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The Surprising Vulnerability of New Zealand Manufacturing to CO2

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					Economic AnAlysis & Policy, Vol. 40 no. 3, DEcEmBER 2010




        The Surprising Vulnerability of New Zealand
        Manufacturing to CO2 Emissions Pricing: The
         Lessons of an International Comparison1,2

                  Elisabeth Numan-Parsons, Kris Iyer* and Matthew Bartleet
                             Ministry of Economic Development
                 33 Bowen Street, PO Box 1473, Wellington 6011, New Zealand
                               (Email: kris.iyer@med.govt.nz)


Abstract:       This paper compares the cost impact of emissions pricing in NZ manufacturing with
                the evidence available for United States, United Kingdom, European Union, Germany,
                Netherlands and Australia. It is observed that, relative to the comparator economies,
                a much larger share of NZ GDP is potentially at risk as a result of emissions pricing
                (even excluding the direct and indirect effects of agriculture). Possible reasons for this
                unexpected finding include: dissimilarities in industry structure, applicable emission
                factors for indirect emissions, level of aggregation at which industries are evaluated
                across countries and concentration of emissions in a small number of firms/industries.
                The paper identifies manufacturing activities are most emission intensive in NZ and
                in comparator economies. While some emission intensive activities are common to
                all examined economies, the food processing cluster is found to be at risk of losing
                competitiveness only in NZ and Australia.



                                           I. INTroDUcTIoN
In 2008, the Kyoto Protocol came into effect. Under the Protocol, industrialised nations (the so
called “Annex B” countries) committed to reduce their collective greenhouse gas emissions by
5.2 percent relative to 1990 levels. This agreement represents the first step towards achieving
a global response to climate change. New Zealand (NZ) ratified the Protocol in 2002 with a
1   Disclaimer: The opinions, findings, recommendations and conclusions expressed in this report are those of the
    authors. Statistics New Zealand (NZ) and the Ministry of Economic Development, NZ take no responsibility for
    any omissions or errors in the information contained here. Access to the data used in this study was provided
    by Statistics NZ in accordance with security and confidentiality provisions of the Statistics Act 1975. only
    people authorised by the Statistics Act 1975 are allowed to see data about a particular, business or organisation.
    The results in this paper have been confidentialised to protect individual businesses from identification.
    Any discussion of data limitations is not related to the data‘s ability to support these government agencies’
    core operational requirements. Any table or other material in this report may be reproduced and published
    without further licence, provided that it does not purport to be published under government authority and that
    acknowledgement is made of this source.
2   The authors would like to thank Adolf Stroombergen, Gilian Lawrence, Martin Brown-Santirso, Julia Gretton
    and Arthur Grimes for very helpful contributions and comments.
*   corresponding author: Kris Iyer


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target of a zero percent reduction of 1990 emissions on average between 2008 and 2012. A
key policy to meet this obligation is an emissions trading scheme (ETS), passed into law in
2008, subsequently amended in 2009.
     Economic models of various ETS scenarios (alternative emission price and sector coverage
assumptions) predict relatively-small impacts on NZ’s GDP (e.g., Infometrics 2008). However,
not all industries or firms in the economy are expected to face similar impacts; some industries
may benefit from a price on emissions, others may face a significant cost, while many may be
largely unaffected. In large part, the degree to which an industry will be affected will depend
on its emissions intensity, the options it has for managing its emissions, and the degree to
which similar price instruments are applied to (if any) its international competitors given the
asymmetric nature of emissions reduction obligations under the Kyoto Protocol.
     Whether and the degree to which assistance should be provided to affected industries is
the subject of extensive debate, including beyond the confines of climate change policy. If
the asymmetry is long lasting, the effect is akin to a long-term reduction in the comparative
advantage of affected industries. In this case, providing assistance could negatively impact on
the economy as a whole as assistance would be provided to industries that lack comparative
advantage (and in doing so effectively prevent the structural change required). However,
history also shows that transition paths matter in the size, distribution and duration of costs.
Arguably, the challenge is one of transitioning but without detrimental (and costly) disruption
including ensuring that the profitability and competitiveness impacts on the industries that are
important to NZ’s economic future are managed.3
     In general, international evidence suggests that only a relatively small number of tradable
sector industries are sufficiently emissions-intensive to have their competitiveness seriously
threatened if brought into an ETS in the current international environment. These industries
include steel, aluminium, paper, petroleum and chemicals, cement, and sheep, beef and dairy
processing. Similar results have been reported in the NZ context (see, Bartleet et al., 2010).
     In this paper we compare the level, distribution and rank of impacted industries within
the NZ manufacturing industry against impacts reported for other developed economies,
specifically United States (Ho et al., 2008), European Union (Hourcade et al., 2007), United
Kingdom (Grubb and Neuhoff, 2006; carbon Trust, 2008), Australia (Muller and Saddler,
2006; Saddler et al., 2006), Germany (Graichen et al., 2009) and the Netherlands (De Bruyn
et al., 2008). These are the countries for which comparable evidence was available. Through
this comparison we estimate the relative impact on NZ’s manufacturing industry.4 The potential
3     Whether all the emissions intensive industries in NZ are important for future competitive advantage is highly
      debatable. However, it could be argued that those industries with deep linkages within the economy of which
      other industries are likely to develop may be of most interest in terms of the effects of emissions pricing. In this
      paper we do not distinguish between emissions intensive industries that are likely to be of future competitive
      advantage and those that are not.
4     This study treats the manufacturing sector in isolation from other industries such that impacts of emissions
      pricing on, for example, the primary sector are not taken into account in estimating the cost impacts on
      manufacturing industries that process primary products. Given the importance of these inter-linkages it
      is reasonable to conclude that a careful consideration of adjustment mechanisms across the value chain is
      required for a comprehensive analysis. But at the time of writing this paper, data on agricultural farm level
      energy emissions are still to be made available. As a result, the indirect emission effects on primary goods
      processing activities that may emanate from energy emission price effects on farms has not been accounted
      for in this paper.


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underlying reasons for the differences observed in the NZ context are explored.5 Understanding
the relative impact and the differences is material for consideration of ‘burden sharing’ in the
negotiation of future emissions reduction targets.
    The rest of the paper is organised as follows. The next section discusses the NZ data
and section 3 briefly profiles emissions in NZ manufacturing. Section 4 compares the NZ
evidence on the cost impacts of emissions pricing with that of other countries and explores the
differences; potential explanations for the observed differences are searched. Finally, section
5 offers concluding remarks.

               II. NZ MANUFAcTUrING SEcTor EMISSIoNS DATA6
The NZ data for this study comes from the prototype Longitudinal Business Database (LBD),
administered by Statistics NZ.7 Among other data, the LBD contains information compiled from
the Manufacturing Energy Use Survey (2006) (MEUS) and Annual Enterprise Survey (2006)
(AES). The MEUS provides energy use data by type for firms in the manufacturing sector
for the year ended March 31, 2006. The bulk of the energy consumption in NZ is accounted
for by a relatively small number of high energy use firms. All of these firms are included in
the MEUS sample, thus making the coverage of energy consumption comprehensive. co2-e
emissions are derived by combining the MEUS energy data with the emission factors by energy
type published by the Ministry of Economic Development (2008).8 AES provides the firm
level financial data, i.e., value added which combined with emissions data enables computing
the variable of interest in this study – maximum value at stake (MVAS). In this paper, MVAS
is defined as total emissions costs as a proportion of value added.9
    Although the MEUS has data on 1026 firms, matching financial data is available from AES
only for 668 of them. Significantly, the reduced sample does not constrain a pertinent analysis
on emissions of the NZ manufacturing sector. The reduced sample of 668 firms accounts for
86 percent of manufacturing sector emissions, 94 percent of manufacturing sector’s energy use
and 57 percent of the manufacturing sector’s value added. These numbers imply that the firms
excluded from the sample are on average, those with significantly lower levels of emissions
intensity. This provides some comfort that the analysis is not likely to systematically omit
emissions intensive firms from the analysis.


5   Care must be taken in comparing cross-country research evidence on the cost impacts of emissions pricing
    because of several reasons (see, Appendix 1).
6   For a detailed discussion on the dataset, see Brown-Santirso and Fu (2008) and Bartleet et al. (2010).
7   The LBD is discussed in more detail in Fabling et al. (2008) and Statistics NZ (2007).
8   The emission factors applied in this study is for direct emissions are the same as in Brown-Santirso and Fu
    (2008). However, the emissions factor for electricity emissions used is a marginal factor rather than the average
    factor. It is conceded that use of an average electricity emissions factor provides a more actuate estimate of
    physical emissions. However, because electricity prices are determined at the margin (during peak periods
    being a mix of gas and coal generation), the emissions costs passed through to consumers will correlate more
    closely to the application of a marginal emissions factor. As a result the estimate of indirect emissions in this
    report differs from Brown-Santirso and Fu.
9   MVAS can also be constructed as total emissions cost as a proportion of gross output or intermediate
    consumption. Each alternative has its pros and cons which are documented in Bartleet et al. (2010). In this
    paper, we use value added to be consistent with comparative studies.


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    600 of the sample firms are classified into 51 sub-sectors by ANZSIc 1996 groups or
classes.10 The remaining 68 firms, which account for half the emissions of the manufacturing
sector, are not classifiable by either groups or classes due to data confidentiality reasons. There
are either too few firms involved in the group (or class), or the concerned firm is dominant
making it possible to estimate their individual information if group (or class) wide statistics
are presented. Further analysis revealed that emissions from 21 of the 68 firms dominate the
distributions of emissions and MVAS. These 21 firms are re-grouped into two additional
mutually exclusive categories for analysis without identifying their ANZSIc group affiliation.
The two categories are: mega emitters (firms with emissions in excess of 20,000 tonnes for the
year ended March 2006) and large emitters (firms with emissions in excess of 5,000 tonnes
but less than 20,000 tonnes). It is possible to pinpoint broadly to which 2 digit industries these
firms belong (See, Table 1).

                Table 1: Mega and Large Emitters by manufacturing 2 digit chapters
            Manufacturing chapters                                            Number of firms
            c21: Food, Beverages & Tobacco                                              6
            c25: Petroleum, coal & chemicals                                            6
            c26: Non-metallic Mineral Products                                          3
            c28: Machinery & Equipment                                                  6
           Note: Following Statistics NZ protocols, data from some manufacturing chapters have been
           suppressed for confidentiality and the number of firms has been random rounded.

    The mega and large emitters’ category contain only those huge emitters that could not be
presented within the 51 sub-sectors.11 It should not be interpreted as groups that include all
the big emitters.

                  III. EMISSIoNS INTENSITy IN NZ MANUFAcTUrING
This paper discusses only materially impacted sub-sectors. of the 51 sub-sectors, 26 are
identified as being materially impacted. Including the mega and large emitters, that provides
28 groups for further analysis. Material impact is when at reasonable and foreseeable emissions
prices, the effects faced by the industry will be noticeable to the extent that it is likely to illicit
a behavioural response. one determining criterion for material impact is the level of emission
intensity which is a corollary of MVAS. Although, there is no universal view on the level at
which an impact becomes material, international studies such as Hourcade et al., (2007) and
carbon trust (2008) have used a cut-off of 400 Kgco2-e per NZ$1000 of value added, i.e.,
MVAS of 2 percent at an assumed carbon price of NZ$50 per tonne. It has been commented
10    The Australian and New Zealand Standard Industrial Classification (ANZSIC) is used for the collection,
      compilation and publication of statistics relating to industry. It is closely based on the international classification
      ISIC, and has a structure comprising categories at four levels, namely Divisions (the broadest level), Subdivisions,
      Groups (3 digits) and Classes (4 digits). ANZSIC96 denotes the 1996 edition of the classification.
11    The Australian and New Zealand Standard Industrial classification (ANZSIc) is used for the collection,
      compilation and publication of statistics relating to industry. It is closely based on the international classification
      ISIc, and has a structure comprising categories at four levels, namely Divisions (the broadest level), Subdivisions,
      Groups (3 digits) and classes (4 digits). ANZSIc96 denotes the 1996 edition of the classification.

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                 Table 2: MVAS of Industry Groups: Decomposed into Direct and
                               Indirect Emission contributions
                                                          MVAS           MVAS
                                             Share in                               MVAS
 Activity / Group                                         (Direct       (Indirect
                                             GDP (%)                                (Total)
                                                         Emissions)    Emissions)
 Mega Emitters                                 2.18        21.15          12.17     33.32
 Aluminium Drawing, rolling &
                                               0.05         0.57         24.51      25.08
 Extruding
 Large Emitters                                0.39         6.94         13.44      20.38
 Iron & Steel                                  0.20         2.74         13.36      16.09
 Pulp, Paper & Paperboard                      0.32         2.87          7.45      10.31
 Sheet Metal Products                          0.21         3.32          6.22       9.54
 Plastic Blow-moulded                          0.05         0.06          7.05       7.10
 Fruit & Vegetable                             0.19         0.95          5.13       6.07
 other Wood Products                           0.34         1.20          4.26       5.47
 Seafood                                       0.45         1.59          3.18       4.78
 Architectural Aluminium                       0.13         3.28          1.46       4.74
 Plastic Injection Moulded Product             0.14         1.21          3.21       4.41
 Textile Fibre                                 0.08         2.42          1.72       4.14
 Log Sawmilling                                0.25         1.61          2.48       4.09
 Structural Metal Products nec                 0.14         0.85          3.21       4.06
 Food excl. Seafood                            0.60         0.41          3.46       3.87
 Fertiliser                                    0.12         1.65          2.10       3.74
 concrete Slurry                               0.09         3.18          0.39       3.57
 Ink & chemical Products nec                   0.08         1.86          1.61       3.47
 Leather & Leather Products                    0.06         2.06          1.29       3.34
 Electrical Equipment & Appliance              0.28         1.17          1.96       3.13
 Ship & Boat building                          0.15         1.12          2.00       3.12
 Fabricated Metal Products                     0.43         1.28          1.81       3.08
 Industrial Machinery & Equipment nec          0.44         1.49          1.24       2.72
 Textile Product                               0.18         1.28          1.38       2.66
 Meat Product                                  0.97         1.10          1.50       2.59
 Bag, Film & other Plastic Products            0.22         0.44          2.14       2.57
 Synthetic resin & organic Industrial
                                               0.37         0.52          1.85       2.37
 chemical
*nec: not elsewhere classified

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that cost increases below these levels are likely to be dwarfed by volatility and variability of
factors like exchange rates, taxation, labour costs or infrastructure provision (Hourcade et
al., 2007). Interestingly, for the NZ manufacturing sector the 2 percent MVAS threshold also
presents as a natural breakpoint in the data (for details, see Bartleet et al., 2010).
     Table 2 presents the MVAS of the 28 materially impacted groups, and the importance of
the groups to the national economy. The MVAS is decomposed into direct emissions (non-
electricity) and indirect emissions (electricity purchased from the grid) components. Notably,
indirect emissions (electricity purchased from the grid) have been calculated using marginal
factors. When considering the affect of emissions pricing on electricity prices, it is the marginal
generation source that sets the price of electricity. In NZ the marginal generation source is
often a mix of coal and gas.
     It is known that the manufacturing economy as a whole accounts for about 15 percent of
NZ’s national GDP. Figure 1 reveals that nearly two thirds of the activities in it (9.11 percent)
have MVAS in excess of 2 percent (at an assumed carbon price of NZ$50). As will be discussed
in the next section, from an international perspective this is a sizeable proportion much higher
than what is observed for the comparator economies.

                          IV. INTErNATIoNAL coMPArISoNS
Table 3 sets out the estimated impact of a $50 per tonne co2e emissions price on the manufacturing
sector of each comparator country. The following table is indicative only. For some countries
the percentages were determined based on visually off diagrams, owing to non-availability
of underlying data. For others (specifically, the USA) gross output was used as disaggregated
value added figures were not available. As gross output is greater than value added, the same
emissions cost would be a smaller proportion of gross output than value added. This means
that the USA figures are likely to be lower than those if value added was used. The table is
derived from the individual results of each country study at the greatest level of disaggregation
provided at a group level.

      Table 3: Proportion of country GDP Potentially at Stake at Alternative Materiality
                                 Thresholds at Group Level
 country                      2 percent MVAS           6 percent MVAS           12 percent MVAS
 New Zealand (VA)                9.11 percent             3.6 percent              2.8 percent
 Australia (VA)                  6.18 percent            1.47 percent             1.34 percent
 UK (VA)                          1.1 percent            1.05 percent              0.4 percent
 Germany(VA)                     2.05 percent            1.20 percent             0.55 percent
 US (Go)                         2.75 percent            0.47 percent             0.4 percent
*VA: value added, Go: gross output


    Table 2 shows that there is a consistent pattern for each country where the proportion of GDP
(the total contribution to GDP of affected industries) at risk declines, although not linearly, as the
threshold for impact increases. It is intriguing that a much larger share of NZ GDP (relative to


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comparator economies) is potentially at risk. There is evidence suggesting that average emission
intensity in NZ manufacturing is lower than that of comparator economies. The emission intensity
in NZ manufacturing has been estimated at 550 tonnes of CO2-e per million dollars of output.
The corresponding statistics for USA, UK, Netherlands and Australia are 809, 599, 712 and
1964 respectively (see, Bartleet et al., 2010). The following explanations are worth considering.

                                      4.1 Position in Value Chain
The world manufacturing industry is in a process of structural change with many developed
countries experiencing a decline in the share of manufacturing of GDP. For many developed
economies, the manufacturing sector has shifted up the value chain. To the extent that
comparable nations have moved into the higher value added segment of the manufacturing
market (typically lower in emissions intensity), a difference in relative emissions intensity
may reflect differing industry structures rather than relative productive inefficiency. relatedly,
it has been documented in oEcD (2006) that NZ has a high proportion of low technology
manufacturing exports compared to all comparator countries (as does Australia). Further,
according to the oEcD report, NZ and Australia have seen declines in both high and medium-
high technology manufacturing exports (as a proportion of total manufacturing exports) in the
decade to 2003 while countries such as the US and UK have seen increases.

                                   4.2 Electricity Emission Factors
Electricity emissions factors may have a material effect on the MVAS results. Electricity, or
indirect energy, comprises a significant portion of manufacturing sector energy use. Across
countries this energy is generated from differing feed stocks and in different market structures.
Table 4 sets out average electricity emissions factors drawn from the International Energy
Agency (IEA) and the electricity emissions factors used in each of the studies for the comparator
countries. As can be seen there is a large variation in electricity emissions factors.

                                Table 4: Electricity Emissions Factors

                                     IEA Average Electricity co2           Electricity co2 emissions
 country
                                      emissions factor12 (t/MWh)        factor (t/MWh) (used in studies)
 New Zealand                                      0.159                               0.520
 Australia                                        0.924                              1.07413
 United Kingdom                                   0.475                               0.410
 Germany                                          0.539                               0.410
 Netherlands                                      0.479                               0.410
 United States                                    0.676                            [not known]


12   U.S. Department of Energy. Voluntary reporting of Greenhouse Gases. Appendix F. Electricity Emissions
     Factors drawn from the IEA Electricty Information Database 2007.
13   Australian National Greenhouse Gas Inventory Australia‘s National Greenhouse Gas Inventory 1990, 1995
     and 1999, End Use Allocation of Emissions. report to the Australian Greenhouse office, George Wilkenfeld
     & Associates Pty Ltd and Energy Strategies (2003).


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                 Table 5: rank of Industries Impacts Above 2 Percent MVAS (Assumed Emissions Price of NZ$50 Per Tonne)




320
      USA                     UK                      Germany                 Netherlands            New Zealand             Australia
      cement                  Lime                    cement                  Fertilizer             Mega emitters          basic non-ferrous
      manufacturing                                                                                  (confidentialised)     metals
      Petrochemical           cement                  Lime                    cement, calcium,       Aluminium Drawing,     Iron and steel (part)
      manufacturing                                                           gypsum                 rolling & Extruding
      Alumina refining,       Basic iron and steel    Fertilizers& nitrogen   Iron and steel         Large Emitters         cement, lime, concrete
      primary aluminium       and ferro-alloys        compounds                                      (confidentialised)
      Iron and steel mills,   refined petroleum       Basic iron & steel      Inorganic chemicals    Iron & Steel           ceramics
      ferroalloy mfg.
      Lime and gypsum         Fertilizers and         Aluminium               Aluminium              Pulp, Paper &          other non-metallic
      product mfg.            nitrogen compounds                                                     Paperboard             mineral products
                              inc. ammonia
      other basic organic     Aluminium               Paper                   other base chemicals   Sheet Metal Products   glass and glass
      chemical mfg.                                                                                                         products
      Fertilizer              other inorganic basic   other basis inorganic   Petrochemical          Architectural          textile, clothing etc
      manufacturing           chemicals               chemicals                                      Aluminium
      Paperboard mills        Pulp, paper and         coke, refined           Glass                  concrete Slurry        wood, paper, printing
                              paperboard              petroleum products &
                                                      nuclear fuel
      Paper mills             Malt                    Starches and starch     Building materials     Fruit & Vegetable      Food, beverages,
                                                      products                                                              tobacco
      other basic inorganic   coke oven products      Flat glass              Paper                  Plastic Blow-moulded   fabricated metal
      chemical mfg                                                                                                          products
                                                                                                                                                                         ThE lEssons of An inTERnATionAl comPARison




      Artificial and          Industrial gases        Pulp                    refineries             Textile Fibre          machinery and
      synthetic fibers,                                                                                                     equipment
      filaments
      Plastics material and   Non-wovens              other basic organic     other non-ferro        other Wood Products    other manufacturing
      resin mfg.                                      chemicals               metals
      refining–LPG            Household and           ceramic tiles                                  Seafood
                              sanitary goods
                                                                                                                                                     ThE suRPRising VulnERABiliTy of nEw ZEAlAnD mAnufAcTuRing To co2 Emissions PRicing:




      refining–others         Finishing of textiles   Bricks, tiles and                              Log Sawmilling
                                                      construction products
                                                      in baked clay
       Glass container            Hollow glass              Hollow glass             Plastic Injection
       manufacturing                                                                 Moulded Product
       Pulp mills                 rubber tyres and          Sugar                    Leather & Leather
                                  tubes                                              Products
       Mineral wool               retreading and            Veneer sheets,           Fertiliser
       manufacturing              rebuilding of rubber      plywood, lamination
                                  tyres                     board, particle and
                                                            fibre board

       other non-metallic         Veneer sheets,            Plastics                 Ink & chemical
       mineral                    plywood, lamination                                Products nec
                                  board etc
       other primary metals       Flat glass                Textile finishing        Structural Metal
                                                            services                 Products nec
       Textile                    other textile weaving     Glass fibres             Fabricated Metal
                                                                                     Products
       Nonferrous metal           copper                    Household and toilet     Electrical Equipment
       foundries                                            paper                    & Appliance
                                  Throwing, preparation     copper products          Industrial Machinery
                                  and texture of silk and                            & Equipment nec
                                  filament yarn
                                  casting of iron           other glass, processed   Ship & Boat
                                                                                     building*
                                                            Dyes and pigments        Fabricated Metal
                                                                                     Products
                                                                                     Industrial Machinery
                                                                                     & Equipment nec
                                                                                                            ElisABETh numAn-PARsons, KRis iyER∗ AnD mATThEw BARTlEET




                                                                                     Textile Products
                                                                                     Meat Products
                                                                                     Bag, Film and other
                                                                                     Plastic Products
                                                                                     Synthetic resin &
                                                                                     organic Industrial
                                                                                     chemicals
      *nec: not elsewhere classified.




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     The emissions factors in the third column of Table 4 are those used in each of the comparable
studies. As can be seen, the NZ and Australian emissions factors used are higher than the
internationally comparable factors (column two) whereas for the European countries the factor
used is lower. The internationally comparable factors are average emissions factors. For NZ
because of the large proportion of hydro generation, the low emissions factor for electricity
is to be expected. However, when considering the effect of emissions pricing on electricity
prices, it is the marginal generation source that sets the price of electricity. In NZ, as observed
earlier, the marginal generation source is often a mix of coal and gas. These sources have higher
emissions content. What is of note for NZ specifically is the degree of difference between
average and marginal emissions factors. Because the electricity emissions factor used for
NZ in this study is significantly higher than the average emissions factor, this may partially
contribute to the MVAS findings in Table 3.

                                    4.3 Industry Aggregation Issues

    The NZ specific study by Bartleet et al. (2010) found that with greater aggregation of
industries, the MVAS results were lower. Given that some studies are of greater or lesser
aggregation, this may go some way to explaining the difference in MVAS results. It is observed
that the Netherlands and Australian results are presented at higher levels of aggregation than
other countries. However, with respect to Australia the aggregation level does not appear to
explain why its MVAS is higher relative to the other countries.

                                     4.4 Concentration of Emissions

In NZ and Australia, emissions are concentrated in a small number of firms/industries that
contribute a significant portion of GDP while other industries have low emissions intensity;
and either:
•     an industry in NZ and Australia is more emissions intensive versus other comparator
      countries; or
•     the mix of industries in NZ and Australia is different relative to other countries (i.e., these
      countries produce goods that are emissions intensive that other countries do not)
The lack of comparable information for the other countries restricts arriving at a definitive view
on whether NZ (and Australia) has more concentrated emissions, although this seems plausible.
     Despite the finding that a relatively greater proportion of NZ production occurs in
emissions intensive industries, the list of industries identified as being materially impacted
is remarkably similar across NZ and comparator economies. Table 5 displays the industries
by rank (descending order) for each country above the approximate 2 percent impact on
value added. It is reiterated that because the studies have been conducted at different levels
of disaggregation and industry classification, care must be taken in comparing the results.
Across the board, the following industries are found to be materially impacted: cement, lime,
refining, fertilizer, aluminium, iron and steel, pulp and paper, glass and plastics – although
their rank shifts around.14 However, food and beverage industries (with the exception of Malt
14    Some of this movement may just be a function of the disaggregation


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in the UK) only feature as materially impacted for NZ and Australia. The food and beverage
industry is critical to NZ. As a share of GDP, the food industry has been estimated at 2.21
percent. This number excludes dominant food processing firms which are categorised as mega
and large emitters whose combined share in NZ GDP is 2.57 percent. Furthermore, emission
pricing effects and GDP contribution at the farm level have not been accounted in this study.
It is reasonable to suggest that the food cluster is at the most risk of losing competitiveness if
emissions prices are imposed in NZ ahead of other countries.

                                V. coNcLUDING rEMArKS
This paper presented a profile of emissions in NZ manufacturing, with a focus on comparing
the NZ evidence with that available for of USA, UK, European Union, Germany, Netherlands
and Australia. comparatively, a relatively greater proportion of manufacturing production in
NZ occurs in emissions intensive industries, although there is evidence to suggest average
emission intensity in NZ is lower. Four potential reasons were uncovered: dissimilarities in
the industry structure, marginal emissions factors for electricity purchased from the grid,
methodological issues associated with aggregation and concentration of emissions in a small
number of firms/industries. It is likely that a combination of these reasons rather than one specific
reason results in a larger share of NZ GDP being potentially at risk of losing competitiveness
as a consequence of an emissions price. The list of industries with a high MVAS is similar
across comparator economies with the notable exception of food processing. only in the case
of NZ and Australia, the food processing industry gets categorised under the potentially at risk
category (MVAS of 2 percent or more at an assumed emissions price of NZ$50 per tonne of
co2-e). The importance of the food cluster to the NZ economy makes this result noteworthy.

                                           rEFErENcES
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      ThE suRPRising VulnERABiliTy of nEw ZEAlAnD mAnufAcTuRing To co2 Emissions PRicing:
                          ThE lEssons of An inTERnATionAl comPARison


Hourcade, J., D. Demailly, K. Neuhoff, and M. Sato (2007). Differentiation and dynamics of EU ETS
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324
                   ElisABETh numAn-PARsons, KRis iyER∗ AnD mATThEw BARTlEET




       APPENDIx 1: coMPArISoN oF croSS-coUNTry rESEArcH
            EVIDENcE oN EMISSIoNS INTENSITy: cAVEATS

•   As a general observation, these studies have faced limitations in the availability of energy
    use data at an industry level. There is often a reliance on a single year of data and often
    survey rather than census information.
•   Differences in methodology (for e.g. whether Gross output or Value Added is used to
    compute maximum value at stake [Total emissions costs as a proportion of value added/
    gross output] – the main variable of interest) can have a material impact on the results.
•   Differences in industry classification may mean that for some industries the comparison
    may not be of ‘like with like’.
•   Differences in the degree of industry disaggregation may mean that countries with more
    aggregated results may appear relatively more impacted (as a proportion of GDP) than
    countries for which there is more disaggregated data. At greater levels of aggregation
    where an industry is highly impacted to the point that other lower impacted sub-industries
    are brought up to the threshold, the relative proportion of GDP at stake will be inflated.
    For example, for Australia Food, Beverage and Tobacco has a maximum value at stake
    of 2.16 percent. For the NZ results a greater level of disaggregation means that only part
    of Food, Beverage and Tobacco meets the 2 percent threshold. Food (excluding Seafood)
    and Meat Processing account for 1.57 percent of GDP and have MVAS of 1.95 percent
    and 1.76 percent respectively.
•   NZ has an unusual industry structure where several of the high ‘maximum value at stake’
    industries comprise a small number of firms. Because of confidentiality considerations,
    it is not possible to include all the results for such industries by sector.
•   Between the various studies different emissions prices have been used. As this method
    essentially involves a straightforward calculation, the results can be scaled up or down on
    a linear basis. Due to the use of different currencies and years, in order to see the effects
    of the same emissions price it is necessary to convert the currency and deflate/inflate the
    price to match to the data year in each study. This naturally introduces further error.




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