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Appendix 2: Methodology

Direct tourism value added

Tourism expenditure and direct tourism value added (or tourism's contribution to gross domestic product (GDP)) are the two major economic aggregates derived in a tourism satellite account (TSA).

Tourism expenditure measures the value of products purchased by visitors, whether before, during, or after travel.

Direct tourism value added measures the value of the output of tourism products by industries, less the value of goods and services used in their production (intermediate consumption). When summed across all industries, it shows the direct value added to the economy by tourism.

Tables 9, 10, 11, and 12 detail the process used to measure direct tourism value added. This involves the following steps:

  • Begin with tourism expenditure by type of product (presented in table 9 – and further dissected by type of tourist in table 10).
  • Match tourism expenditure by type of product with the total supply of products in the annual supply and use tables of the New Zealand economy. Derive the tourism product ratio for each product by dividing the value of tourism expenditure by total supply of the product.
  • Multiply each industry’s supply by product by the tourism product ratio, to calculate tourism supply by industry. Table 11 presents tourism supply for tourism-characteristic industries, all other industries, and imports.
  • Divide tourism supply by total output by industry, to give tourism industry ratios – the proportion of each industry’s total output that is purchased by tourists.
  • Multiply the tourism industry ratios through each industry’s production account. Sum the resulting series to obtain total tourism value added. Table 12 presents total tourism value added resulting from tourism-characteristic industries and all other industries.

The same methodology underlies the calculation of direct tourism value added for final and provisional accounts, and is ordered according to the steps above. However, the derivation of inputs into the calculation process and the level at which calculations are performed differ between final and provisional accounts. The main reasons for this are:

  • The lack of balanced supply and use results for the provisional accounts limits the level at which expenditure by product can be calculated for business and government travellers.
  • The same constraints apply to the supply of tourism products. The absence of balanced supply and use accounts means the supply of each product by industry cannot be derived reliably at the same level of detail as in a final account.
  • The industry production accounts, and therefore industry value added, are provisional and are yet to be balanced within a supply and use framework to derive a final GDP figure.

Differences in deriving input data for final and provisional accounts are outlined in the following sections.

Calculating tourism expenditure

Table 10 presents tourism expenditure by type of product and by type of tourist: international (international visitors and international students); household; and business and government. We describe below how we calculate expenditure by the three types of tourist.

International tourism expenditure

International tourism expenditure comprises both international visitors’ and international students’ expenditure.

Final accounts

Expenditure by international tourists in New Zealand is derived from the International Visitor Survey (IVS) published by the Ministry of Business, Innovation and Employment (MBIE).

The International Visitor Survey is a sample survey of approximately 9,800 international visitors to New Zealand aged 15 years or older per year, excluding individuals whose purpose of visiting New Zealand was to attend a recognised educational institute, and are foreign-fee paying students.

The International Visitor Survey draws its visitor sample based on measures of the actual number of target population visitors who departed New Zealand from our international airports over the survey time period in the previous year. Using actual historical visitor departure information, time periods are randomly selected with the probably of being selected based on the number of flights during that period – periods with no flights will have no probability of being selected, while those with a high number of flights have a high probability. For Auckland, Wellington, and Queenstown airports, two-hour time periods are used, while for Christchurch airport it is a four-hour time period.

The International Visitor Survey uses a two-part collection process. The first part involves screening departing visitors during the selected time periods for eligibility and collecting email addresses. The second part, where the bulk of the information is captured, is via an online survey, a link to which is sent to those eligible and agreeing to participate.

Each respondent within the sample is weighted to represent their fraction of the total number of all international visitors departing New Zealand using migration data within the survey’s target population. Survey response weights are adjusted to reflect the unequal probabilities of respondent selection from the composition of the target population, and known discrepancies between the sample and the population definitions.

The IVS data is supplemented with breakdowns from balanced supply and use accounts, consumers price index (CPI) weightings, and tourism producers' own data. In some instances, tourism producers can provide estimates of the proportions of their output consumed by international visitors.

Broad-level valuations of international visitors' expenditure in New Zealand are derived from transportation and travel services items in the balance of payments (BoP). IVS data is a major source for BoP statistics, but several supplementary sources are also used. TSA totals exclude people who are visiting New Zealand specifically to obtain medical treatment (an adjustment needed because of a conceptual difference between TSA and BoP statistics). Small revisions have been made to the source data in some years. We break down these totals into tourism products, using proportions from balanced supply and use accounts. We compare these splits with other data sources, and refine the totals where additional estimates are available.

Provisional accounts

The same basic data source, the IVS, is also used in the provisional accounts. However, in the absence of supply and use tables, the IVS is not broken down to the same level of product detail found in final accounts. We use the breakdown for the latest final account to derive the initial product breakdown for the provisional years. This initial product breakdown is subsequently refined during the balancing process (covered in more detail later in this appendix – see ‘Balancing tourism expenditure and tourism production’).

Cruise ship expenditure by international visitors

Expenditure by international cruise ship tourists visiting New Zealand is only partly captured in the IVS. Visitors who complete their cruise journey in New Zealand and depart via a New Zealand airport are within scope to be surveyed by the IVS, and therefore their expenditure reported in the IVS and consequently the TSA.

Visitors who cruise in and cruise out of New Zealand or fly into and cruise out of New Zealand are currently outside of scope for measurement due to the airport departure–based collection of the IVS. These visitors’ spending is not included nor estimated in the IVS and the TSA. Statistics NZ and MBIE, together with the cruise industry, are working to determine the full expenditure value of cruise visitors.

Tourism expenditure by international students

International students are defined as those studying in New Zealand for less than 12 months. Tourism Satellite Account: 2016 incorporates revisions made to source data. This includes changes to student numbers, and the application of GST on tuition fees across the time series used to derive tourism expenditure by international students.

Tourism expenditure by international students is calculated using the following steps:

  • Obtain total international student numbers from the Ministry of Education.
  • Derive the number of international students studying in New Zealand for less than 12 months as a proportion of total student numbers, by using the number of short-term passenger arrivals visiting New Zealand for education purposes.
  • Calculate expenditure on tuition fees using the Ministry of Education's Export Education Levy data (inclusive of GST), a census of international students studying in New Zealand. It includes average tuition fees for students studying at schools, tertiary education institutes, and private tertiary establishments (such as English language schools).
  • Calculate expenditure on living costs (including accommodation costs) consistent with how it is calculated by BoP. This involves taking average tuition fee data and applying predetermined living cost multipliers for each type of student.
  • Calculate expenditure on airfares by short-term students by multiplying the number of students in New Zealand for less than 12 months as a proportion of total international arrivals, by the total airfare income of resident airlines (from BoP).
  • Sum expenditure on tuition fees, living costs, and airfares, to obtain the total tourism expenditure by international students in New Zealand for less than 12 months.

Household tourism expenditure

Household tourism expenditure, shown as household demand in table 10, consists of four components.

These are:

  1. Household domestic travel expenditure
  2. Outbound travel purchased from New Zealand-resident firms
  3. Off-trip purchases of tourism-specific consumer durable goods
  4. Imputed rental on holiday homes.

1. Household domestic travel expenditure

Tourism Satellite Account: 2016 uses an administrative data source based on electronic card transaction data to collect and determine household domestic travel expenditure. The Household Tourism Expenditure Estimates (HTEE), developed by Statistics NZ and funded by MBIE, cover the years ended March 2009–16. Prior to the year ended March 2009, we used data from the Domestic Travel Survey (DTS) undertaken by MBIE. The DTS collected the expenditure and behaviours of domestic travellers within New Zealand.

The DTS data collection began in 1999, with data available as both quarterly and annual series through to its cessation in 2013. The DTS data provided information on the nature of domestic travel activity, including the origin and destination of domestic travellers. MBIE categorised the data by purpose of travel, expenditure type, and length of trip (either day trip or overnight trip). The four travel purposes were: holiday, visiting friends and relatives, business, and other. The eight expenditure categories were: transport, accommodation, food, alcohol, gifts and souvenirs, recreation, other shopping, and gambling. DTS expenditure was available by purpose of travel, expenditure category, and length of trip.

We then supplemented the DTS with additional household tourism expenditure for outbound travel, off-trip purchases, and imputed rental on holiday homes – using a mix of sources and methods, as outlined in the following sections.

In the year ended March 2014, the DTS was replaced by a developmental version of the HTEE, which was further developed and fully integrated into Tourism Satellite Account: 2015. We have made additional refinements to these estimates for Tourism Satellite Account: 2016. The HTEE uses geographic information to determine tourism spending in New Zealand by New Zealanders and is available from the year ending March 2009. The DTS is used in determining prior year estimates.

HTEE source data

Electronic card transaction data is provided to us by Marketview Ltd, who get it from two main sources:

  • Paymark – the largest electronic card payment network in New Zealand
  • Bank of New Zealand (BNZ) – spending by BNZ cardholders, which excludes any personal identifiers. We call this depersonalised spending.
Paymark data

Data is derived from all transactions made at merchants on the Paymark network. Approximately 70 percent of New Zealand retailers use the Paymark network. The dataset includes all eftpos and credit card transactions made at these retailers. There is no link to the person making the transaction, but transactions are linked to merchants. The Paymark dataset excludes ‘cash-out’ transactions.

From this data a complete valuation of New Zealanders’ spending can be generated, comprising:

  • day of the week and time of the day
  • where in New Zealand the transaction occurred
  • ANZSIC06 (2006 Australian and New Zealand Standard Industry Classification) storetype
  • domestic or internationally issued card.
BNZ data

The BNZ dataset is based on the depersonalised eftpos (debit card) and credit card spending of approximately 600,000 BNZ cardholders in the New Zealand retail market. BNZ has approximately a 20 percent share of the cards market, meaning BNZ cardholders account for approximately 1 in 5 retail transactions. These cardholders are representative of the national population. The dataset includes spending at Paymark and non-Paymark retailers. It excludes ‘cash out’ transactions and bank transfers.

Through the BNZ dataset, Marketview receives a view of spending at virtually all merchants in New Zealand which receive electronic card spending, regardless of whether the merchant uses the Paymark network or not. They can identify where in New Zealand the transaction occurred and whether the transaction was conducted at a physical store or online.

Sample management

To ensure the BNZ cardholder base is both geographically and demographically distributed in line with the New Zealand population, a weighting is applied by Marketview.

While BNZ cardholders are distributed throughout New Zealand, small variations exist down to an area unit / customer age level. This weighting was calculated by determining the distribution of cardholders and comparing this to the distribution of the overall population.

Marketview use Statistics NZ’s area unit population estimates as the basis for the national population. This enables the distribution to change over time, as each year of the data was compared with a different population estimate. For example, Marketview data from 2016 is weighted according to the 2015 population estimates. This ensures significant population changes – such as after the Canterbury earthquakes, or new subdivisions opening – are accounted for in the dataset.

The weighting factor is applied to the dataset by age (in five-year bands starting at 15–19), by census area unit, and by month. This weighting ensures the distribution of BNZ cardholders matches the distribution of the national population, by age, location, and over time. Weighting by age and location ensures management of any bias in the sample, as income and wealth typically increase with age, and wealth can correlate with where a person lives.

Combining data sources

By combining Paymark and BNZ data, Marketview produce a dataset that accurately quantifies:

  • the value of spending of each transaction
  • the source and origin of those payments eg business vs personal, domestic vs. international tourist
  • where in New Zealand the cardholder lives
  • where each transaction took place eg physical store vs online, Auckland vs Invercargill
  • the industry category of the merchants, as defined by 2006 ANZSIC codes
  • the time and day of the purchase.
Defining household tourism expenditure

Household tourism expenditure is defined as expenditure that occurs outside a 40km radius of the meshblock in which the cardholder’s address is located, and aligns with industries defined as tourism industries. The 40km reflects the New Zealand definition of travel outside one’s usual environment. Tourism industries encompass both characteristic and related industry data along with selected non-tourism industries.

Marketview apply this 40km radius to the combined Paymark and BNZ dataset to determine the HTEE. Exceptions are made where regular behavioural spending patterns show a person’s usual environment extends to an area outside the 40km radius, such as commuters. This is removed from the HTEE.

Additional data on internet transactions is collected specifically for selected tourism industries that require travel in order to consume a purchased good. For example, internet expenditure on accommodation and air passenger transport is collected.

Scaling household tourism expenditure data to total economy

As electronic card data reflects only one aspect of household tourism expenditure across the New Zealand economy, Marketview upscale their dataset by adding in a factor for cash and other payment methods. This is calculated as the difference between electronic card spending and total economy spending based on ANZSIC industry information supplied from our Annual Enterprise Survey (AES).

For example, Marketview may record the total value of electronic card spending in ANZSIC industry G4110 at $100 for the year, with 10 percent being tourism ($10). The total industry value of G4110 as calculated from AES was $120. The Marketview card value is thus upscaled by a multiple of 1.2, yielding a total market value of $120, consistent with AES. The tourism component is still 10 percent, hence tourism spending for that year is calculated at $12.

The assumption used is that consumer and business spending on cash versus card on tourism and non-tourism related trips are equal.

The HTEE dataset

The HTEE dataset provided by Marketview covers the years 2009–16. At the time of compilation, AES data was available to the 2015 financial year. To produce the HTEE through to 2016, Marketview have estimated the value of each industry in the 2016 provisional year by applying movements for each industry from additional Statistics NZ data sources, including GST data, to the 2015 AES data.

For example, Marketview took annual movements in spending for ANZSIC industry G4110 from the Retail Trade Survey. They applied this to the 2015 AES data to determine a 2016 provisional estimate. They estimated other industries from data indicators sourced from Statistics NZ.

Marketview will update the provisional year estimate as AES data becomes available and indicator data is revised as part of the annual publication cycle of the Tourism Satellite Account.

Turning industry based HTEE into tourism products

The HTEE industry dataset is then broken down into tourism defined products using annual supply-use commodity proportions and retail industries sales data. For validation purposes it is then confronted against HCE commodity data net of overseas visitor expenditure and New Zealanders’ travel expenditure abroad. This isolates New Zealanders’ spending within New Zealand, allowing for a comparison on an equivalent expenditure basis with the HTEE.

Additional household tourism expenditure

While the HTEE dataset provided by Marketview captures most household tourism expenditure, the TSA supplements the HTEE product breakdowns with its own product expenditure estimates. These include some off-trip purchases of tourism-specific consumer durable goods and imputed rental on holiday homes.

Both the HTEE and additional Statistics NZ tourism product data then provide the initial expenditure levels to feed into the balancing process. These levels can be subsequently modified where necessary (the balancing process is covered in more detail later in this appendix – see ‘Balancing tourism expenditure and tourism production’).

2. Outbound travel purchased from New Zealand-resident firms

All years

Household tourism expenditure in the TSA includes expenditure on overseas travel, where New Zealanders purchase New Zealand-produced goods and services. This expenditure includes fares paid to resident air carriers for flying a household tourist overseas, commissions paid to resident travel agents for booking household outbound travel, pre-paid travel insurance, and vaccinations needed by household outbound tourists. We estimate this expenditure from sources including the HTEE and company data.

3. Off-trip purchases of tourism-specific consumer durable goods

All years

Off-trip expenditure by households on tourism-specific consumer durables (such as tents and sleeping bags) is included in household tourism expenditure. These off-trip purchases are based on data sourced from the HES together with supply-side product data and are added to the on-trip purchases of these goods. Off-trip tourism expenditure is defined in ‘Tourism expenditure’ in appendix 1 ‘Conceptual framework’. Read more about consumer durables in the TSA in the ‘Special treatments’ section later in this appendix.

4. Imputed rental on holiday homes

All years

The TSA includes an imputed rental on dwellings owned by households that are used as holiday homes. We calculate the total number of holiday homes using data from the Census of Population and Dwellings and an annual volume change indicator. We calculate annually an average weekly imputed rental price derived from national accounts imputed rental data. We multiply this price by the number of weeks in the year to give an annual imputed rental price. We then multiply the number of holiday homes by the annual imputed rental price to give the total imputed rental value.

Business and government travel expenditure

Final accounts

Business and government travel expenditure is drawn from intermediate consumption of industry data in the balanced supply and use accounts. We calculate it by applying product ratios reflecting travel expenses to total intermediate consumption for each of business and government from the latest final account. This provides the initial product breakdown, which we subsequently modify during the balancing process (covered in more detail later in this appendix – see ‘Balancing tourism expenditure and tourism production’).

Provisional accounts

In the absence of balanced supply and use accounts, we first derive intermediate consumption by applying a variety of data sources, including the Annual Enterprise Survey, GST purchases, and annual report data to the latest final account year. Each year is then subsequently derived from the previous year's totals by applying key data source movements. We then apply the product ratio reflecting travel expenses to the derived total intermediate consumption for each of business and government. This provides the initial product breakdown, which we subsequently modify during the balancing process.

Production of tourism goods and services

Final accounts

Analysing the production of tourism-characteristic and tourism-related products starts with the production accounts by industry that underlie the supply and use table. Within the balanced supply and use accounts, we break down each industry's output and intermediate consumption into products. Final demand categories such as household consumption expenditure and exports are also broken down by product. For the TSA, we rearrange output product data from balanced supply and use tables to focus on tourism-characteristic and tourism-related products. We arrange total sales by each industry into tourism-characteristic, tourism-related, and non-tourism-related products.

Provisional accounts

Constraints on the availability of data for provisional accounts (no balanced supply and use results available) mean that supply by product is shown only for tourism-characteristic industries and for all other industries. Without balanced supply and use accounts, we derive total output by industry using a variety of indicators, including GST sales, the Retail Trade Survey, the Annual Enterprise Survey, the Accommodation Survey, and annual reports. We break down this output into the supply of tourism products by using the latest final account breakdown of output by product and industry. This provides the initial product breakdown, which we subsequently modify during the balancing process (covered in more detail in Balancing tourism expenditure and tourism production’ – see below).

Balancing tourism expenditure and tourism production

Final accounts

Supply and use balancing is an established and integral process when compiling the national accounts. It is used "for checking the consistency of statistics on flows of goods and services obtained from quite different kinds of statistical sources" (Inter-Secretariat Working Group on National Accounts, 2008). The supply and use balancing process rigorously examines diverse data sources, reconciling them in a framework that reduces the error margins implicit in the individual data sources.

The supply and use approach provides the best framework to bring the demand and supply sides of the economy into balance. The usual process is to confront supply and demand by product, and perform adjustments so that the value of the supply of each product is equal to the value used. We make adjustments to either supply or demand, depending on the relative strength of each data source. In doing so, the potential for errors that may result from using a single data source, either supply- or demand-based, is reduced. We also performed similar checking of supply and use by product, which underlies Statistics NZ’s annual supply and use models.

The TSA begins with the balanced supply and use tables, so we balance all products in terms of their total supply and total use. We break down these 'product accounts' further into their tourism and non-tourism components. The resulting tourism supply and tourism use may no longer be balanced because of the methodology used to make this split. We then use the same type of data confrontation as used in supply and use balancing to ensure that tourism supply is equal to tourism use.

A typical example of how this process is undertaken follows:

  1. Compare the total supply of tourism-characteristic and tourism-related products with the total direct tourism demand and non-tourism demand for these products. This comparison identifies areas where the tourism product ratio is unexpected or obviously incorrect. Note that GST is deducted from tourism expenditure for this comparison – so production for and expenditure on tourism products are both valued in producers’ prices.
  2. Re-examine the methodology used, checking for errors, conceptual inconsistencies, and methodological problems.
  3. Compare the strength of the respective supply- and demand-side data sources, identifying areas where particular strengths and weaknesses lie. Typically, the strengths are in the supply-side industry and product data, and the total demand by type of tourist data. Demand for individual products is often considered to be of weaker quality.

The focus is to strengthen the breakdown of total tourism expenditure types into products. The first step is to look for any extra data sources to provide indications of what these should be. Where possible, we incorporate changes. In areas where no data is available, we make iterative changes to these products, keeping particular areas of confidence 'locked'. We continue this process until the ratios for each product come into line with expectations. The outcome of the balancing process is a strengthened analysis and a complete set of tourism product ratios – that is, the proportion of the supply of products that make up tourism demand. The tourism industry ratios, and thus tourism value added, are derived from these.

Provisional accounts

The same checking of supply and use by product that underlies the annual supply and use analysis is performed in the provisional accounts. However, due to data constraints, the process is at a more aggregated product level. Furthermore, the relative strengths of supply and use data sources are quite different between provisional and final accounts.

Calculating direct tourism value added

Derivation of the tourism product ratio

Tourism consumption for each product is divided by total supply to give the tourism product ratio. This ratio measures the proportion of a product’s output that is used by tourists.

Derivation of tourism supply and the tourism industry ratio

Calculation of tourism supply and the tourism industry ratio for each industry is an important intermediate step in deriving direct tourism value added and employment.

To derive tourism supply by product by industry, we apply the tourism product ratio (from table 10) to the supply of that product by each industry. We then calculate total tourism supply by each industry by summing tourism supply for all products.

For example, we applied the tourism product ratio for accommodation services to the output of all industries supplying this product. This gave tourism supply of accommodation services by each industry. We then divided tourism supply by each industry by total industry output, to give the tourism industry ratio. It is worth noting that although the accommodation industry is the dominant supplier of accommodation services they are not the sole supplier, as other industries can also supply this product.

While calculating the tourism industry ratio and tourism supply by industry is an important step in deriving direct tourism value added, neither is shown in provisional years as these values are themselves derived from the gross output of each industry. Table 11 shows total supply and tourism supply by product for tourism-characteristic and all other industries.

Derivation of direct tourism value added

The tourism industry ratio is applied to the production account for each industry to obtain direct tourism value added.

Production accounts by industry are not available for provisional years. Therefore, before we can calculate tourism value added, we derive provisional production accounts for each industry. We use data from a variety of sources, including GST sales and purchases, annual reports, and the Annual Enterprise Survey, to break down the latest published total value added to give value added by industry.

Final TSA account tables present full production accounts, as well as tourism production accounts by industry. Direct tourism value added in provisional TSA accounts is split by tourism-characteristic and all other industries. This reflects the less detailed nature of total value added by industry in years in which tourism value added is derived as a subset.

We make a major assumption relating to the use of the tourism product ratio and the tourism industry ratios in compiling the TSA. The industry technology assumption is that the input requirements of tourism and non-tourism products are identical for an industry. That is, if 50 percent of the output of an industry is goods and services sold to tourists, then 50 percent of its inputs are used to produce those goods and services. This is likely to be a more valid assumption for an industry that makes a range of products that are very similar, requiring similar inputs. However, in some instances the assumption is likely to be less valid; for example where an industry has a low degree of tourism specialisation, and a diverse range of products are produced.

An alternate assumption is to relate specific inputs to outputs – that is, a product technology assumption. However, this approach is not easily implemented due to the lack of sufficiently detailed product data. Industry data, on the other hand, are far more readily available. Both the industry and product technology assumptions are sanctioned by the UNWTO.

Direct tourism employment

Direct tourism employment (see table 15) is derived by applying tourism industry ratios to the number of people employed in each industry. This approach produces a value for the number of people in each industry as a result of tourism.

In Tourism Satellite Account: 2016, employment numbers come from Linked Employer-Employee Data (LEED) annual statistics by each industry. Employment and tourism employment are presented by the number of people employed, for both employees and working proprietors, with a series available from 2000.

LEED data is based on administrative tax data, where the number of hours worked is not available, so we cannot provide a full-time and part-time split. Further discussion about LEED is covered in the ‘Tourism employment source data’ section later in this appendix.

Tourism industry profitability

Tourism gross operating surplus as a percentage of total tourism output is one measure of tourism profitability. It reflects national accounting rather than commercial concepts. Gross operating surplus is before interest and depreciation.

Indirect effects of tourism

Indirect imports and tourism value added

As described in appendix 1 (see ‘Relating direct tourism value added and tourism expenditure’), the basis of a TSA’s measure of indirect tourism value added (or tourism's indirect contribution to GDP) is:

   Total tourism expenditure
 less  GST
 equals  tourism demand
 less  imports sold directly to tourists by retailers
 equals  tourism output
 less  tourism intermediate consumption (inclusive of goods for resale)
 equals  direct tourism value added
   
   Tourism intermediate consumption (inclusive of goods for resale)
 less  imports used in production of goods and services sold to tourists
 equals  indirect tourism value added.

We discuss the derivation of imports used in producing goods and services sold to tourists and indirect tourism value added below.

Imports used in production of goods and services sold to tourists

Indirect tourism imports represent imported products not sold directly to tourists, but used in producing tourism supply.

We calculate the value of imports used in producing products sold to tourists using the table of cumulated import coefficients of industries, and categories of final demand, from 2007 input-output tables. This is the most recent cumulated import coefficients table available. It may be updated when the relevant tables from more recent years become available. The cumulated imports coefficients table shows how many units of imports are required for an industry to produce a unit of output. Tourism supply by industry is derived as part of the direct tourism value added calculation. Multiplying this supply by the relevant import coefficients by industry produces the value of imports used in producing goods and services sold to tourists.

Indirect tourism value added

Indirect tourism value added may be calculated directly by using the supply and use framework, or derived indirectly as a residual item. The indirect method calculates total tourism expenditure (excluding GST), then subtracts direct tourism value added, imports sold directly to tourists by retailers, and imports used in the production of goods and services that are sold to tourists.

Final accounts

Indirect tourism value added is calculated directly using the table of industry-by-industry total requirements from 2007 input-output tables, the most recent total requirements table available.

Provisional accounts

Indirect tourism value added is derived using the subtraction method, after first deriving imports used in production of goods and services sold to tourists. The advantage of this method is that it is simpler, does not require multiple iterations, and industry total value added is a less critical input.

Indirect tourism employment

The number of people employed indirectly in tourism is presented in table 5.

Final accounts

Indirect tourism employment takes, as its starting point, indirect tourism value added by industry. We calculate the ratio of indirect tourism value added to value added, and multiply it by employment by industry, to give indirect tourism employment. We sum these industry estimates to calculate the number of people employed indirectly in tourism.

Provisional accounts

For provisional years, neither direct tourism value added nor indirect tourism value added is available by industry in the New Zealand System of National Accounts (NZSNA). Therefore, we calculate the ratio of indirect tourism value added to value added, by industry, from the latest final year. We multiply this by employment by industry, to give the number of people employed indirectly in tourism.

Supply and use framework

Final accounts

The TSA is a rearrangement of the NZSNA. More specifically, we derive the tables for final accounts from the annual supply and use analyses of the New Zealand economy. Supply and use analyses are both a statistical and economic representation of the economy, broken down by industry, product, primary input category (for example, compensation of employees, consumption of fixed capital), and final demand category (such as household consumption expenditure and exports). By adopting the supply and use framework, a tourism industry can be presented in the same way as those for the agriculture and manufacturing industries are presented. It is then possible for tourism to be compared with other industries and with total national accounts aggregates, such as GDP.

Additionally, by compiling the TSA within a supply and use framework, we can produce derived tables that allow further analyses. For example, an impact analysis can be completed, which allows the user to trace the direct and indirect impact of tourism expenditure on the economy. This shows the flow-on effects of tourism, as expenditure on tourism products first affects industries that directly supply tourists, and then industries that provide indirect inputs to the industries supplying tourists.

The supply and use structure also allows economic data on tourism to be easily linked to non-financial data such as employment. Balanced supply and use accounts provide detail, at the product level, of both the structure of industry output (supply), and the demand for these products by business and final demand categories (eg household spending). They are the starting point from which a TSA is derived.

Provisional accounts

Balanced supply and use accounts are not yet available for provisional years. Only total economy-wide value added has been published for these years. Therefore, we calculate aggregated supply of products sold to tourists by industry. This involves:

  • deriving the output of each industry (as outlined earlier in this appendix)
  • breaking down total output into supply of each tourism product, using the industry output breakdown from the latest available supply and use analysis. This provides the initial product breakdown, which we subsequently modify during the balancing process
  • calculating value added by industry within the constraint of published total value added.

The absence of balanced supply and use accounts results in less robust estimates of tourism value added for these later years.

Employment source data

Linked Employer-Employee Data (LEED)

LEED uses existing administrative data from the Inland Revenue taxation system and business data from Statistics NZ’s Business Register (BR). LEED provides statistics on a variety of job measurements including the number of people employed, number of filled jobs, job flows, worker flows, mean and median earnings for continuing jobs and new hires, and total earnings. This information gives an insight into the operation of New Zealand's labour market on both a quarterly and annual basis from a national, regional, and territorial authority perspective.

The LEED annual statistics cover all individuals (‘employees’) who either receive income from which tax is deducted at source, or from self-employment. In LEED, the employer is the geographical unit or physical location of the business rather than the administrative reporting unit. For example, a nationwide retail chain may have one Inland Revenue reporting unit covering all of its retail branches. In LEED, each branch is considered to be a distinct employer.

For inclusion in LEED annual statistics, a person must:

  • be aged 15 years and over at the start of the tax year
  • have received non-zero income with tax deducted at source through the Employer Monthly Schedule (EMS) system, or self-employment income in the reference period.

All income measures are before tax.

The Tourism Satellite Account uses the LEED annual Table 1.5: Main earnings source, by industry (ANZSIC06) measure, which allocates a person to the industry where they have generated the most earnings from in the tax year.

For more information about LEED employment, refer to Linked Employer-Employee Data (LEED).

Employment and tourism employment estimates for 2015 and 2016

Employment and tourism employment are presented by the number of people employed, for both employees and working proprietors, with a series available from 2000. As LEED annual statistics are only available up until 2014 at the time of publication, Tourism Satellite Account: 2016 estimates for the years 2015 and 2016. We will update these estimates as LEED becomes available as part of the annual publication cycle of the Tourism Satellite Account.

These are derived for both employees and working proprietors using differing employment data sources.

  • Employee estimates for 2015 and 2016 are derived using a more timely, summary source of EMS data. This data is currently used as an experimental series and business size indicator for the BR. For the purposes of the TSA, the annual March month movements are then applied to 2014 employee industry data.
  • Working proprietor estimates for 2015 and 2016 are derived by applying the year ended March (quarterly mean) annual HLFS industry movements to 2014 LEED working proprietor industry data.

Tourism employment LEED examples

The following tourism industry examples illustrate how to use the LEED-based ‘number of people employed in tourism’ measure. Examples of how employment would be measured from a LEED filled-jobs measure perspective are provided for comparison.

1. Angelique holds three part-time jobs in Queenstown – at a tourist attraction, in a restaurant, and at an accommodation provider. During the year Angelique’s highest earnings were generated from the restaurant, therefore she would be assigned to the food and beverage services industry.

Under the LEED-based measures this equates to:

  • number of people employed = 1
  • number of filled jobs = 3.

2. Chase holds a full-time job in summer in Ohakune working at an outdoor equipment retail store. In winter, he works full time at the cafés on the ski field. Over the year Chase generated more earnings from the retail store than his café work, therefore he would be assigned to the retail trade industry.

Under the LEED-based measures this equates to:

  • number of people employed = 1
  • number of filled jobs = 2.

3. Michael is an owner-operator running two seasonal businesses in Nelson – one sightseeing, and the other fishing tours. As a working proprietor, Michael has a unique ID number and the businesses he runs will also have their own separate ID number. The same rule for jobs data can be applied to working proprietors, where the link between the person and geographic business location is the key relationship.

For Michael’s two seasonal businesses, the data is recorded as:

 Name of business  Owner ID number  Business ID number
 Michael’s first seasonal business  12345  98765
 Michael’s second seasonal business  12345  87654

Most of Michael’s self-employed income was generated from his first seasonal business, therefore he would be allocated to that business’s industry. Under the LEED-based measures this equates to:

  • number of people employed = 1
  • number of filled jobs = 2.

4. Michelle and James live together in Napier on the understanding that Michelle is the breadwinner and James is the homemaker. Michelle operates her own small business selling tourist souvenirs during the week, while on the weekends she works for the local holiday park. James helps at the holiday park in the month of February – his only employment for the year. Michelle’s highest earnings were generated from her retail business, therefore she would be allocated to the retail trade industry. James’s employment would be allocated to the accommodation industry. Under the LEED-based measures this equates to:

  • number of people employed = 2 (1 Michelle and 1 James)
  • number of filled jobs = 3 (2 Michelle and 1 James).

Special treatments

This section details areas in TSA methodology that receive special treatment.

Treatment of the margin

In the national accounts, purchases of retail goods can effectively be split into three components:

  • the margin (or 'mark-up') of the retailer selling the product
  • the margin charged by the wholesaler
  • the price received by the manufacturer.

The treatment adopted in the TSA is illustrated in the following example.

A tourist purchases a jersey for $100, comprising a $10 mark-up from the retailer (who has direct contact with the tourist), a $15 margin from the wholesaler, and $75 charged by the manufacturer. The breakdown is as follows:

  • the full purchase price of the jersey ($100) is recorded as total tourism expenditure
  • the margin (or mark-up) by the retailer selling the jersey to the tourist is the retail output ($10) from which direct tourism value added is then derived
  • the remaining $90 is the price received by the manufacturer ($75) and the margin charged by the wholesaler ($15); neither of these has direct contact with the tourist and is the output from which indirect value added is derived.

Consumer durables

Two types of expenditure on consumer durables are included in tourism expenditure in a TSA, consistent with UNWTO recommendations:

  • Conceptually, all consumer durables acquired on a trip are included in tourism demand. This includes the purchase of high-value consumer durables during a trip, such as motor vehicles, even though the primary purpose may not be for tourism use. The estimate of purchases of motor vehicles by households while on trips is related to the proportion of New Zealanders living in rural areas. This is based on the assumption that rural residents will travel outside their 'usual environment' (defined in appendix 1) to purchase a motor vehicle. It is recognised that the usual environment for a rural New Zealander may well include urban areas that fall outside the strict TSA definition of 'usual environment'. While the measurement attempts to take this into consideration, there is little hard data with which to refine it. As a result, these estimates may be revisited in the future.
  • Off-trip purchases of a specific range of consumer durables with very high tourism use are included. For example, luggage and tents are acquired primarily for tourism purposes, so are always considered tourism expenditure. TSAs have a defined set of consumer durables with very high tourism use, based on a list developed by the OECD that is supplemented with consumer durables having high tourism use in New Zealand. (See appendix 3 ‘Tourism product classification’ for items included as tourism consumer durables.)

Holiday homes

An imputed rental on owner-occupied dwellings is calculated in the national accounts. This is to avoid distortions over time resulting from changes in the number of people renting rather than owning homes (otherwise, an increase in the number of people renting homes would increase GDP). This imputed rental is applied to both first and second homes (which includes holiday homes).

Although a holiday home may not be in full-time use, we assume it is available to be used all year, and therefore allocate the rental from owning the holiday home to tourism expenditure.

For a TSA, we assume demand for holiday homes to come solely from domestic recreational tourists, due to a lack of data on the origin of holiday homes. We set total supply of holiday homes equal to the total imputed holiday home rental (and therefore total demand) of domestic household tourists, as holiday home supply is provided solely for the purposes of tourism.

Package tours

TSAs apply the net approach to recording package tour expenditure, where the organiser's margin for arranging the tour is recorded as the sole output, while the components of the tour are treated as being purchased directly by the tourist.

For example, a travel agent sells a package tour to a tourist. The travel agent (organiser) records a margin from the sale of the package tour. The expenditure on each of the components of the tour is captured under the respective industry’s output.

Travel agency services

Travel agents obtain their income in two major ways. Firstly, they earn income by buying travel products (generally at a bulk discount) and selling them to travellers, thereby earning a margin. Secondly, an agent may book a traveller's fare or accommodation with the service provider, and receive commission from the service provider (on behalf of the traveller). TSAs use special treatments for each of these means of generating income:

  • Where travel agents have sold travel to travellers, we record travellers as having bought travel (from the travel provider) and travel agency services (the travel agent's margin).
  • Where travel agents have received commissions, we assume providers to have purchased travel agency services on behalf of the tourist. This means that these travel agency services are included in direct tourism demand and therefore contribute to direct tourism value added. Consequently, business travel expenditure includes a high level of demand for travel agency services.

Non-market output consumed by tourists

The New Zealand TSA does not include an imputation for providing individual non-market tourism services in total tourism consumption. These services include information centres, museums, and libraries, and any other services that tourists use without having to pay for them, such as national parks. This is a recommended inclusion in UNWTO TSA methodology.

To implement the UNWTO recommendation requires:

  • a very detailed functional breakdown of the expenditure of government and non-profit institutions, that is, separately identifying those entities which provide 'individualised' services
  • splitting this expenditure between tourist and non-tourist consumption.

Identifying individualised and collective non-market consumption is a recommendation from System of National Accounts 2008 (Inter-Secretariat Working Group on National Accounts, 2008). However, we have only partly implemented this (local government has not been fully split). In areas that have been split, the breakdowns are not sufficiently detailed for TSA purposes.

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