1. Influence of the adopted methodological solutions on the assessments of the monetary poverty range. The case of Poland. Seminar on Poverty Measurement Geneva, 5-6th May 2015 Anna Bieńkuńska, CSO of Poland Karol Sobestjański, CSO of Poland

2. Aim of the analysis Presentation how choice of different methodological solutions influences poverty rates

3. Analysed aspects Equivalence scales Measures of the economic welfare Data sources

4. Equivalence scales Applying of different equivalence scales in context of the assessment of the relative poverty range

5. Equivalence scales Equivalence scaleEquivalence units Original OECD equivalence scale 1 - for the first adult household member, 0,5 – for each additional adult household member and 0,3 - for every child in the household at the age of 14 or less Modified OECD equivalence scale 1 - for the first adult household member, 0,7 – for each additional adult household member and 0,5 - for every child in the household at the age of 14 or less Square root scale √ n - the square root of household size is treated as a number of the equivalent units Income per person in household n - value 1 for each person in a household

6. Relative poverty rates in Poland in 2013 by age (based on EU-SILC) Poverty threshold – 60% of median equivalised disposable income Scale Total Persons aged 0-1718-6565 or more % of persons in households Original OECD equivalence scale 1-0.7-0.5 18,0 26,317,59,5 Modified OECD equivalence scale 1-0.5-0.3 17,3 23,216,712,3 Square root scale sqrt(n) 17,7 22,616,715,8 Per person n 20,133,219,27,7 Source: EU-SILC 2013

7. Applying of different equivalence scale does not have a significant impact on the assessments of poverty rates at the level of the whole population, however it does have the influence on the results broken down into different age groups. Relative poverty rates calculated with the use of different equivalence scales

8. Measures of the economic welfare Expenditures vs. Income

9. Definitions: o Disposable income (based on the HBS) is defined as a sum of monetary income (in cash), the income in kind (including natural consumption) as well as goods and services received free of charge. o Expenditures (value of consumption) comprise expenditures on consumer goods and services (including value of the natural consumption and products received free of charge) and other expenditures. Expenditures vs. Income Analyses on a basis of the Household Budget Survey (HBS)

10. Extreme poverty rates in Poland in 2013 by socio-economic groups (based on HBS) Poverty threshold – Extreme poverty rates in Poland in 2013 by socio-economic groups (based on HBS) Poverty threshold – subsistence minimum which includes only these needs which cannot be postponed by the households Socio-economic groups % of persons at risk of extreme poverty calculated on a basis of households' expenditures calculated on a basis of households' income Total population7,46,1 Employees6,43,5 Farmers13,423,9 Self-employed3,93,3 Retirees4,82,3 Pensioners13,212,0 Living off other, non-earned sources of income 21,526,8 Source: Own calculations on a basis of Household Budget Survey

11. Among households which have the permanent sources of income (i.e. households living off hired work or pensions), there are observed different trends than in case of households not having stable sources of income (i.e. household living off non- earned sources or households of farmers). Expenditures vs. Income Analyses on a basis of the Household Budget Survey (HBS)

12. Measures of the economic welfare Expenditures vs. Income A choice between expenditures and income is mainly conditioned by the availability and quality of data. A choice of each measure requires a different interpretation of the poverty rates. Because in case of the HBS income refers to one month only, expenditures are considered as more reliable and stable measure of welfare.

13. Data sources EU-SILC vs. HBS

14. Age % of persons in households at risk of extreme poverty calculated on a basis of EU-SILC calculated on a basis of Household Budget Survey Total population4,45,6 0 - 17 years old6,77,6 18 - 64 years old4,45,6 65 or more years old0,92,3 Source: Own calculations on a basis of EU-SILC 2013 and Household Budget Survey 2012 EU-SILC vs. HBS Extreme poverty rates in Poland in 2012 by age

15. Methodology of income surveying applied in EU-SILC survey is not fully coherent with the methodology of the household budget survey. Differences in methodology: Method of surveying Refrence period Definition of the total disposable income Data sources EU-SILC vs. HBS

16. Method of surveying In the EU-SILC the information on income is collected during the interview and then missing data are imputed. Information on income on a basis of the Household Budget Survey is derived from the current household’s notes, made in the so-called ‘budgetary diary’. Refrence period In the EU-SILC survey information refers to the income received within the whole calendar year preceding the survey. In case of the Household Budget Survey, the reference period is one month. EU-SILC vs. HBS Differences in methodology

17. Definition of the total disposable income Total disposable income calculated on a basis of the EU-SILC survey does not include a value of natural consumption (i.e. consumer goods and services taken from individual farm or own economic activity to satisfy household’s needs), while the assessments based on the household budget survey include this element as a part of the total household income EU-SILC vs. HBS Differences in methodology Disposable income in EU-SILC Disposable income in HBS Income in cash Income in cash Income in kind

18. Assessments concerning the level of poverty in Poland conducted on a basis of both surveys not only differ from each other, but also require to be interpreted differently. Data sources EU-SILC vs. HBS

19. Conclusions To minimalize the risk of misinterpretation of the information on poverty, it is necessary to provide the high quality metadata to the statistical data users. It seems very important to consistently use the applied methodological solutions over the time. It is the only way to obtain valuable and comparable throughout the years statistical data, which will provide the reliable monitoring of poverty.