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Use of the Statistics New Zealand Business Register for the agriculture industry and the not for profit sector Geoff Mead

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Presentation on theme: "Use of the Statistics New Zealand Business Register for the agriculture industry and the not for profit sector Geoff Mead"— Presentation transcript:

1 Use of the Statistics New Zealand Business Register for the agriculture industry and the not for profit sector Geoff Mead geoff.mead@stats.govt.nz

2 Introduction Use of the Statistics NZ Business Frame (BF) for –Agriculture production statistics –Non profit institutions satellite account Challenges Benefits Future developments

3 Statistics NZ Business Frame (BF) Based on administrative tax data All enterprises over a minimum threshold of tax activity 460,000 enterprises

4 Agriculture industry in NZ Temperate climate suited to farming activities Major industry, over 44% of exports 32.4 mill sheep 5.9 mill dairy cattle 1.6 mill ha plantation forestry 33,000 ha grapes Formal businesses

5 frame list of farms annual census frame list of farms etc annual census Agriculture production statistics Collected since 1861 Annual agriculture production census from 1956 to 1987>> Census maintained the frame of farms, frame was essential for the census

6 From 1988 to 2001 – financial constraints could no longer afford the annual census list of farms was not maintained –mix of censuses, sample surveys, no surveys –a number of different frames used, none entirely satisfactory the traditional list of farms, only partially maintained list of farms integrated with BF industry lists other administrative land based sources no comprehensive survey feedback to the BF

7 From 2002…….. From 2002 in partnership with the Ministry of Agriculture and Forestry –new agriculture production statistics programme –5 yearly censuses, sample surveys in other years –resourced Statistics NZ Business Frame (BF) used as the frame

8 Why was the BF used from 2002? –BF has comprehensive coverage of all enterprises with over a minimum threshold of tax activity –Benefits in coherence and consistency with other statistical outputs –BF existed, low cost compared with other options –No viable alternative administrative data based frame –Knowledge of the weaknesses of using the BF for agriculture production statistics

9 Robust agriculture production statistics are being produced using the BF Mainly a postal collection Processes to update the BF with agriculture survey feedback –supplements admin data updates to BF –improved BF quality

10 Sheep Dairy cattle

11 Comparison of satellite imagery to agriculture production statistics based on BF Type of land (Land Cover Database categories) Satellite imagery 2002 (Land Cover Database) ha Agriculture Production survey 2002 ha High producing grassland 8,886,0008,243,000 Exotic (plantation) forest 1,962,0001,828,000 Primarily horticulture (includes horticulture, viticulture, cropping) 417,000534,000

12 Coherence and consistency with other statistical outputs

13 BF coverage Missing very small informal farms outside tax system Hobby farms, lifestyle farms Common in New Zealand on fringes of urban areas Owner works in town No solution to date Quality caveats for users on coverage

14 Challenge one farm many enterprises multiple survey reporting units double counting risk Enterprise 1 farm operator Enterprise 2 land owner Enterprise 3 share farmer Managed by Correct industry codes on BF Filter questions in survey questionnaire Flags on BF, share farmers etc

15 Feedback from the agriculture production survey to the BF Improved BF quality –Industry classification updates BF population of enterprises in agriculture & forestry

16 Future developments BF and agriculture production statistics Ideal – integration with: 1. land based administrative systems 2. administrative systems that record livestock for disease control Incremental steps towards the ideal, but unlikely to be fully achieved in the foreseeable future BF tax admin data Land admin data Livestoc k register admin data

17 A population of not for profit units Statistics NZ published a non profit institutions satellite account in 2007 BF was the foundation of the population

18 Additional administrative data sources used to extend BF coverage BF coverage based on VAT and employment tax sources –Market orientated –And employers Many small units outside the BF coverage –In tax system but below BF tax thresholds or –Outside tax system

19 BF coverage extended with administrative registers of 1. Incorporated societies 2. Charitable trusts Care required to avoid duplications Charitable Trusts Incorporated societies BF

20 97,000 non profit institutions identified –18% from BF –82% from other registers –BF covered all employers and units with significant turnover Number of non profit institutions

21 Quality of population Medium sized town used Gathered all possible lists of non profit institutions Matched lists against population constructed from BF and other admin registers Lists had an additional 8% of units

22 Conclusion Two outcomes –BF provides a robust population for agriculture production surveys –BF provides the core but requires extension for non profit institutions Benefits in using centralised business register for as many outputs as possible –Coherence across statistical outputs –Efficiency –BF quality Future developments –Extending BF beyond market orientated coverage –Ideally integration with other administrative sources of agriculture data


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