Official Statistics – what they are and how we can use

them.

Richard ArnoldVictoria University of Wellingtonrichard.arnold@msor.vuw.ac.nz

Sharleen ForbesAdjunct Professor of Official Statistics

Victoria University of Wellingtonsharleen.forbes@vuw.ac.nz

Statistics• statistics (n.) 1770, "science dealing with data about the condition

of a state or community" [Barnhart]

• from German Statistik, popularized and perhaps coined by German political scientist Gottfried Aschenwall (1719-1772) in his "Vorbereitung zur Staatswissenschaft" (1748)

• from Modern Latin statisticum (collegium) "(lecture course on) state affairs"

• from Italian statista "one skilled in statecraft"

• from Latin status “state”

• OED points out that "the context shows that [Aschenwall] did not regard the term as novel," but current use of it seems to trace to him. Sir John Sinclair is credited with introducing it in English use. Meaning "numerical data collected and classified" is from 1829; hence the study of any subject by means of extensive enumeration.

• Abbreviated form stats first recorded 1961http://www.etymonline.com/index.php?term=statistics 2

What are Official Statistics?

• Official statistics are all statistics produced by government departments.

Definition

• Statistics Act 1975 – ‘… collected to provide information required by the Executive Government of New Zealand, Government Departments, local authorities, and businesses for the purpose of making policy decisions, and to facilitate the appreciation of economic, social, demographic, and other matters of interest to the said Government, Government Departments, local authorities, businesses and to the general public.’

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What are Official Statistics?

Examples• Maori population of New Zealand = 598,605 people or 14.9% of NZ pop

(2013 Census, an increase from 565,329 in the 2006 Census)• Between the December 2013 and March 2014 the Labour force participation

rate rose +0.4% to 65.1% and the unemployment rate was unchanged at 6.0% (Household Labour Force Survey)

• Gross Domestic Product, quarterly GDP rose by 1.0% in the March 2014 quarter (Statistics New Zealand Surveys)

• Consumer Price Index, CPI rose 0.3% in the March 2014 quarter (Statistics New Zealand Surveys)

• Total Number of Recorded Offences decreased from 451,405 in 2009 to 360,411 in 2013 (Police Administrative data)

• Participation (enrolment) rate of 0-4 years olds in Early Childhood Education rose from 56.5% in 2003 to 64.5% in 2013 (Ministry of Education Administrative data)

What are Official Statistics?

• They:

• are the cornerstones of good government• assist in policy development, monitoring, evaluation, revision• support public confidence in good government. • provide a window to the work and performance of government• show the scale of activity in areas of public policy • allow citizens to assess the impact of public policies and actions• are the basis of independent academic research• assist individuals, communities, businesses, political parties to

quantify their needs, opportunities, progress and impact

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What are Official Statistics?

• The majority of official statistics are produced by Statistics NZ although many other government agencies also produce official statistics.

• Cabinet has agreed on a set of key (Tier One) official statistics that are essential to central government decision making and are of high public interest.

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Strengths and weakness

Strengths• Often full coverage of population of interest

(may involve mandatory participation or use of administrative data)

• Often internationally comparable measures (standards may be set by international treaty)

• Generally reliable, accurate, consistent over time

Strengths and weakness

Weaknesses• Definitional problems: NOT what you expect, or may be inconsistent

CRIME RATE = number of crimes per head of population, NOT number of people committing crimes.

Early Childhood Education based on Enrolments NOT ChildrenEthnicity data – has inconsistent collection

(use of different questions between agencies or over time)

• Observational not experimental data: Limited information on causality

• Coverage: Administrative data sets cover populations receiving Government services but DON’T cover population NOT receiving services

• Timing: Collection dates may differ making comparisons difficult

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What is different about official statistics?OFFICIAL STATISTICS ”OTHER” STATISTICS / RESEARCH

Sometimes have statutory powers – but also underlying international principles

Usually governed by national or local ethics committees (if at all)

Often based on complex sample designs; observational

Often simple surveys or designed experiments (interventions)

Broad coverage (many variables – often high-level measures)

In-depth studies

Large-scale (provide comparisons between groups, including minortties)

Usually relatively small scale(experiments or surveys)

Usually repeated regularly(provide long time series)

Mainly cross-sectional (single point of time)

Internationally comparable(agreed standards, classifications)Multi-purpose, developed in consultation with stakeholders

Relevant to population studied (focused on research/policy question)May be innovative, but not generalisable

Simple analysis provided by collectors (e.g. simple 1- or 2-way associations)

Sophisticated analysis (e.g. multiple regression)

Provide primary data source Can involve secondary analysis (of other data sources)

High cost Generally lower cost 9

Approval

process

Uses - A Government Policy perspective

Policy

Monitoring/ Evaluation

•Information•Opinion•Evidence

Consultation

Government

Lobby Groups

Research

Public Opinion

‘Hard’/numerical/statistical data is useful at all stages of the policy cycle

Eval

uation

of

effec

tive

ness

Modification

Form

ulat

ion

o Provide access/ensure equityo Provide incentives/ disincentiveso Legislate or regulate behaviours

Users, Stakeholders, Agencies

GOALEvidence Based Policy

Makingor at least…

Evidence Assisted Policy Making

Copied from Hidalgo (2010)

Official Statistics Influence Policy

Florence Nightingale created her 1858 ‘Rose’ summarising military deaths in Eastern Europe, when her written report to Queen Victoria on British Army conditions was not acted on. As a result health policy changed.

April 1854-March 1855Each wedge = 1 month

Counts of deathsBlue = Preventable DiseaseRed = Deaths from WoundsBlack = All other causes

The use of statistics to influence policy

Copied from Hidalgo (2010)

Example: Housing and Health• Evidence: Many lines of evidence indicate that NZ’s poorly insulated

housing stock may be contributing to poor health outcomes• Randomised community trial finds lower numbers of GP visits, fewer days off

school in houses that were insulated (Howden-Chapman et al. 2007)

• Policy Development: Key stakeholders are Ministry of Economic Development, Ministry of Social Development, Ministry of Health, EECA

• 2008: National Party led Government with Green Party introduces Warm Up New Zealand Heat Smart Policy – (almost) anyone can get a subsidy for a efficient heating and insulation

• Evaluation: Ministry of Economic Development contracts independent researchers to evaluate the policy

• 46,500 treated houses compared to 200,000 controls during the period 2009-2010. Risk of mortality reduced in 65+ years who had had a prior cardiovascular hospital admission (Telfar-Barnard et al. 2011), net benefits >$400M (Grimes et al. 2011)

• Revision: Budget 2013 funded the programme for a further 3 years. 13

Official statistics provide base national informationThe social backbone

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Changes – over time

Changes – between cohorts

LabourForce

Education Crime SocialWelfare

Health

Morbidity Mortality

}}Participation Rates}

Rates

HousingIncome

DistributionLife

Expectancy

National Identity

Census

Long policy timeframes – where is the evidence?• Example: Fifty years of smoking policies

1940’s to 2010s

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(from isolated regulatory policies to a complex mix of incentive, disincentive, education, regulation and legislation)

Policy development process

• Accumulation of research/ statistical information provided evidence of a CAUSAL LINK between smoking and early death - led to Educational Programmes/Warnings of Risks from Smoking

• Analysis of costs of care/hospitalisation for smoking related illnesses and loss-opportunity costs of early death (financial and administrative data) -led to regulations about sale of cigarettes, etc. and disincentives such as tax rises

• Evidence of effects from ‘passive’ as well as ‘active’ smoking research/statistics - led to legislation restricting smoking, incentives for quitting such as subsidies for nicotine patches.

• Monitoring of smoking patterns using official statistics over time shows effectiveness of policy interventions.

Policy development process

• Census data Question 21/22: do you smoke? Ever/never/currenthad a major effect on tobacco policy in New Zealand, when it

gave the anti-tobacco lobbies some idea of the magnitude of the phenomenon.

‘Almost everyone recounting the successes of the movement in the last two decades mentions the census as a major stimulant in the campaign’.

Thomson, S cited in Easton, 1995. Smoking in New Zealand: A Census Investigation.

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A Long Term Change in Attitude & Policy: Non-Smoking Policy Development

• First information indicating a possible link between smoking and health came from small clinical analysis and trials. (Statistical analysis/ research)

• E.g. Doll & Hill (1950), etc

De gre e of Lung Damage by Y e ars Smoking

010

203040

5060

7080

0 10 20 30 40 50 60

Num ber of years Sm oked

Lu

ng

Da

ma

ge

• Mean number of years smoked = 31.9• Mean lung damage = 53• Correlation coefficient r=0.774• Best-fitting (regression) line: y = 11.21 + 1.31x• R-squared = (0.774)^2 = 0.6 (60% of variation

explained by line)

Doll and Hill (1950): Case Control study

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Cigarettes/ Day

0 1-4 5-14 15-24 25+ Total

Lung cancer 2 12 36 27 21 98

Control 9 9 50 19 11 98

Br Med J. Sep 30, 1950; 2(4682): 739–748. Smoking and Carcinoma of the Lung

Table XI: most recent amount smoked and disease statusChi-squared=11.68, 4df, p=0.0199

Increased lung cancer mortalityTobacco Statistics 1991 Trends in Tobacco Consumption and Smoking Prevalence in New Zealand (Department of Statistics & Department of Health, 1992)] Dramatic increase in deaths from lung cancer, between 1940 and 1998. An average annual increase for males aged between 35-64 of 6.5% between 1940-1969 and for females of 7.7%.

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Current smoking among those aged 15 years and over, 1983–2008 (unadjusted prevalence)

Sources: ACNielsen NZ Ltd (1983–1995, 1997–2005); 1996 and 2006 Censuses of Population and Dwellings, Statistics New Zealand; 2006/07 New Zealand Health Survey; NZ Tobacco Use Survey 2008

Submission to the Youth Parliament 2010 Health Select Committee Inquiry into creating a smoke-free generation of young Kiwis by 2020, Ministry of Health 2010Note: The 2006 Census recorded 654,000 daily smokers, in 2013 this had dropped to 463,000

A drop of 1% in population prevalence is approx 30,000 smokers.

0

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25

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35

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Year

Percent

Monitoring the impact on smoking

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Prevalence of cigarette smoking (%), by ethnicity, 1990–2005

Per

cen

t

0

10

20

30

40

50

60

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Year

Maori Pacific peoples European/Other

Notesa. The classification of ethnic grouping changed from 1997 onwards, so ethnic specific data before and after 1997 may not be comparable.b. 1990–2002 data points represent the prevalence of cigarette smoking (%) (15+ years).c. 2003 data points represent the prevalence of cigarette smoking (%) (18+ years).d. 2004 data points represent the prevalence of cigarette smoking (%) (15+ years).

Source: ACNielsen (NZ) Ltd

Smoking prevalence not the same for all groupsSubmission to the Youth Parliament 2010 Health Select Committee Inquiry into creating a smoke-free generation of young Kiwis by 2020, Ministry of Health 2010

Further ‘detective’ work Tobacco Statistics: Cancer Society of NZ, 2000 / Statistics New ZealandData source: Statistics New Zealand Censuses of Population and Dwellings

Non-Maori men Maori men

Non-Maori women Maori women

0%

10%

20%

30%

40%

50%

60%

70%

15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+

Smo

kin

g p

reva

len

ce (p

erce

nta

ge o

f po

pu

lati

on

)

Age group

1976

1981

1996

2006

0%

10%

20%

30%

40%

50%

60%

70%

15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+

Smo

kin

g p

reva

len

ce (p

erce

nta

ge o

f po

pu

lati

on

)

Age group

1976

1981

1996

2006

0%

10%

20%

30%

40%

50%

60%

70%

15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+

Smok

ing

prev

alen

ce (p

erce

ntag

e of

pop

ulati

on)

Age group

1976

1981

1996

2006

0%

10%

20%

30%

40%

50%

60%

70%

15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+

Smok

ing

prev

alen

ce (p

erce

ntag

e of

pop

ulati

on)

Age group

1976

1981

1996

2006

Other indicators?-Tobacco consumption‘In 2009, tobacco consumption was 961 cigarette equivalents per person aged 15 years and over, down slightly from 1,011 in 2008. Between 1991 and 2003, tobacco consumption fell by 43 percent, but there has been little change in recent years. Since 1991, the drop in tobacco consumption has been more rapid than the drop in smoking prevalence’. 2010 The Social Report. Te purongo oranga tangata 2010

Tobacco consumption, cigarette equivalents per person aged 15 years and over, 1991–2009

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Source: Statistics New ZealandNote: The data includes cigarettes and tobacco available for consumption.

In the late 1970’s the cigarette equivalents per adult were approximately 3000.

The economic backboneNote: the Statistics New Zealand Business Frame comprises all enterprises (businesses, schools, hospitals, etc.) that contribute to New Zealand’s economy (are GST registered)

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Business Demographics and Dynamics

Business Accounts

National Accounts (GDP, etc)

Balance of Payments

Satellite Accounts (Tourism, Energy, Not

for Profit, Marine)

}} Annual Indicators}

Prices(CPI, PPI, etc)

Monthly(Food Price Index,

Retail Trade, Accommodation etc)

Quarterly(Manufacturing, Building

Activity, Wholesale Trade, Imports & Exports etc.)

Business Frame

}} Sub-annual indicators}

Consumers Price Index (CPI)A measure of how prices that households face have changed over time

Estimated by collecting prices on a basket of actual purchased goods (i.e. by investigating expenditure patterns)

It gives the percentage change between different periods for each class, subgroup, group, or for the overall CPI. 26

Computing a price index

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New Zealand CPI: 1916-2013

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Visualising the 11 components of the CPI

• http://www.stats.govt.nz/datavisualisation/cpi.html 29

The German CPI Price Kaleidoscope https://www.destatis.de/Voronoi/PriceKaleidoscope.svg

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Telling stories with official statistics

Infographics

http://www.stats.govt.nz/browse_for_stats/snapshots-of-nz/infographics.aspx

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Uses of the Consumers Price Index

• By the media to inform the public:of price (and standard of living) changes

• to adjust New Zealand Superannuation and unemployment benefit payments by the government once a year to help ensure that these payments maintain their purchasing power.

• to help set monetary policy:as the Policy Targets Agreement between the Governor of the Reserve Bank and the Minister of Finance, aims to keep annual inflation (CPI) movements between 1 and 3 percent over the medium term. In doing this, the Governor increases or decreases the official cash rate and changes in this rate have an impact on mortgage interest rates that households pay.

• by employers and employees in wage negotiations:The main reason cited by employers for increasing pay rates is to reflect changes in the cost of living (first use of price indices was by the Arbitration Court)

Other Uses of economic statistics• Business decisions

• What is the market (my market segment) doing?• What type of shop would do well in this area?

• Service decisions• How many pre-schools will be needed in the next

decade?• What kind of health services should we have in this

area?• What pension reserves will be needed in future?

• Personal decisions• How long am I likely to live – what kind of

superannuation should I have?• What kind of area do I want to live in?

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Using statistics at a local level- technology enables new ways of visualising datae.g. Dynamic and interactive ‘spider’ maps

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View and explore data by linking web visualisation with a GIS (Geographic Information System )•Local authority planning - public transport, disaster mitigation •Policy analysis - labour market geography

Commuting data in its raw form

Far North District

Whangarei District

Kaipara District

Rodney District

North Shore City

Waitakere City

Auckland City

Manukau City

Total Akld Papakura District

Far North District 16860 396 36 30 36 12 108 42 201 9Whangarei District 285 26379 276 75 57 36 171 54 321 12Kaipara District 42 327 5931 315 33 12 69 27 138 0Rodney District 30 48 126 21183 6822 1701 5706 627 14856 54North Shore City 48 63 24 1755 58383 1905 28188 2604 91077 180Waitakere City 48 48 12 1155 4332 31794 30957 3288 70371 258Auckland City 201 141 39 738 7257 6183 140517 16023 169983 942Manukau City 75 69 18 282 1824 1050 40881 66210 109962 3384Total AKld 372 321 93 3930 71793 40932 240543 88122 441396 4764Papakura District 9 15 0 33 177 84 3894 5079 9231 6567Franklin District 12 15 3 48 171 99 3117 3720 7110 1869

• Large and complex tables• By different sized areas in New Zealand:

o Territorial Authority by Territorial Authority = over 5,000 cells

o Area Unit by Area Unit = more than 3 million cells!o Meshblock by Meshblock… forget it (2 billion cells).

Using official statistics at an international level: country comparisons

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New Zealand’s Better Life Index

http://www.oecdbetterlifeindex.org/countries/new-zealand/

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International principles for official statisticsUnited Nations Statistics Commission Fundamental Principles of Official Statistics (1994)These principles can be summarised as ensuring; 1. Equal access to all to a comprehensive range of social and economic measures; 2. Professional and scientific processes for data collection, processing, storage and presentation; 3. Robust analyses and provision of metadata (information about the data); 4. Official advice of the misinterpretation or misuse of data; 5. Use of appropriate sources of data to maintain quality but minimize respondent burden; 6. Confidentiality of an individual’s information; 7. Transparency of policies and procedures: 8. National coordination of official statistics; 9. International comparability and 10. International cooperation.

… Democratic; High Quality; Confidential; Transparent; Useful

Official statistics are a balancing act

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Constraints: Desires:

Continuity over time Relevance to today

Burden on respondents Information needs

Objectivity Responsiveness

Administrative needs Statistical need

Accuracy Timeliness

Confidentiality Access to data

Principal 6:Privacy, security and confidentiality

PRIVACY –considered at Input (Data collection) stage Should we ask this? What is a person’s right to their own data?

SECURITY – at Processing/Storage/Access stageWho gets to see data? Where /how do we store data?

CONFIDENTIALITY – at Output stageWhat can be found out about individuals?

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Privacy concerns can lead to item nonresponse

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• 12-15% refusal to answer questions about income

(Frick and Grabka, 2007, Item Non-Response and Imputation of Annual Labor Income in Panel Surveys from a Cross-National Perspective: a study of HILDA [Aus], BHPS [UK] and SOEP [Germany])

But not always when you might expect it…

• 3.2% refusal to trial question on gender identity in the UK Integrated Household Survey

(ONS, 2010, Measuring Sexual Identity, an Evaluation Report)

Confidentiality: It pops up everywhere?

Trim datase

t

Tables galoreTables

galoreTables galoreTables

galoreTables galoreTables

galore

Graphs and Analytical

output

Papers

etc

Tables

Microdata

Raw datase

t

A typical Census output table

Ethnic Groups in Wellington Region and New Zealand, 2006 Census

Ethnic groups Region/City/District New Zealand

European  302,973  2,609,589

Māori  55,434  565,326

Pacific peoples  34,752  265,974

Asian  36,477  354,552

Middle Eastern/Latin American/African

 5,346  34,746

Other ethnicity

New Zealander  47,193  429,429

Other ethnicity–other

 159  1,491

     Total  47,352  430,881

Total people  434,034  3,860,16343

Random rounding to base 3

• All cells are a multiple of 3.• Cells are rounded up or down to the nearest three

according to some probability rule.• Marginal cells are randomly rounded independent

of the cells within the table.• Derived values (such as percentages) are calculated

on the randomly rounded values.

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Random rounding to base 3:

Rounded number/Actual number 0 1 2 3 4 5 6

0 1

1 2/3 1/3

2 1/3 2/3

3 1

4 2/3 1/3

5 1/3 2/3

6 1

7 2/3

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Exercise:Using dice to randomly round the following table

Number of people by area and height – made up data

  Height

Area Short Tall Total

Symonds 5 2 7

Grafton 9 2 11

Total 14 4 18

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http://www.bgfl.org/bgfl/custom/resources_ftp/client_ftp/ks1/maths/dice/six.htm If divisible by 3 already – no change, if not: round ‘far’ if roll 5,6, otherwise round ‘near’

Utility and Safety:They form a pool table:

Safe

Unsafe Useless Useful

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The pocket

Raw dataset

Non release

Overview of official statistics• Used by many groups in society –tell social and economic

stories

• Provide base data for government policy development and monitoring

• Have their own methodological challenges

• Provide fun, real-world detective work that CAN make a difference

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Data collection exercise

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