Quantitative methods for forecasting tourist arrivals can be subdivided into causal methods and non-causal methods. Non-causal time series methods remain popular tourism forecasting tools due to the accuracy of their forecasting ability and general ease of use. Since tourist arrivals exhibit seasonality, Seasonal Autoregressive Integrated Moving Average (SARIMA) models are often found to be the most accurate. However, these models assume that the time series is linear. This article compares the baseline seasonal Naïve and SARIMA forecasts of a seasonal tourist destination faced with a structural break in the data with alternative non-linear methods, with the aim of determining the accuracy of the various methods. These methods include the unobserved components model, smooth transition autoregressive model and singular spectrum analysis. The results show that the non-linear forecasts outperform the other methods. The linear methods show some superiority in short-term forecasts when there are no structural changes in the time series.

Background: The informal economy in South Africa provides employment to large numbers of people who would otherwise have no opportunity to earn a living. Yet informal activities, such as day labouring, generate highly uncertain returns. Although it seems reasonable to conclude that day labourers would be dissatisfied with their lives, this is not necessarily the case as several factors contribute to people’s subjective well-being. Aim: This study is in response to a call for more research on the subjective well-being of marginalised groups in South Africa’s informal labour market. Setting: The day labour market in South Africa, whose members congregate at hiring sites hoping to be picked up by passers-by in need of temporary, casual workers. Methods: Using Sen’s Capability Approach, the study builds on earlier research conducted on the general well-being of day labourers in South Africa, with specific focus on their subjective well-being and geographical location. The results from a countrywide survey of 3830 day labourers were used in a regression analysis to compare the subjective well-being among day labourers across the nine provinces of South Africa. Results: There are statistically significant differences in the well-being of day labourers across the nine provinces. Economic variables play a role in both objective and subjective measures of well-being, while attitudinal and comparison variables are significant for the objective and subjective measures, respectively. Conclusions: Although they have to operate in harsh conditions, day labourers in South Africa display agency by choosing to migrate to richer provinces in search of greater economic opportunity and reward. However, these potential gains are often negated by increased levels of competition and thus depressed wage levels. How to nurture marginalised groups’ abilities to exercise agency and take more control of their lives represents fertile ground for researchers in future.

Past research provided evidence of the negative effect that individual unemployment can have on subjective well-being. The persistent high levels of unemployment and poverty in South Africa INTRODUCTION AND AIM OF THE PAPERhere was a time when the study of well-being, and subjective well-being in particular, was, for the most part, excluded from economic analysis as a result of the disciplinary paradigm of logical positivism. Yet, economic theories often include reference to values, expectations, and the like (Easterlin 2001: 225).Since the 1940s, the landscape has changed and, recently, Helliwell and Barrington-Leigh (2010) have argued that growing awareness is being raised in academic, policy, and public areas to subjective measures of wellbeing. This represents an important shift towards greater realism in the study of economic behaviour. Subsequently, a significant body of literature emerged on the determinants of well-being in developed countries. Recent research findings on well-being in developing countries specifically have added more depth to the development debate (Tiwari 2009: 129).Most studies on subjective well-being in transitional economies focus on either rural areas or gender groups. Prominent scholars in South Africa ensured that South Africa's transitional experience and its influence on well-being form part of this important research agenda (Møller and Schlemmer, 1989;Møller, 1998;Møller and Saris, 2001;Møller and Dickow, 2002;Ebrahim, Botha, and Snowball, 2011;Botha and Booysen, 2011). A constant theme in South African literature is that, in the main, the wealthier testify to higher levels of satisfaction and On the other hand, people in the Eastern Cape, a province with the high levels of unemployment and deep poverty, are principally unhappy, dissatisfied, and pessimistic.Cramm, Møller, and Nieboer (2010: 1013) state that there is a scarcity of research on well-being among the poorest of the poor. As a result, the experiences in terms of the well-being of marginalised groups in the South African labour market have not received sufficient attention in South African research on the subject.Past research results provided evidence of the negative effect that individual unemployment can have on subjective well-being (Winkelmann, 2009: 421). The persistent high levels of unemployment and the severity of absolute poverty in South Africa have been well documented. As a result, many people are forced into the informal economy where they engage a variety of survivalist activities. Offering their labour on street corners and at intersections as day labourers is a pertinent example in this regard. Blaauw (2010) found no pure economic rationale for the sustainability of this activity, given the cost and the low and uncertain levels of income in this market, yet many day labourers have been involved in this activity for many years. Researching the well-being in this informal labour market is an important extension of the research into the employee side of the informal economy. It takes cognisa...

Orientation: High exchange rate volatility has implications for business and policy decisions and exchange rate movements are important in debates around trade and trade policies. Research purpose: The purpose of the research was to determine the impact of exchange rate volatility on exports in emerging markets. Motivation for the study: A lack of clarity in literature regarding this relationship increases the risk of improper planning by export organisations as well as implementing suboptimal economic policies. Research design, approach and method: This research analysed the effect of exchange rate volatility on emerging market exports using a sample of nine emerging countries from 1995 to 2010. Panel data analysis was conducted. Volatility was measured by Generalised Autoregressive Conditional Heteroscedasticity and conventional standard deviation in order to determine if the instrument of volatility used influenced the nature of the relationship between exchange rate volatility and exports. The Pedroni residual cointegration method was used to test for panel cointegration in order to determine if there was a long-run relationship. Main findings: The results showed that exchange rate volatility had a significant negative effect on the performance of exports, regardless of the measure of volatility used. It was also evident that a long-run relationship did exist. Practical/managerial implications: The study concluded that the policy mix that will reduce exchange rate volatility (such as managed exchange rate regimes) and relatively competitive exchange rates were essential for emerging markets in order to sustain their exports performance. Contribution/value-add: This research provided policy makers of emerging market economies with new evidence pertaining to the relationship between exchange rate volatility and the performance of exports. This research contributed to the existing knowledge on the topic and provides a base for future research on related topics.

A new approach is proposed to identify trading opportunities in the equity market by using the information contained in the bivariate dependence structure of two equities. The relationships between the equity pairs are modelled with bivariate copulas and the fitted copula structures are utilised to identify the trading opportunities. Two trading strategies are considered that take advantage of the relative mispricing between a pair of correlated stocks and involve taking a position on the stocks when they diverge from their historical relationship. The position is then reversed when the two stocks revert to their historical relationship. Only stock-pairs with relatively high correlations are considered. The dependence structures of the chosen stock-pairs very often exhibited both upper- and lower-tail dependence, which implies that copulas with the correct characteristics should be more effective than the more traditional approaches typically applied. To identify trading opportunities, the conditional copula functions are used to derive confidence intervals for the two stocks. It is shown that the number of trading opportunities is highly dependent on the confidence level and it is argued that the chosen confidence level should take the strength of the dependence between the two stocks into account. The backtest results of the pairs-trading strategy are disappointing in that even though the strategy leads to profits in most cases, the profits are largely consumed by the trading costs. The second trading strategy entails using single stock futures and it is shown to have more potential as a statistical arbitrage approach to construct a portfolio.