Allocating mineral valuations using
unit record data
Statistics New Zealand
Introduction
•
•
•
•
•
•
Statistics New Zealand’s role
Stats NZ’s environment statistics programme
New Zealand’s mineral asset valuation
Methodological issues
Data issues
Alternative valuation method – using unit
record data
• Discussion
Broadly speaking, Statistics NZ’s role is
to:
• Lead New Zealand’s Official Statistics
System
• Be the key contributor to the collection,
analysis and dissemination of official
statistics relating to New Zealand’s
economy, environment and society
Statistics New Zealand’s role with regard
to environment statistics is to:
• Provide a leadership role in producing
environment statistics at a national and
subnational level.
• Other agencies collect data that contributes to
the natural resource accounts
• Ministry for the Environment, Ministry of
Economic Development, Department of
Conservation, and others.
Development of NRAs in NZ
• SEEA was chosen as framework
• Since 2001, Accounts developed for:
– Energy and emissions
– Fish
– Forestry
– Freshwater
– Non-energy minerals
– Environmental Protection Expenditure
NZ’s minerals account
• Monetary and physical stock account
developed in 2003.
• Encompassed NZ’s major non-energy
minerals
• Developed along SEEA guidelines
• Provided valuations of major mineral
commodities
The NZ mining industry
• Dominant minerals are aggregates
(used for roading, construction etc.) and
gold.
• Aggregate mining is characterized by a
large number of producers.
• Gold mining is dominated by a small
number of large producers.
Source: Crown Minerals and the Institute of Geological and Nuclear Sciences
Source: Crown Minerals
Minerals account - data sources
• National Accounts
– Net Operating Surplus from the Annual Enterprise
Survey (AES)
– Capital Stock from capital stock model
• Crown Minerals, Ministry of Economic
Development
– Mineral Production Data
• Annual Enterprise Survey (AES)
– Unit record data for this study
Minerals account - methodology
• Perpetual Inventory Model
– Net present value of calculated resource rent
(resource rent is treated as constant into the
future)
• Rate of return and Discount rate
–
–
–
–
Fixed rate of return of 8%
Discount rate of 4%
3 year symmetric moving average
Chosen based on international precedent
• Total value disaggregated to individual
mineral values by share of monetary output
Minerals account - asset valuation
• Volatile time series
1400
$million
1200
1000
800
600
400
200
0
-2001988
1989
1990
1991
1992
1993
1994
1995
1996
1997
-400
-600
-800
-1000
Gold
Aggregate
Limestone
Ironsand
Other
1998
1999
2000
Mineral account – asset valuation
• Aggregate minerals have highest value
1400
– Aggregate is an abundantly available, low
value, high volume commodity.
$million
1200
1000
800
600
400
200
• Concern that the ‘output share’ method
may be undervaluing NZ’s gold
resource
0
-2001988
-400
-600
-800
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
– Gold is a scarce, low-volume, high value
commodity
-1000
Gold
Aggregate
Limestone
Ironsand
Other
2000
Methodological issues
• Fixed rate of return to produced capital
creates volatility in calculated mineral
asset values
• Potential improvement:
– Floating rate of return to produced
capital(?)
Methodological issues - Variable rate of return
1400
$million
Standard valuation including a
4% discount rate, an 8% rate of
return to capital and a 3 year
symmetric moving average
1200
1000
800
600
400
200
0
-2001988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
-400
Overall values seem a little to high
when using a variable rate of return
-600
-800
-1000
Gold
Aggregate
Limestone
Ironsand
Other
$million
1400
Alternative valuation including a
4% discount rate, and a variable
rate of return to capital
1200
1000
800
600
 r
400
200
0
1988
1989
1990
1991
1992
Gold
1993
1994
Aggregate
1995
Limestone
1996
Ironsand
1997
Other
1998
1999

2000
n
N
= rate of return to produced capital
r = typical real rate of return (8% Eurostat)
n = nominal rate of return of the industry (NOS/V)
N = typical nominal rate of return (NOS/V)
Other methodological issues
• Difficult to disaggregate asset value to
specific minerals
– No commodity-level data available via
Statistics NZ’s business surveys
– Mineral commodity production data
available from Crown Minerals
– NPV calculated for ‘other mining’ industry
– Allocated to individual commodities based
on share of industry output
Data issues
• Design of AES
– Not designed to produce data at the level of detail
required
• Capital Stock Model
– Not designed to produce estimates of capital stock
at this level
– Inconsistencies with consumption of fixed capital
data from AES at this level.
Proposed alternative method
• Use AES unit record data to calculate
proportions for allocating overall NPV
• Hoped to increase accuracy of
allocation
• Expectation that the asset value of gold
would be higher using this method
Results
NPV - Unit Re cord Allocation
800 $million
700
600
500
400
300
200
100
0
1997
1998
Gold
Other
Aggregate
1999
Limestone
Ironsand
2000
Results
NPV -Output Share Allocation
$million
800
700
600
500
400
300
200
100
0
1997
1998
Gold
Aggregat e
Limest one
1999
Ironsand
Ot her
2000
Results
NP V - Unit Re cord Alloca tion
800 $mi llion
700
600
• Unit record method yielded similar results
• Dominance of aggregate even more
pronounced
500
400
300
200
100
0
1997
– Against expectations
1998
Gold
Other
Aggregate
1999
Limes tone
2000
Ironsand
NPV -Output Share Allocation
• Explanation:
$million
800
700
600
– Regional scarcity of aggregate
– International price fluctuation of gold
500
400
300
200
100
0
1997
1998
Gold
Aggregat e
Limest one
1999
Ir onsand
Ot her
2000
Recommendations from study
• Given:
– The relative difficulty of unit record basis
– Questionability of AES data at such a low industry level
– The similarity of results
• It was recommended that the output share method be
retained for future updates of the minerals account
Discussion - Methodology
• Is the output share method appropriate
for such economically different
commodities?
• Can the volatility of the current NPV
method of asset valuation provide a
useful time series in the short run?
Discussion - SEEA framework
• What minimum level of
commitment/investment is required
before the benefits of the SEEA
framework are realised
– What it is the value of having a partial set
of accounts?
– What length of time-series will yield
meaningful results?
Discussion - communication
• How to communicate the value of the
SEEA, and its limitations, to users of the
data?
– More information in upcoming SEEA to
empower countries to do this.
– A process of regular review of the
proposed SEEA to incorporate countries’
experiences.