Presentation on theme: "Allocating mineral valuations using unit record data Statistics New Zealand."— Presentation transcript:
Allocating mineral valuations using unit record data Statistics New Zealand
Introduction Statistics New Zealands role Stats NZs environment statistics programme New Zealands mineral asset valuation Methodological issues Data issues Alternative valuation method – using unit record data Discussion
Broadly speaking, Statistics NZs role is to: Lead New Zealands Official Statistics System Be the key contributor to the collection, analysis and dissemination of official statistics relating to New Zealands economy, environment and society
Statistics New Zealands 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
NZs minerals account Monetary and physical stock account developed in 2003. Encompassed NZs 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
Mineral account – asset valuation Aggregate minerals have highest value –Aggregate is an abundantly available, low value, high volume commodity. Concern that the output share method may be undervaluing NZs gold resource –Gold is a scarce, low-volume, high value commodity
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 Standard valuation including a 4% discount rate, an 8% rate of return to capital and a 3 year symmetric moving average Alternative valuation including a 4% discount rate, and a variable rate of return to capital = 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) Overall values seem a little to high when using a variable rate of return
Other methodological issues Difficult to disaggregate asset value to specific minerals –No commodity-level data available via Statistics NZs 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
Unit record method yielded similar results Dominance of aggregate even more pronounced –Against expectations Explanation: –Regional scarcity of aggregate –International price fluctuation of gold
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.