Working with household income variables Practical computing session I – Part 3

Heike WirthGESIS – Leibniz Institut für Sozialwissenschaften

DwB-Training Cource on EU-SILC , February 13-15, 2013Romanian Social Data Archive at the Departement of SociologyUniversity of Bucharest, Romania

• EU-Silc is the most important data source regarding comparative description and analysis of poverty across the European countries

• Headline indicator AROPE (at risk of poverty or social exclusion) based on

1. At risik of poverty2. Severe material deprivation3. Very low work intensity

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• highest AROPE rates: BG, RO, LV• lowest AROPE rates: CZ, SE, NL

At risk of poverty (HX080)• less than 60% of the national median equivalised household

income

Severe material deprivation (HX110)• couldn’t afford at least 4 out of 9 material deprivation items

(HS010 – HS110)

Very low work intensity (RX050)• ratio of workable months and actually worked months < 0.2

All three indicators are included in the data as well as the combined indicator AROPE (PX070)

In the following the focus is on ‘at risk of poverty’ indicator or rather its components

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• Does poverty vary widely between different country in Europe

• How is income poverty correlated with gender, age, education, urban and other characteristics?

• What are the main sources of income for the poor?

• How does unemployment affect poverty?

• How is income poverty linked to health conditions & access to health services?

• Consistency of poverty• How long people are poor?• How often people are poor over a period?

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Some Questions regarding Poverty

• By poverty status: Poor versus non-poor• Summarize the distributions of characteristics, e.g. household

type, household size, activity status, educational level, urbanisation degree of residence, age …

• By characteristics: e.g. age, health condition, number of children, educational level, occupation of household head, region of residence. • Report the poverty rate for each components.

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Types of exploring poverty profiles

• All income variables in the UDB are in € (EURO)

• For countries not members of the euro area the conversion factor can be found in variables HX010 & PX010. • Income data (euro) i. e. HY020 * HX010 = income data (national

currency)

• HY010 – Total household gross income• HY020 – Total disposable household income• HY022 – Total disposable HH income before social transfer

• These variables do not include PY080 although published indicators were calculated with PY080

• Remember PY080G was summarized across household members and added as the variable 'pens' to the household data

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Hands on – Good to know

• HY025 =Within-household non-response inflation factor

• Factor by which it is necessary to multiply • the total gross income (HY010); • the total disposable income (HY020) or • the total disposable income before social transfers (HY022)

to compensate the non-response in individual questionnaires

If the data are not corrected by the effect of non-responding individuals within a household, income of individuals not interviewed is not added up into the total household Income.

For further details see guidelines10

Please note:

***********************************************************.* Exercise 3.1a** Compute the equivalised household income (OECD scale) by yourself,* name the new computed variable: HX090_new*** Check your results by comparing the means of HY020, HX090_new, HX090* by HH type(HX060), &* by country (HB020)* * Did you get what you expected?***********************************************************.

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Hands on – (for more hints see the exercise sheet)

* open the household dataset.GET FILE='data_path/household_data.sav'.

compute HX090_new = ((HY020+PENS)* HY025)/HX050.var lab HX090_new 'oecd scale'.

mean tables HY020 HX090 HX090_new by HX060/cells = mean .mean tables HY020 HX090 HX090_new by HB020/cells = mean .

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Hands on – Exercise 3.1a

************************************************************************************.* Exercise 3.1b ** Compare the means of the equivalised Income according to the OECD Scale * with equivalised Income based on** Per-Capita scale (divide disposable income by number of household members), and* LIS-equivalence scale (divide disposable income by square root of number of household members)* * across Household Type* across countries* what are the main findings?* * Compute the mean of the equivalised disposable income depending on the * number of unemployed persons (unemp) in the household, by country** Collapse categories for number of unemployed persons: 0, 1, >=2***********************************************************************************.

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Hands on - Exercise 3.1b

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Hands on - Exercise 3.1b* Per capita income.compute pc_income = ((HY020+PENS)* HY025)/HX040.

* SQUARE ROOT EQUIVALISED HOUSEHOLD-INCOME.compute HX040_2 = sqrt(HX040).compute lis_income = ((HY020+PENS)*HY025)/HX040_2.var lab pc_income 'per capita income'/ lis_income 'squareroot hhsize'.

means tables HX090 pc_income lis_income by HX060 HB020/ cells = mean .temporary.select if (HB020 ne 'DK').means tables HX090 pc_income lis_income by HX060 HB020/ cells = mean .

* Equivalised Income by number of unemployed persons in the household *.recode unemp (0=0) (1=1) (2 thru highest = 2)into unemp_n.val lab unemp_n 2 '>=2'.

* check your new variable *.cross unemp by unemp_n.means tables = hx090 by unemp_n by hb020/cells = mean.

***************************************************************************** Now compute the equivalised income based on the disposable income before social* transfers excl. old-age-benefits (HY022)* Name the new variable HY22_equi** Remember to take into account the variable 'pens' as well as the inflation factor (HY025).* * Compare the means of HX090 and HY022_equi by country* What are the main findings?** Compute the mean of the equivalised disposable income (before social transfers) by * number of unemployed persons (unemp_n) in the household, by country**************************************************************************.

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Hands on - Exercise 3.1c - Optional

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Hands on - Exercise 3.1c - Optional

* equivalised income before social transfers *.

compute HY022_equi = ((HY022+PENS)* HY025)/HX050.

means tables = HY022_equi HX090 by HB020/ cells = mean .

means tables = HX090 HY022_equi by unemp_n by hb020 /cells = mean.

************************************************************************************* The at-risk-of-poverty rate is the share of people with an equivalised disposable income * (after social transfer) below 60 % of the national median equivalised disposable income after social transfers * This poverty indicator is included in the EU-SILC data (HX080).* Below you find an example of how to compute this poverty line*Step 1: compute the national median, name it median_sample *.aggregate outfile = * mode = addvariables overwrite = yes /break = HB010 HB020 /median_sample = median(HX090).

means tables median_sample by hb020.

step 2: compute the poverty line, name it povline_60 *.compute povline_60 = median_sample * 0.6.

step 3: compute the poverty- indicator - name it at_risk_60 *.compute at_risk_60 = 0.if (hx090 lt povline_60) at_risk_60 = 1.

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Exercise 3.1d - Optional - At Risk of Poverty

***************************************************** compare the findings with poverty indicator (HX080) provided in the

data• Reason for the discrepancies ?• * * Compute the percentage of households at risk of poverty depending

on the number of unemployed persons (unemp_n) by country****************************************************.* % of households at risk by number of unemployed persons in hh, by

country *.cross unemp_n by HX080 povline_60 by HB020 / cells = row.

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Exercise 3.1d - Optional - At Risk of Poverty

************************************************************************************.* Subjective indicators regarding the financial situation of the household* HS120: Ability to make ends meet (scale 1-6: with great difficulties (1) ... very easily(6))* HS130: Lowest monthly income to make ends meet* * Compute the average ability to make ends meet depending on whether a household is at * risk of poverty or not, by country** Focus on households with difficulties or great difficulties to make ends meet.* Compare the average of the lowest monthly income needed (HS130) to the disposable income, by* country.* * Do the same for households which make ends meet easily or very easily* Main points ?

************************************************************************************.

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Exercise 3.1e - Optional - Make ends meet

* average ability to make ends meet by risk at poverty & country *.means table HS120 by HX080 by HB020 / cells = mean.

* Which income variable seems approriate for this comparison?.* Equivalised income (HX090)* Total disposable income (HY020) respectively the published HY020* HY022_pens = ((HY020+PENS)* HY025)* what else ?.

compute monthly = (HX090/12).compute HY020_pub = ((HY020+Pens)*HY025)/12.* compute HY020_m = (HY020/12).

* All households *.means HX090 monthly HY020_pub HS130 by HB020 /cells = mean.

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Exercise 3.1e - Optional - Make ends meet

* only households with difficulties or great difficulties *.

compute difficult = (HS120 le 2).compute easily = (HS120 ge 5).val lab difficult 1 'difficulties' 0 'no difficulties'.val lab easily 1 'easily' 0 'not so easily'.

cross hs120 by difficult easily.

filter by difficult.means monthly HY020_pub HS130 by HB020 /cells = mean.

filter by easily.means monthly HY020_pub HS130 by HB020 /cells = mean.

filter off.21

Exercise 3.1e - Optional - Make ends meet

*******************************************************.

Calculate Income Quintile for households, by country Calculate the mean of equivalised disposable income for the lowest

& highest income quintile, by country Calculate the mean of lowest monthly income to make ends meet

by income quintile & country Calculate percentage of households with difficulties/great

difficulites to make ends meet, by income quintile and country e) Severe material deprivation rate, by income quintile and

country

*******************************************************.

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Exercise optional

*compute the quintiles for each country based on HX090 *.* Option 1 - use the comand split file *.

split file by hb020.RANK VARIABLES= HX090/NTILES(5) INTO Quintile /print = yes.

freq quintile.split file off.

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Exercise optional

************************************************************************Option 2 - Rank variables (however HB020 = string variable)=> use HB020_num************************************************************************.

autorecode variables = HB020 / into HB020_num.

RANK VARIABLES= HX090 by HB020_num/NTILES(5) INTO Quintil.

cross HB020 by quintil.

* mean of equivalised disposable income for the lowest & highest income quintile, by country *.

Temporary.select if (quintil = 1 or quintil = 5).means tables hx090 by hb020 by quintil /cells = means.

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Exercise optional

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Exercise optional

* Calculate the mean of lowest monthly income to make ends meet by income quintile & country *.

means tables HY020_pub HS130 by HB020 by quintile /cells = means.

* difficulties/great difficulites to make ends meet, by income quintile and country *.

cross hb020 by difficult easily by quintil / cells = row.

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You did it …… at leastfor today

Source: : http://www.hierschreibenwir.de/node/32556

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Types of equivalence measure

Household size: 4; income 4000 €

Per-capita income = 4000/4 = 500 €Lis-equival. income = 4000/Square root(4) = 2000 €

OECD (new)=4000/(1+1*0.5+2*0.3)=4000/2.1= 1905 €Source: : http://www.hierschreibenwir.de/node/32556

>= 14

>=14

<= 14

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If not taking HY25 into account

Household size: 4; income 2000 €

Per-capita income = 2000/4 = 1000 €Lis-equival. income = 2000/Square root(4) = 2000 €

OECD (new)=2000/(1+(1*0.5)+(2*0.3))=2000/2.1= 1905 €Source: : http://www.hierschreibenwir.de/node/32556

2000 €

0 €