Average spend per day for visitors to New Zealand from Japan
Excl. education, 1999–2018, 2019–2025 forecast, NZD per day
Year | Series | NZD per day |
---|---|---|
1999 | Actual | 448.44 |
2000 | Actual | 588.06 |
2001 | Actual | 448.51 |
2002 | Actual | 441.45 |
2003 | Actual | 312.9 |
2004 | Actual | 358.16 |
2005 | Actual | 375.86 |
2006 | Actual | 340.13 |
2007 | Actual | 410.62 |
2008 | Actual | 327.73 |
2009 | Actual | 355.06 |
2010 | Actual | 400.46 |
2011 | Actual | 338.22 |
2012 | Actual | 282.04 |
2013 | Actual | 264.57 |
2014 | Actual | 150.03 |
2015 | Actual | 132.03 |
2016 | Actual | 222.97 |
2017 | Actual | 199.65 |
2018 | Actual | 228.06 |
2019 | Forecast | 237.4 |
2020 | Forecast | 236.09 |
2021 | Forecast | 237.64 |
2022 | Forecast | 238.04 |
2023 | Forecast | 237.84 |
2024 | Forecast | 238.29 |
2025 | Forecast | 238.64 |
Definitions
Country of residence: the country where the person last lived or will next live for 12 months or more. This may include New Zealand citizens living abroad.
Travel purpose: the main purpose for the visit to New Zealand. Categories are holiday, visiting friends and relatives, business (including conferences and conventions), other (including education.
Visitor arrivals: Visitor arrivals are overseas residents arriving in New Zealand for a stay of less than 12 months.
Average length of stay per visitor: Average of the intended stay of each visitor, as per stated on the Arrival Card. Their actual stay in New Zealand may differ.
Total visitor days: Visitor arrivals multiplied by average length of stay per visitor.
Total visitor spend: Estimate of the aggregate expenditure by international visitors, excluding international airfares. This also excludes all spend by international students.
Average spend per day per visitor: Total visitor spend divided by total visitor days, excluding international students.
Limitations of the data
These forecasts were issued prior to the Covid-19 pandemic. As a consequence they are now highly inaccurate, and should NOT be used for decision-making purposes, other than a mere reference to tourism volumes that were being expected prior to the crisis.
Actual figures will be reviewed in subsequent publications.
Inclusions
Business visitors include convention/conferences.
'Other' visitors include education.
Exclusions
Please note that the spend measures exclude international students and should not be used in conjunction with the other measures in this dataset.
Data provided by
Ministry of Business, Innovation, and Employment
Dataset name
New Zealand Tourism Forecasts: 2019–2025
Webpage:
How to find the data
At above link select 'New Zealand Tourism Forecasts 2019-2025 [XLSX, 88 KB]' to download file.
Import & extraction details
File as imported: New Zealand Tourism Forecasts: 2019–2025
From the dataset New Zealand Tourism Forecasts: 2019–2025, this data was extracted:
- Sheet: data
- Range:
B2:J659
- Provided: 5,499 data points
This data forms the table Tourism - International visitor forecasts by country and travel purpose 1979–2025.
Dataset originally released on:
May 16, 2019
About this dataset
Each year MBIE produces this report to inform and support planning and investment decisions in the tourism industry. The forecasts are based on econometric modelling, current trends and best available forecasts of international factors and have been developed with input from members of the tourism industry.
Method of collection/Data provider
The historical data from 1979 to 2018 is based on the International Travel and Migration data collection (arrivals and length of stay) and the International Visitor Survey (spend only).
The forecast data from 2019 to 2025 is updated annually. The forecasts are based on econometric modelling, current trends and best available predictions of international factors. They provide a baseline for what will happen ‘if things keep going this way’. The forecasts are subject to the global situation. The data provider has modelled a range of possible outcomes and present an average of these. The actual values in the future are likely to deviate from the modelled average.