Dairy's role in sustaining New Zealand - Fonterra

Dairy’s role
in sustaining
New Zealand
- the sector’s contribution to
the economy
REPORT TO FONTERRA AND DAIRY NZ
December 2010

About NZIER
NZIER is a specialist consulting firm that uses applied economic research and analysis
to provide a wide range of strategic advice to clients in the public and private sectors,
throughout New Zealand and Australia, and further afield.
NZIER is also known for its long-established Quarterly Survey of Business Opinion and
Quarterly Predictions.
Our aim is to be the premier centre of applied economic research in New Zealand. We pride
ourselves on our reputation for independence and delivering quality analysis in the right
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projects, critical review at internal seminars, and by peer review at various stages through a
project by a senior staff member otherwise not involved in the project.
NZIER was established in 1958.
Authorship
Prepared by: Chris Schilling, James Zuccollo and Chris Nixon
Quality approved by: John Ballingall
Date: 15/11/2010 3:49 PM
Version: Final
Acknowledgements:

Key points
Dairy makes a very strong direct contribution to the NZ economy
• The dairy sector directly accounts for 2.8% of GDP, or $5 billion. This contribution is:
o greater than the GDP contribution of the fishing, forestry and mining sectors
combined
o around 10 times as large as the GDP of the wine sector
o about 3 times as large as the forestry and logging sector
o over a third of the GDP contribution of the entire primary sector (dairy and meat
farming and processing, horticulture, fishing, forestry, mining)
o 40% larger than the entire utilities sector (electricity, gas and water)
o 2/3 as large as the entire construction sector
o 15% of the total GDP of the goods producing industries and
o provides 26% of New Zealand’s total goods exports.
And contributes to the health of the NZ economy in many ways
• But the sector’s influence extends well beyond its direct impacts. Dairy is closely
intertwined with the rest of the economy. This includes the jobs it delivers, the income
that these workers earn, its links to supplying firms, the effects of rural economic growth
on urban centres, the tax revenue it provides and the public services that can be funded
from this tax revenue. These links are shown in the figure at the end of this section.
• Of the $10.4 billion of dairy products exported in 2009,
o $7.5 billion is used to purchase raw milk from the dairy farming sector.
o $1.5 billion is retained as returns to labour and capital (i.e. wages and rate of return).
o $625 million is spent on intermediate inputs from New Zealand. This includes $85
million of plastic containers, $45 million on electricity and $22.5 million on financial
services.
o Imported intermediate inputs account for $310 million – largely plastic containers
($182 million) and other food products to be used in processing ($30 million).
o $730 million is spent on retailing/wholesaling costs that get the dairy products from
the plant to market.
• Of the $7.5 billion value of raw milk output, $3.0 billion is retained as returns to land,
labour and capital. A further $3.6 billion is spent on domestically produced intermediate
inputs, such as fertilizer ($447 million), feed ($723 million), agricultural services ($446
million), financial services
Dairy’s role in generating growth
C

D Dairy’s role in generating growth
It generates jobs
• The dairy sector employs around 35,000 workers, excluding those who are self-employed
(which could be up to 10,000 people). The sector will indirectly support many more jobs
in industries that supply dairy, and that experience the benefits of additional income
flowing into the region due to dairy volume and/or price growth.
• It provides more jobs than each of the finance and accommodation sectors; around 65%
more than the sheep and beef farming sector; 75% more than the fruit growing sector
and double the jobs in the wood processing sector.
• In districts such as South Taranaki, Waimate, Otorohanga and Matamata-Piako, the dairy
sector directly accounts for between 1 in 4 and 1 in 5 of the total number of jobs in the
region.
• A $1 per kg payout increase results in the wealthier dairy sector and upstream and
downstream industries employing approximately 4,600 more full time equivalent workers.
It creates export earnings that improve Kiwis’ standard of living
• Dairy exports were $10.4 billion in calendar year 2009, accounting for around 26% of NZ’s
total goods exports.
• This contribution far outstrips that of any other goods export sector. Dairy exports are
twice those of the meat sector, over 6 times larger than all fruit exports, nine times larger
than wine exports, twelve times larger than aluminium exports and 17 times larger than
wool exports.
• In fact, dairy exports are about the same as the sum of the next four largest export
sectors: meat, wood, mineral fuels (oil) and fruit & nuts.
• Through its export earnings, the dairy sector makes a positive contribution to narrowing
the current account deficit. Without this export growth, New Zealand would have had to
face increased foreign liabilities and interest on foreign debt.
• A smaller deficit reduces New Zealand’s country risk premium on mortgage and other
borrowing costs, which benefits all households and firms that are borrowers.
• The volume growth in the dairy sector over the last decade has resulted in New Zealand
households being a cumulative $6.4 billion better off than if dairy activity had stagnated
at 1999 levels.
• A $1 dairy payout increase delivers additional income of over $270 per year of additional
spending per man, woman and child in New Zealand. This year’s increase of $1.17 per kg
will generate an extra $316 per person in New Zealand.
It fills the tax coffers
• The dairy sector generates a substantial amount of tax revenue for the government,
through the income taxes of farmers, corporate taxes of processors, and the GST and
other taxes on the income and spending that dairy stimulates in the rest of the economy.
• And because the sector has raised taxation revenue, benefits flow not just to the dairying
districts but across the country as a whole.
• Increased tax revenue coming in means more money to spend on essential services such
as schools, hospitals and police. In 2009, these sectors are 0.7%, 0.6% and 0.2% better off
because of the growth in the dairy sector over the past decade.

It drives many rural economies: “when dairy farmers are smiling, the whole
region smiles”
• Dairy production is hugely important for many regional economies. It injected over $700
million into the Southland economy in 2009, with South Taranaki and Matamata-Piako
both receiving well over half a billion dollars.
• For smaller district economies such as Ashburton ($471 million), Waipa ($361 million)
and Selwyn ($270 million), the value of dairy production, relative to the total size of the
economy, is likely to be significant.
• As noted above, as many as 1 in 4 jobs in some rural areas are in the dairy farming and
processing sectors.
• The dairy volume expansion over the past decade has delivered an additional $650 of
income per person in the Southland region and $590 per person in the Canterbury region
above what would otherwise have happened. Northland ($110 per person) and the
Waikato ($270) have also been major winners.
• A $1/kg increase in milk solid prices delivers $170 per person of additional income in
Northland and Taranaki, $130 per person in the Waikato and $140 in the Manawatu-
Wanganui region.
It benefits urban consumers too
• Firms benefit from selling goods and services to the dairy sector. The average dairy
farmer spends well over half of their income on goods and services to support on-farm
operations. Many of these goods will come from urban areas.
• Households benefit from the additional government spending that is facilitated by the
tax revenue generated by the dairy sector.
• They also pay lower mortgage and business borrowing costs due to the reduction in the
current account deficit (and thus the interest rate premium on overseas funds) due to
dairy export revenue.
• The dairy sector’s strong export growth over the last decade has improved New Zealand’s
balance of trade, and allowed for increased consumption spending. This export growth
reduced New Zealand’s net foreign liabilities to GDP ratio by over 1%. Together with the
exchange rate appreciation, this has saved households a cumulative $1.2 billion in interest
repayments on foreign debt over the past decade.
Dairy’s role in generating growth
E

Figure 1
F Dairy’s role in generating growth

Contents
1. The current contribution of dairy 1
1.1 Purpose of report 1
1.2 Direct contribution to GDP 1
1.3 Contribution to regional incomes 2
1.4 Contribution to export performance 2
1.5 Contribution to Balance of Payments 4
1.6 Contribution to employment 4
1.7 Contribution to other sectors’performance 5
1.7.1 Supply chain 5
1.7.2 Dairy farming 6
1.7.3 Dairy processing 7
2. Modelling dairy’s economic contribution over the past decade 9
2.1 Objective of modelling 9
2.2 Modelling technique 9
2.3 Advantages of CGE modelling 9
2.4 Modelling scenarios 10
2.4.1 Scenario 1: The price of milk solids 10
2.4.2 Scenario 2: The growth of dairying over the past decade 11
2.5 How we analyse the modelling results 12
3. Milk solids price spike 13
3.1 Headline results 13
3.2 Detailed results 13
3.2.1 Direct effects: the dairy sector 13
3.2.2 Indirect impact on other industries 16
3.2.3 Macroeconomic effects 17
3.2.4 Regional impacts 18
4. Production growth over the last decade 19
4.1 Headline results 19
4.2 Detailed results 20
4.2.1 Direct impacts 20
4.2.2 Indirect impacts on other industries 20
4.2.3 Macroeconomic effects 21
4.2.4 Regional impacts 22
5. Conclusion 24
Dairy’s role in generating growth
G

Appendices
Figures
Tables
H Dairy’s role in generating growth
Appendix A CGE modelling framework 25
A.1 The MONASH-New Zealand CGE model: overview 25
A.2 Dynamics of the MONASH-NZ model 26
A.3 Database structure 26
A.4 Production structure (Horridge, 2008b) 28
A.5 Regional extension 29
Appendix B CGE and multiplier analysis 30
Appendix C Limitations of analysis 32
Appendix D References 33
Appendix E Dairy employment statistics 34
Appendix F Value of regional dairy production 38
Appendix G Changing dairy export markets 39
Figure 1 Impacts of dairy growth on the rest of the economy F
Figure 2 Growth in dairy exports over past decades 4
Figure 3 Importance of dairy to regional employment 5
Figure 4 Model structure of the sector 6
Figure 5 Change in milk solids price: 1998-2009 11
Figure 6 Processed milk solids 11
Figure 7 Gross regional product impacts 17
Figure 8 Dairy gains since 1998/99 21
Figure 9 2009 Gross regional product impacts 23
Figure 10 Components of a CGE model 25
Figure 11 The MONASH-NZ database 27
Figure 12 Production structure 28
Figure 13 Changing markets for New Zealand’s dairy exports 39
Table 1 Value of regional dairy production 2
Table 2 Export values 3
Table 3 Farming industry structure 7
Table 4 Dairy processing industry structure 7
Table 5 Indirect impacts 2010 15
Table 6 National results 16
Table 7 Increase in gross regional product 17
Table 8 Average Cap Farm Cashflow 18
Table 9 Indirect impacts 2008/09 21
Table 10 National results 2009 22
Table 11 Increase in gross regional product 23
Table 12 IO vs. CGE multipliers 31

1. The current contribution of dairy
1.1 Purpose of report
This report identifies the dairy sector’s current contribution to the New Zealand economy
and looks at how changes in the dairy sector over the past decade have benefited districts
and households in New Zealand.
1.2 Direct contribution to GDP
The dairy sector, comprising farmers and dairy processors, directly contributed around $5.0
billion of value added (or GDP) to the New Zealand economy in 2010, around 2.8% of the
total GDP figure 1 . By way of comparison, dairy GDP:
• is greater than the GDP contribution of the fishing, forestry and mining sectors combined
• is around 10 times as large as the GDP of the wine sector
• is about 3 times as large as the forestry and logging sector
• accounts for over a third of the GDP contribution of the entire primary sector (dairy and
meat farming and processing, horticulture, fishing, forestry, mining)
• is 40% larger than the entire utilities sector (electricity, gas and water)
• is 2/3 as large as the entire construction sector
• accounts for 15% of the total GDP of the goods producing industries
Note that these figures are the direct contributions only. They do not take into account the
links that the dairy sector has with the wider economy. In reality, the dairy sector also has
indirect and induced effects on the New Zealand economy. The indirect effects accrue via
the industries supporting the dairy sector (fertiliser, agricultural services, transport, etc). When
the dairy sector grows, these supporting industries will also grow. The induced effects are
attributable to the additional spending of dairy sector farmers and workers following a boost
in dairy returns. This spending will be directed into sectors such as housing, clothing, bars and
cafes, entertainment, etc. Some of these linkages are discussed in section 1.7 below. 2
1. Calculated from Statistics New Zealand SNA GDP by industry data and NZIER’s industry database. Measured in 2010 prices.
2. Unless one uses an unrealistic and non-credible methodology, it is not possible to calculate the total (direct plus indirect
and induced) GDP contribution of dairy. See section 2.3 and Appendix B for further explanation
Dairy’s role in generating growth
1

2 Dairy’s role in generating growth
1.3 Contribution to regional incomes
In many rural areas, the contribution of the dairy sector to the local economy is far greater
than the national average of 2.8% mentioned above. The dairy sector pumps hundreds of
millions of dollars of revenue into regional economies each year. Table 1 shows the 15 highest
revenue generating dairy districts in New Zealand.
Dairy production injected over $700 million into the Southland district economy in 2009, with
South Taranaki and Matamata-Piako both receiving well over half a billion dollars. For smaller
district economies such as Ashburton ($471 million), Waipa ($361 million) and Selwyn ($270
million), the value of dairy production, relative to the total size of the district economy, is likely
to be significant 3 . Also see Box story 1.
Table 1 Value of regional dairy production
$ millions, 2009
Region Dairy revenue
Southland 710.35
South Taranaki 616.56
Matamata-Piako 552.12
Ashburton 471.11
Waikato 389.91
Waipa 361.00
Selwyn 269.91
South Waikato 262.53
Rotorua 253.55
Otorohanga 234.54
New Plymouth 206.31
Hauraki 196.40
Tararua 188.28
Timaru 185.13
Clutha 181.72
Notes: (1) Based on $5.50 price per Kg MS, 35c per Kg MS for stock sales and 4c per Kg of MS for other income
Source: Dairy New Zealand, Fonterra, NZIER
1.4 Contribution to export performance
Dairy exports were $10.4 billion in calendar year 2009, accounting for around 26% of NZ’s
total goods exports. As Table 2 shows, this contribution far outstrips that of any other goods
export sector. The third column in the table shows that dairy exports are twice those of the
meat sector, over 6 times larger than all fruit exports, nine times larger than wine exports,
twelve times larger than aluminium exports and 17 times larger than wool exports.
In fact, dairy exports are about the same as the sum of the next four largest export sectors:
meat, wood, mineral fuels (oil) and fruit & nuts.
3. Regional GDP information at this level of detail is not available from Statistics New Zealand, so the shares cannot be
calculated.

Table 2 Export values
$ millions, 2009
Sector Export value How many times dairy
exports are larger than
sector’s
Dairy products 10,398
Meat products 5,142 2.0
Wood products 2,316 4.5
Mineral fuels 1,891 5.6
Fruit & nuts 1,597 6.6
Machinery parts 1,294 8.1
Fish 1,260 8.3
Miscellaneous 1,211 8.7
Wine & other beverages 1,183 8.9
Aluminium 880 11.9
Electrical machinery 826 12.7
Precious metals & stones 764 13.7
Wool 637 16.5
Wood pulp 610 17.2
Iron & steel 565 18.6
Optical & medical equipment 546 19.2
Paper & paperboard 526 20.0
Vegetables 405 25.9
Plastics 401 26.2
Hides & skins 375 28.0
Notes: (1)
Source: Dairy NZ, Fonterra, NZIER
Final report - 16 November 2010
Over the past decade, dairy export values have grown by more than 8% per year. Dairy has
grown more rapidly than most primary sectors, and has become an increasingly important
contributor to New Zealand’s total food and beverages and overall merchandise trade.
Figure 2 Growth in dairy exports over past decades
Figure Annual average 2 Growth growth in in dairy export exports values, 1999-2009 over past decades
Annual average growth in export values, 1999-2009
Source: Statistics New Zealand, NZIER
Source: Statistics New Zealand, NZIER
Dairy’s role in generating growth
Export growth has been driven by a combination of strong global income growth for
3

4 Dairy’s role in generating growth
Export growth has been driven by a combination of strong global income growth for the
majority of the decade, as well as a change in the composition of the markets that we sell to.
As economies such as China and other parts of Asia experience higher living standards, their
tastes and preferences change, and staples such as rice, lentil and beans are replaced with
higher protein foods. The changing composition of New Zealand’s dairy markets is shown
in Figure 13 in Appendix G. China, for example, accounted for 0.4% of New Zealand’s dairy
exports in 1989 and now takes over 12%. The relative importance of major markets such as
the UK, Japan and Mexico has dropped over this period.
1.5 Contribution to Balance of Payments
The strong export growth from the dairy sector has been a key factor in New Zealand’s
current account deficit (CAD) narrowing in recent years. This is important because as the CAD
rises as a proportion of GDP, foreign investors and ratings agencies start to have concerns
over the ability of the New Zealand economy to withstand any unexpected negative
economic shock (such as a global pandemic or financial crisis). These concerns translate into
New Zealand having a higher risk premium attached to it on foreign borrowings – that is, it
becomes more expensive for New Zealand firms, households and the government to borrow
on international markets. The most obvious channel would be through higher household
mortgage repayments.
The strength of the dairy sector has been very evident as New Zealand recovers from the
global financial crisis and domestic recession. With domestic demand continuing to be
anaemic, it is the export side of the economy that is being relied on to generate economic
growth. It has recently been noted that dairy’s growth has resulted in New Zealand’s trade
surplus being at its highest level for eight years.
1.6 Contribution to employment
National
The dairy sector in New Zealand is a major employer, and is vital for a number of districts.
On-farm employment is around 24,000 nationwide, with dairy processing providing another
10,000 jobs. These figures do not include those dairy farmers who are registered as selfemployed.
Although dairy employment does not reach the employment levels present in a number of
services sectors (for example, there are 110,000 workers in pre-school and school education
alone), it provides more jobs than each of the finance and accommodation sectors (both
around 32,000); around 65% more than the sheep and beef farming sector (20,500); 75% more
than the fruit growing sector (19,300) and double the jobs in the wood processing sector.
Regional
In districts such as South Taranaki, Waimate, Otorohanga and Matamata-Piako, the dairy sector
directly accounts for between 1 in 4 and 1 in 5 of the total number of jobs in the region.
The sector will indirectly support many more jobs in industries that supply dairy, and that
experience the benefits of additional income flowing into the region due to dairy volume
and/or price growth.
4. Department of Labour (DoL), ‘Regional Industry Tool 2009’http://www.dol.govt.nz/services/LMI/tools/regional-industry-tool.asp
5. There is no official count of self-employed dairy farmers, but the figure has been estimated by Dairy NZ at around 10,000 based on
owner-operator and sharemilker numbers.

Figure 3 Importance of dairy to regional employment
Dairy farm and processing jobs as % of total in region
Figure 3 Importance of dairy to regional employment
Dairy farm and processing jobs as % of total in region
Source: DoL, NZIER
A complete
A complete
table
table
of
of
dairy employment
employment
statistics
statistics
for each
for
of New
each
Zealand’s
of New
74 Territorial
Zealand’s
Local
74
Authorities is contained in Appendix E.
Territorial Local Authorities is contained in Appendix E.
1.7 Contribution to other sectors’ performance
Final report - 16 November 2010
Of course, the dairy farming and processing sector do not operate in isolation. They have
strong upstream and downstream links to other parts of the New Zealand economy.
1.7 Contribution to other sectors’ performance
1.7.1 Supply chain
Of course, the dairy farming and processing sector do not operate in isolation. They
The dairy sector can conceptually be broken into a dairy farming industry and a dairy
have strong
processing
upstream
industry. Dairy
and
farming
downstream
generates
links
the raw
to
milk
other
that the
parts
dairy
of
processing
the New
industry
Zealand
economy. uses as an input, and produces processed dairy products for sale to domestic consumers,
export markets and other industries.
1.7.1 Supply chain
The dairy sector can conceptually be broken into a dairy farming industry and a dairy
processing industry. Dairy farming generates the raw milk that the dairy processing
industry uses as an input, and produces processed dairy products 6 for sale to
domestic consumers, export markets and other industries.
6
In our model, we have a variety of processed dairy products, but for simplification for this work,
we consider one generic processed dairy product. Similarly, farm income from other sources than
just milk 6. In (e.g. our model, stock we have and a variety other of processed sales) dairy is included products, but in for the simplification modelling for this but work, not we consider singled one generic out in processed the
reporting.
dairy product. Similarly, farm income from other sources than just milk (e.g. stock and other sales) is included in the modelling but
not singled out in the reporting.
NZIER – Dairy’s role in generating growth
6
Dairy’s role in generating growth
5

Figure 4 Model structure of the sector
Figure 4 Model structure of the sector
Source: NZIER
At each stage of production there is also labour, capital and other intermediate employment.
At each stage of production there is also labour, capital and other intermediate
employment. 1.7.2 Dairy farming
The structure of the farming industry is shown in Table 3. The farming sector produced around
1.7.2 $7.5 Dairy billion farming worth of raw milk in the 2009/10 production year for sale to the processing
operations. As expected, farming uses a lot of land and the labour is not a large part of the
The structure of the farming industry is shown in Table 3. The farming sector
farm’s costs. The on-farm sector employs around 24,000 full time equivalent (FTE) workers. The
produced around $7.5 billion worth of raw milk in the 2009/10 production year for sale
primary cashflow costs for farmers are fertiliser for the land and feed for the animals. These
to the processing two industries operations. are heavily affected As expected, by movements farming in demand uses for a milk lot of products. land and the labour
is not a large part of the farm’s costs. The on-farm sector employs around 24,000 full
We can break down the $7.5 billion of raw milk into the following parts:
time equivalent (FTE) workers. The primary cashflow costs for farmers are fertiliser
for the • land $3.0and billion feed is retained for the as returns animals. to land, These labour two andindustries capital. are heavily affected by
movements • $3.6 in billion demand is spent for on milk domestically products. produced intermediate inputs, such as fertilizer ($447
million), straw and feed ($723 million), agricultural services ($446 million), financial services
We can break ($341down million), the machinery $7.5 billion repairs of ($198 raw million) milk into andthe petrol/diesel following ($80 parts: million).
• $3.0 • billion $440 million is retained is spent as onreturns imported to inputs land, such labour as fertilizer and capital. ($138 million), pharmaceuticals
($111 million), feed ($31 million), agricultural equipment ($26 million) and pesticides ($16
• $3.6 billion million). is spent on domestically produced intermediate inputs, such as
fertilizer ($447 million), straw and feed ($723 million), agricultural services ($446
• $290 million is spent on margin services such as transport.
million), financial services ($341 million), machinery repairs ($198 million) and
petrol/diesel ($80 million).
NZIER – Dairy’s role in generating growth
6 Dairy’s role in generating growth
Final report - 16 November 2010
• $440 million is spent on imported inputs such as fertilizer ($138 million),
pharmaceuticals ($111 million), feed ($31 million), agricultural equipment ($26
million) and pesticides ($16 million).
• $290 million is spent on margin services such as transport.
7

Table 3 Farming industry structure
Input Dairy farming Comment
Land 21% Includes Gross Margin
Capital 15%
Labour 5%
Domestic intermediates 47% Ag services, feed, fertilizer
Imported intermediates 8% Fertilizer, pharmaceuticals,
feed
Margins 4% Transport
Source: NZIER
1.7.3 Dairy processing
The dairy processing industry takes the raw milk and turns it in to products that can be sold to
customers and consumers. The industry produces a wide range of dairy products, from milk
and cheese to ice cream and butter.
The vast majority of the industry’s input costs are the purchase of the raw milk, which
accounts for 70% of the industry’s costs. In addition, the processing industry uses about $1.1
billion of capital and employs close to 10,000 FTE employees.
Of the $10.4 billion exported by our model’s dairy processing sector:
• $7.5 billion is used to purchase raw milk from the dairy farming sector.
• $1.5 billion is retained as returns to labour and capital (i.e. wages and rate of return).
• $625 million is spent on intermediate inputs from New Zealand. This includes $85 million
of plastic containers, $45 million on electricity and $22.5 million on financial services.
• Imported intermediate inputs account for $310 million – largely plastic containers ($182
million) and other food products to be used in processing ($30 million).
• $730 million is spent on retailing/wholesaling costs that get the dairy products from the
plant to market.
Table 4 Dairy processing industry structure
Input Share Comment
Capital 7% Includes Gross Margin
Labour 7%
Raw milk 66%
Other intermediates 12% Other farm inputs
Other imported intermediates 6% Mostly plastic – packaging
Margins 2% Retailing and wholesaling
costs
Source: NZIER
Dairy’s role in generating growth
7

8 Dairy’s role in generating growth
Dairy exports and rural livelihoods
Any inquiry into the New Zealand economy and its workings has to at some point focus
on the central driving force of economic growth: trade. Trade is important because over
time New Zealand’s spending must equal its income. Without international trade the
income of New Zealand businesses is limited by domestic spending. International trade
removes this limit.
With dairy exports at 26% of goods exports, the impact of the dairy industry on
economic activity is considerable. The money that farmers spend in their communities
and in other parts of the country drives further economic activity – the more they earn
on international markets the more they spend in New Zealand. Dairy farmers’success is
mirrored not only in their local communities but also in the cities of New Zealand which
produce the goods and services that are bought by farmers. Even imports have a local
component since they have to be transported to the point of sale.
Nobody understands this more than the mayors of the districts, regions and cities of New
Zealand. Peter Tennent, Mayor of New Plymouth, says that “while the dairy industry in his
region only makes up 2% of the workforce, 100% of the community are the benefactors
of their efforts. When dairy farmers are smiling, the region smiles”. Hugh Vercoe, Mayor of
the Matamata Piako District, also knows how important dairy is to his district: “not only
are we reliant on the dairy [farming] industry, we have five dairy processing plants and
very active sale yards. This helps to maintain a vibrant community”. David Adamson, CEO
of the Southland District Council says that the dairy industry has “changed the face of
Southland”. He adds that “its economy has weathered the recession well, mainly because
of the influence of the dairy industry”.
In the first instance farmers spend their incomes on industries that directly support
their activities. They buy more cows, upgrade equipment, buy fertilizer, repay debt and
make land improvements. David Adamson suggests that this is the most visible sign
of the impact of dairy growth on the Southland region: “most of the money earned by
farmers is spun out into the community”. Since most of the goods and services come
from outside of the provinces, other communities benefit as well. In work done by
NZIER (2003) it is shown that it takes about 18 months for this economic ‘ripple’effect of
additional export revenue to fully work through the New Zealand economy, all of which
leads to stronger household spending and business investment.
What would New Zealand look like without the dairy industry? Peter Tennent finds it
difficult to imagine this situation but one thing he does know is that “New Plymouth
would not have been judged the best place to live on the planet by the United Nations
backed Liv.com Awards without the dairy industry … we’d still be smiling but not as
wide … and there’d be far fewer businesses here”. Similar sentiments are echoed by
David Adamson and Hugh Vercoe. Both said there would be fewer businesses, less
vibrant community, and fewer job opportunities. Not only would there be fewer job
opportunities and increased movement of people to the cities, those cities would also be
poorer.
The dairy industry has had a major impact on New Zealand society and economy for
over 130 years. Those involved in running districts and cities closest to the dairy industry
well understand the positive impact of dairying, not just on their regions and cities but
on the rest of New Zealand.

2. Modelling dairy’s economic contribution
over the past decade
2.1 Objective of modelling
The section above has shown that the dairy sector has witnessed significant growth over the
past decade. A key question is: how has this growth benefited the rest of the economy? In
particular, we are interested in two aspects of this growth:
• The short term impacts of milk solids payout increases
• The longer term impacts of volume growth in the sector over the last 10 years.
We examine these two aspects using a relatively newly developed economic model of the
New Zealand economy.
2.2 Modelling technique
The dairy sector interacts with the rest of the economy by generating exports and
employment, using intermediate inputs such as fertilizer, and competing for use of land,
labour and investment. In order to get a sense of how the New Zealand economy as a whole
might be impacted by production and price changes in the dairy sector, we need to use
an economic model that takes these interactions into account. We use NZIER’s dynamic
Computable General Equilibrium (CGE) model of the New Zealand economy to evaluate the
impacts of the price and volume growth in the dairy sector.
2.3 Advantages of CGE modelling
Our dynamic CGE model is a more robust framework than alternatives approaches for
estimating the contribution of the dairy sector to the New Zealand economy. The most
commonly used alternative is input-output (IO) or ‘multiplier’analysis. IO or multiplier analysis
has two significant limitations:
• It does not adequately consider the reallocation of resources following a ‘shock’to the
economy, such as a surge in demand for dairy exports. In particular, multiplier analysis
assumes that resources (land, labour, capital, energy, intermediate inputs) are available
Dairy’s role in generating growth
9

10 Dairy’s role in generating growth
in unlimited quantities for the expansion of a sector. It does not consider how those
resources might otherwise have been used in the economy – their opportunity cost. In
reality, resources are scarce and any additional resources used in the dairy sector must
be diverted from other industries. The output of these industries must therefore fall. The
overall macroeconomic impact of the increase in demand in one sector should take into
account these losses elsewhere in the economy.
• It does not account for relative price changes. For example, it assumes that wage rates
do not change as the demand for labour rises or falls, and that the prices of intermediate
goods such as transport and business services do not change in response to shifts in
demand. In reality, if there is additional demand for workers in the dairy sector, this will
place upward pressure on wages across the economy. Even though this wage pressure
might be relatively small, it will still have a negative impact on input costs for other firms
in the economy, and could lead to a drop in output. A similar story is true for intermediate
inputs. As the dairy sector demands more of these inputs, their price rises for all other
firms in the economy, causing their output to fall.
Multiplier analysis therefore tends to vastly overstate the economic impacts of changes
in demand in a specific sector. These unrealistically large impacts are thus not particularly
informative for policy makers or firms.
CGE models explicitly address both resource allocation and relative price shifts, allowing for
a more credible, richer analysis of economic contribution. These models tend to produce
more conservative estimates of impacts, but are more consistent with economic theory and
practice. See Appendix B for a fuller discussion.
2.4 Modelling scenarios
We investigate the impact of the dairy sector with two historical scenarios to show how real
changes in the dairy sector translate into benefits for the rest of the economy. The historical
scenarios examine the benefits that have accrued over the past decade:
• milk solids payout increases
• growth in the sector over the last 10 years.
These two scenarios jointly capture both the benefits to the economy of the long term
growth in the sector and the short-run wealth gains from increased milk solids payouts.
• milk solids payout increases
• growth in the sector over the last 10 years.
These two scenarios jointly capture both the benefits to the economy of the long term
growth in the sector and the short-run wealth gains from increased milk solids payouts.
2.4.1 Scenario 1: The price of milk solids
The world price of milk solids has a significant impact on the dairy industry and the wider
New Zealand economy. It has also been fairly volatile of late, as can be seen from Figure 5.
This first scenario assesses the effects on the economy of changes in the milk solids price paid
to farmers. In order to generate higher prices for milk solids we assume that the world price
has risen due to increased world demand for dairy produce. Increased world demand for
New Zealand’s dairy produce leads to rises in both milk prices for New Zealand dairy farmers
and over a sustained period a rise in the quantity of milk solids produced domestically.
We calibrate the price increases in this simulation to be ± $1/kg milk solids in Fonterra’s
payout. So we are asking: what are the flow-on impacts for the New Zealand economy from a
$1 increase or decrease in the Fonterra payout?

Figure 5 Change in milk solids price: 1998-2009
$ per kg, 2008-09 prices
Figure 5 Change in milk solids price: 1998-2009
$ per kg, 2008-09 prices
Figure 5 Change in milk solids price: 1998-2009
$ per kg, 2008-09 prices
Source: Dairy NZ
Final report - 16 November 2010
2.4.2 Scenario Source: 2: Dairy The NZ growth of dairying over the past decade
Over the 2.4.2 last Scenario 10 years 2: The the growth dairy of sector dairying has over grown the past significantly, decade increasing milk solid
production 2.4.2 Scenario
Over the
by
last
58% 2:
10 years
between The growth
the dairy
1998/89 of
sector has
and dairying
grown
2008/09. over
significantly,
In the this
increasing
case past
milk
study, decade
solid
we ask the
questions: Over the production last ‘what 10 by if years 58% it hadn’t between the dairy grown’? 1998/89 sector and has 2008/09. ‘what grown would In this significantly, case the study, economy weincreasing askhave the questions: missed milk solid out
on production if dairy ‘what had if by it hadn’t stagnated 58% grown’? between at and 1999 1998/89 ‘what production wouldand the economy 2008/09. levels’? have In missed this case out onstudy, if dairywe had ask the
questions: stagnated ‘what at 1999 if it hadn’t production grown’? levels’? and ‘what would the economy have missed out
The factual is the actual volume path as it occurred; the counterfactual is volumes
on if dairy The factual had stagnated is the actualat volume 1999 path production as it occurred; levels’? the counterfactual is volumes remaining
remaining at 1998/99 levels, as per Figure 6.
at 1998/99 levels, as per Figure 6.
The factual is the actual volume path as it occurred; the counterfactual is volumes
remaining Figure at 1998/99 6 6 Processed levels, milk as milk solids per Figure solids 6.
Million kgs
Figure 6 Processed milk solids
Million kgs
Source: Dairy Statistics 2008/09
Source: Dairy Statistics 2008/09
NZIER – Dairy’s role in generating growth
NZIER – Dairy’s role in generating growth
12
12
Dairy’s role in generating growth
11

12 Dairy’s role in generating growth
2.5 How we analyse the modelling results
In analysing the modelling results we take a systematic approach of tracking the impacts as
they flow through the economy, beginning with the direct impacts on the dairy sector itself.
We look at the export and domestic markets, and how the sector responds to growth with
increased employment and investment.
We then analyse the flow-on or indirect impacts on other industries. We split indirect impacts
into the following industry categories:
• Supplying industries – industries that supply dairy with intermediate inputs are likely to
benefit from a stronger dairy sector. These are industries such as agricultural services and
the fertilizer industry.
• Household expenditure industries – industries that households spend money on are
likely to benefit from increased income that comes through higher employment and
wages, and increased returns to capital from a growing dairy sector.
• Government industries – industries that rely on government funding are positively
impacted by a stronger economy and bigger tax takes, as this increases the money
available for the government to spend.
• Competing export industries – industries that compete for resources (such as land and
labour) with the dairy sector lose from dairy’s growth.
Finally, we examine the macroeconomic effects. Here we report both value-add (GDP) and
Net Economic Benefit/welfare (private and public consumption) measures.
There are two ways to think about the way that export growth will affect GDP:
(i) GDP is the sum of the value of expenditure on goods and services made in New
Zealand and exports are a component of that expenditure, so a change in exports
directly affects the level of GDP. The change in exports will then have flow-on effects
on other parts of the economy, as described in our results section.
(ii) GDP is also the sum of the value of resources utilised in the economy. Increased dairy
exports are generated, in part, by gains in productivity. Greater productivity allows
the same resources – capital, land and labour – to generate greater value, so GDP
increases as productivity rises. Thus we expect export growth to have a direct impact
on GDP and, in the long run, a positive impact.
Although GDP is the most commonly used measure of economic performance, it does
not capture necessarily how ‘well off’we are as a country. GDP is essentially a measure of
how many goods and services New Zealand produces – it shows the size of the economy.
Consumption shows how much household and government spending increases following
a change in the economy. It is more appropriate than GDP as a measure of welfare (see
Coleman, 2008), particularly in cases where we expect changes in the terms of trade 7 .
Ultimately, the objective of an economic development is to raise the living standards of the
population. Living standards are better proxied by household and government spending
ability than by GDP. Thus our preferred NEB/welfare measure is consumption. Our CGE model
allows us to determine, once all inter-industry effects and factor price changes have occurred,
the additional boost to New Zealand’s GDP and NEB/welfare resulting from a price change
in the milk solids payout or volume growth in the sector. In addition, we also report other
macroeconomic indicators such as wages and employment.
7. We use the term ‘welfare’here not in the technical economic sense but merely as a synonym for ‘wellbeing’. The claim is merely that
changes in consumption better proxy changes in welfare than do changes in GDP. We do not claim to actually measure welfare in
the technical sense.

3. Milk solids price spike
3.1 Headline results
A short term increase in the price of milk solids generates immediate benefits for the national
economy. The national benefit of an increase of $1/kg in the Fonterra payout is a welfare
gain of $1.2 billion, as proxied by private and public consumption. In addition, national GDP
is expected to rise by $400 million 8 . The richer dairy sector would generate employment of
approximately 4,600 more FTEs and wages would later start to rise 9 .
The welfare gain is larger than the GDP gain due to the impact of exchange rate movements:
• the improved terms of trade allows us to consume more of our GDP (i.e. we have to
export less to pay for a given amount of imports – making the country better off as a
whole)
• the currency appreciation leads to a reduction in the value of New Zealand’s foreign debt.
Both effects improve New Zealanders’household purchasing power and allow greater
consumption of goods and services.
3.2 Detailed results
3.2.1 Direct effects: the dairy sector
In the first simulation the increased world demand for dairy products drives up both the price
and volume of dairy exports. That is passed on down the supply chain and results in a $1
per kilogram of milk solids increase in payments to dairy farmers. The increased payout and
volumes cause the dairy sector grows strongly to generate the extra production.
The increased payout causes investment in the farming industry to grow by 44%, and
employment by 20%. Investment in the processing component of the industry grows by
14% and employment by 5.5%, relative to what would otherwise have occurred. Investment
growth is higher than employment growth because capital accumulation tends to lag behind
employment growth. The farming component of the sector grows more strongly because
we have assumed that the benefits of higher world prices will be passed on to farmers. If
dairy processors were to increase their profit margins instead then the differences would
diminish 10 .
8. This is on top of the income generated by the ‘base’price. That is, if the 2011 price (say) is $5 and the 2012 payout is $6, our results
look just at the additional income generated by the $1 price increase.
9. The direct impact on the economy of a $1 increase in the milk solids price is a $1.3 billion increase in gross output. That gross
output generates about $590 million of GDP once the cost of intermediate inputs is subtracted. Furthermore, the effect of the
increased dairy output is to increase the price of resources to other industries and thus reduce their output. The net effect on GDP
of the $1.3 billion injection, once all these effects have been taken in to account, is the $400 million we report.
Dairy’s role in generating growth
13

14 Dairy’s role in generating growth
3.2.2 Indirect impact on other industries
The indirect impacts can be broken down into the industry categories described in section
2.5. The numerical results are summarised in Table 5.
• Supplying industries – industries that supply dairy with intermediate inputs are likely
to benefit from a stronger dairy sector. However, the fertilizer industry loses 0.2% of its
sales. That counterintuitive result arises from the movements in the exchange rate, which
will be discussed further in the next section. As exports rise, imports become relatively
cheaper and that causes primary producers to switch away from domestically produced
fertiliser in favour of imported fertilisers.
• Government expenditure industries – as expected, the increased incomes from the
higher milk solids payout boost tax revenues and enable the government to spend more
providing services such as education, health, and law and order.
• Household expenditure industries – industries that households spend money on
are likely to benefit from increased incomes generated in the dairy sector through
employment and wage increases, and increased returns to capital. Such industries
include housing and real estate (which takes a large share of households’budget), and
consumption goods from the retail trade sector.
• Competing export industries – industries that compete for resources with the dairy
sector suffer from the dairy sector’s increased spending power. That is particularly so
for the sheep and beef sector, which uses many of the same resources. In addition,
the appreciation of the New Zealand dollar that results from increased exports of
dairy products hurts all exporters, as seen by the drop in production of the textile and
horticulture sectors.
10. The second simulation with a $1 per kilogram price decrease shows near identical effects in the opposite direction. In the interests
of brevity we report only the results for the price increase here.

Table 5 Indirect impacts 2010
Percentage deviation in value added from BAU levels, selected industries
Industry Type Impact
Agricultural services Supplying 0.09%
Fertilizer Supplying -0.2%
Retail Household expenditure 0.7%
Real estate Household expenditure 1.1%
Residential property Household expenditure 0.03%
Schools Government 1.1%
Hospitals Government 1.3%
Police Government 0.8%
Apple and Pear Competing export -3.0%
Sheep and Beef Competing export -0.4%
Textiles Competing export -1.3%
Source: NZIER
3.2.3 Macroeconomic effects
The national results follow naturally from the direct and indirect impacts described above. We
focus on the key macroeconomic variables described in section 2.5: employment and Gross
Domestic Product (GDP), as well as consumption, which is a measure of NEB (how ‘well off’
we are).
The NEB/welfare gain for New Zealand, proxied by private and public consumption is an
increase of 1.2%. That represents an extra $1.2 billion of goods consumed in New Zealand,
relative to the situation if the price of milk solids had remained constant. This equates to over
$270 of additional spending per man, woman and child in New Zealand due to the $1/kg
price increase.
The change in real GDP of 0.24%, or $395 million, represents the increase in the value of
goods and services produced in the economy. The benefits arise from the increased flows of
income to farmers being distributed throughout the economy via supplying industries and
government and household spending.
The NEB gain is larger than the GDP gain for two reasons:
• An increase in the price of dairy exports improves New Zealand’s terms of trade. An
increase in the terms of trade allows us to consume more of our GDP.
• The assumed increase in demand for dairy exports causes a currency appreciation that
leads to a reduction in the domestic currency value of New Zealand’s interest repayments
on foreign debt. This improves New Zealanders’household purchasing power and allows
greater consumption of goods and services. Under different assumptions about the
mechanisms of foreign investment, this contribution is dampened (see Appendix C).
Overall, the increased milk solids price draws wealth into the country via dairy exports and
that leads to an increase in New Zealand’s wealth and, thus, our living standards.
The impact on export competing industries is negative because of the appreciation of our
currency. However, that same appreciation allows us to buy more from overseas as can be
seen by the rise in imports and private consumption (see Table 6).
Dairy’s role in generating growth
15

16 Dairy’s role in generating growth
The increased production in dairy draws in more labour, which is shown by the rise in
employment. Note however that, in our modelling, employment is assumed to vary much
more quickly than wages. In the short timeframe of this simulation we would not expect to
see much impact on wages because they have not had time to adjust. Similarly, while the
rate of return on dairy capital has risen, the level of capital in the industry has not yet had
time to accumulate.
Table 6 National results
Real percentage deviation from BAU levels
Indicator Percentage change Levels change,
$ millions
GDP 0.24% $400
Private Consumption 1.2% $1,200
Public Consumption 1.2% $360
Exports (volume) -1.8% -$1,000
Imports (volume) 1.4% $720
Employment 0.35% 4,600 FTEs
Hospitals Government 1.3%
Police Government 0.8%
Apple and Pear Competing export -3.0%
Sheep and Beef Competing export -0.4%
Textiles Competing export -1.3%
Source: NZIER
3.2.4 Regional impacts
The impact on the districts is in proportion to the importance of the dairy industry to the
region. The majority of New Zealand’s dairying is in the central North Island and that is
reflected in the strong growth of Taranaki, Waikato and the Manawatu. However, dairy is
also very important to the small Northland economy, which is why the large gains are seen
there. Districts that have strong red meat industries, such as Canterbury, suffer due to the
competition for resources from the growing dairy sector in this simulation. Similarly, districts
that depend on exports, such as Tasman’s wine and Auckland’s manufacturing, see low
growth due to the costs imposed by the appreciation of the exchange rate.
The impacts of a $1/kg price increase on per person consumption or living standards in each
region are shown in Table 7.

Figure 7 Gross regional product impacts
Real Figure percentage 7 Gross deviation regional from BAU product levels impacts
Real percentage deviation from BAU levels
Source: NZIER
Source: NZIER
Table 7 Increase in gross regional product
Table 7 Increase in gross regional product
Region Northland $170 Per person increase in GRP
Northland
Auckland -$4
$170
Auckland
Waikato $130
-$4
Waikato
Bay Of Plenty
Bay Of Plenty
Gisborne
Gisborne
$66
$100
$130
$66
$100
Hawkes Bay
Hawkes Bay
$39
$39
Taranaki
Taranaki $160
$160
Manawatu-Wanganui $140
$140
Wellington $140
$140
Tasman-Nelson $12
$12
Marlborough $54
$54
West West Coast Coast $69
$69
Canterbury
Canterbury $41
$41
Otago
Otago
Southland
Southland
Source: NZIER
Source: NZIER
$82
$68
$82
$68
NZIER – Dairy’s role in generating growth
Region Per person increase in GRP
Final report - 16 November 2010
Dairy’s role in generating 19 growth
17

18 Dairy’s role in generating growth
Where the money goes
To illustrate the impact of dairy farmer spending in the New Zealand economy, Table 8 sets
out the key cash flow items for an average dairy farm operation for the current 2010/11 June
year. In the current year Dairy NZ expects the average dairy farm to produce around 130,000
kg of milksolids. The cash income is the dollar amount received for milksolids sold to the
factory (i.e. Fonterra) and also includes net livestock sales.
Table 8: Average farm cashflow
$ per farm, $ per kg MS
2010/11
$ per kg MS
2010/11
$ per kg MS
Cash Income 840,000 6.80
Less farm working expenses 475,000 3.60
Cash Operating Surplus 365,000 3.20
Less
Interest and rent 185,000 1.50
Tax 35,000 0.25
Drawings 85,000 0.70
Cash available for development/
investment/debt repayment
60,000 0.75
Apple and Pear Competing export -3.0%
Sheep and Beef Competing export -0.4%
Textiles Competing export -1.3%
Note: Figures are rounded so do not exactly add up
Source: Dairy New Zealand 2010
A substantial part of farmers’expenses are the farm working expenses. Farm working
expenses typically include wages, animal health and breeding, feed made and purchased,
stock grazing fertiliser, expenditure on removing weed and pests, repairs and maintenance,
fuel, vehicle charges, administration, insurance, ACC, and rates.
This leaves what is known as the cash operating surplus. This is less than half of the initial
cash income. From this farmers pay off interest and rent (this includes overdraft and term
payments and also rent of land), tax (terminal and estimated tax), and drawings (family living
expenses). This leaves the cash available for farm development, any investments made and
repaying principal on debt.
This demonstrates that most of the money received by farmers as their cash income in one
form or another is spent in New Zealand. This is of fundamental importance for the New
Zealand economy since it drives further income generation and has a major impact on
domestic economic activity.

4. Production growth over the last decade
4.1 Headline results
At the national level, the growth in the dairy sector over the last decade has resulted in:
• New Zealand’s 2009 GDP increasing by $690 million, relative to what it would have been
had the dairy sector stagnated at 1998/99 levels. While labour and land can switch to
alternative uses should dairy have stagnated, productivity gains and capital accumulation
within the sector are net gains to the economy.
• New Zealand’s 2009 welfare as proxied by private and public consumption being
$1.1 billion higher than it would otherwise been. From the point of view of 1999, the
cumulative net present value (NPV) of the decade’s consumption growth to 2009 is $6.4
billion.
• The dairy sector’s strong export growth over the last decade has improved New Zealand’s
balance of trade, and allowed for increased consumption spending. This export growth
reduced New Zealand’s net foreign liabilities to GDP ratio by over 1%. Together with the
exchange rate appreciation, this saved $231 million in interest repayments on foreign
debt in 2009, or cumulatively $1.2 billion from 1999.
• Real wages in 2009 increasing by 0.9% as increasing incomes means increased demand
for goods and services, which in turn results in higher wages for employees.
Significantly, the gains from the growth in the dairy sector, including wage rises, are not just
felt within the sector itself, but more widely throughout the economy:
• Growth in the fertilizer and agricultural service industries, which supply the dairy sector
with intermediate inputs, are up by 0.9% and 4.3% in 2009, relative to what they would
have been if dairy stagnated.
• Industries where households spend their income, such as retail and housing, also benefit
from the growth in the dairy sector, with activity in 2009 0.5% and 0.9% higher than had
dairy not grown as experienced.
• These positive flow-on impacts have further flow-on impacts to the tax-take of the
government. Increased tax revenue coming in means more money to spend on essential
services such as schools, hospitals and police. In 2009, these sectors are 0.7%, 0.6% and
0.2% better off because of the growth in the dairy sector.
• Conversely, there are industries that have lost from growth in the dairy sector, most
notably the sheep and beef sector which competes for resources. Our modelling
suggests that this industry would have grown by an extra 10% over the last decade,
had dairy stagnated rather than grown. Similarly, other export industries such as textiles
and apples and pears suffered from a higher exchange rate, down by -2.3% and -3.0%
respectively.
Regionally, the results favour those areas where dairy farming has grown the most:
• Canterbury and Southland 2009 regional GDP levels are 1.4% and 1.3% higher than they
would have been had dairying not increased the economic activity within their districts.
• Hawkes Bay, with a strong dependence on fruit and horticulture, is 0.3% worse off
because of the currency appreciation caused by the growth in dairying.
Dairy’s role in generating growth
19

20 Dairy’s role in generating growth
because of the currency appreciation caused by the growth in dairying.
4.2 Detailed results
4.2.1 Direct impacts
4.2 Detailed results
The direct
4.2.1
impacts
Direct
are
impacts
the gains of the dairy sector over the last decade. Figure 8
shows that the dairy sector grew substantially between 1998/99 and 2008/09. Milk
The direct impacts are the gains of the dairy sector over the last decade. Figure 8 shows
solids output
that the
increased
dairy sector grew
by
substantially
58%, use
between
of land
1998/99
grew
and
by
2008/09.
25%,
Milk
while
solids
total
output
factor
productivity increased remained by 58%, usepositive of land grewfor by 25%, most whileof total the factordecade, productivitybefore remaineddropping, positive
unsurprisingly, for most of during the decade, the drought before dropping, seasons. unsurprisingly, Productivity during growth the drought is likely seasons. to return to
positive Productivity trend levels growth now is likely that to more return‘normal’ to positiveclimatic trend levels conditions now that more have ‘normal’climatic returned. The
sector’s conditions employment have grew returned. by The around sector’s 7,500 employment FTEs. grew These by around gains 7,500 would FTEs. have These been gainslost
if dairy remaining would have stagnant been lost if at dairy 1998/99 remaining levels. stagnant at 1998/99 levels.
Figure 8 Dairy gains since 1998/99
Figure 8 Dairy gains since 1998/99
Source: Dairy NZ
Source: NZIER
4.2.2 Indirect impacts on other industries
4.2.2 Indirect impacts on other industries
A growing dairy sector indirectly impacts other industries. These indirect impacts can be split
A growing into dairy the following sector categories: indirectly impacts other industries. These indirect impacts can
be split into • Supplying the following industries categories: – industries that supply dairy with intermediate inputs are likely to
benefit from a stronger dairy sector. Both agricultural services and the fertilizer industry
• Supplying industries – industries that supply dairy with intermediate inputs are
achieve significant gains, up 0.9% and 4.2% in 2009 versus where they would have been
likely to benefit from a stronger dairy sector. Both agricultural services and the
had dairy not grown over the last decade.
fertilizer industry achieve significant gains, up 0.9% and 4.2% in 2009 versus
where • they Household would expenditure have been industries had dairy – industries not grown that households over the last spend decade.
money on are
likely to benefit from increased income that comes through employment and wages, and
increased returns to capital from a growing dairy sector. Retail trade and real estate are
both up: 0.5% and 0.7% respectively.
• Government industries – industries that rely on government funding are positively
NZIER – Dairy’s
impacted
role in
by
generating
a stronger economy
growth
22
and bigger tax takes, as this increases the money
available for the government to spend. Spending on hospitals, schools and police are up
0.6%, 0.7% and 0.2% respectively.
• Competing export industries – industries that compete for resources (such as land and
labour) with the dairy sector lose from dairy’s growth. Sheep and beef, in particular, grew
by 10% less, crowded out by the growth in dairying. Similarly, apple and pear and the
textiles industry both suffer from a higher currency that is a result of the growth in dairy.

Table 9 Indirect impacts 2008/09
Percentage deviation from BAU levels, selected industries
Industry Type Impact
Agricultural services Supplying 0.9%
Fertilizer Supplying 4.2%
Retail Household expenditure 0.5%
Real estate Household expenditure 0.7%
Residential property Household expenditure 0.9%
Schools Government 0.7%
Hospitals Government 0.6%
Police Government 0.2%
Apple and Pear Competing export -2.3%
Sheep and Beef Competing export -9.9%
Textiles Competing export -3.0%
Source: NZIER
4.2.3 Macroeconomic effects
The overall national result for the case study of the growth in the dairy sector over the last
decade, relative to a case where it stagnated at 1998/99 levels, is a real GDP gain of 0.37% by
2009, or around $690 million. The result is positive for NZ Inc because of:
• export, capital and productivity gains that accrued over the last decade within the dairy sector
• positive flow-on impacts to supplying industries, household expenditure industries, and
government funded industries.
The NEB/welfare gain for New Zealand, proxied by private and public consumption
(household and government spending respectively), is an increase of 0.8%. That represents a
gain of $1.1 billion of consumption in 2009, relative to BAU. The NEB result is greater than the
GDP gain for the same reasons given in section 3.2.3.
An alternative way to think about the gains from growth in dairy production is through
their cumulative effect. In each year there is an increase in consumption that is enjoyed
by consumers. So far, we have measured that by giving the gain in 2009 of $1.1 billion.
Examining instead the net present value (NPV) of the years’consumption gains gives a better
picture of the cumulative benefit to the nation. 11 From the point of view of 1999, the NPV
of the decade’s consumption growth to 2009 is $6.4 billion. That is to say the gains realised
from 1999-2009 are equivalent to the nation’s consumption increasing by $6.4 billion in 1999,
which would have been 4.3% of 1999’s total consumption.
The significant export gains from dairying reduce the ratio of New Zealand’s foreign debt to
GDP by over 1%. Together with the exchange rate appreciation, this saves the country $231
million in interest repayments on foreign debt. Across the decade, the NPV of the interest
savings from the viewpoint of 1999 total $1.2 billion.
These positive impacts are partially offset by crowding out of the sheep and beef and other
exporting industries that suffer from a currency appreciation, and the decreased availability
of resources (capital, labour and land). Our modelling captures the fact that land or labour not
being used by a growing dairy sector could have been used by other industries such as sheep
and beef. This dampens the impact of the growth in the dairy sector, but doesn’t fully offset it. 12
11. We use the Treasury’s preferred social discount rate of 8%pa.
12. We do not consider Crown costs associated with the increased greenhouse gas emissions resulting from dairy production. In our
modelling framework, if dairy had not grown since 1998/99, other sectors would have soaked up the spare resources (land, labour,
capital, energy, etc). These sectors would then have produced additional emissions. Ascertaining the net effect of this shift in
production is difficult.
Dairy’s role in generating growth
21

22 Dairy’s role in generating growth
The slight reduction in overall export volumes is a result of an increased terms of trade, which
allows New Zealand to export less quantity for more value.
Overall, a combination of higher output and higher exports means New Zealand is
fundamentally wealthier because of the growth in the dairy sector. In terms of the nation’s
overall productive capacity, labour and land are able to switch to alternative uses (and
therefore could have been used by alternative industries); however productivity and capital
gains during the growth of the dairy sector lead to an increase in New Zealand’s GDP.
Table 10 National results 2009
Real percentage deviation from BAU levels
Indicator Percentage change Levels change, $
millions
GDP 0.37 $690
Private Consumption 0.77 $860
Public Consumption 0.77 $290
Exports (volume) -0.13 -$66
Imports (volume) 0.95 $350
Real wage 0.92 n/a
Capital 0.61 n/a
Ratio foreign liabilities to GDP -1.04 -$231 (1)
Source: NZIER
(1) Change in interest repayments on foreign debt
4.2.4 Regional impacts
The regional results in Figure 9 show that the impacts of growth in the dairy sector are not
uniformly distributed across the country. Some of the benefits are distinctly regional: much of
the growth in dairying over the last decade has been in Canterbury and Southland. While this
has reduced land available for sheep and beef farming, the increased economic activity in the
form of exports, wages and employment leads to strong growth in these districts.
Northland and Waikato districts also benefit significantly from growth in the dairy industry.
Increases in government spending lead to a benefit to the Wellington regional economy,
while Hawkes Bay, which is home to a large fruit and horticulture sector, has been slightly
crowded out by the growth in the dairy sector.
The impacts of volume growth on per person consumption or living standards in each region
are shown in Table 11.

Figure 9 2009 Gross regional product impacts
Real percentage deviation from BAU levels
Figure 7 Gross regional product impacts
Real percentage deviation from BAU levels
Source: NZIER
Source: NZIER
Table 7 11 Increase in in gross regional product
Region
Region
Per person increase in GRP
Per person increase in GRP
Northland
Northland
Auckland
Auckland
Waikato
$170
-$4
$110
$8
$270
Waikato
Bay Of Plenty
$130
$84
Bay Gisborne Of Plenty $66
$74
Gisborne Hawkes Bay $100
-$100
Hawkes Taranaki Bay $39
$140
Taranaki Manawatu-Wanganui $160
$120
Manawatu-Wanganui Wellington $140
$160
Wellington Tasman-Nelson $140
$12
Marlborough
Tasman-Nelson $12
-$4
West Coast
Marlborough
Canterbury
West Coast
Otago
$54
$69
$7
$590
$39
Canterbury
Southland
$41
$650
Otago $82
Source: NZIER
Southland $68
Source: NZIER
NZIER – Dairy’s role in generating growth
Final report - 16 November 2010
Dairy’s role in 19 generating growth
23

24 Dairy’s role in generating growth
5. Conclusion
Our modelling shows that the dairy sector has delivered significant and ongoing benefits to
the New Zealand economy. Two historical case studies, based on events of the last decade,
illustrate how tangible and widely known changes to the dairy sector have flowed through
to the rest of the economy. Volume and price growth in the sector has delivered benefits
to a wide range of sectors outside of the dairy industry, and has generated living standard
improvements across New Zealand’s regional economies, including in metropolitan areas
such as Auckland and Wellington.

Appendix A CGE modelling framework
A.1 The MONASH-New Zealand CGE model: overview
The MONASH-NZ dynamic CGE model contains information on 131 industries and 210
commodities in its basic form. CGE modelling is a highly-respected and well-developed
technique that has a rich history for assessing policy, regional and industry questions. Our
model was developed in close collaboration with Monash University, a global leader in
building and applying CGE models. It captures the various inter-linkages between these
sectors, as well as their links to households (via the labour market), the government sector,
capital markets and the global economy (via imports and exports). A visual representation is
shown in Figure 10 highlighting the complex and multidirectional relationships between the
various parts of an economy.
For this study we have calibrated the dairy industry in our database to match the aggregate
dairy industry figures provided by Fonterra and Dairy NZ. More technical detail on the model
is presented below.
The model also includes a regional component. A ‘top-down’approach is used to
decompose national impacts to the regional level, using regional employment data as
weighting. If a region has a high share of national output, then its regional industry output
will be proportionally affected. The exception is industries that produce commodities
(mostly services) that are largely consumed within a region. These are deemed to be local
industries, and it is assumed that their output moves in line with the local demand for the
corresponding commodity, rather than with the national industry output. Final This report captures - 16 November 2010
“regional multiplier”effects: spending within a region specifically benefits services with that
region (Horridge, 2008).
Figure 10 Components of a CGE model
Figure 10 Components of a CGE model
Source: NZIER
A.2 Dynamics of the MONASH-NZ model
Dairy’s role in generating growth
MONASH-NZ is a recursive dynamic CGE model based on the ORANI-NZ core. It
25

26 Dairy’s role in generating growth
A.2 Dynamics of the MONASH-NZ model
MONASH-NZ is a recursive dynamic CGE model based on the ORANI-NZ core. It can be
thought of as a series of static simulations linked by three dynamic adjustment procedures.
Each year’s simulation takes the final database of the previous year’s simulation as its starting
point and applies the current period’s shocks. Because the solution for the current period
depends only on the previous period’s solution and the current period’s shocks, it can be
solved recursively, rather than having to solve all periods simultaneously. Economists might
refer to this sort of model as having adaptive, rather than rational, expectations formation.
In addition to solving a ‘static’problem in each period, the MONASH-NZ model improves
upon ORANI-NZ simulations by adding three dynamic adjustment processes:
• Labour market adjustment: We assume that wages are sticky in the short run and
gradually adjust over time. A mechanism in the model allows employment to first
respond to increases in aggregate demand and then return to the NAIRU over time as
wages adjust.
• Capital formation: An industry-specific capital accumulation mechanism allows industries
to build their stock of capital over time. Capital is generated by investment, which in turn
responds to rates of return in each industry.
• Balance of payments adjustment: The model tracks changes in the current account and
capital account over time. Changes in net foreign liabilities affect domestic consumption
through the level of interest that must be paid to service the foreign debt.
A.3 Database structure
The model is based on a large database containing the value flows of the economy, as per
Figure 11. The database defines the initial structure of the economy, which by definition is
assumed to be in equilibrium in all markets. The structure of the database is broadly similar
to traditional input-output tables; for example commodities may be used as intermediate
input for further production, utilised in investment, exported or consumed by households
and the government. Industry costs include the cost of intermediates, margins, taxes and
primary factor costs for labour, land and capital. As per the accounting identities in inputoutput
tables, the total value sum of producers’input costs (including margins, taxes, returns
to factors and other costs) equates to the total value of output production (the ‘MAKE’matrix
in the database).
The MONASH-NZ model consists of:
• 131 industries
• 210 commodities
• 14 regions
• 1 household
• 24 occupations
The database has been sourced initially from Statistics New Zealand 1995/96 Inter-Industry
tables, updated using the subsequently released 2003 Supply and Use tables, and finally ‘upscaled’to
2007 levels using latest Statistics New Zealand macroeconomic data.

Figure 11 The MONASH-NZ database
Figure 11 The MONASH-NZ database
Basic
Flows
Margins
Taxes
Labour
Capital
Land
Production
Tax
Other
Costs
Source: Horridge, 2008b NZIER
NZIER – Dairy’s role in generating growth
Final report - 16 November 2010
Absorption Matrix
1 2 3 4 5 6
Producers Investors Household Export
Change in
Government
Inventories
Size
↑
← I → ← I → ← 1 → ← 1 → ← 1 → ← 1 →
C×S
↓
↑
V1BAS V2BAS V3BAS V4BAS V5BAS V6BAS
C×S×M
↓
↑
V1MAR V2MAR V3MAR V4MAR V5MAR n/a
C×S
↓
V1TAX V2TAX V3TAX V4TAX V5TAX n/a
↑
O V1LAB
C = 210 Commodities
↓
I = 131 Industries
↑
1 V1CAP
S = 2: Domestic, Imported
↓
O = 24 Occupation Types
↑
1
↓
↑
V1LND
M = 5 Commodities used as Margins
1
↓
↑
V1PTX
1
↓
V1OCT
Joint Production
Matrix
Import Duty
Size ← I → Size ← 1 →
↑
C
↓
MAKE
Source: Horridge, 2008b; NZIER
↑
C
↓
V0TAR
A.4 Production structure (Horridge, 2008b)
The production structure of the model is presented in Figure 12. Each industry can
produce a number of different commodities. Production inputs are intermediate
commodities, both domestic and imported, and primary factors labour, land and
capital. Working from bottom to top, we see constant elasticity of substitution (CES)
production nests for occupations, primary factors and the choice between imported
and domestic commodities. In this case, an increase in price moves sourcing
towards another input, for example, if the price of imports increases, more domestic
commodities are demanded in the intermediate sourcing CES nest.
31
Dairy’s role in generating growth
27

A.4 Production structure (Horridge, 2008b)
The production structure of the model is presented in Figure 12. Each industry can produce
a number of different commodities. Production inputs are intermediate commodities, both
domestic and imported, and primary factors labour, land and capital. Working from bottom
to top, we see constant elasticity of substitution (CES) production nests for occupations,
primary factors and the choice between imported and domestic commodities. Final report - In 16 this November 2010
case, an increase in price moves sourcing towards another input, for example, if the price of
imports increases, more domestic commodities are demanded in the intermediate sourcing
CES nest.
Figure Figure 12 12 Production structure
Source: Horridge, 2008
Source: Horridge, 2008
At the activity level, intermediate goods, primary factors and other costs are
combined using a Leontief production function. This means the proportion of
production inputs does not change. On the output side, there are two further
constant elasticity of transformation (CET)
28 Dairy’s role in generating growth
13 nests. The production mix of each
industry is dependent on the relative prices of each commodity. Similarly, the export

At the activity level, intermediate goods, primary factors and other costs are combined
using a Leontief production function. This means the proportion of production inputs does
not change. On the output side, there are two further constant elasticity of transformation
(CET) 13 nests. The production mix of each industry is dependent on the relative prices of each
commodity. Similarly, the export nest determines local and export market shares depending
on relative prices.
A.5 Regional extension
Policy impacts are often unevenly spread across industries and regions. To capture these
heterogeneous effects, the model is extended to include a regional component. A ‘topdown’approach
is used to decompose national impacts to the regional level, using regional
employment data as weighting. If a region has a high share of national output, then its
regional industry output will be proportionally affected. The exception is industries that
produce commodities (mostly services) that are largely consumed within a region. These are
deemed to be local industries, and it is assumed that their output moves in line with the local
demand for the corresponding commodity, rather than with the national industry output.
Note that an inherent assumption in the ‘top-down’approach is that industries use the same
production technology across all regions (Horridge, 2008).
13. A CET function is identical to a CES function except that the transformation parameter has the opposite sign (i.e. increasing price
increases output in a CET; in a CES, increasing price reduces demand)
Dairy’s role in generating growth
29

30 Dairy’s role in generating growth
Appendix B CGE and multiplier analysis
Many studies attempt to quantify the economic contribution of a certain sector or
project using input-output (IO) multipliers. This is a technique that NZIER (and many other
consultancies) has used in the past.
Despite their popularity, IO models have a number of significant drawbacks.
The primary issue with IO models is that they assume that supply is unconstrained. That is,
inputs such as labour, capital and land are always available for expanding a sector. There is no
recognition of the reality that resources used in one part of the economy are not available for
use elsewhere. Labour and capital are unconstrained and available at a constant price in an IO
framework. That is important because they are also assumed to be used in fixed proportions.
Hence an IO model excludes any consideration of substitutability between factors of
production.
Furthermore, since IO models exclude prices, they also assume that supply is perfectly elastic.
This means that no matter how much labour (for example) is used, there is no change in
wages. The consequence is that they exclude all supply constraints, rigidities and price
effects, leading to unrealistically large shifts in resource use and economic activity.
The absence of substitution effects also extends to demand. There is no substitution between
different goods as incomes rise. Rather, consumption is assumed to rise linearly with incomes
and the proportion of different goods consumed remains constant. In reality, as incomes rise,
people tend to buy relatively more luxuries and fewer necessities, and more services (such as
tourism).
IO models also exclude a treatment of exports and imports. Imports do not compete with
domestic goods and exports are exogenously determined. Neither depends on prices, since
relative prices cannot change.
Among the other drawbacks, savings are fixed as a proportion of incomes, so financial
markets are not included in the model. Technology is exogenous so technological progress
cannot be modelled. This reflects the static nature of the model, which has no dynamic (time)
element to it. The lack of explicit dynamics is problematic for a model which seeks to capture
the change in industry flows over time.
As a consequence of the limitations outlined above, IO multipliers tend to systematically
overestimate the true ripple effects and provide an unjustifiably rosy picture of the economic
impacts of a project. This is particularly the case for employment multipliers (Mules, 1999).
IO models are only appropriate for circumstances where there are no supply constraints
and demand considerations completely dominate the analysis (Bandara, 1991). This set of
circumstances may hold in small regional economies (Dwyer et al, 2005). In such economies
factor and commodity flows from outside the region tend to be very free. If the region is
small enough then relative prices can safely be regarded as exogenous, which allows IO
models to be safely used so long as the assumptions and deficiencies are recognised.
CGE models explicitly address many of the shortcomings in IO analysis. They allow resources
to move between sectors in response to a shock, and the demand and supply of goods and
factors respond to relative prices. CGE models tend to produce smaller economic impacts
than IO models, primarily because they consider the opportunity costs of the expansion (or
contraction) of a sector.
It is helpful to consider an illustrative example of how IO multipliers compare to CGE
estimates. A comparative assessment of CGE and IO multipliers was carried out for the
regional and national impact of the Australian leg of the Formula 1 Grand Prix circuit. The
2005 analysis of the 2000 Grand Prix resulted in the multipliers reported in Table 12.

Table 12 IO vs. CGE multipliers
Multiplier values
IO model CGE model
Regional National Regional National
Output multiplier 2.2 2.3 1.2 0.9
Value added multiplier 0.8 0.8 0.4 0.3
Employment multiplier 10.2 11.6 6.2 2.5
Source: Dwyer et al (2005)
As expected, the CGE multipliers are far lower than the IO multipliers, primarily due to the
price and resource constraints included in the CGE model. The CGE estimates in this study are
between 20% and 55% of the IO multipliers. Such differences are not unusual in the literature.
CGE models are a significant improvement on the previous generation of IO models,
particularly when estimating the nationwide or regional effects of projects which are likely
to have significant price effects. Indeed, CGE modelling has become one of the most widely
used tools for economic policy analysis over the past three decades. Today, the leading CGE
modelling institutions are the World Bank, the International Food Policy Research Institute
(IFPRI) and the Centre of Policy Studies at Monash University (CoPS). Much of the World Bank’s
economic assessment of trade and environmental impacts is conducted using their LINKAGE
and Env-LINKAGE CGE models. CoPS has done extensive work advising the government in
Australia using their CGE models. Variants of their models are used in over 400 organisations
in over 70 countries.
The widespread usage and acceptance of CGE results over the last thirty years reinforces the
view taken in the literature that it is now the best method available for analysing the impact
of economy-wide shocks.
14. For example, Dixon, Parmenter and Rimmer (2000); Adams et al (1994); Dixon, Picton, and Rimmer (2005), Dixon, Madden, and Peter
(1993); Dixon and Rimmer (1999).
15. GEMPACK homepage http://www.monash.edu.au/policy/gempack.htm
Dairy’s role in generating growth
31

32 Dairy’s role in generating growth
Appendix C Limitations of analysis
• Aggregation bias. We have not split out the dairy sector, but use aggregated dairy
farming and dairy processing industries. This leads to aggregation bias. For example,
irrigated and non-irrigated farming practices and industry structures are likely to be quite
different, and at present this is not captured within our modelling. Given adequate time,
the model can be disaggregated to more accurately model the specific dairy sector.
• Foreign debt accounting. We employ a standard ‘MONASH’method for accounting for
the foreign debts – changes in net foreign liabilities come about if our investment is not
met by domestic savings. We pay interest on foreign debt that is subtracted from national
income. The interest, in foreign currency, is converted to domestic currency by the
exchange rate. In this simulation, the exchange rate appreciation leads to a decrease in
the domestic currency value of the interest repayments. It could be argued that much of
the interest on this foreign debt is likely to be dividend payments on equity. In this case,
the appreciation of the exchange rate should not decrease overseas payments.
• ‘Top-down’ regional modelling. Regional data is by far the most difficult data to obtain
across the diverse range of industries and commodities that we have incorporated within
our model. ‘Bottom-up’regional modelling provides a clearer picture of regional activity
and in-particular cross-region flows, however requires significant data resources. The topdown
approach here provides indicative regional splits.
• Model structure. The CGE model is based on Statistics New Zealand Input Output tables,
with decisions based on neoclassical economics. Structural changes to the economy from
the reforms are therefore not captured in the modelling, nor are any non-competitive
market structures. This means the distributional elements of the results may differ in
reality if firms with market power do not pass on benefits.

Appendix D References
Bandara, J. S. (1991). ‘Computable General Equilibrium Models for Development Policy
Analysis in LDCs’. Journal of Economic Surveys 5, no. 1 (1991): 3-69.
Coleman, W. (2008). ‘Gauging economic performance under changing terms of trade: real
gross domestic income or real gross domestic product?’ Economic Papers, Vol. 27 no.4,
December 2008, pp. 329-343.
Dixon, P. B., J. R. Madden, and M. W. Peter. (1993). ‘The effects of reallocating general revenue
assistance among the Australian states’. Economic Record 69, no. 207 (1993): 367–381.
Dixon, P. B., and B. R. Parmenter. (1996). ‘Computable general equilibrium modelling for policy
analysis and forecasting’. Handbook of computational economics 1 (1996): 3–85.
Dixon, P. B., B. R. Parmenter, and M. T. Rimmer. (2000). ‘Forecasting and policy analysis with a
dynamic CGE model of Australia’. Contributions to Economic Analysis 248 (2000): 363–406.
Dixon, P. B, M. R Picton, and M. T Rimmer. (2005). ‘Efficiency effects of changes in
Commonwealth grants to the states: A CGE analysis’. Australian Economic Papers 44, no. 1
(2005): 82–104.
Dixon, P. B., and M. T Rimmer. (1999). ‘Changes in indirect taxes in Australia: A dynamic general
equilibrium analysis’. The Australian Economic Review 32, no. 4 (1999): 327–348.
Dwyer, L, P. Forsyth, and R. Spurr. (2005). “Estimating the Impacts of Special Events on an
Economy’. Journal of Travel Research 43, no. 4 (May 1, 2005): 351-359. http://jtr.sagepub.com/
cgi/content/abstract/43/4/351
Horridge, 2008. ‘Orani-G: A generic single-country computable general equilibrium model’.
CopS/IMPACT Working Paper op-93; Centre of Policy Studies, Monash University. First
Published 2000. Revised 2008.
Mules, T. (1999). ‘Estimating the economic impact of an event on a local government area,
region, state or territory’. Valuing tourism: Methods and techniques.
NZIER. (2003). Globalisation a New Zealand perspective. CEDA chapter March 2003.
Dairy’s role in generating growth
33

Appendix E Dairy employment statistics
Farming
Milk & cream Ice cream Cheese
Total dairy Total dairy Total regional Dairy as % Region as % of
employment processing processing processing & processing employment employment of regional total NZ dairy
employment employment other dairy employment
employment employment
employment
South Taranaki 1,450 0 0 1,570 1,570 3,020 11,675 25.9% 8.9%
District
Matamata-Piako 1,260 0 0 1,130 1,130 2,390 13,306 18.0% 7.1%
District
Southland 1,980 0 0 390 390 2,370 15,651 15.1% 7.0%
District
Waipa District 1,050 0 3 420 423 1,473 14,991 9.8% 4.4%
Timaru District 530 0 0 650 650 1,180 21,151 5.6% 3.5%
Ashburton 1,180 0 0 0 0 1,180 14,423 8.2% 3.5%
District
Whakatane 600 0 0 550 550 1,150 12,285 9.4% 3.4%
District
South Waikato 740 0 0 270 270 1,010 7,722 13.1% 3.0%
District
Waikato District 920 0 0 0 0 920 12,160 7.6% 2.7%
Whangarei 510 0 0 400 400 910 30,341 3.0% 2.7%
District
Selwyn District 850 9 0 40 49 899 12,136 7.4% 2.7%
Manawatu 540 210 0 140 350 890 8,660 10.3% 2.6%
District
Clutha District 680 0 0 150 150 830 8,440 9.8% 2.5%
Hamilton City 50 50 0 720 770 820 75,536 1.1% 2.4%
Rotorua District 570 0 0 180 180 750 29,341 2.6% 2.2%
Kaipara District 580 0 0 130 130 710 5,445 13.0% 2.1%
Tararua District 520 0 0 180 180 700 5,924 11.8% 2.1%
Otorohanga 610 0 0 0 0 610 3,227 18.9% 1.8%
District
Taupo District 600 0 0 0 0 600 14,291 4.2% 1.8%
Rangitikei District 280 0 0 290 290 570 5,926 9.6% 1.7%
34 Dairy’s role in generating growth

Farming
Milk & cream Ice cream Cheese
Total dairy Total dairy Total regional Dairy as % Region as % of
employment processing processing processing & processing employment employment of regional total NZ dairy
employment employment other dairy employment
employment employment
employment
New Plymouth 560 0 0 6 6 566 34,711 1.6% 1.7%
District
Waitaki District 460 0 0 75 75 535 9,410 5.7% 1.6%
Westland District 270 0 0 240 240 510 3,730 13.7% 1.5%
Waimate District 410 0 0 60 60 470 2,242 21.0% 1.4%
Western Bay of 460 0 0 6 6 466 13,868 3.4% 1.4%
Plenty District
Tasman District 340 0 12 110 122 462 18,146 2.5% 1.4%
Hauraki District 450 0 0 0 0 450 5,382 8.4% 1.3%
Far North District 420 0 0 9 9 429 18,641 2.3% 1.3%
Papakura District 20 140 0 250 390 410 15,071 2.7% 1.2%
Dunedin City 130 270 9 0 279 409 55,662 0.7% 1.2%
Horowhenua 370 0 0 0 0 370 8,293 4.5% 1.1%
District
Franklin District 330 15 0 18 33 363 18,581 2.0% 1.1%
Auckland City 3 9 320 25 354 357 307,312 0.1% 1.1%
Hurunui District 330 0 0 0 0 330 4,100 8.0% 1.0%
Buller District 330 0 0 0 0 330 4,475 7.4% 1.0%
Waimakariri 300 0 0 15 15 315 10,457 3.0% 0.9%
District
Christchurch City 40 210 12 45 267 307 188,948 0.2% 0.9%
Stratford District 300 0 0 0 0 300 2,882 10.4% 0.9%
Palmerston 80 110 0 85 195 275 45,355 0.6% 0.8%
North City
Gore District 260 0 0 0 0 260 6,500 4.0% 0.8%
South Wairarapa 250 0 0 0 0 250 2,967 8.4% 0.7%
District
Rodney District 210 0 0 40 40 250 23,146 1.1% 0.7%
Grey District 200 0 0 0 0 200 7,048 2.8% 0.6%
Waitomo District 200 0 0 0 0 200 4,365 4.6% 0.6%
Kapiti Coast 50 0 0 130 130 180 11,852 1.5% 0.5%
District
Dairy’s role in generating growth
35

Farming
Milk & cream Ice cream Cheese
Total dairy Total dairy Total regional Dairy as % Region as % of
employment processing processing processing & processing employment employment of regional total NZ dairy
employment employment other dairy employment
employment employment
employment
Central Hawke’s 180 0 0 0 0 180 5,925 3.0% 0.5%
Bay District
Opotiki District 180 0 0 0 0 180 3,003 6.0% 0.5%
Invercargill City 140 15 12 9 36 176 26,151 0.7% 0.5%
Hastings District 120 0 0 35 35 155 41,110 0.4% 0.5%
Manukau City 30 0 90 35 125 155 127,635 0.1% 0.5%
North Shore City 0 0 65 85 150 150 86,346 0.2% 0.4%
Marlborough 130 0 0 3 3 133 23,976 0.6% 0.4%
District
Carterton District 130 0 0 0 0 130 2,694 4.8% 0.4%
Thames- 100 0 0 9 9 109 9,625 1.1% 0.3%
Coromandel
District
Kaikoura District 75 0 0 25 25 100 1,656 6.0% 0.3%
Wanganui 75 0 0 0 0 75 18,001 0.4% 0.2%
District
Gisborne District 50 0 0 25 25 75 20,196 0.4% 0.2%
Masterton 55 0 0 3 3 58 10,437 0.6% 0.2%
District
Central Otago 50 0 0 0 0 50 10,757 0.5% 0.1%
District
Ruapehu District 40 0 0 0 0 40 5,994 0.7% 0.1%
Mackenzie 35 0 0 0 0 35 1,886 1.9% 0.1%
District
Tauranga City 12 0 0 12 12 24 48,791 0.0% 0.1%
Nelson City 12 0 9 0 9 21 24,656 0.1% 0.1%
Wairoa District 18 0 0 0 0 18 3,586 0.5% 0.1%
Lower Hutt City 0 0 0 6 6 6 44,927 0.0% 0.0%
Waitakere City 0 0 3 0 3 3 46,742 0.0% 0.0%
36 Dairy’s role in generating growth

Farming
Milk & cream Ice cream Cheese
Total dairy Total dairy Total regional Dairy as % Region as % of
employment processing processing processing & processing employment employment of regional total NZ dairy
employment employment other dairy employment
employment employment
employment
Area Outside 0 0 0 0 0 0 33 0.0% 0.0%
Territorial
Authority
Queenstown- 0 0 0 0 0 0 15,353 0.0% 0.0%
Lakes District
Chatham Islands 0 0 0 0 0 0 310 0.0% 0.0%
Territory
Wellington City 0 0 0 0 0 0 137,966 0.0% 0.0%
Upper Hutt City 0 0 0 0 0 0 11,395 0.0% 0.0%
Porirua City 0 0 0 0 0 0 15,401 0.0% 0.0%
Napier City 0 0 0 0 0 0 25,940 0.0% 0.0%
Kawerau District 0 0 0 0 0 0 2,924 0.0% 0.0%
Total (excl not 23,705 1,038 535 8,571 10,144 33,849 1,919,197 1.8% 100.0%
elsw incl)
Source: Calculated by NZIER from Department of Labour, ‘Regional Industry Tool 2009’http://www.dol.govt.nz/services/LMI/tools/regional-industry-tool.asp
Dairy’s role in generating growth
37

38 Dairy’s role in generating growth
Appendix F Value of regional dairy production
Southland $ 710.35
South Taranaki $ 616.56
Matamata-Piako $ 552.12
Ashburton $ 471.11
Waikato $ 389.91
Waipa $ 361.00
Selwyn $ 269.91
South Waikato $ 262.53
Rotorua $ 253.55
Otorohanga $ 234.54
New Plymouth $ 206.31
Hauraki $ 196.40
Tararua $ 188.28
Timaru $ 185.13
Clutha $ 181.72
Kawerau/Whakatane $ 180.33
Manawatu $ 174.45
Taupo $ 172.00
Kaipara $ 167.59
Whangarei $ 159.00
Waitaki $ 146.93
Gore $ 144.88
Waimate $ 143.14
Western Bay of Plenty $ 116.78
Stratford $ 116.45
Franklin $ 112.07
Hurunui $ 106.17
Far North $ 106.08
Tasman / Nelson $ 101.73
Westland $ 97.06
Waimakariri $ 94.65
Horowhenua $ 87.16
Buller $ 85.02
Rangitikei $ 74.10
Grey $ 71.19
Rodney $ 70.08
South Wairarapa $ 69.68
Invercargill $ 67.21
Dunedin City $ 49.74
Central Hawkes Bay $ 49.13
Opotiki $ 43.54
Thames-Coromandel $ 39.93
Waitomo $ 39.87
Carterton $ 38.01
Marlborough $ 31.99
Palmerston North City $ 27.97
Napier $ 23.66
Kaikoura $ 19.69
Ruapehu $ 18.72
MacKenzie $ 16.24
Masterton $ 16.12
Wanganui $ 14.94
Central Otago $ 14.29
Christchurch City $ 11.17
Kapiti Coast $ 10.12
Hamilton City $ 7.76
Manukau City $ 6.53
Wairoa $ 4.72
Tauranga $ 4.72
Hastings $ 4.64
Banks Peninsula $ 3.82
Gisborne $ 2.84
Upper Hutt City $ 1.40
Papakura $ 1.38
North Island $ 5,217.92
South Island $ 2,993.32
New Zealand $ 8,090.98

Appendix G Changing dairy export markets
Final report - 16 November 2010
Appendix G Changing dairy export markets
Figure 13 Changing markets for New Zealand’s dairy exports
% of export value
Figure 13 Changing markets for New Zealand’s dairy exports
% of export value
1989
2009
Source: NZIER
Source: NZIER
NZIER – Dairy’s role in generating growth
44
Dairy’s role in generating growth
39