◽  
Local Economic Development ◽  
Tourism Industry ◽  
Local Economy ◽  
Series Data ◽  
Economic Forecast ◽  
The Relationship ◽  
Tourism Revenue

With the rapid development of tourism, tourism revenue, as one of the important indicators to measure the development of the tourism economy, has high research value. The quasi-prediction of tourism revenue can drive the development of a series of related industries and accelerate the development of the domestic economy. When forecasting tourism income, it is necessary to examine the causal relationship between tourism income and local economic development. The traditional cointegration analysis method is to extract the promotion characteristics of tourism income to the local economy and construct a tourism income prediction model, but it cannot accurately describe the causal relationship between tourism income and local economic development and cannot accurately predict tourism income. We propose an optimized forecasting method of tourism revenue based on time series. This method first conducts a cointegration test on the time series data of the relationship between tourism income and local economic development, constructs a two-variable autoregressive model of tourism income and local economy, and uses the swarm intelligence method to test the causal relationship and the relationship between tourism income and local economic development, calculate the proportion of tourism industry, define the calculation result as the direct influence factor of tourism industry on the local economy, calculate the relevant effect of local tourism development and economic income, and construct tourism income optimization forecast model. The simulation results show that the model used can accurately predict tourism revenue.

scholarly journals An assessment of the interrelations between country risk, economic growth and good governance: The case of the Visegrád four

2021 ◽  
Vol 8 (4) ◽  
pp. 610-627
Author(s):  
Daniel Francois Meyer
Keyword(s):  
Risk Factors ◽  
Economic Growth ◽  
Economic Performance ◽  
Quantitative Research ◽  
Time Series Data ◽  
Good Governance ◽  
Risk Index ◽  
Country Risk ◽  
Series Data ◽  
Short Run

nvestors assess the environment and the level of risk before they invest in a specific region or country. Several country risk indexes have been developed since the beginning of the 1990s, using risk factors such as politics, the economy and sovereign risk factors. This study aims to determine the relationships between the country risk index, economic performance and good governance. The study implemented a quantitative research methodology with panel data, focusing on the four Visegrad countries, using time-series data from 1996 to 2019. The results indicate both long- and short-run relationships. Both GDP and good governance significantly impact the country risk index with coefficients of between 0.17 to 0.31 and 0.02 to 0.15 according to different estimation models. The Granger causality results indicated that both GDP and good governance cause changes in the country risk indexes of the countries, and good governance causes increased economic performance. In conclusion, the study showed clear evidence that a lower country risk index is important to attract investment and sustained economic growth and good governance is critical in this process.          

scholarly journals How applicable is export-led growth and import-led growth hypotheses to South African economy?

2015 ◽  
Vol 4 (2) ◽  
pp. 15-24
Author(s):  
Ntebogang Dinah Moroke ◽  
Molebogeng Manoto
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Adverse Effect ◽  
Time Series ◽  
South African ◽  
Time Series Data ◽  
Series Data ◽  
Long Run ◽  
Reserve Bank ◽  
Equilibrium Relationship

This paper investigated exports, imports and the economic growth nexus in the context of South Africa. The paper sets out to examine if long-run and causal relationships exist between these variables. Quarterly time series data ranging between 1998 and 2013 obtained from the South African Reserve Bank and Quantec databases was employed. Initial data analysis proved that the variables are integrated at their levels. The results further indicated that exports, imports and economic growth are co-integrated, confirming an existence of a long-run equilibrium relationship. Granger causal results were shown running from exports and imports to GDP and from imports to exports, validating export-led and import-led growth hypotheses in South Africa. A significant causality running from imports to exports, suggests that South Africa imported finished goods in excess. If this is not avoided, lots of problems could be caused. A suggestion was made to avoid such problematic issues as they may lead to replaced domestic output and displacement of employees. Another dreadful ramification may be an adverse effect on the economy which may further be experienced in the long-run.

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