A Review on the Leading Indicator Approach towards Economic Forecasting

Economic cycle is defined as the fluctuation of an economy via expansion and contraction periods, influenced by varies kinds of macroeconomic indicators. The repeatable movement of economic indicators enables the accurate detection of these cycles with a forecasting approach that aims to improve economic development, especially by specific industries. Thus, economists and researchers have focused on the usefulness of the composite leading indicator in economic forecasting. It is regarded as a good illustration of an economic cycle or trend. This is due to its ease of use during the interpretation process, as several indicators can be aggregated and explained at once. This may provide useful insights for policy planning, risk monitoring and community development using the information gained from macroeconomic aggregates

Responsible Recovery from COVID-19: An Empirical Overview of Tourism Industry

Over the past few decades, the world has seen a stunning transformation of the tourism industry. The tourism industry is one of the world's largest and fastest growing economic sectors. Thus, it is one of the key economic drivers in most developed and developing countries. Despite the rapid growth of the tourism industry, it is considered a vulnerable industry because it must accommodate the demand changes of tourists, shifts in economic environmental and other unexpected factors such as natural disasters and crises, especially the recent COVID-19 pandemic. Therefore, this paper aims to review the key determinants affecting tourism demand. In general, the tourist arrivals and tourism receipts have been chosen to proxy tourism demand in the existing literatures. In modelling tourism demand model, the independent variables consist of f income level of the tourists, tourism price, exchange rate, transportation cost, word of mouth and other key parameters. Various techniques such as ARDL, Markov-switching, and panel analysis have been utilized in previous studies to investigate the dynamic relationship between the variables in tourism demand model. The recent outbreak, COVID-19 is leaving tremendous impacts to the world economy, especially the tourism industry. In sum, the research on pre-crisis, mid-crisis, and post-crisis are equally important in gathering information for future tourism recovery and development plans

A Bibliometric Analysis on Tourism Sustainable Competitiveness Research

The present bibliometric review of research intends to document and synthesize research trends in the domain of sustainable competitiveness over the past decade. Through bibliographical analysis of 1259 Scopus-indexed documents, the literature published from 2010 to 2020 has been identified. Publication output analysis, citation analysis, journal analysis, geographical distribution analysis, and co-occurrence keywords network analysis are utilised in this study to identify the trending research and future direction of this specific field of study using VOSviewer software and Harzing’s Publish and Perish software. Findings revealed that the literature on both sustainability and competitiveness solely is in its growth stage. The most productive countries in this domain are the United States, China, and the United Kingdom. In the retrieved documents, the sustainable competitiveness indeed plays a pivotal part in the evolution of the tourism field and laid a solid foundation for future research. As this paper provides an understanding on the possible mutual reinforcing relationship between two concepts, a stronger linkage on sustainable competitiveness that may catalyse tourism development can offer reference for future research through in-depth analysis

Tourism sustainable competitiveness indicator for ASEAN block : A random forest approach

This study aims to reveal the tourism performance among ASEAN countries by creating a tourism sustainable competitiveness indicator (TSCI). This study introduces an ensemble random forest approach in developing an integrative framework that incorporates tourism, sustainability and competitiveness. It demonstrates the management of multi-faceted tourism development with the constructed indicator. Six main enablers have been identified for TSCI indicator, including policy and regulatory environment, environmental sustainability, sociocultural sustainability, economic sustainability, infrastructure, and intellectual capital and innovation. As a benchmarking tool for policymakers, organisations, and tourism-related authorities in the implementation of policies and business or marketing strategic planning, the sustainable competitiveness indicator for tourism identified the factors that affect the sustainability and competitiveness of tourism. This indicator enhances the tourism value chains in the Association of Southeast Asian Nations (ASEAN) bloc, as well as it offers significant assistance to the ASEAN Tourism Strategic Plan of 2025. Especially in the context of regionalization, which proceeds along the same trajectory as tourism, it is becoming increasingly significant in building areas of cooperation in the connected Southeast Asian region. Thus, measuring the performance level of the tourism economy is a critical agenda that is worthy of receiving concern as a means of accomplishing sustainable development goals (SDGs)

Macroeconomic Determinants of Tourism Demand in Malaysia: A Markov Switching Regression Approach

A wave of studies has always surrounded the nexus of tourism development and economic growth in a nation. An assessment is provided in this study to examine the Malaysian tourism market dynamics. A series of macroeconomic variables has been utilised to model tourism demand and examine causal linkages among tourism and economic growth. Spanning from 2000 till 2018 on a monthly basis, the Markov regime switching regression provides an overview of tourism market performance and potential influences during recession and expansion periods of the Malaysian tourism cycle. Notably, the results present a reference chronology of the crises happening over the past two decades, the Granger causality of the variables, and different behavioural changes of the variables as well for both recession and expansion periods. Significant relationships have been revealed in this study that suggest that overall international tourism can drive economic growth and vice versa

Forecasting Tourism Demand with Composite Indicator Approach for Fiji

This study attempts to scrutinize the fluctuations of the Fijian tourism market and forecast the early warning signals of tourism market vulnerability using the tourism composite indicator (TCI). The data employed on a monthly basis from 2000M01 to 2017M12 and the indicator construction steps were adopted from the ideology of the National Bureau of Economic Research (NBER). A parsimonious macroeconomic and non-economic fundamental determinant are included for the construction of TCI. Subsequently, the procedure then employed the seasonal adjustment using Census X-12, Christiano-Fitzgerald filtering approach, and Bry-Boschan dating algorithm. Empirical evidence highlighted the signalling attributes against Fijian tourism demand with an average lead time of 2.75 months and around 54 percent of directional accuracy rate, which is significant at 5 percent significance level. Thus, the non-parametric technique can forecast the tourism market outlook and the constructed TCI can provide information content from a macroeconomic perspective for policymakers, tourism market players and investors

A Bibliometric Analysis of Tourism Sustainable Competitiveness Research

The present bibliometric review of research intends to document and synthesize research trends in the domain of sustainable competitiveness over the past decade. Through bibliographical analysis of 1,259 Scopus-indexed documents, the literature published from 2010 to 2020 have been identified. Publication output analysis, citation analysis, journal analysis, geographical distribution analysis, and co-occurrence keywords network analysis are utilised in this study to identify the trending research and future direction of this specific field of study using VOSviewer software and Harzing’s Publish and Perish software. Findings revealed that the literature on both tourism sustainability and tourism competitiveness solely is in its growth stage. The most productive countries in this domain are the United States, China, and the United Kingdom. In the retrieved documents, the sustainable competitiveness indeed plays a pivotal part in the evolution of the tourism field and laid a solid foundation for future research. As this paper provides an understanding on the possible mutual reinforcing relationship between two concepts, a stronger linkage on sustainable competitiveness that may catalyst the tourism development can offer reference for future research through in-depth analysis

Construction of tourism cycle indicator : a signalling tool for tourism market dynamics

The composite leading indicators approach has been popularised in general business and property forecasting extensively, but only rarely in a tourism framework. By utilising the National Bureau of Economic Research (NBER) approach in the construction of a tourism cycle indicator (TCI) for Maldives, a significant signalling attribute regarding international tourists arrivals (TA) to Maldives can be determined. This study spanned approximately two decades of data (2000-2017). Both logarithm forms of TCI and TA with seasonal adjustment are detrended by Hodrick-Prescott (HP) filter. Turning points are detected using Bry-Boschan (BB) dating algorithm. This study explored the possibility of a TCI to capture the information needed for policy planning, risk monitoring and community development. Empirical findings highlighted that the forecasting ability of TCI is vital in reducing crisis burden and should be considered by Maldivians policymakers and tourism industry players

A Review on the Leading Indicator Approach towards Economic Forecasting

Economic cycle is defined as the fluctuation of an economy via expansion and contraction periods, influenced by varies kinds of macroeconomic indicators. The repeatable movement of economic indicators enables the accurate detection of these cycles with a forecasting approach that aims to improve economic development, especially by specific industries. Thus, economists and researchers have focused on the usefulness of the composite leading indicator in economic forecasting. It is regarded as a good illustration of an economic cycle or trend. This is due to its ease of use during the interpretation process, as several indicators can be aggregated and explained at once. This may provide useful insights for policy planning, risk monitoring and community development using the information gained from macroeconomic aggregates

Forecasting Tourism Market for Fiji based on Indicator Approach

The tourism market is inextricably linked to a nation’s economy. There is scant evidence, but growing interest, in the context of tourism, in using the composite leading indicator approach, despite it having been widely applied in the business cycle. The aim of this study is to construct a tourism cycle indicator (TCI) to anticipate the cyclical movements of tourism development. The time duration investigated spanned approximately two decades from 2000 to 2017. Apart from utilising the composite leading indicator approach, a filtering extraction method, a dating algorithm for turning point detection and directional accuracy and binomial tests, this study also included Markov regime switching as well, for identifying the transition probabilities. The empirical findings revealed that the movement of the constructed TCI was consistently in advance of the reference series, international tourist arrivals (TA), in Fiji, with an average lead time of 2.75 months. Moreover, the transition probabilities that resulted from the Markov regime-switching model indicated that the duration of the transition from one regime to another was on average 12.86 months. These empirical estimation analysis results highlighted the potential ability of the leading indicator to predict the outlook of the tourism market, additionally, the information gained from the macroeconomic perspective should be useful for policy planning, risk monitoring, and community development