Dairy s role in sustaining New Zealand

Transcription

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

2 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 form, and at the right time, for our clients. We ensure quality through teamwork on individual 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 Authorship Prepared by: Chris Schilling, James Zuccollo and Chris Nixon Quality approved by: John Ballingall Date: Version: 15/11/2010 3:49 PM Final Acknowledgements:

3 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 C

4 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. D

5 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. E

6 Figure 1 F

7 Contents 1. The current contribution of dairy Purpose of report Direct contribution to GDP Contribution to regional incomes Contribution to export performance Contribution to Balance of Payments Contribution to Contribution to other sectors performance Supply chain Dairy farming Dairy processing 7 2. Modelling dairy s economic contribution over the past decade Objective of modelling Modelling technique Advantages of CGE modelling Modelling scenarios Scenario 1: The price of milk solids Scenario 2: The growth of dairying over the past decade How we analyse the modelling results Milk solids price spike Headline results Detailed results Direct effects: the dairy sector Indirect impact on other industries Macroeconomic effects Regional impacts Production growth over the last decade Headline results Detailed results Direct impacts Indirect impacts on other industries Macroeconomic effects Regional impacts Conclusion 24 G

8 Appendices Figures Tables 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 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 5 Figure 4 Model structure of the sector 6 Figure 5 Change in milk solids price: Figure 6 Processed milk solids 11 Figure 7 Gross regional product impacts 17 Figure 8 Dairy gains since 1998/99 21 Figure 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 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 Table 11 Increase in gross regional product 23 Table 12 IO vs. CGE multipliers 31 H

9 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 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 1

10 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 South Taranaki Matamata-Piako Ashburton Waikato Waipa Selwyn South Waikato Rotorua Otorohanga New Plymouth Hauraki Tararua Timaru Clutha Notes: Source: (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 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. 2

11 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, Wood products 2, Mineral fuels 1, Fruit & nuts 1, Machinery parts 1, Fish 1, Miscellaneous 1, Wine & other beverages 1, Aluminium Electrical machinery Precious metals & stones Wool Wood pulp Iron & steel Optical & medical equipment Paper & paperboard Vegetables Plastics Hides & skins Notes: (1) Source: Dairy NZ, Fonterra, NZIER 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 Annual average growth in export values, Source: Statistics New Zealand, NZIER 3

12 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 National The dairy sector in New Zealand is a major employer, and is vital for a number of districts. On-farm 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 does not reach the 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 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. 4

13 Figure 3 Importance of dairy to regional Dairy farm and processing jobs as % of total in region Source: DoL, NZIER A complete table of dairy statistics for each of New Zealand s 74 Territorial Local Authorities is contained in Appendix E. 1.7 Contribution to other sectors performance 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 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 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 (e.g. stock and other sales) is included in the modelling but not singled out in the reporting. 5

14 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 Dairy farming The structure of the farming industry is shown in Table 3. The farming sector produced around $7.5 billion 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 farm s costs. The on-farm sector employs around 24,000 full time equivalent (FTE) workers. The primary cashflow costs for farmers are fertiliser for the land and feed for the animals. These two industries are heavily affected by movements in demand for milk products. We can break down the $7.5 billion of raw milk into the following parts: $3.0 billion is retained as returns to land, labour and capital. $3.6 billion is spent on domestically produced intermediate inputs, such as fertilizer ($447 million), straw and feed ($723 million), agricultural services ($446 million), financial services ($341 million), machinery repairs ($198 million) and petrol/diesel ($80 million). $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. 6

15 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 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 7

16 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. 8

17 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, 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 9

18 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 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? 10

19 Figure 5 Change in milk solids price: $ per kg, prices $ per kg, prices Source: Dairy NZ Scenario 2: The growth of dairying over the past decade Over the last 10 years the dairy sector has grown significantly, increasing milk solid production by 58% between 1998/89 and 2008/09. In this case study, we ask the questions: what if it hadn t grown? and what would the economy have missed out on if dairy had stagnated at 1999 production levels? The factual is the actual volume path as it occurred; the counterfactual is volumes remaining at 1998/99 levels, as per Figure 6. Figure 6 Processed milk solids Million kgs Source: Dairy Statistics 2008/09 11

20 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 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 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. 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. 12

21 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 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 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 by 20%. Investment in the processing component of the industry grows by 14% and by 5.5%, relative to what would otherwise have occurred. Investment growth is higher than growth because capital accumulation tends to lag behind 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 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. 13

22 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 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. 14

23 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 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: 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). 15

24 The increased production in dairy draws in more labour, which is shown by the rise in. Note however that, in our modelling, 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 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. 16

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

26 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, Less farm working expenses 475, Cash Operating Surplus 365, Less Interest and rent 185, Tax 35, Drawings 85, Cash available for development/ 60, investment/debt repayment 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. 18

27 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 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 % 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. 19

28 4.2 Detailed results Direct impacts The direct impacts are 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 solids output increased by 58%, use of land grew by 25%, while total factor productivity remained positive for most of the decade, before dropping, unsurprisingly, during the drought seasons. Productivity growth is likely to return to positive trend levels now that more normal climatic conditions have returned. The sector s grew by around 7,500 FTEs. These gains would have been lost if dairy remaining stagnant at 1998/99 levels. Figure 8 Dairy gains since 1998/99 Figure 8 Dairy gains since 1998/99 Source: NZIER Indirect impacts on other industries A growing dairy sector indirectly impacts other industries. These indirect impacts can be split into the following categories: Supplying industries industries that supply dairy with intermediate inputs are likely to benefit from a stronger dairy sector. Both agricultural services and the fertilizer industry achieve significant gains, up 0.9% and 4.2% in 2009 versus where they would have been had dairy not grown over the last decade. Household expenditure industries industries that households spend money on are likely to benefit from increased income that comes through 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 impacted by a stronger economy 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. 20

29 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 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 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 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 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. 21

30 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) $66 Imports (volume) 0.95 $350 Real wage 0.92 n/a Capital 0.61 n/a Ratio foreign liabilities to GDP $231 (1) Source: NZIER (1) Change in interest repayments on foreign debt 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 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

31 Figure Gross regional product impacts Real percentage deviation from BAU levels Real percentage deviation from BAU levels Source: NZIER Source: NZIER Table 11 Increase in gross regional product Region Per person increase in GRP Northland $110 Auckland $8 Waikato $270 Bay Of Plenty $84 Gisborne $74 Hawkes Bay -$100 Taranaki $140 Manawatu-Wanganui $120 Wellington $160 Tasman-Nelson $12 Marlborough -$4 West Coast $7 Canterbury $590 Otago $39 Southland $650 Source: NZIER 23

32 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. 24

33 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 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. This captures 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 25

34 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 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. 26

35 Figure 11 The MONASH-NZ database Basic Flows Margins Taxes Labour Capital Land Production Tax Other Costs Absorption Matrix Producers Investors Household Export Government Change in Inventories Size I I 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 C V0TAR Source: Horridge, 2008b NZIER 27

36 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. Figure 12 Production structure e: Horridge, 2008 Source: Horridge,

37 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 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) 29

38 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 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

39 Table 12 IO vs. CGE multipliers Multiplier values IO model CGE model Regional National Regional National Output multiplier Value added multiplier Employment multiplier 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 31

40 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. 32

41 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): 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 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): Dixon, P. B., and B. R. Parmenter. (1996). Computable general equilibrium modelling for policy analysis and forecasting. Handbook of computational economics 1 (1996): 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): 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): 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): 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): cgi/content/abstract/43/4/351 Horridge, Orani-G: A generic single-country computable general equilibrium model. CopS/IMPACT Working Paper op-93; Centre of Policy Studies, Monash University. First Published Revised 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

42 Appendix E Dairy statistics South Taranaki District Matamata-Piako District Southland District Farming Milk & cream processing Ice cream processing Cheese processing & other dairy Total dairy processing Total dairy Total regional Dairy as % of regional 1, ,570 1,570 3,020 11, % 8.9% 1, ,130 1,130 2,390 13, % 7.1% 1, ,370 15, % 7.0% Waipa District 1, ,473 14, % 4.4% Timaru District ,180 21, % 3.5% Ashburton 1, ,180 14, % 3.5% District Whakatane ,150 12, % 3.4% District South Waikato ,010 7, % 3.0% District Waikato District , % 2.7% Whangarei , % 2.7% District Selwyn District , % 2.7% Manawatu , % 2.6% District Clutha District , % 2.5% Hamilton City , % 2.4% Rotorua District , % 2.2% Kaipara District , % 2.1% Tararua District , % 2.1% Otorohanga , % 1.8% District Taupo District , % 1.8% Rangitikei District , % 1.7% Region as % of total NZ dairy 34

43 New Plymouth District Farming Milk & cream processing Ice cream processing Cheese processing & other dairy Total dairy processing Total dairy Total regional Dairy as % of regional , % 1.7% Waitaki District , % 1.6% Westland District , % 1.5% Waimate District , % 1.4% Western Bay of , % 1.4% Plenty District Tasman District , % 1.4% Hauraki District , % 1.3% Far North District , % 1.3% Papakura District , % 1.2% Dunedin City , % 1.2% Horowhenua , % 1.1% District Franklin District , % 1.1% Auckland City , % 1.1% Hurunui District , % 1.0% Buller District , % 1.0% Waimakariri , % 0.9% District Christchurch City , % 0.9% Stratford District , % 0.9% Palmerston , % 0.8% North City Gore District , % 0.8% South Wairarapa , % 0.7% District Rodney District , % 0.7% Grey District , % 0.6% Waitomo District , % 0.6% Kapiti Coast , % 0.5% District Region as % of total NZ dairy 35

44 Central Hawke s Bay District Farming Milk & cream processing Ice cream processing Cheese processing & other dairy Total dairy processing Total dairy Total regional Dairy as % of regional , % 0.5% Opotiki District , % 0.5% Invercargill City , % 0.5% Hastings District , % 0.5% Manukau City , % 0.5% North Shore City , % 0.4% Marlborough , % 0.4% District Carterton District , % 0.4% Thames , % 0.3% Coromandel District Kaikoura District , % 0.3% Wanganui , % 0.2% District Gisborne District , % 0.2% Masterton , % 0.2% District Central Otago , % 0.1% District Ruapehu District , % 0.1% Mackenzie , % 0.1% District Tauranga City , % 0.1% Nelson City , % 0.1% Wairoa District , % 0.1% Lower Hutt City , % 0.0% Waitakere City , % 0.0% Region as % of total NZ dairy 36

45 Area Outside Territorial Authority Queenstown- Lakes District Chatham Islands Territory Farming Milk & cream processing Ice cream processing Cheese processing & other dairy Total dairy processing Total dairy Total regional Dairy as % of regional % 0.0% , % 0.0% % 0.0% Wellington City , % 0.0% Upper Hutt City , % 0.0% Porirua City , % 0.0% Napier City , % 0.0% Kawerau District , % 0.0% Total (excl not 23,705 1, ,571 10,144 33,849 1,919, % 100.0% elsw incl) Region as % of total NZ dairy Source: Calculated by NZIER from Department of Labour, Regional Industry Tool

46 Appendix F Value of regional dairy production Southland $ South Taranaki $ Matamata-Piako $ Ashburton $ Waikato $ Waipa $ Selwyn $ South Waikato $ Rotorua $ Otorohanga $ New Plymouth $ Hauraki $ Tararua $ Timaru $ Clutha $ Kawerau/Whakatane $ Manawatu $ Taupo $ Kaipara $ Whangarei $ Waitaki $ Gore $ Waimate $ Western Bay of Plenty $ Stratford $ Franklin $ Hurunui $ Far North $ Tasman / Nelson $ Westland $ Waimakariri $ Horowhenua $ Buller $ Rangitikei $ Grey $ Rodney $ South Wairarapa $ Invercargill $ Dunedin City $ Central Hawkes Bay $ Opotiki $ Thames-Coromandel $ Waitomo $ Carterton $ Marlborough $ Palmerston North City $ Napier $ Kaikoura $ Ruapehu $ MacKenzie $ Masterton $ Wanganui $ Central Otago $ Christchurch City $ Kapiti Coast $ 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, South Island $ 2, New Zealand $ 8,

47 Appendix G Changing dairy export markets Figure 13 Changing markets for New Zealand s dairy exports % of export value Source: NZIER Source: NZIER 39

48