LIS
Highlights from Research Based on LIS:
Poverty and Employment
Janet Gornick, LIS DirectorWorkshop
Tokyo, Japan
13 January 2011

14:30-15:30

Using the LIS Database to study poverty

Poverty has been at the core of research using the LIS Database since
LIS was founded
founded.
● 245 LIS Working Papers include keywords “poverty, poor, low income”.
● Many focus on cross
cross-national
national variation in levels; some assess trends
trends.
● Common areas of inquiry include:-- Relative risk of poverty in and across vulnerable subgroups
subgroups, such as
children, single parents, women, and/or the elderly.
-- Extent to which earnings/employment mitigate the risk of being poor,and for whomwhom.
-- Extent to which taxes and income transfers reduce poverty, with afocus on the relative roles of means-tested versus universal transfers-- Asset/debt holding of the poor (a new area of study, enabled by LWS!)

Using the LIS Database to study poverty

Several methodological decisions are required:● Selection of unit of analysis: households or persons.
When carrying out person-level analyses, researchers generally
assess persons’ likelihood of living in poor households.
● Definition of countable income.
Many use LIS variable “disposable income”, which is the sum of
income from earnings, capital, private transfers, public social insurance
and public social assistance – net of income taxes and social security
contributions. (Imputed rents, and irregular incomes, such as lumpsums and capital gains/losses are not included.)● Choice of equivalence scale
scale.
Many divide unadjusted income by the square root of household size.
● Setting of poverty line – absolute or relative.
Most use relative poverty lines
lines, typically setting the poverty line at 50%(or 60%) of national median equivalised income.

Using the LIS Database to study poverty

Three illustrative findings
1. Gornick and Jantti 2010 – a study of women and poverty.
LIS WP534, also a book chapter.

Women s likelihood of living in poverty: comparing absolute versus
Women’srelative poverty rates.
1. Gornick and Jantti 2010 – a study of women and poverty.
LIS WP534, also a book chapter.

Women’s likelihood of living in poverty: comparing poverty “pre-transfer”
versus “post-transfer.”
3 Gornick3.
G i k andd JJantti
tti 2009 – a studyt d off children
hildandd poverty.
t
LIS WP509, also a book chapter.

Children’s poverty rates: comparing poverty rates among young children
versus older children
children, and among all children versus all persons
persons.

Example 1:
Percentage of women living in poor households,
absolute
b l t povertyt versus relative
l ti povertyt(post-tax, post-transfer)Example 2:
Percentage of women living in poor households,
pre-transfertf povertyt versus post-transfer-poverty
tt
ft(relative poverty)

Example 3:
Ratio of poverty rates,
young children
hild((< age 6) tto allll children
hild((< age 18)18),and all children (< age 18) to all persons

Using the LIS Database to study employment

Starting in the 1990s, many researchers have used the LIS data to study
various labour market outcomesoutcomes.
● Approximately 250 LIS Working Papers fall into this category.
● Many assess employment rates and earnings; some address hours
worked and/or job characteristics such as industry and occupation.
● Common areas of inquiry include:-- Gender gaps in all labour market outcomes.
-- Outcomes in and across subgroups, such as young adults, mothers,
persons over age 5050.
-- Interplay between earned and unearned income.
-- Effect of policies/institutions on labor market outcomesoutcomes. Many of thesestudies combine aggregate (country-level) indicators with our microdata.

Using the LIS Database to study employment

Several methodological decisions are required:● Selection of unit of analysis: households or persons.
Researchers working at the household level are often interested in
employment characteristics associated with the household head.
● Choice of reference period.
Reference periods vary within and across datasets. E.g., in somecases, the dataset includes employment data “at present”; in othercases during the income reference period
period, which is often both earlier
and of longer duration.
● Decisions regarding standardizing across datasets.
The employment data are generally categorical,categorical and the categories
often vary across datasets. The LIS staff have standardized manyvariables; users typically have to make some additional decisions inorder to maximize standardization across datasets.

Using the LIS Database to study employment

Four illustrative findings
1. Gornick and Jantti 2010 – a study of women and poverty.
LIS WP534, also a book chapter.

Women’s likelihood of living in poverty: comparing those with weak versus
strongt
attachmenttt ht tot theth labourl bmarket.
k t
2. Gornick and Meyers 2003
Book: Families that Work

Share of earnings: comparing women’s versus men’s shares, by family type.
3. England, Gornick and Shafer (forthcoming) – a study of the education
gradient in gender equality at work.
Mean weekly work hours by educational level, comparing women and men.
4. Gornick and Meyers 2003
Book: Families that Work

Effect of having a preschool-aged child on the odds of being employed:comparing mothers versus fathers.

Example 1:
PPercentagetoff women li
livingiini poor households,
hh ld
by labour market status(relative post-transfer-poverty)

Example 2:
g byyggenderEarnings

Example 3:
Weekly work hours by educational level attained:
age 25-54, married, with young child (under age 7),(this figure includes those who work zero hours)Example 4:
Regression-adjusted
Regression
adjusted effect of having a preschool-agedpreschool aged child (age 33-5)
5)
on the odds that married parents are employed
10%

6%
3%
1%

2%

1%

0%

0%
-1%

-1%

-2%

-5%

-10%

-4%

-5%

-6%
-12%

-13%
-15%

-20%

-16%

-17%

-19%

-19%

-30%

-30%
-31%

-40%

-50%
DKSW

Source: LISdataFINWBEFRNLGECN

measured as percentage difference in employment rates
between parents with youngest child aged 3-5
and parents with youngest child aged 13-17
mothers

fathers

UKUS