Page 1

HILDA Survey Annual Report 2012


Melbourne Institute of Applied Economic and Social Research Faculty of Business and Economics Building Level 5, 111 Barry Street The University of Melbourne Victoria 3010 Australia T: +61 3 8344 2100 F: +61 3 8344 2111 E: hilda-inquiries@unimelb.edu.au W: www.melbourneinstitute.com/hilda Š 2013 The University of Melbourne, Melbourne Institute of Applied Economic and Social Research. COPYRIGHT: All rights reserved. Apart from fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright Act 1968, no part of this publication may be reproduced, stored or transmitted in any form or by any means without the prior permission in writing of the Publisher. ISSN 1447-476X (Print) ISSN 1447-5812 (Online) Photos by the University of Melbourne, Roy Morgan Research, and the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs. Printed and bound by UniPrint Pty Ltd.


Contents Foreword from the Minister for Families, Community Services and Indigenous Affairs

4

Director’s Report

5

Personnel, 2012

7

Wave 11

10

Presentations and Publications about the HILDA Survey and Data

20

2013 HILDA Survey Research Conference

21

The HILDA Data User Community

22

Publications by HILDA Data Users, 2012 and Forthcoming

25

Accessing the Data

29

HILDA project team meeting: (from left) Nicole Watson, Michelle Summerfield, Mark Wooden, Ninette Macalalad, Simon Freidin

Page 3 – HILDA Survey Annual Report 2012


Foreword from the Minister for Families, Community Services and Indigenous Affairs

The Hon Jenny Macklin, MP

With an ageing population, continuing migration and a low fertility rate, Australia will undergo many changes in the coming decades, presenting opportunities and challenges for all of us. The HILDA Survey is an invaluable resource in helping researchers and policy makers understand the causes and effects of these changes. For 12 years, HILDA has taught us about ourselves—how we juggle work and family life, how we manage our finances, and how we adapt to a changing world. Wave 11 of the HILDA Survey has a strong focus on people’s plans for and their experiences of retirement, fertility and family formation. This new information allows policy makers to understand how people make decisions about starting a family or retiring from the workforce. The rich diversity of our migrant population can be seen in the variety of ancestries and birthplaces reported in the 2012 survey. In 2011, the HILDA Survey interviewed 2,153 new households on top of its continuing sample, allowing it to include new migrants and other Australians, and ensuring the HILDA Survey continues to reflect the great depth and diversity of our people. The HILDA Survey helps policy makers plan ahead to ensure the right policies and programs are in place to support modern families. The Government is ensuring Australia will continue to be a great place to live, work and raise a family, with recent reforms including Australia’s first National Paid Parental Leave scheme, more support for families with children in school, and the National Disability Insurance Scheme, DisabilityCare Australia. With the continuing support of around 13,000 people, the HILDA Survey has collected data about households, income and labour dynamics every year since 2001. I want to acknowledge everyone involved in this year’s HILDA Survey and welcome those households who are responding to the survey for the first time. I especially thank the individuals who have participated in the HILDA Survey every year, giving us important insights into our changing society. Your contribution allows us to build on the strengths of the Australian community and take active steps to shape our future.

The Hon Jenny Macklin, MP Minister for Families, Community Services and Indigenous Affairs

Page 4 – HILDA Survey Annual Report 2012


Director’s Report

“Going forward … it will be very much business as usual for the HILDA Survey, just with a sample that is almost 30 per cent larger.”

Professor Mark Wooden

Overview

Yet again the HILDA Survey can point to another year of outstanding achievements. Most notable was the completion of the first refreshment or top-up sample, with an additional 2,153 households recruited into the HILDA Survey. Further, the achieved household response rate for this top-up was almost 70 per cent, noticeably higher than what was achieved when the HILDA Survey commenced back in 2001. Meanwhile the re-interview rate for the main sample was maintained yet again at a level in excess of 96 per cent. The size of the data user community also continues to grow, with over 520 orders for Data Release 10, the highest yet for any annual data release. It was thus against this background that the Melbourne Institute was successful in securing the contract (following a competitive tender process) from the Department of Families, Housing, Community Services and Indigenous Affairs to manage the HILDA Survey project for Waves 13 to 16 (with an option to extend for a further two years). In turn, the University of Melbourne offered Roy Morgan Research an extension of its sub-contract to continue to provide fieldwork services for the project, which it accepted. Going forward, therefore, it will be very much business as usual for the HILDA Survey, just with a sample that is almost 30 per cent larger.

Wave 11

Data collection for Wave 11 was completed in February 2012. As already mentioned, Wave 11 is notable for the introduction for the first time of a top-up sample. Among members of the ‘original’ or ‘main’ sample a re-interview rate of 96.5 per cent was achieved, and it is the third year in succession we have exceeded 96 per cent. A total of 13,603 persons were successfully interviewed in Wave 11 as part of the main sample, which compares with 13,526 in Wave 10. For the top-up sample, interviews were obtained at 2,153 households out of a total of 3,117 selected households identified as in-scope, giving a household response rate of 69.1 per cent. Within these participating households there were 4,280 persons eligible for interview, 93.7 per cent of whom (4,009) were successfully interviewed. This represents a considerable improvement on the household response rate recorded in Wave 1 (65.7 per cent). Given the accumulated experience of both the survey managers and interviewers, this perhaps should not be surprising.

Page 5 – HILDA Survey Annual Report 2012


Nevertheless, it contrasts with the international experience from both repeated crosssections and other household panel studies, where the accepted wisdom is that it is increasingly difficult to persuade populations to participate in voluntary surveys. Possibly the only disappointing outcome from Wave 11 was the response rate for the self-completion questionnaire, which in the main sample was 87.8 per cent of interviewees, and in the top-up sample just 85.2 per cent. Wave 12

2012 also saw the commencement of fieldwork for our 12th annual survey wave. Key features of the survey content for Wave 12 include: (i) the re-introduction of the sequences on non-co-residential family relationships (with parents, adult children and siblings) previously included in Wave 8; and (ii) the inclusion of new question sequences with a focus on education and skills formation and abilities. Of particular interest, as part of the latter we have included three short ‘tests’ of cognitive ability.

Wave 13

Work also began on the development of the interview scripts and questionnaires for Wave 13. This wave will see the re-inclusion of a module of additional healthrelated questions previously included in Wave 9. We are also testing new questions designed to measure: (i) waist circumference; (ii) quantity and quality of sleep; and (iii) the extent of illicit drug use.

Data users

As noted earlier, the size of the HILDA Survey data user community continues to grow, with over 520 orders for Release 10, the highest in the history of the study to date, and with 175 of these orders from first time users. It is also very pleasing to see both the large number and wide variety of outputs that have made use of the data. Every year the number of published articles, papers and reports continues to grow and I am sure 2013 will be no exception.

Personnel

The HILDA Survey today employs, directly or indirectly, over 200 persons spread across three organisations. The majority of these are employed at Roy Morgan Research, which conducts the fieldwork. Since 2009, when Roy Morgan Research assumed responsibility for the HILDA Survey fieldwork, this small army of people has been managed by Athina Katiforis. During 2012 this came to an end, with Athina moving to the Executive team at Roy Morgan Research. She has been replaced by Tania Sperti, who for two years has effectively been working as Athina’s deputy. I would thus like to thank Athina for her wonderful dedication and service to the HILDA Survey project during four very critical years, and to congratulate Tania on her promotion.

Professor Mark Wooden Project Director

Page 6 – HILDA Survey Annual Report 2012


Personnel, 2012 Melbourne Institute survey management team Director Professor Mark Wooden Deputy Director, Survey Management Ms Michelle Summerfield

External Reference Group

Technical Reference Group

Professor Janeen Baxter (Chair) University of Queensland

Professor Robert Breunig Australian National University

Professor Garry Barrett University of New South Wales

Dr John Henstridge Data Analysis Australia

Dr Bruce Bradbury University of New South Wales

Database Manager Mr Simon Freidin

Professor David de Vaus University of Queensland

Mr Stephen Horn Department of Families, Housing, Community Services and Indigenous Affairs

Database Support Officers Mr Peter Ittak Ms Ninette Macalalad

Dr Ann Evans Australian National University

Mr Ross Watmuff Australian Bureau of Statistics

Deputy Director, Research Associate Professor Roger Wilkins Professorial Research Fellow Professor Richard Burkhauser Research Officer Mr Markus Hahn Deputy Director, Survey Methodology Ms Nicole Watson Survey Methodologist Dr Ning Li

Professor Bryan Rodgers Australian National University Professor Steven Stillman University of Otago Ms Ruth Weston Australian Institute of Family Studies

HILDA FaHCSIA team Dr Annette Neuendorf (Section Manager) Ms Joanne Harrison Ms Deborah Kikkawa Ms Gae Major Ms Jenefer Tan

Administrative Assistant Ms Victoria Lane

Participants in the External Reference Group Meeting, 5 December 2012. Back row (from left): Michelle Summerfield, David de Vaus, Ruth Weston, Garry Barrett, Bryan Rodgers, Nicole Watson Front row (from left): Roger Wilkins, Janeen Baxter, Annette Neuendorf, Mark Wooden Absent: Steven Stillman, Ann Evans, Bruce Bradbury

Page 7 – HILDA Survey Annual Report 2012


Roy Morgan Research HILDA Project team

Isabelle Bertoli

Pam Bowtell

Michael Bradford (Project Manager Systems)

Rinata Buccheri

Chris Brennan

Neil Cabatingan

Lauren Busch

Joshua Button (Systems Team Leader)

Fiona Crockett (Supervisor)

Linda Buttel

Shannon Carter (Sample Support Officer)

Kerrie Dinneen

Frances Carr-Boyd

Nico Disseldorp

Jay Clark

Gary Dunstan (Data Manager)

Joanna El-Masri (Supervisor)

Lisa Coleman

Stephen Gibson (Chief Operations Officer)

Alex Findlay

Andrew Craker

Jemimah Gray

Sean Cranny

Davina Heng (Administration Officer)

Ariel Gross

Beryl Cuff

Roopa Kamath (Sample Support Officer)

Monique Hameed

Anne Dedman

Christine Harding

Lea Densem

William Hollingsworth (Supervisor)

Delwyn Dix

Joelle Horan

Paul Dodds

David Kenshole (Team 1800 Coordinator)

Brendan Howe

Bev Edwards

Ximena Ilich

Sandra Essex

Troy Kohut (General Manager – Customised Research)

Louise La Sala (Supervisor)

Jennifer Eurell

Deborah Louwen (Materials Coordinator)

Tim Macpherson (Supervisor)

Gary Feder

Jasmine Miu

Henry Ferst

Vivek Malpani (Confirmit Programmer)

Jodi Norton (Supervisor)

Anthony Foley

Joshua Osei-Duro

Portia-Ann Forrest

Sigmund Marques (Sample Support Officer)

Brad Paez

Peter George

Mary-Ann Patterson (Interviewer Team Leader and Trainer)

Anna Panipucci

Shaaron Glynn

Paul Pugliese

Kerry Green

Kirk Pereira (Sample Team Leader)

Vaughan Quinn

Sandy Grieve

Shane Pickard (Sample Support Officer)

Lia Sharard

Elizabeth Griffiths

Billy Sheldon

Garry Grooms

Tania Sperti (Project Director, from July 2012)

Daniel Stojkovich (Supervisor)

Tim Haddad

Sean Walton

Pat Timmins (Project Manager Field and Respondent)

Dzemal Hadzismajlovic

Tim Williams

Penelope Hamilton-Smith

Athina Katiforis (Project Director, to July 2012)

Matthew Williamson (General Manager – Operations)

Marie Hammond

HILDA face-to-face field interviewing team

Philip Hands

Jan Alcock

Linda Hill

Cathy Andrew

Louise Hill

HILDA team 1800

Zoe Arslan

Margaret Hocking

Abdul Abdullahi-Mohamed

Farah Aslankoohi

Josie Holland

Eugene Baiden Assan

Francene Beattie

Jan Houghton

Tarun Bajaj

Merril Bennett

Ben Huisman

Rowena York (Sample Team Leader)

Page 8 – HILDA Survey Annual Report 2012

Donna Hickey


Frances Husher

Narelle Nocevski

Rici Tandy

Patricia Huynh

Vicky Nowak

Lynda Taylor

Dylan Hyde

Marta Ogilvie

Ewan Tolhurst

Paul Inglis

Marilyn Paul

Julia Tolj

Kim Jackson

Faye Payne

Fay Tomholt

Andrew James

Shelley Pearce

Suzie Torok

Christine Jolly

Gabriella Pendergast

Ingrid Tozer

Trudy Jones

Cheryl Perrett

Robin Trotter

Richard Joyce

Tara Perrett

Suzanne Turner

Deborah Kairn

Zoe Perrett

Irina Vasilenko

Margaretha Kassanis

David Plant

Tim Walker

Pat Kempster

Sandra Potter

Julia Ward

John Kenney

Beverley Price

Elizabeth Waymark

Ray Kerkhove

Yvette Pryor

Jayne Wiche

Jennie Knight

Ananda Ranasinghe

Marlene Wills

Jenny Komyshan

David Reed

Jilanne Wilson

Paola Kumlin

Margaret Reid

Laurie Wilson

Dianne Lavender

Marg Reynolds

Greg Lay

Lynndal Richards

Christine Leece

Aaron Rinder

Murray Legro

Gillian Rivers

Karen Leslie

Oriana Roinich

Dorothy Lucks

Pat Roy

Additional support

Sue Lukies

Lorna Russell

Murray Bishop

Cindy Macdonald

Roxanne Russell

Rachel Brown

John Macdonald-Hill

Ramiz Sargious

Ken Ferns

Paul McIntyre

Rodney Scherer

Mike Fitzgerald

Lyn McKeaveney

Robyn Schulz

Mark Hall

Jo McKee

George Shaw

Lindsay Lucas

Catherine McMahon

Michelle Short

Asif Malik

Rita Maio

Barry Simpfendorfer

Peter Newby

Dayne Matthews

Beryl Sinapius

Marcus Nguyen

Nabil Mohammad

Barbara Slattery

Deb Perriman

Peter Mulholland

Muriel Smith

Nick Petroulias

Virginia Murphy

Karen Steele

Jared Pool

Don Murray

Phillip Stock

Paul Roach

Rob Neal

Margaret Stubbs

Suvinder Sawhney

Ann Newbery

Helen Szuty

Marcus Tarrant

Marija Nikolic-Paterson

Bridgitte Tadrosse

Sabrina Verhage

Bev Worrall Jayne Wymer Jeffrey Yap

Page 9 – HILDA Survey Annual Report 2012


Wave 11 Top-up sample

As highlighted in the Director’s Report, Wave 11 is notable for the inclusion of a new expansion, or top-up, sample. The process for selecting the top-up sample for Wave 11 was very similar to that used for the main sample in Wave 1. Thus sampling began with a random selection of Census Collection Districts (CDs), with 125 CDs selected (compared with 488 in Wave 1). A total of 3,250 new addresses were issued to field. After the removal of addresses determined to be out of scope and adjusting for addresses with multiple households, the initial top-up sample numbered 3,117 households.

Fieldwork

Given the additional fieldwork required to administer the top-up sample, fieldwork in Wave 11 commenced earlier than in previous waves. Specifically, the Wave 11 interviews commenced towards the end of July 2011 and were completed by mid-February 2012. Table 1 compares the distribution of the interviews over the fieldwork period for each wave. By the end of September, 77 per cent of interviews had been completed for the main sample and 70 per cent for the top-up sample. By the end of December, this figure had risen to 97 per cent for the main sample and 92 per cent for the top-up sample. A total of 167 interviewers were employed on Wave 11. Despite the marked increase in the total sample size, the size of the interviewer workforce was increased only slightly in comparison to Wave 10 (see Table 2). Further, most of this increase was due to an expansion in the size of the Team 1800 telephone interviewers. The number of face-to-face interviewers changed very little, with the greater workload spread among the existing interviewer workforce.

Table 1: Percentage of individual interviews conducted each month, Waves 1 to 11 July

Aug

Sep

Oct

Nov

Dec

Jan

Feb

Mar

Total

Wave 1

1.1

40.2

36.9

14.0

7.4

0.4

100

Wave 2

5.7

55.8

24.8

10.6

0.9

2.1

0.2

100

Wave 3

7.7

57.9

22.9

8.3

1.2

0.2

1.6

100

Wave 4

12.4

60.1

18.0

6.1

1.1

0.2

2.1

100

Wave 5

3.2

53.3

30.5

7.4

1.6

1.5

2.4

100

Wave 6

4.1

57.3

28.0

7.0

1.4

1.1

1.1

100

Wave 7

4.4

55.7

29.3

7.2

0.8

1.3

1.3

100

Wave 8

7.7

57.6

23.1

7.7

1.0

1.4

1.6

100

Wave 9

4.9

54.1

29.1

6.1

1.7

2.1

2.0

100

Wave 10

12.7

50.8

24.6

6.7

1.5

2.3

1.4

100

Wave 11 (MS)

0.3

36.9

40.2

12.3

5.9

1.0

1.9

1.5

0.0

100

Wave 11 (TU)

4.8

47.9

16.8

6.4

13.7

2.0

5.1

3.4

100

Note: MS denotes main sample; TU denotes top-up sample.

Page 10 – HILDA Survey Annual Report 2012


Wave 11 response: main sample

Table 3 describes the progression of the responding individual sample over the first 11 waves. Of those initially interviewed in Wave 1, 8,780 were re-interviewed in Wave 11 (which is 68.9 per cent of those who are still in-scope). The number interviewed in all 11 waves is 7,229. The wave-on-wave response rates for all sample groups are provided in Table 4. The second set of response rates reported in this table are for those individuals belonging to or joining households that responded in the previous wave and thus arguably provides a more realistic comparison of response rates over time, since these people have a recent connection to the study. The response rate for previous wave respondents was, at 96.5 per cent, slightly higher than in the previous wave, and is the highest recorded in the survey’s history. The response rates for previous wave children and new sample entrants to existing households also remain at levels that are reasonably high compared to the survey’s history.

Wave 11 response: top-up sample

For the top-up sample, interviews were obtained at 2,153 households out of the 3,117 selected households identified as in-scope, giving a household response rate of 69.1 per cent. Within these participating households there were 4,280 persons eligible for interview, 93.7 per cent of whom (4,009) were successfully interviewed. This 69 per cent response rate is noticeably higher than the household response rate achieved in Wave 1 (66 per cent) (see Table 5). Given the accumulated experience of both the survey managers and interviewers, this perhaps should not be surprising. Nevertheless, it contrasts with the international experience from both repeated cross-sections and other household panel studies.

Table 2: Number of interviewers and percentage of new interviewers, Waves 1 to 11 Face-to-face interviewers

Telephone interviewers

All interviewers

Percentage new

Number

Percentage new

0

133

100.0

33.8

9

100.0

142

38.0

118

18.6

10

60.0

128

21.9

Wave 4

117

12.8

9

44.4

126

15.1

Wave 5

122

14.8

10

80.0

132

19.7

Wave 6

127

28.3

13

53.8

140

30.7

Wave 7

126

0.6

15

53.3

141

24.1

Wave 8

123

11.4

15

46.7

138

15.2

Wave 9

135

34.1

24

95.8

159

43.4

Wave 10

132

11.4

23

69.6

155

20.0

Wave 11

135

15.6

32

56.3

167

23.4

Number

Percentage new

Wave 1

133

100.0

Wave 2

133

Wave 3

Number

Page 11 – HILDA Survey Annual Report 2012


Table 3: Individual interviews completed, Waves 1 to 11 Wave first interviewed

Wave 1

Wave 2

Wave 3

Wave 4

Wave 5

Wave 6

Wave 7

Wave 8

Wave 9

Wave 10

Wave 11

Wave 1

13,969

11,993

11,190

10,565

10,392

10,085

 9,628

 9,354

 9,245

 9,002

 8,780

Wave 2

 1,048

   705

   594

   572

   542

   512

   483

   488

   475

   461

Wave 3

   833

   543

   482

   429

   403

   376

   383

   365

   354

Wave 4

   706

   494

   426

   408

   369

   374

   362

   348

Wave 5

   819

   578

   511

   462

   459

   441

   407

Wave 6

   845

   641

   545

   525

   499

   468

Wave 7

   686

   509

   448

   427

   409

Wave 8

   687

   526

   491

   445

Wave 9

   853

   640

   583

Wave 10

   824

   599

Wave 11

 4,758

13,969

13,041

12,728

12,408

12,759

12,905

12,789

12,785

13,301

13,526

17,612

Total

Table 4: Individual response rates, Waves 2 to 11 Wave 2

Wave 3

Wave 4

Wave 5

Wave 6

Wave 7

Wave 8

Wave 9

Wave 10

Wave 11 (MS)

Previous wave respondent

86.8

90.4

91.6

94.4

94.9

94.7

95.2

96.3

96.3

96.5

Previous wave non-respondent

19.7

17.6

12.7

14.7

 8.4

 5.6

 5.7

 8.5

 4.5

 3.8

Previous wave child

80.4

71.3

70.7

74.6

75.4

70.8

73.7

73.4

72.0

70.0

New entrant this wave

73.3

76.1

70.4

81.7

81.1

79.7

79.5

81.3

82.9

80.7

Previous wave respondent

86.8

90.4

91.6

94.4

94.9

94.7

95.2

96.3

96.3

96.5

Previous wave non-respondent

19.7

19.8

18.1

25.3

18.3

13.2

15.0

25.9

16.2

15.4

Previous wave child

80.4

81.8

81.2

87.3

89.5

90.5

90.9

93.0

92.3

93.0

New entrant this wave

73.3

78.5

71.8

85.4

81.0

80.2

81.2

81.4

83.5

82.0

All people

People attached to responding household in previous wave

Note: MS denotes main sample.

Page 12 – HILDA Survey Annual Report 2012


SCQ response

Of the 13,603 Wave 11 respondents in the main sample, 11,946 returned a selfcompletion questionnaire (SCQ), resulting in an SCQ response rate of 87.8 per cent. Of the 4,009 Wave 11 top-up respondents 3,415 returned an SCQ, resulting in an SCQ response rate of 85.2 per cent. (See Table 6.) Both these rates are somewhat disappointing, possibly suggesting a return to the longer run downward trend in SCQ responses that had been arrested (and indeed reversed) in Wave 10.

Attrition bias

The fact that not all sample members agree to participate each year raises concerns about the possibility that those who choose to respond are systematically different from those who drop out. Table 7 reports the percentage of Wave 1 respondents who have been re-interviewed, both in all waves (the balanced panel) and in Wave 11, by various respondent characteristics measured at Wave 1. People who have died or moved overseas are excluded from these figures.

Table 5: Wave 1 and Wave 11 top-up sample household outcomes compared

Wave 1

Wave 11 top-up

Sample outcome

Number

Per cent

Number

Per cent

Addresses issued

12,252

3,250

  Less out-of-scope (vacant, non-residential,  foreign)

   804

  212

  Plus multi-households additional to sample

   245

    79

Total households

11,693

100.0

3,117

100.0

Refusals to interviewer

2,670

 22.8

  885

28.4

Refusals to fieldwork company (via 1800 number or email)

   431

  3.7

   16

0.5

Non-response with contact

   469

  4.0

   16

0.5

Non-contact

   441

  3.8

   47

1.5

Fully responding households

 6,872

 58.8

1,963

63.0

Partially responding households

   810

  6.9

  190

6.1

Table 6: SCQ response rates, Waves 1 to 11 Wave 1

Wave 2

Wave 3

Wave 4

Wave 5

Wave 6

Wave 7

Wave 8

Wave 9

Wave 10

Wave 11 (MS)

Wave 11 (TU)

Face-to-face interviews

93.7

93.9

93.5

93.3

91.8

92.7

91.5

90.7

89.3

91.6

90.5

85.7

Phone interviews

52.7

63.3

68.1

68.2

62.3

64.1

62.2

59.7

63.0

62.4

59.6

56.2

Overall

93.5

93.0

92.3

91.9

89.9

90.8

89.0

87.6

86.9

89.0

87.8

85.2

Percentage of phone interviews

 0.5

 3.0

 4.6

 5.6

 6.5

 6.9

 8.4

10.1

 9.1

 8.4

 8.6

 1.8

Note: MS denotes main sample; TU denotes top-up sample.

Page 13 – HILDA Survey Annual Report 2012


Table 7: Percentage of Wave 1 respondents re-interviewed by selected sample characteristics Wave 1 characteristics

In all waves

In Wave 11

Area

Wave 1 characteristics

In all waves

In Wave 11

Indigenous status

 Sydney

54.3

66.4

 Indigenous

44.7

68.9

  Rest of New South Wales

60.2

70.4

 Non-Indigenous

58.4

68.0

 Melbourne

56.1

68.2

Education attainment

  Rest of Victoria

55.3

64.8

  Year 11 or below

53.2

64.4

 Brisbane

62.6

71.1

  Year 12

55.8

67.4

  Rest of Queensland

60.3

70.0

  Certificate

57.5

68.4

 Adelaide

61.8

71.6

 Diploma

65.1

74.7

  Rest of South Australia

57.7

71.5

  Degree or higher

68.7

77.9

 Perth

59.1

67.4

Dwelling type

  Rest of Western Australia

54.6

68.1

 House

58.4

69.3

 Tasmania

58.6

69.3

 Semi-detached

59.8

69.8

  Northern Territory

73.4

87.9

  Flat, unit, apartment

53.3

63.7

  Australian Capital Territory

60.8

73.0

 Other

51.8

64.3

Sex

Labour force status

 Male

56.4

67.5

  Employed full-time

58.6

69.6

 Female

59.6

70.0

  Employed part-time

61.0

72.3

 Unemployed

46.7

58.6

57.1

67.0

Age group (years)  15–19

42.3

60.5

  Not in the labour force

 20–24

46.2

62.5

Employment status in main joba

 25–34

55.4

67.8

 Employee

59.3

70.6

 35–44

60.7

70.8

 Employer

57.3

67.7

 45–54

62.9

71.8

  Own account worker

61.3

70.6

 55–64

67.5

75.8

  Contributing family worker

57.1

74.2

 65–74

67.1

73.2

Occupationa

 75+

41.0

47.7

 Managers/administrators

63.4

74.6

 Professionals

68.2

77.9

Marital status  Married

61.6

70.7

  Associate professionals

59.1

70.0

  De facto

55.3

68.1

 Tradespersons

53.8

66.0

 Separated

59.1

69.7

  Advanced clerical/service

58.7

69.3

 Divorced

66.5

75.9

  Intermediate clerical/sales/service

59.6

70.8

 Widowed

60.0

65.5

  Intermediate production/transport

53.6

62.8

 Single

48.3

63.7

  Elementary clerical/sales/service

55.9

68.8

 Labourers

50.7

63.3

59.7

70.4

58.1

68.9

7,229

8,780

Country of birth  Australia  Overseas

Total

   Main English-speaking

60.5

69.2

  Other

47.3

60.3

Note: (a) Employed sub-sample only.

Page 14 – HILDA Survey Annual Report 2012

Number responding


As we have noted in previous Annual Reports, the likelihood of having responded in every wave is relatively low for people who in Wave 1 were: • relatively young (aged between 15 and 24 years); • born in a non-English-speaking country; • of Aboriginal or Torres Strait Islander descent; • single; • unemployed; or • working in low-skilled occupations. Nevertheless, there is still a reasonably high level of engagement among most respondents in these groups. Take Indigenous people for example, while less than half of the Indigenous respondents have been re-interviewed every wave, 69 per cent were interviewed in Wave 11, which is slightly higher than the proportion of non-Indigenous sample members. Fortunately, the extensive array of characteristics collected over time means that many of the characteristics of attritors can be identified and hence controlled for in analyses of the data. Users can either directly model the attrition process or use the weights included in the dataset. Top-up sample characteristics

Table 8 provides a summary of selected characteristics of respondents in the top-up sample compared to population estimates from the Australian Bureau of Statistics (ABS) Labour Force Survey. The top-up sample, like the main sample selected in 2001, is intended to be broadly representative of the wider population. There are, however, some differences between the top-up sample and the ABS estimates. Specifically, and similar to what was found in the main sample in 2001: • Sydney residents are under-represented; • males are less likely to respond than females; and • married people are more likely to respond than unmarried people (though this may reflect the exclusion from the HILDA sample of people living in institutions rather than any difference in response likelihood). Unlike our main sample in 2001 where immigrants from a non-English-speaking background were under-represented and Australian-born people were overrepresented, we have a different result for the top-up sample. Here people born overseas in (the main) English-speaking countries are over-represented. This is perhaps because the saliency of being included in a top-up sample in 2011 is strongest for those who did not have a chance of being included in the main sample in 2001. The differences between the HILDA Survey estimates and the Labour Force Survey are mostly eliminated through the use of weights which adjust for differences in the probability of selection and response. Indeed, the HILDA Survey estimates for area of usual residence, sex, age, marital status and employment status will match the Labour Force Survey estimates exactly as these are used to calibrate the HILDA weights.

Page 15 – HILDA Survey Annual Report 2012


Table 8: Selected Wave 11 individual top-up sample characteristics compared to ABS estimates (per cent) HILDA top-upa

ABSb

Area

HILDA top-upa

ABSb

Sex

 Sydney

17.4

20.4

 Male

47.8

49.3

  Rest of New South Wales

13.5

12.0

 Female

52.2

50.7

 Melbourne

17.8

18.4

Marital status

  Rest of Victoria

 6.3

 6.7

  Married/De facto

63.2

58.2

 Brisbane

 9.8

 8.9

  Not married

36.8

41.8

  Rest of Queensland

10.2

11.1

Indigenous

 2.5

 2.1

 Adelaide

 7.3

 5.5

Birthplace

  Rest of South Australia

 2.2

 2.0

  Born in Australia

68.7

70.1

 Perth

 6.3

 7.7

  Main English-speaking country

13.0

10.8

  Rest of Western Australia

 3.5

 2.6

  Other country

18.3

19.1

 Tasmania

 3.7

 2.2

Labour force status

  Northern Territory

 0.5

 0.9

  Employed full-time

41.4

44.3

  Australian Capital Territory

 1.5

 1.6

  Employed part-time

20.9

18.3

 Unemployed

 3.6

 3.4

34.0

34.0

Age (years) at 30 September  15–19

 8.5

 8.1

  Not in the labour force

 20–24

 8.3

 9.0

Employment status in main job

 25–34

17.1

17.8

(employed persons only)

 35–44

18.6

17.3

 Employee

90.3

89.2

 45–54

15.8

16.6

 Employer

 2.0

 2.9

 55–64

14.5

14.1

  Own account worker

 7.3

 7.8

 65+

17.3

17.1

  Contributing family worker

 0.4

 0.0

Notes: (a) The HILDA estimates are for people aged 15 years and over in the top-up sample, but include defence force personnel and exclude people living in very remote parts of Australia and those living in special dwellings. The HILDA estimates have been weighted by the design weight which adjusts for the probability of selection. (b) The ABS estimates come from the Labour Force Survey for September 2011 (or May 2011 for education, August 2011 for occupation, industry and employment status, and 2011 in general for Indigenous status). With the exception of country of birth, the population that these estimates apply to includes all civilians aged 15 years and over. The country of birth figures exclude people living in institutions.

Page 16 – HILDA Survey Annual Report 2012


Combining the main and top-up samples

One of the main reasons for adding the top-up sample was to address an issue of bias creeping into the weighted cross-sectional HILDA estimates due to the inability of the ‘following rules’ to capture a representative sample of recent immigrants. Figure 1 shows that since the study began in 2001, the cross-sectional HILDA Survey estimate for the proportion of people aged 15 and older who arrived in Australia in 2001 or later is markedly different from the ABS Labour Force Survey estimate. By 2011, the two estimates differ by 7 percentage points. This gap is greatly reduced by the inclusion of the top-up sample and the use of the weights developed for the combined sample. The amount of bias that this lack of recent immigrants can inject into the crosssectional estimates between 2002 and 2010 will vary depending on how strongly associated the variables are to immigration. An example of a variable that is highly affected is country of birth. Figure 2 shows the proportion of the Australian population aged 15 and over who were born in Australia. Over the nine-year period between 2001 and 2010, the HILDA estimate suggests that the proportion of the adult population born in Australia has been increasing over time, whereas for the same period, the ABS Labour Force estimate has been declining. Again, combining the main sample with the top-up sample removes this bias from the HILDA Survey estimates. Figure 1: Proportion born overseas and arrived in 2001 or later (aged 15+), 2001 to 2011 0.12

HILDA main HILDA combined

0.10

ABS Labour Force Survey 0.08

0.06

0.04

0.02

0 2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Page 17 – HILDA Survey Annual Report 2012


While the impact of the top-up sample on country of birth and year of arrival is quite large, many variables will only have a small impact or none at all. Table 9 compares the estimates from the ABS Labour Force Survey with those from the main sample and the combined sample. The combined estimate is generally very similar to the estimate from the main sample alone. Where there are differences, the combined estimate is usually closer to the ABS estimate than the main sample. There are, however, two exceptions: the highest level of education and the number of hours worked. Differences in the questions asked and the use of proxy interviews by the ABS may explain some of these results. Users of the HILDA data who would like more information about the top-up sample, how the two samples have been combined and the impact this has had on the cross-sectional estimates are directed to a recently released paper in the HILDA Technical Paper series entitled Longitudinal and Cross-Sectional Weighting Methodology for the HILDA Survey. Figure 2: Proportion born in Australia (aged 15+), 2001 to 2011 0.80

HILDA main

0.78

HILDA combined ABS Labour Force Survey

0.76 0.74 0.72 0.70 0.68 0.66 2001

Page 18 – HILDA Survey Annual Report 2012

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011


Table 9: Wave 11 respondent characteristics and comparisons with the ABS Labour Force Survey (per cent)

Wave 11 characteristics

Combined Main sample sample

ABS

Relationship in household Couple with children <15

21.7

21.6

22.0

Wave 11 characteristics

Combined Main sample sample

ABS

Indigenous

 2.5

 2.2

 2.1

Part-time workera

32.0

32.8

30.6

Managers

13.0

13.2

13.0

Professionals

23.3

23.5

21.6

Technicians and trade workers

14.7

13.7

14.2

Community and personal service workers

 9.5

10.0

 9.7

Occupationa

Couple with dependent student (no child <15)

 5.5

 5.7

 4.5

Couple with non-dependent children

 5.7

 5.4

 5.1

Couple without children

26.3

26.6

27.7

Lone parent with children <15

 2.7

 2.8

 3.0

Lone parent with dependent student (no child <15)

 1.0

 1.0

 0.8

15.4

14.8

15.1

Lone parent with nondependent children

Clerical and administrative workers

 2.6

 2.2

 1.7

Sales workers

 9.1

 9.3

9.4

Dependent student

 8.7

 8.6

 7.1

Machinery operators and drivers

 6.0

 5.8

 6.8

Labourers

 9.1

 9.7

10.2

Health care and social assistance

12.1

12.5

11.7

Retail trade

10.7

10.6

10.8

Construction

 8.4

 8.4

 9.1

Manufacturing

 8.4

 8.2

 8.3

Other industries

60.6

60.3

60.1

Employee

90.5

90.4

89.2

Employer

 2.2

 2.1

 2.9

Non-dependent child

 9.6

 8.5

 8.5

Other family member

 2.7

 3.2

 2.6

Unrelated to all household members

 1.9

 3.0

 5.2

Lone person

11.6

11.6

11.8

Highest level of education (15–64 year olds) Masters or doctorate

 4.1

 5.5

 4.6

Grad diploma or grad certificate

 5.0

 5.3

 2.1

Bachelor or honours

14.6

15.7

17.0

Advanced diploma or diploma

 8.6

 8.9

 9.1

Certificate IV or III

21.3

20.6

17.4

Year 12

19.0

17.9

20.6

Year 11 or below (incl. Cert I, II, n.f.d.)b

27.2

26.1

29.1

Undetermined

 0.1

 0.1

Country of birth Australia

75.5

70.0

70.1

Main English-speaking

 8.8

10.8

10.8

Other country

15.7

19.2

19.1

Before 1971

27.9

22.3

24.0

1971–1980

14.2

11.2

11.6

1981–1990

25.7

17.0

16.8

1991–2000

24.6

16.5

16.4

2001–2005

 4.0

 9.7

 9.8

2006–2011

 3.6

23.4

21.4

Year of arrival (if born overseas)

Industrya

Employment

statusa

Own account worker

 7.1

 7.2

 7.8

Contributing family member

 0.3

 0.3

 0.0

0

 0.1

 0.0

 0.2

1–15

12.4

12.7

11.6

16–29

13.5

14.0

13.0

30–34

 6.0

 6.1

 5.7

35–39

19.2

19.6

23.4

40

16.9

16.3

19.7

41–44

 4.2

 4.3

 3.2

Usual hours

workeda

45–49

 9.2

 9.1

 7.1

50–59

11.6

10.9

 9.3

60+

 6.9

 6.9

 6.7

Notes: (a) Employed sub-sample only. (b) n.f.d. denotes not further defined.

Page 19 – HILDA Survey Annual Report 2012


Presentations and Publications about the HILDA Survey and Data Publications Watson, N. and Wooden, M., ‘The HILDA Survey: A Case Study in the Design and Development of a Successful Household Panel Study’, Longitudinal and Life Course Studies, vol. 3, no. 3, pp. 369–381. Wilkins, R. and Warren, D., Families, Incomes and Jobs, Volume 7: A Statistical Report on Waves 1 to 9 of the Household, Income and Labour Dynamics in Australia Survey, Melbourne Institute of Applied Economic and Social Research, University of Melbourne, July.

Melbourne Institute Working Paper Series Watson, N. and Wilkins, R., ‘Experimental Change from Paper-Based Interviewing to ComputerAssisted Interviewing in the HILDA Survey’, no. 6/12, February.

Presentations/conference papers Li, N., ‘Testing Survey Data for Rounding Errors’, Paper presented at the SSAI Australian Statistical Conference, Adelaide, 9–12 July. Watson, N., ‘HILDA Data Security’, Presentation at the Symposium on the Disclosure Risk of Linked and Longitudinal Data, Canberra, 27 April. Watson, N., ‘Measuring Employment: Exploring Bias in Inequality Research’, Paper presented at the RC33 Eighth International Conference on Social Science Methodology, Sydney, 9–13 July. Watson, N., ‘A Tale of Two Surveys: Panel Attrition, Health and Employment’, Paper presented at the 3rd International Panel Survey Methods Workshop, Melbourne, 5–6 July.

HILDA Discussion Paper Series Watson, N. and Wilkins, R., ‘The Impact of Computer-Assisted Interviewing on Interview Length’, no. 1/12, April.

HILDA Technical Paper Series Watson, N., ‘Longitudinal and Cross-Sectional Weighting Methodology for the HILDA Survey’, no. 2/12, December. Wooden, M., Mackinnon, A., Rodgers, B. and Windsor, T., ‘The Development of Cognitive Ability Measures in the HILDA Survey’, no. 1/12, June.

Page 20 – HILDA Survey Annual Report 2012

Watson, N., ‘Weighting Issues in Longitudinal Surveys: HILDA’s Experience’, Presentation at the Symposium on Analysis of Longitudinal Data, Canberra, 16 October. Watson, N., ‘Weighting Strategy to Integrate a New Top-Up Sample with an Ongoing Longitudinal Sample’, Paper presented at the SSAI Australian Statistical Conference, Adelaide, 9–12 July. Wilkins, R., ‘Recent Developments in the HILDA Survey’, Presentation to the ABS Labour Statistics Advisory Group, Canberra, 12 December. Wooden, M., ‘The Development of a Successful Household Panel Survey: The HILDA Experience’, Presentation at the MOTU Research Workshop ‘Issues and Options for a NZ Household Panel Survey’, Wellington (NZ), 20 August.


2013 HILDA Survey Research Conference The 2013 HILDA Survey Research Conference will be held on 3 and 4 October 2013 at the University of Melbourne. The aim of the conference is to provide a forum for the discussion of research based on the Household, Income and Labour Dynamics in Australia (HILDA) Survey. Attendance at the conference is open to all, but should be of special interest to users of the HILDA Survey data as well as persons with an interest in the outcomes from longitudinal survey research in the broad field of economic and social policy. An official call for papers has been made, and as in past years we will cover all travel and accommodation costs for Australian-based presenters, as well as offer travel subsidies for a select number of overseas-based presenters. There will be two submission streams: a refereed stream and a non-refereed stream. Selection of papers for the refereed stream will be on the basis of full papers while selection of papers for the non-refereed stream will be on the basis of abstracts. Competition for places is expected to be high, with priority being given to papers that exploit the longitudinal nature of the data. Papers on methods and crossnational comparisons are also welcome. Further details about this upcoming conference can be found on the HILDA Survey website at http://www.melbourneinstitute.com/miaesr/events/conferences/

Page 21 â&#x20AC;&#x201C; HILDA Survey Annual Report 2012


The HILDA Data User Community Data users: How many and who are they?

As shown in Table 10, the total number of persons who have been approved access to at least one of the 10 public data releases has steadily been growing. There were just over 200 users of the first version released in late 2002. By the end of November 2012, this total had grown to 1,726. In addition, there were 90 users of the HILDA-Cross-National Equivalent File (HILDA-CNEF). Further details about the composition of our user community are provided in Table 11. Table 10: HILDA data user community, Releases 1 to 10 Total data orders

Orders by new users

Release 1

204

204

204

Release 2

265

169

373

Release 3

279

157

530

Release 4

329

176

706

Release 5

387

196

902

Release 6

401

176

1,078

Release 7

455

199

1,277

Release 8

431

125

1,402

Release 9

500

141

1,543

Release 10

529

180

1,726

Release

Cumulative number of users

Table 11: HILDA data users by type, Releases 1 to 10 Rel. 1

Rel. 2

Rel. 3

Rel. 4

Rel. 5

Rel. 6

Rel. 7

Rel. 8

Rel. 9

Rel. 10 30 Nov 2012

Academic: Australia

 84

112

126

142

169

178

206

199

241

257

Academic: Overseas

  5

 15

 18

 19

 24

 25

 37

 24

 51

 65

Student: Honours year

  3

 13

 16

 15

 13

  7

 13

 17

 13

 22

Student: Postgraduate

  9

 16

 18

 31

 42

 41

 40

 44

 59

 63

Government: Commonwealth

 87

 87

 82

103

120

134

137

120

112

114

Government: State/Local

  8

 14

  8

 11

   8

  5

 10

  6

  9

  7

Other

  8

  8

 11

  8

  11

 11

 12

 21

 15

  1

Total

204

265

279

329

387

401

455

431

500

529

Type of user

Organisational Licences

At the end of November 2012, the number of individuals on a Deed of Confidentiality under the Organisational Licence for Release 10 was 366, compared to 163 individuals who signed an individual Deed of Licence. In addition, there was a cumulative total of 91 organisations with an Organisational Deed of Licence:

Page 22 – HILDA Survey Annual Report 2012


• ANZ Banking Group Limited • Australian Bureau of Agricultural and Resource Economics and Sciences • Australian Bureau of Statistics • Australian Consortium for Social and Political Research Incorporated • Australian Council for Educational Research • Australian Council of Trade Unions • Australian Government Department of Human Services • Australian Institute of Family Studies • Australian Institute of Health and Welfare • Australian Taxation Office • Australian Treasury • Bureau of Crime Statistics and Research (NSW) • Business Council of Australia • Cape York Institute for Policy and Leadership • Catholic Archdiocese of Sydney • Commonwealth Scientific and Industrial Research Organisation, Human Nutrition Division • CQ University, Institute for Health and Social Science Research • Deakin University • Deloitte Access Economics Pty Ltd • Department of Community Services (NSW) • Department of Education and Communities (NSW) • Department of Education, Employment and Workplace Relations • Department of Families, Housing, Community Services and Indigenous Affairs • Department of Finance and Deregulation • Department of Human Services, Government of Victoria • Department of Immigration and Citizenship • Department of Industry, Innovation, Science, Research and Tertiary Education • Department of the Premier and Cabinet, Government of Western Australia • Department of the Prime Minister and Cabinet • Economic and Social Research Institute • Fair Work Commission • Flinders University • Gender and Work Database • Grattan Institute • Griffith University • Industry Super Network • Ingham Institute for Applied Medical Research • IZA Institute for the Study of Labor • James Cook University • La Trobe University, Rural Health School • London School of Economics, Research Laboratory • Macquarie University • Monash University • Motu Economic and Public Policy Research • Murdoch Children’s Research Institute • Murdoch University • National Centre for Vocational Education Research

• New Zealand Social Statistics Network • New Zealand Treasury • Open University • Organisation for Economic Co-operation and Development • Parenting Research Centre • Productivity Commission • Queensland University of Technology • Reserve Bank of Australia • Rice Warner Actuaries Pty Ltd • RMIT University ‘‘ AHURI Research Centre ‘‘ School of Economics, Finance and Marketing • Swinburne University of Technology • Telethon Institute for Child Health Research • The Australia Institute • The Smith Family • The World Bank Group • Towers Watson Australia Pty Ltd • University College Dublin • University of Adelaide • University of Canberra, NATSEM • University of Essex, Institute for Social and Economic Research • University of Georgia, Department of Sociology • University of Melbourne ‘‘ Centre for Human Resource Management ‘‘ Department of Economics ‘‘ Department of Management and Marketing ‘‘ School of Languages and Linguistics ‘‘ School of Population Health • University of New South Wales • University of Newcastle, Centre of Full Employment and Equity • University of Otago ‘‘ Division of Commerce ‘‘ Division of Health Sciences • University of Queensland • University of Sheffield • University of South Australia • University of St Gallen • University of Sydney ‘‘ Faculty of Agriculture, Food and Natural Resources ‘‘ Faculty of Health Sciences ‘‘ School of Economics ‘‘ School of Public Health • University of Technology, Sydney • University of Washington, Foster School of Business • University of Western Sydney • University of Wollongong • University of York • University of Zurich, Institute of Political Science • Victoria University of Wellington

Page 23 – HILDA Survey Annual Report 2012


HILDA user training 2012

April 2012 and September 2012 •

Getting Started: Analysing HILDA with STATA Wednesday 11 April and Thursday 12 April and Monday 10 September to Wednesday 12 September Designed for people who are interested in using the HILDA Survey data but have not yet done so

November 2012 •

Panel Data Analysis Techniques with HILDA Examples Tuesday 27 November to Thursday 29 November Lecture series plus hands-on training with STATA examples Dynamic Modelling for Panel Data Friday 30 November Lecture series with worked examples (does not include hands-on training)

Mary-Ann Patterson leads interviewer training (Melbourne)

Page 24 – HILDA Survey Annual Report 2012


Publications by HILDA Data Users, 2012 and Forthcoming Journal articles Ambrey, C.L. and Fleming, C.M., ‘Valuing Australia’s Protected Areas: A Life Satisfaction Approach’, New Zealand Economic Papers, vol. 46, no. 3, pp. 191–209. Baker, D., ‘Match Making: Finding People Missing Out on Government Assistance’, Journal of Economic and Social Policy, vol. 15, no. 1, article no. 3. Barrett, G.F. and Brzozowski, M., ‘Food Expenditure and Involuntary Retirement: Resolving the RetirementConsumption Puzzle’, American Journal of Agricultural Economics, vol. 95, no. 4, pp. 945–955. Baxter, J., Qu, L., Weston, R., Moloney, L. and Hayes, A., ‘Experiences and Effects of Life Events: Evidence from Two Australian Longitudinal Studies’, Family Matters, vol. 90, pp. 6–18. Bechtel, L., Lordan, G. and Prasada Rao, D.S., ‘Income Inequality and Mental Health: Empirical Evidence from Australia’, Health Economics, vol. 21, no. S1, pp. 4–17. Bentley, R., Baker, E. and Mason, K., ‘Cumulative Exposure to Poor Housing Affordability and Its Association with Mental Health in Men and Women’, Journal of Epidemiology and Community Health, vol. 66, no. 9, pp. 761–766. Black, D., Polidano, C. and Tseng, Y., ‘The Re-engagement in Education of Early School Leavers’, Economic Papers, vol. 31, no. 2, pp. 202–215. Booth, A., Leigh, A. and Varganova, E., ‘Does Ethnic Discrimination Vary across Minority Groups? Evidence from a Field Experiment’, Oxford Bulletin of Economics and Statistics, vol. 74, no. 4, pp. 547–573. Brandon, P.D., ‘The Rise of ThreeGeneration Households among Households Headed by Two Parents and Mothers Only in Australia’, Journal of Family and Economic Issues, vol. 33, no. 3, pp. 376–388. Breunig, R., Gong, X. and King, A., ‘Partnered Women’s Labour Supply and Child Care Costs in Australia:

Measurement Error and the Child Care Price’, Economic Record, vol. 88, Special Issue, pp. 51–69. Brown, M., ‘Responses to Work Intensification: Does Generation Matter?’, International Journal of Human Resource Management, vol. 23, no. 17, pp. 3,578–3,595. Brown, H. and Adams, J., ‘The Role of Time Preference in Smoking Cessation: A Longitudinal Analysis of Data from the Household Income and Labour Dynamics of Australia Survey, 2001–08’, Journal of Epidemiology and Community Health, vol. 66, no. S1, pp. A51–A52. Brown, H. and Adams, J., ‘The Role of Time Preference in Smoking Cessation: A Longitudinal Analysis of Data from the Household Income and Labour Dynamics of Australia Survey, 2001– 08’, Society for the Study of Addiction, vol. 108, no. 1, pp. 186–192. Cai, L. and Waddoups, C.J., ‘Unobserved Heterogeneity, Job Training, and the Employer Size–Wage Effect in Australia’, Australian Economic Review, vol. 45, no. 2, pp. 158–175. Cobb-Clark, D.A., ‘That Pesky Problem of Persistent Gender Bias’, Australian Economic Review, vol. 45, no. 2, pp. 211–215. Cobb-Clark, D.A. and Ribar, D., ‘Financial Stress, Family Conflict, and Australian Youths’ Transitions from Home and School’, Review of Economics of the Household, vol. 10, no. 4, pp. 469–490. Cobb-Clark, D.A. and Schurer, S., ‘The Stability of Big-Five Personality Traits’, Economics Letters, vol. 115, no. 1, pp. 11–15. Cvetkovski, S., Reavley, N.J. and Jorm, A.F., ‘The Prevalence and Correlates of Psychological Distress in Australian Tertiary Students Compared to Their Community Peers’, Australian and New Zealand Journal of Psychiatry, vol. 46, no. 5, pp. 457–467. Dickerson, A. and Green, F., ‘Fears and Realisations of Employment Insecurity’, Labour Economics, vol. 19, no. 2, pp. 198–210.

Dockery, A.M., ‘Deriving the Labor Supply Curve from Happiness Data’, Economics Letters, vol. 117, no. 3, pp. 898–900. Dorian, J. and Skinner, N., ‘Alcohol Consumption Patterns of Shiftworkers Compared with Dayworkers’, Chronobiology International, vol. 29, no. 5, pp. 610–618. Emerson, E., Llewellyn, G., Honey, A. and Kariuki, M., ‘The Lower WellBeing of Young Australian Adults with Self-Reported Disability Reflects Their Poorer Living Conditions Rather than Health Issues’, Australian and New Zealand Journal of Public Health, vol. 36, no. 2, pp. 176–182. Feeny, S., Ong, R., Spong, H. and Wood, G., ‘The Impact of Housing Assistance on the Employment Outcomes of Labour Market Programme Participants in Australia’, Urban Studies, vol. 49, no. 4, pp. 821–844. Foster, G., Frijters, P. and Johnston, D.W., ‘The Triumph of Hope over Disappointment: A Note on the Utility Value of Good Health Expectations’, Journal of Economic Psychology, vol. 33, no. 1, pp. 206–214. Frijters, P. and Beatton, T., ‘The Mystery of the U-Shaped Relationship between Happiness and Age’, Journal of Economic Behavior and Organization, vol. 82, nos 2–3, pp. 525–542. Frijters, P., Johnston, D.W. and Shields, M.A., ‘The Optimality of Tax Transfers: What Does Life Satisfaction Data Tell Us?’, Journal of Happiness Studies, vol. 13, no. 5, pp. 821–832. Gatina, L., ‘The Impact of Home Institutions on the Financial Risk of Immigrants: Evidence from Australia’, International Journal of Diversity in Organizations, Communities and Nations, vol. 11, no. 4, pp. 37–54. Guven, C., Senik, C. and Stichnoth, H., ‘You Can’t Be Happier than Your Wife. Happiness Gaps and Divorce’, Journal of Economic Behavior and Organization, vol. 82, no. 1, pp. 110–130.

Page 25 – HILDA Survey Annual Report 2012


Hewitt, B. and Baxter, J., ‘Who Gets Married in Australia? The Characteristics Associated with a Transition into First Marriage 2001–6’, Journal of Sociology, vol. 48, no. 1, pp. 43–61. Hewitt, B., Turrell, G. and Giskes, K., ‘Marital Loss, Mental Health and the Role of Perceived Social Support: Findings from Six Waves of an Australian Population Based Panel Study’, Journal of Epidemiology and Community Health, vol. 66, no. 4, pp. 308–314. Johnston, D.W. and Lee, W., ‘Climbing the Job Ladder: New Evidence of Gender Inequity’, Industrial Relations, vol. 51, no. 1, pp. 129–151. Jorm, A.F., Bourchier, S.J., Cvetkovski, S. and Stewart, G., ‘Mental Health of Indigenous Australians: A Review of Findings from Community Surveys’, Medical Journal of Australia, vol. 196, no. 2, pp. 118–121. Katsaiti, M.S., ‘Obesity and Happiness’, Applied Economics, vol. 44, no. 31, pp. 4,101–4,115. Kifle, T. and Desta, I.H., ‘The Relationship between Body Mass Index and Socioeconomic and Demographic Indicators: Evidence from Australia’, International Journal of Public Health, vol. 57, no. 1, pp. 135–143. Kim, S., Sargent-Cox, K.A., French, D.J., Kendig, H. and Anstey, K.J., ‘Cross-National Insights into the Relationship between Wealth and Wellbeing: A Comparison between Australia, the United States of America and South Korea’, Ageing and Society, vol. 32, no. 1, pp. 41–59. Kortt, M.A. and Dollery, B., ‘Religion and the Rate of Return to Human Capital: Evidence from Australia’, Applied Economics Letters, vol. 19, no. 10, pp. 943–946. Kortt, M.A., Dollery, B. and Grant, B., ‘Protestantism and Work Ethic: Evidence from Australia’, Empirical Economic Letters, vol. 11, no. 2, pp. 197–202. Kortt, M.A., Dollery, B. and Pervan, S., ‘Religion and Education: Recent Evidence from the US’, Applied Economics Letters, vol. 19, no. 12, pp. 1,175–1,178.

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Leach, L., Butterworth, P. and Whiteford, H.A., ‘Private Health Insurance, Mental Health and Service Use in Australia’, Australian and New Zealand Journal of Psychiatry, vol. 46, no. 5, pp. 468–475. Leach, L., Pirkis, J. and Kelaher, M., ‘Poor Mental Health Influences Risk and Duration of Unemployment: A Prospective Study’, Social Psychiatry and Psychiatric Epidemiology, vol. 47, no. 6, pp. 1,013–1,021. Lucas, R.E. and Donnellan, M.B., ‘Estimating the Reliability of SingleItem Life Satisfaction Measures: Results from Four National Panel Studies’, Social Indicators Research, vol. 105, no. 3, pp. 323–331. Luhmann, M., Lucas, R.E., Eid, M. and Diener, E., ‘The Prospective Effect of Life Satisfaction on Life Events’, Social Psychological and Personality Science, vol. 4, no. 1, pp. 39–45. McPhedran, S., ‘The Labour of a Lifetime? Health and Occupation Type as Predictors of Workforce Exit among Older Australians’, Journal of Aging and Health, vol. 24, no. 3, pp. 345–360. Magee, C.A., Stefanic, N., Caputi, P. and Iverson, D.C., ‘The Association between Job Demands/Control and Health in Employed Parents: The Mediating Role of Work-to-Family Interference and Enhancement’, Journal of Occupational Health Psychology, vol. 17, no. 2, pp. 196–205. Mavromaras, K. and McGuinness, S., ‘Overskilling Dynamics and Education Pathways’, Economics of Education Review, vol. 31, no. 5, pp. 619–628. Mavromaras, K., Sloane, P. and Wei, Z., ‘The Role of Education Pathways in the Relationship between Job Mismatch, Wages and Job Satisfaction: A Panel Estimation Approach’, Education Economics, vol. 20, no. 3, pp. 303–321. Nicholas, A. and Ray, R., ‘Duration and Persistence in Multidimensional Deprivation: Methodology and Australian Application’, Economic Record, vol. 88, no. 280, pp. 106–126. Oguzoglu, U., ‘Is There a Better Measure of Self-Assessed Disability?’,

Applied Economics Letters, vol. 19, no. 14, pp. 1,335–1,338. Olesen, S.C., Butterworth, P. and Rodgers, B., ‘Is Poor Mental Health a Risk Factor for Retirement? Findings from a Longitudinal Population Survey’, Social Psychiatry and Psychiatric Epidemiology, vol. 47, no. 5, pp. 735–744. Ong, R. and Shah, S., ‘Job Security Satisfaction in Australia: Do Migrant Characteristics and Gender Matter?’, Australian Journal of Labour Economics, vol. 15, no. 2, pp. 123–139. Parr, N., ‘Trends in Differentials in the Workforce Participation of Mothers with Young Children in Australia 2002– 2008’, Journal of Population Research, vol. 29, no. 3, pp. 203–227. Rehm, P., Hacker, J.S. and Schlesinger, M., ‘Insecure Alliances: Risk, Inequality, and Support for the Welfare State’, American Political Science Review, vol. 106, no. 2, pp. 386–406. Richardson, S., Lester, L.H. and Zhang, G., ‘Are Casual and Contract Terms of Employment Hazardous for Mental Health in Australia?’, Journal of Industrial Relations, vol. 54, no. 5, pp. 557–578. Sargent-Cox, K.A., Anstey, K.J., Kendig, H. and Skladzien, E., ‘Determinants of Retirement Timing Expectations in the United States and Australia: A Cross-National Comparison of the Effects of Health and Retirement Benefit Policies on Retirement Timing Decisions’, Journal of Aging and Social Policy, vol. 24, no. 3, pp. 291–308. Siminski, P., ‘Are Low Skill Public Sector Workers Really Overpaid?’, Applied Economics, vol. 45, no. 14, pp. 1,915–1,929. Stavrunova, O. and Yerokhin, O., ‘TwoPart Fractional Regression Model for the Demand for Risky Assets’, Applied Economics, vol. 44, no. 1, pp. 21–26. Stromback, T., ‘The Employment Effect of Intensive Support’, Australian Journal of Labour Economics, vol. 15, no. 1, pp. 57–76. Watson, N. and Wooden, M., ‘The HILDA Survey: A Case Study in the Design and Development of a


Successful Household Panel Study’, Longitudinal and Life Course Studies, vol. 3, no. 3, pp. 369–381. Wood, G., Ong, R. and McMurray, C.I., ‘Housing Tenure, Energy Consumption and the Split-Incentive Issue in Australia’, International Journal of Housing Policy, vol. 12, no. 4, pp. 439–469. Wood, G., Ong, R. and Winter, I., ‘Stamp Duties, Land Tax and Housing Affordability: The Case for Reform’, Australian Tax Forum, vol. 27, no. 2, pp. 331–349.

Forthcoming journal articles Ambrey, C.L. and Fleming, C.M., ‘Life Satisfaction in Australia: Evidence from Ten Years of the HILDA Survey’, Social Indicators Research. Baxter, J. and Hewitt, B., ‘Economic Independence or Bargaining Power? The Relationship between Women’s Earnings and Housework Time in Australia’, Feminist Economics. Boyce, C.J., Wood, A.M. and Powdthavee, N., ‘Is Personality Fixed? Personality Changes as Much as “Variable” Economic Factors and More Strongly Predicts Changes to Life Satisfaction’, Social Indicators Research. French, D.J., Jang, S.N., Tait, R.J. and Anstey, K.J., ‘Cross-National Gender Differences in the Socioeconomic Factors Associated with Smoking in Australia, the United States of America and South Korea’, International Journal of Public Health. Gray, E., Evans, A. and Reimondos, A., ‘Childbearing Desires of Childless Men and Women: When Are Goals Adjusted?’, Advances in Life Course Research. Guest, R. and Parr, N., ‘Family Policy and Couples’ Labour Supply: An Empirical Assessment’, Journal of Population Economics. Headey, B., Muffels, R. and Wagner, G.G., ‘Choices which Change Life Satisfaction: Similar Results for Australia, Britain and Germany’, Social Indicators Research.

Hulley, H., McKibbin, R., Pedersen, A. and Thorp, S., ‘Means-Tested Income Support, Portfolio Choice and Decumulation in Retirement’, Economic Record. Kifle, T., ‘Relative Income and Job Satisfaction: Evidence from Australia’, Applied Research in Quality of Life. Kortt, M.A. and Dollery, B., ‘Religion and BMI in Australia’, Journal of Religion and Health. Ng, S.K. and McLachlan, G.J., ‘Mixture Models for Clustering Multilevel Growth Trajectories’, Computational Statistics and Data Analysis. Siminski, P. and Yerokhin, O., ‘Is the Age Gradient in Self-Reported Material Hardship Explained by Resources, Needs, Behaviours, or Reporting Bias?’, Review of Income and Wealth. Wilkins, R. and Wooden, M., ‘Gender Differences in Involuntary Job Loss: Why Are Men More Likely to Lose Their Jobs?’, Industrial Relations: A Journal of Economy and Society.

Other publications Apps, P., Kabatek, J., Rees, R. and van Soest, A., Labor Supply Heterogeneity and Demand for Child Care of Mothers with Young Children, Research Paper, Sydney University Law School, February. Australian Government, Social Inclusion in Australia: How Australia Is Faring, 2nd Edition, Australian Social Inclusion Board. Australian Institute of Health and Welfare, The Desire to Age in Place among Older Australians, Volume 1: Reasons for Staying or Moving, Canberra. Australian Institute of Health and Welfare, A Picture of Australia’s Children 2012, Cat. no. PHE 167, Canberra. Azpitarte, F., ‘Has Economic Growth in Australia Been Pro-Poor?: Analysing Income Changes 2001 to 2008’, Brotherhood Comment, April, pp. 6–7. Baker, D., All the Lonely People: Loneliness in Australia, 2001–2009,

Paper no. 9, Australia Institute, Canberra, June. Berger-Thomson, L. and Roberts, N., ‘Labour Market Dynamics: CrossCountry Insights from Panel Data’, Reserve Bank of Australia Bulletin, September, pp. 27–36. Bradbury, B. and Mendolia, S., Living Standards after Retirement: Perceptions and Expenditure Patterns, Final Report from the Project: ‘Expenditure Costs’, Social Policy Research Centre, University of New South Wales, May. Cassells, R. and Miranti, R., Outside School Hours Care: Social Gradients and Patterns of Use, Report prepared for Social Justice Unit, Uniting Care, March. Cassells, R., Miranti, R., Abello, A., Mohanty, I., D’Souza, G., Watson, I. and Vidyattama, Y., Women in NSW 2012, Family and Community Services, Women NSW. Davis, K., Superannuation over the Past Decade: Individual Experiences, Report by the Australian Centre for Financial Studies for Australian Institute of Superannuation Trustees (AIST), March. Dockery, A.M. and Miller, P.W., OverEducation, Under-Education and Credentialism in the Australian Labour Market, Monograph Series 10/2012, National Centre for Vocational Education Research (NCVER), Adelaide. Finlay, R., ‘The Distribution of Household Wealth in Australia: Evidence from the 2010 HILDA Survey’, Reserve Bank of Australia Bulletin, March, pp. 19–28. Hulse, K., Burke, T., Ralston, L. and Stone, W., The Australian Private Rental Sector: Changes and Challenges, Positioning Paper no. 149, Australian Housing and Urban Research Institute (AHURI), Melbourne, July. Leonard, W., Pitts, M., Mitchell, A., Lyons, A., Smith, A., Patel, S., Couch, M. and Barrett, A., Private Lives 2: The Second National Survey of the Health and Wellbeing of Gay, Lesbian,

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Bisexual and Transgender (GLBT) Australians, Monograph Series no. 86, Australian Research Centre in Sex, Health & Society, La Trobe University, Melbourne, April. Palangkaraya, A., Webster, E. and Cherastidtham, I., Evidence-Based Policy: Data Needed for Robust Evaluation of Industry Policies, Report for the Australian Department of Industry, Innovation, Science, Research and Tertiary Education, Melbourne, October. Peetz, D., Murray, G. and Muurlink, O., Work and Hours amongst Mining and Energy Workers, Australian Coal and Energy Survey, First Phase Report, Centre for Work, Organisation and Wellbeing, Griffith University, November. Productivity Commission, Impacts of COAG Reforms: Business Regulation and VET, Research Report vol. 3, Canberra, April.

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Reserve Bank of Australia, ‘Household and Business Balance Sheets’, Financial Stability Review, March, pp. 41–52.

Education, Analysis supporting Grattan’s Graduate Winners Report, Grattan Institute, Melbourne, August.

Reserve Bank of Australia, ‘Household and Business Balance Sheets’, Financial Stability Review, September, pp. 37–48.

Stone, W. and Reynolds, M., Social Inclusion and Housing: Towards a Household and Local Area Analysis, Positioning Paper no. 146, Australian Housing and Urban Research Institute (AHURI), Melbourne, March.

Richardson, S., Lester, L. and Zhang, G., Are Casual and Contract Terms of Employment Hazardous for Mental Health in Australia?, Changing Patterns of Work: Impacts on Physical & Mental Health & the Meditating Role of Resiliency & Social Capital Research Project, Adelaide, April. Rowley, S. and Ong, R., Housing Affordability, Housing Stress and Household Wellbeing in Australia, Final Report no. 192, Australian Housing and Urban Research Institute (AHURI), Melbourne, September. Savage, J. and Norton, A., NonFinancial Benefits of Higher

Wood, G. and Ong, R., Sustaining Home Ownership in the 21st Century: Emerging Policy Concerns, Final Report no. 187, Australian Housing and Urban Research Institute (AHURI), Melbourne, April. Wood, G., Ong, R., Cidgem, M. and Taylor, E., The Spatial and Distributional Impacts of the Henry Review Recommendations on Stamp Duty and Land Tax, Final Report no. 182, Australian Housing and Urban Research Institute (AHURI), Melbourne, April.


Accessing the Data The Release 11 DVD

Each year, data files are made publicly available. Release 11 became available in early December 2012. The Release 11 DVD includes unit record data for Wave 11 together with revised data files for the previous waves. All data are provided in SAS, SPSS and Stata format. In addition, the DVD includes codebooks and other relevant documentation.

Improvements to the Release 11 DVD

We have made a number of improvements to the data package for Release 11. • Wave 11 includes the first sample replenishment for HILDA. Referred to as the Top-Up sample, two additional forms were used: a top-up household form (TU-HF) and a top-up new person questionnaire (TU-NPQ). The TU-HF includes additional questions from the Wave 1 HF (how well speaks English, external characteristics of the dwelling) which are used in matching the new sample to benchmarks for weighting. The TU-NPQ does not include the Wave 11 special topic PQ modules on ‘retirement’ and ‘intentions and plans’ as new sample members are not asked any modular content until their second interview (this was the approach with the initial HILDA sample at Wave 1). Both new forms are included in ‘marked-up questionnaires and showcards.pdf’. The top-up data are integrated into the Wave 11 household, person and combined files, with two additional variables to indicate if a record is a top-up household (khhtuh) or a top-up person (khhtup). • Biological parent cross-wave identifiers have been added to the datasets. The biological parent’s xwaveid is carried back or forward to all waves even if the parent is not a co-resident but the child has been enumerated. • Ever co-resident twin cross-wave identifier has been added to the datasets. The twin’s xwaveid is carried back or forward to all waves even if the twin is not a co-resident. Adult not-co-resident twins are recorded in the PQ section on siblings asked in Waves 8 and 12 (section HS), but they are not added to _hhtwxid (insufficient information to determine if they are part of the sample). Triplets, quadruplets etc. are not included in the twin identifiers. • Grandparent cross-wave identifiers have been added to the datasets. Grandparents where the lineage (paternal or maternal) is not yet known are excluded (that is, in households where only the grandparents and grandchildren have been co-resident (across all the waves)). In addition, the variations that step parents and step grandparents and grand step parents introduce, both in terms of the number of relationships and the variation over time, have led to step relationships being excluded. Researchers can create their own extended grandparent identifiers including these groups. • The union membership variable _jbmtuea (from Wave 9 onwards) combines whether the respondent belongs to a trade union, other union or employee association (_jbou and _jbtu). Respondents who do not know whether they belong to a trade union, other union or employee association are treated as not belonging to one. This provides a consistent definition with Waves 1 to 8 where only one question is asked (_jbmunio). For Waves 1 to 8 _jbmtuea is the recoding of _jbmunio where respondents who do not know whether they belong to a trade union or employee association are treated as not belonging to one. _jbmtabs (derived from Wave 9 onwards) is a recoding of _jbtu where respondents who do not know whether they belong to a trade union are treated as not belonging to one (which is consistent with the ABS definition).

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_hgni is a new indicator variable which differentiates enumerated persons into 0. Interviewed adult 1. Not interviewed adult 2. Not interviewed child (aged 0–14) For the variable _edagels ‘History: Age left school’, there was a problem in the updating of this variable which did not take into account errors made by continuing persons at A2 ‘Whether they had spent any time enrolled in school since last interviewed’. If they said they had spent time in school and then in the next wave when they were interviewed they said they were not enrolled in school _edagels would be increased inappropriately. An age restriction (≤ 26) has been applied to the updates on _edagels, so adults who make a mistake at A2 do not get adult ages for age left school at a later wave. To simplify the indexing of loops in their programs, the HF has been padded or reduced to 16 persons at all waves. (Persons 15 and 16 have been added to the HF for Waves 1 to 5; the unused variables for Persons 17 to 20 have been removed from Wave 9 onwards.) In addition, derived variables for householdfamily type, HF18 relationship-pairs and enumerated weights have been expanded to 16 persons at all waves. The Household Questionnaire items for who pays board and, in wealth years, who are the property owners have also been adjusted. In wealth years, the PQ items for household members who are joint owners of bank accounts and credit cards have been adjusted. Lists of affected variables have been included in the attachment of changes made to each wave. Self-Completion Questionnaire (SCQ) was matched to Person Interview (_scmatch). An indicator variable for whether an SCQ had been scanned and matched to a corresponding person interview is now included in both the General Release and In-Confidence datasets. The old (in-confidence file) indicators _hhmpid and _hhmatch have been dropped. The office-use ‘SCQ has been picked up’ or ‘Will be returned by mail’ variables (HF20 _hgscq, _hgsi, _hgsf and _hgs) have been dropped from the General Release files as they were being confused with SCQ to PQ matching. The HILDA-Cross-National Equivalent File (CNEF) data are no longer supplied as a separate zip on the DVD. The appropriate files are now included in the SAS, STATA, SPSS and Documentation zips. The dataset filenames have been changed from the CNEF convention (named ‘hilda-cnef’ rather than ‘hequiv’), but the contents are otherwise identical to the files you would have previously received from the CNEF project. For the geography variable, some inconsistencies in _hhcd01 2001 Census Collection District had occurred when some, but not all, individuals in a household had corrections applied to their CD. This led to inconsistencies in _hhcd01 between the household data and the enumerated person data (the Household and Combined datasets were correct, so if you only used these two files, or you used Panelwhiz, you would not be impacted). Between three and 30 households needed correction each wave. _hhcd01 is not supplied in the General Release datasets.

More details about these changes can be found in the ‘Readme 110.pdf’ file on the DVD.

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Data requests

Individual Licences Requests for a copy of the Release 11 DVD can be made by sending the appropriate forms to FaHCSIA. A charge of A$77.00 (GST inclusive) to cover postage and administrative costs is payable to the Melbourne Institute, University of Melbourne (A$121.00 for overseas users). The Deed of Licence is available from the HILDA Survey website. Organisational Licences A flat fee of A$330.00 (GST inclusive) is charged for each release of data. Overseas organisations pay A$330.00 which is GST exclusive. The fee covers all datasets until the next release is available. Please contact FaHCSIA at longitudinalsurveys@fahcsia.gov.au if your organisation would like to apply for an Organisational Licence. Organisational Licences are ongoing and do not have to be signed each year. However, users at organisations with an existing Organisational Licence who wish to obtain access to the latest data release will need to complete a new Deed of Confidentiality, which can be obtained from your Data Manager.

HILDA website

http://www.melbourneinstitute.com/hilda/ The HILDA Survey website provides further details about the HILDA Survey and its progress. Copies of all survey instruments, the User Manual and various discussion and technical papers can be viewed and downloaded from the HILDA Survey website. Individual Licence Order Forms and Deeds of Licence for the dataset can also be found on this site.

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