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on Tourism Economics |
| By: | Fieger, Peter; Rice, John |
| Abstract: | The city of Christchurch is the main gateway to New Zealand’s South Island and attracts a significant number of tourists every year. In 2010 and 2011, significant damage to the city’s building stock and infrastructure occurred as a result of two successive earthquakes. Consequently, Christchurch’s tourist arrivals and associated tourist spending declined significantly. However, the rebuilding efforts since 2011 and the re-opening of tourist facilities and infrastructure have led to a steady increase in visitor arrivals and expenditure. This paper investigates whether tourism expenditure as well as the prevailing exchange rate influence local gross domestic product for the city of Christchurch. We separate domestic and international expenditure analysis into two different vector auto-regression models followed by causality analysis to determine the direction of relationships between these three variables. Our results show that increased domestic and international visitor spending is followed by a measurable and significant increase of local GDP. Exchange rates have a small but non-significant impact on international tourist spending. We conclude that stimulating tourism is an essential element to achieve substantial economic growth in Christchurch. |
| Keywords: | Tourism economics; New Zealand tourism |
| JEL: | L83 O1 O47 |
| Date: | 2016–11–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:75470&r=tur |
| By: | Michele Coscia; Ricardo Hausmann; Frank Neffke |
| Abstract: | Tourism is one of the most important economic activities in the world: for many countries it represents the single largest product in their export basket. However, it is a product difficult to chart: "exporters" of tourism do not ship it abroad, but they welcome importers inside the country. Current research uses social accounting matrices and general equilibrium models, but the standard industry classifications they use make it hard to identify which domestic industries cater to foreign visitors. In this paper, we make use of open source data and of anonymized and aggregated transaction data giving us insights about the spend behavior of foreigners inside two countries, Colombia and the Netherlands, to inform our research. With this data, we are able to describe what constitutes the tourism sector, and to map the most attractive destinations for visitors. In particular, we find that countries might observe different geographical tourists' patterns -- concentration versus decentralization --; we show the importance of distance, a country's reported wealth and cultural affinity in informing tourism; and we show the potential of combining open source data and anonymized and aggregated transaction data on foreign spend patterns in gaining insight as to the evolution of tourism from one year to another. |
| Date: | 2016–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1611.09893&r=tur |
| By: | Fieger, Peter; Rice, John |
| Abstract: | New data and modelling approaches are improving the usefulness of internet search data for forecasting inbound tourist arrivals. This short paper provides evidence of the usefulness of Baidu search data in predicting Chinese inbound tourist arrivals into a specific region in New Zealand. It also compares three modelling approaches, finding a Vector Autoregressive approach the most useful. |
| Keywords: | Tourism forecasting, Applied Econometrics |
| JEL: | D12 L83 R1 |
| Date: | 2016–10–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:75468&r=tur |
| By: | Blom Västberg, Oskar; Karlström, Anders; Jonsson, Daniel; Sundberg, Marcus |
| Abstract: | Activity based travel demand models are based on the idea that travel is derived from the demand to participate in different activities. Predicting travel demand should therefore include the prediction of demand for activity participation. Time-space constraints, such as working hours, restricts when and where different activities can be conducted, and plays an important role in determining how people choose to travel. Travelling is seen as a possibly costly link between different activities, that also implicitly leads to missed opportunities for activity participation. With a microeconomic foundation, activity based models can further be used for appraisal and for accessibility measures. However, most models up to date lack some dynamic consistency that, e.g., might make it hard to capture the trade-off between activity decisions at different times of the day. In this paper, we show how dynamic discrete choice theory can be used to formulate a travel demand model which includes choice of departure time for all trips, as well as number of trips, location, purpose and mode of transport. We estimate the model on travel diaries and show that the it is able to reproduce the distribution of, e.g., number of trips per day, departure times and travel time distributions. |
| Keywords: | Travel demand, Discrete choice, Dynamic discrete choice, Activity based modelling, |
| JEL: | R41 |
| Date: | 2016–11–11 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:75336&r=tur |