Modelling conditional correlations in the volatility of Asian rubber spot and futures returns

Asia is presently the most important market for the production and consumption of natural rubber. World prices of rubber are not only subject to changes in demand, but also to speculation regarding future markets. Japan and Singapore are the major futures markets for rubber, while Thailand is one of the world’s largest producers of rubber. As rubber prices are influenced by external markets, it is important to analyse the relationship between the relevant markets in Thailand, Japan and Singapore. The analysis is conducted using several alternative multivariate GARCH models. The empirical results indicate that the constant conditional correlations arising from the CCC model of Bollerslev (1990) lie in the low to medium range. The results from the VARMA-GARCH model of Ling and McAleer (2003) and the VARMA-AGARCH model of McAleer et al. (2009) suggest the presence of volatility spillovers and asymmetric effects of positive and negative return shocks on conditional volatility. Finally, the DCC model of Engle (2002) suggests that the conditional correlations can vary dramatically over time. In general, the dynamic conditional correlations in rubber spot and futures returns shocks can be independent or interdependent

IV estimation of a panel threshold model of tourism specialization and economic development

The significant impact of international tourism in stimulating economic growth is especially important from a policy perspective. For this reason, the relationship between international tourism and economic growth would seem to be an interesting and topical empirical issue. The paper investigates whether tourism specialization was important for economic development in 159 countries over the period 1989–2008. The results from panel threshold regressions show a positive relationship between economic growth and tourism. Instrumental variable estimation of a threshold regression is used to quantify the contributions of tourism specialization to economic growth, while correcting for endogeneity between the regressors and error term. The significant impact of tourism specialization on economic growth in most regressions is robust to different specifications of tourism specialization, as well as to differences in real GDP measurement. However, the coefficients of the tourism specialization variables in the two regimes are significantly different, with a higher impact of tourism on economic growth found in the low regime. These findings do not alter with changes in the threshold variables. The empirical results suggest that tourism growth does not always lead to substantial economic growth