Analysing seasonal changes in New Zealand's largest inbound market

The purpose of the paper is to analyse seasonal changes in tourism demand by New Zealand's major tourist source market, Australia, for the period 1979-2005. A time series regression model is used to test the significance of monthly seasonality. By examining sub-periods that are based on major exogenous events which have had significant impacts on international travel demand to New Zealand, seasonal distributions and intra-year seasonal variations over the 27-year period are subsequently estimated using normalized seasonal indices, coefficient of variation, seasonal ratio and the Gini coefficient. Compared with the findings of previous studies for other countries, the empirical evidence suggests that, while the tourism flow distribution or concentration is not significant for New Zealand, the seasonality in tourism demand by New Zealand's largest inbound market has changed over time

Modelling the Determinants of International Tourism Demand to Australia,

Prior to the recent Asian currency and economic crises, tourism from Asia had rapidly become Australia's major tourism export industry. Tourists from Singapore, which is Australia's fifth major market, represented 6% of international tourist arrivals to Australia in 1996. The average annual growth rate of tourist arrivals from Singapore of around 20% over 1990-96 far exceeded the 10.5% average annual percentage growth rate of all tourist arrivals to Australia over the same period (Australian Bureau of Statistics, 1997). Despite the Asian currency and economic crises in 1997-98, tourist arrivals to Australia from Singapore has continued to grow slowly. It is imperative from the tourism marketing SWOT (strengths, weaknesses, opportunities and threats) analysis to consider the economic factors influencing international tourism demand for Australia by Singapore, and to undertake a primary competitor analysis of New Zealand. The purpose of the paper is to estimate the income, price and transportation cost elasticities of inbound tourism from Singapore to Australia using seasonally unadjusted quarterly data, to determine if Australia and New Zealand are substitute or complementary destinations for Singaporean tourists, and to examine issues such as nonstationarity, cointegration and spurious regressions.

"Ecologically Sustainable Tourism Management"

One of the primary challenges facing ecotourism management is to establish a profitable and ecologically sustainable industry, while simultaneously achieving a satisfying experience for visitors and raising standards of living in the host community. This paper analyses the management practices and challenges faced by two ecotourism attractions on the Gold Coast in Queensland, Australia, namely Couran Cove Island Resort and Boondall Wetlands Reserve. As an ecotourism-based resort on one of the world's few naturally-occurring sand islands, Couran Cove is active in implementing a range of initiatives for sustainable environmental management. This is particularly important as Couran Cove is home to a wide variety of plant communities and one of the largest remnants of the rare Livistona rainforest on the Gold Coast. The Boondall Wetlands Reserve is internationally recognized as an important feeding and resting habitat for migratory wading birds from Alaska, China, Japan, Mongolia and Siberia. Through the activities of the Visitor Centre, the Boondall Wetlands Reserve aims to: (i) promote environmental awareness within the local and regional communities; (ii) provide community education and information about wetlands systems within the local, regional and global context; (iii) offer nature-based recreation and tourism services; and (iv) demonstrate how wetlands can diversify the tourism and ecotourism industries.

"Modelling International Travel Demand from Singapore to Australia"

Prior to the recent Asian currency and economic crises, tourism from Asia had rapidly become Australia's major tourism export industry. Tourists from Singapore, which is Australia's fifth major market, represented 6% of international tourist arrivals to Australia in 1996. The average annual growth rate of tourist arrivals from Singapore of around 20% over 1990-96 far exceeded the 10.5% average annual percentage growth rate of all tourist arrivals to Australia over the same period (Australian Bureau of Statistics, 1997). Despite the Asian currency and economic crises in 1997-98, tourist arrivals to Australia from Singapore has continued to grow slowly. It is imperative to consider the economic factors influencing international tourism demand for Australia by Singapore, and to undertake a sensitivity analysis of tourist arrivals to changes in the factors. The purpose of the paper is to estimate the income, price and transportation cost elasticities of inbound tourism from Singapore to Australia using seasonally unadjusted quarterly data. Initially, estimation is undertaken using ordinary least squares. Given New Zealand's proximity to Australia, it is also useful to determine using a single-equation model if Australia and New Zealand are substitute or complementary destinations for Singaporean tourists by examining the effects of the relative price changes in New Zealand and Australia on international travel demand for Australia. In addition, seasonal influences are examined using the single-equation model. The OLS estimates of the appropriate single-equation model are also compared with the estimates obtained using the cointegration method in Lim and McAleer (2001).

Time Series Forecasts of International Tourism Demand for Australia,

This paper examines stationary and nonstationary time series by formally testing for the presence of unit roots and seasonal unit roots prior to estimation, model selection and forecasting. Various Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) models are estimated over the period 1975(1)-1989(4) for tourist arrivals to Australia from Hong Kong, Malaysia and Singapore. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as measures of forecast accuracy. As the best fitting ARIMA model is found to have the lowest RMSE, it is used to obtain post-sample forecasts. Tourist arrivals data for 1990(1) to 1996(4) are compared with the forecast performance of the ARIMA model for each origin market. The fitted ARIMA model forecasts tourist arrivals from Singapore between 1990(1)-1996(4) very well. Although the ARIMA model outperforms the seasonal ARIMA models for Hong Kong and Malaysia, the forecast of tourist arrivals is not as accurate as in the case of Singapore.

Modelling the Volatility in Short and Long Haul Japanese Tourist Arrivals to New Zealand and Taiwan

This paper estimates the effects of short and long haul volatility (or risk) in monthly Japanese tourist arrivals to Taiwan and New Zealand, respectively. In order to model appropriately the volatilities of international tourist arrivals, we use symmetric and asymmetric conditional volatility models that are commonly used in financial econometrics, namely the GARCH (1,1), GJR (1,1) and EGARCH (1,1) models. The data series are for the period January 1997 to December 2007. The volatility estimates for the monthly growth in Japanese tourists to New Zealand and Taiwan are different, and indicate that the former has an asymmetric effect on risk from positive and negative shocks of equal magnitude, while the latter has no asymmetric effect. Moreover, there is a leverage effect in the monthly growth rate of Japanese tourists to New Zealand, whereby negative shocks increase volatility but positive shocks of similar magnitude decrease volatility. These empirical results seem to be similar to a wide range of financial stock market prices, so that the models used in financial economics, and hence the issues related to risk and leverage effects, are also applicable to international tourism flows.Tourist arrivals, Long haul, Short haul, Risk, Conditional volatility, Asymmetric effect, Leverage.

"Modelling Short and Long Haul Volatility in Japanese Tourist Arrivals to New Zealand and Taiwan"

This paper estimates the effects of short and long haul volatility (or risk) in monthly Japanese tourist arrivals to Taiwan and New Zealand , respectively. In order to model appropriately the volatilities of international tourist arrivals, we use symmetric and asymmetric conditional volatility models that are commonly used in financial econometrics, namely the GARCH (1,1), GJR (1,1) and EGARCH (1,1) models. The data series are for the period January 1997 to December 2007. The volatility estimates for the monthly growth in Japanese tourists to New Zealand and Taiwan are different, and indicate that the former has an asymmetric effect on risk from positive and negative shocks of equal magnitude, while the latter has no asymmetric effect. Moreover, there is a leverage effect in the monthly growth rate of Japanese tourists to New Zealand, whereby negative shocks increase volatility but positive shocks of very similar magnitude decrease volatility. These empirical results seem to be similar to a wide range of financial stock market prices, so that the models used in financial economics, and hence also the issues related to risk and leverage effects, are also applicable to international tourism flows.

"Time Series Modelling of Tourism Demand from the USA, Japan and Malaysia to Thailand"

Even though tourism has been recognized as one of the key sectors for the Thai economy, international tourism demand, or tourist arrivals, to Thailand have recently experienced dramatic fluctuations. The purpose of the paper is to investigate the relationship between the demand for international tourism to Thailand and its major determinants. The paper includes arrivals from the USA, which represents the long haul inbound market, from Japan as the most important medium haul inbound market, and from Malaysia as the most important short haul inbound market. The time series of tourist arrivals and economic determinants from 1971 to 2005 are examined using ARIMA with exogenous variables (ARMAX) models to analyze the relationships between tourist arrivals from these countries to Thailand. The economic determinants and ARMA are used to predict the effects of the economic, financial and political determinants on the numbers of tourists to Thailand.

Modified Gravity Makes Galaxies Brighter

We investigate the effect of modifed gravity with screening mechanisms, such as the chameleon or symmetron models, upon the structure of main sequence stars. We find that unscreened stars can be significantly more luminous and ephemeral than their screened doppelgangers. By embedding these stars into dwarf galaxies, which can be unscreened for values of the parameters not yet ruled out observationally, we show that the cumulative effect of their increased luminosity can enhance the total galactic luminosity. We estimate this enhancement and find that it can be considerable given model parameters that are still under experimental scrutiny. By looking for systematic offsets between screened dwarf galaxies in clusters and unscreened galaxies in voids, these effects could form the basis of an independent observational test that can potentially lower the current experimental bounds on the model independent parameters of these theories by and order of magnitude or more.Comment: 16 pages, six figure

Time series forecasts of international tourism demand for Australia

This paper examines stationary and nonstationary time series by formally testing for the presence of unit roots and seasonal unit roots prior to estimation, model selection and forecasting. Various Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) models are estimated over the period 1975(1)-1989(4) for tourist arrivals to Australia from Hong Kong, Malaysia and Singapore. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as measures of forecast accuracy. As the best fitting ARIMA model is found to have the lowest RMSE, it is used to obtain post-sample forecasts. Tourist arrivals data for 1990(1) to 1996(4) are compared with the forecast performance of the ARIMA model for each origin market. The fitted ARIMA model forecasts tourist arrivals from Singapore between 1990(1)-1996(4) very well. Although the ARIMA model outperforms the seasonal ARIMA models for Hong Kong and Malaysia, the forecast of tourist arrivals is not as accurate as in the case of Singapore