Are Combined Tourism Forecasts Better at Minimizing Forecasting Errors?

This study, which was contracted by the European Commission and is geared towards easy replicability by practitioners, compares the accuracy of individual and combined approaches to forecasting tourism demand for the total European Union. The evaluation of the forecasting accuracies was performed recursively (i.e., based on expanding estimation windows) for eight quarterly periods spanning two years in order to check the stability of the outcomes during a changing macroeconomic environment. The study sample includes Eurostat data from January 2005 until August 2017, and out of sample forecasts were calculated for the last two years for three and six months ahead. The analysis of the out-of-sample forecasts for arrivals and overnights showed that forecast combinations taking the historical forecasting performance of individual approaches such as Autoregressive Integrated Moving Average (ARIMA) models, REGARIMA models with different trend variables, and Error Trend Seasonal (ETS) models into account deliver the best results

A comparative analysis of tourism destination demand in Portugal

Tourism has experienced different levels of development in the different regions of Portugal. To frame this development, in this paper dynamic panel data models were estimated with the objective of explaining the evolution of international overnight stays in each region. Secondary data from 2000 to 2011 was used. The analysis includes the main tourism source markets for Portugal, such as the United Kingdom, Germany, the Netherlands, Ireland, France and Spain. The tourism literature suggests that, among others, the main determinants of tourism demand are income (GDP), household consumption, unemployment rate and the harmonised consumer price index. Per capita income, unemployment rate and final household consumption were identified as the most shared explanatory variables in each tourism region. However, in some regions, the high elasticity with respect to per capita income was confirmed, suggesting that tourism is a luxury good. It is observed that, although significant, the explanatory power of these variables varies according to the origin and the destination region considered. Findings suggest heterogeneous behaviour of the main international tourism demand by region. Furthermore, results also suggest some implications for public and private tourism authorities. Stakeholders can update the analysis, trends and forecasts of international tourism demand, put forward in the National Strategic Plan for Tourism for the period from 2013 to 2015, by taking into account the different macroeconomic variables that help explain international overnight stays in each region of Portugal. (C) 2013 Elsevier Ltd. All rights reserved

How strong is the linkage between tourism and economic growth in Europe?

In this study, we examine the dynamic relationship between tourism growth and economic growth, using a newly introduced spillover index approach. Based on monthly data for 10 European countries over the period 1995{2012, our analysis reveals the following empirical regularities. First, the tourism-economic growth relationship is not stable over time in terms of both magnitude and direction, indicating that the tourism{led economic growth (TLEG) and the economic{driven tourism growth (EDTG) hypotheses are time{dependent. Second, the aforementioned relationship is also highly economic event{dependent, as it is influenced by the Great Recession of 2007 and the ongoing Eurozone debt crisis that began in 2010. Finally, the impact of these economic events is more pronounced in Cyprus,Greece, Portugal and Spain, which are the European countries that have witnessed the greatest economic downturn since 2009. Plausible explanations of these results are provided and policy implications are drawn

Tourism economics research: A review and assessment

This paper aims to provide the most up-to-date survey of tourism economics research and to summarise the key trends in its recent development. Particular attention is paid to the research progress made over the last decade in respect of approaches, methodological innovations, emerging topics, research gaps, and directions for future research. Remarkable but unbalanced developments have been observed across different sub-research areas in tourism economics. While neoclassical economics has contributed the most to the development of tourism economics, alternative schools of thought in economics have also emerged in advancing our understanding of tourism from different perspectives. As tourism studies are multi- and inter-disciplinary, integrating economics with other social science disciplines will further contribute to knowledge creation in tourism studies

Labor Productivity - The Use of Staffing Guides and Other Productivity Methods in U.S. Hotels: A Survey Study

This paper examines the issue of labor productivity in hotels. It elaborates on various measurement methods used by American hoteliers including staffing guides, with a special focus on productivity standards. Advantages of physical, financial and mixed methods such as percentage methods, revenue per employee, value-added, Data Envelope Analysis and Stochastic Frontier Analysis are discussed. While the use of percentages and staffing guides were found to be commonplace, results revealed that some fairly stable standards were already in place in the surveyed hotels. Results also revealed that at least in the surveyed companies, few hoteliers attempted to monitor or improve revenue per employee, focusing instead on physical labor inputs and outputs or simple labor percentages

The economic importance of meetings and conferences: A satellite account approach

Meetings and conventions (MICE) visitation is often considered an important element of the travel economy, and destinations target such activities to encourage their growth. It has hitherto been difficult to measure the economic significance of such activity at any spatial scale. Latterly, the development and codification of tourism satellite account (TSA) approaches to the economic measurement of tourism offers an opportunity to develop a parallel approach to understanding the MICE economy. This paper presents an estimate of the direct economic impact of MICE activity in the UK in 2011, following TSA approaches. The potential to extend the core Meetings Satellite Account, to estimate indirect economic impact and sub-national economic impacts, is also assessed

Tourism and Economic Globalization: An Emerging Research Agenda

Globalization characterizes the economic, social, political, and cultural spheres of the modern world. Tourism has long been claimed as a crucial force shaping globalization, while in turn the developments of the tourism sector are under the influences of growing interdependence across the world. As globalization proceeds, destination countries have become more and more susceptible to local and global events. By linking the existing literature coherently, this study explores a number of themes on economic globalization in tourism. It attempts to identify the forces underpinning globalization and assess the implications on both the supply side and the demand side of the tourism sector. In view of a lack of quantitative evidence, future directions for empirical research have been suggested to investigate the interdependence of tourism demand, the convergence of tourism productivity, and the impact of global events

Forecasting U.S. Tourist arrivals using optimal Singular Spectrum Analysis

This study examines the potential advantages of using Singular Spectrum Analysis (SSA) for forecasting tourism demand. To do this it examines the performance of SSA forecasts using monthly data for tourist arrivals into the United States over the period 1996 to 2012. The SSA forecasts are compared to those from a range of other forecasting approaches previously used to forecast tourism demand. These include ARIMA, exponential smoothing and neural networks. The results presented show that the SSA approach produces forecasts which perform (statistically) significantly better than the alternative methods in forecasting total tourist arrivals into the U.S. Forecasts using the SSA approach are also shown to offer a significantly better forecasting performance for arrivals into the U.S. from individual source countries. Of the alternative forecasting approaches exponential smoothing and feed-forward neural networks in particular were found to perform poorly. The key conclusion is that Singular Spectrum Analysis (SSA) offers significant advantages in forecasting tourist arrivals into the US and is worthy of consideration for other forecasting studies of tourism demand