What would you use the data for?

• Straightforward secondary analysis– To assess theoretical accounts– To quantify characteristics or behaviours– To challenge official views– To apply alternative definitions

• Context to your own primary research – Your research could be quantitative or

qualitative– To assess the national context of an area study– To assess whether your sample is typical– To assess the scale of behaviours

The Research Use of the Government Surveys:

Why use the data?• Already seen that the data are:

– Free to academics and easy to access– Good quality with good documentation

•Also:– Allows comparison over time– Large samples– Hierarchical– Flexible

Using and producing the time seriesEconomic activity rates:1,2 by sex

United KingdomPercentages

1 Males aged 16-64, females aged 16-59. The percentage of the population that is in the labour force. 2 Data are seasonally adjusted, at spring.Source: Labour Force Survey, Office for National Statistics

0

20

40

60

80

100

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

Males

Females

All

Hours of work in reference week by employment and sex

Source: Labour Force Survey (Computer Files) 1981, 1991 and 1996

Base: all women 16-59, all men 16-64 (including students)

0

5

10

15

20

25

30

35

40

1981 1991 1996

all men

all men in work

all women

all women inwork

‘Before and after’ policy analysis

• Ginn – interested in impact of change in pensions policy in 1988

• GHS collects information about pensions as well as socio-demographics & employment

• Compared data for 1987 with 1993/4

Source Ginn in Gilbert (2001) Researching Social Life

Private pension arrangements: men and women aged 20 -59 in 1987 and

1993-4

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Men 87 Men 93-4 Women87

Women93-4

No private pension

Appropriate personalpension

Occupational scheme

Using successive cross-sectional data over time

Pros…• Reasonable amount of

comparability• Can pool years/quarters• Data is representative at

each time point• Good at looking at

impacts on groups

Cons…• Limits to continuity in the

data (e.g. ethnic)• Cannot establish individual

change – Cannot look at dynamics– Unlikely to be able to look

at individual process (e.g. modelling with predictor variable)

Hierarchical data

P erson 1M ale

5 6se lf

P erson 2F em ale

5 2sp ou se o f p e rson 1

P erson 3M ale

2 3son o f p e rson 1

F am ily 1

P erson 4F em ale

8 2m oth er o f p e rson 1

F am ily 2

H ou seh o ld 1

P erson 1F em ale

6 7se lf

F am ily 1

H ou seh o ld 2

•Data: GHS, LFS, EFS, FRS, HSE, SARs (BCS)

•Other levels – benefit unit, event

Use the hierarchy to…

• Better describe the household• Describe the household context of an

individual• Look at intra-household differences

(& sameness)

Describing the household

e.g. Is the household deprived / in poverty?

• Equivalising income (e.g. FRS)– Need information on total income (all

members not just Household Reference Person)

– Need information on household composition

• Identifying workless households– E.g. Gregg and Wadsworth (1999)

Workless households (source FES, various years 1968-1996)

0

5

10

15

20

25

68 70 72 74 76 78 80 82 84 86 88 90 92 94 96

Year

Pe

rce

nta

ge

(o

f p

res

en

t w

ork

ing

ag

e h

oh

)

workless households

children in worklesshouseholds

Source: Richard Dickens, Paul Gregg and Jonathan Wadsworth(2000) ‘New Labour and the Labour Market, CMPO Working Paper Series 00/19 Table 5

The effect of partnership (mothers)

Employment Activity by all mothers (of dependent children) aged 16-59 by Partnership 1975-1996

0

10

20

30

40

50

1975 1981 1991 1996

Year

Perc

enta

ge

Partnered, f/t

Partnered, p/t

Unpartnered, f/t

Unpartnered, p/t

Looking at small populations

• Only the Samples of Anonymised Records have larger sample sizes

• Many surveys with 10+k respondents– Permits minority groups to be represented– Rare subpopulations sample size may be too

small… can consider combining years if appropriate

Blackaby et. al. (1999) ‘Unemployment Among Britain’s Ethnic Minorities’ The Manchester School 67(1): 1-20

Combined Annual LFS data 1987-91 to give:• 100,000 men• 2,716 Indians• 1,575 West Indian/Guyanese• 1,495 Pakistani/Bangladeshi

Used data to model (probit) each ethnic group’s employment separately

Concludes :• W.Indian/Guyanese appear to suffer discrimination• Pakistani/Bangladeshi education appears to have

least benefit• If Indians/Pakistani/Bangladeshi groups had the same

charactersistics as whites they would not have higher unemployment

Combining datasets to increase sample size

How has the data been used?

• Lists of publications based on the data are available on the ESDS Website

• CCSR will be looking for others…

Summary

• Use the data as the heart of a project or to give context to a primary study

• Key strengths– Flexibility– Comparison over time– Sample size– Hierarchy

• Need to be clear what you need before deciding which dataset to use, and look at the documentation beforehand